Processes doi: 10.3390/pr12030607
Authors: Minbo Yang Xiao Feng
Process system engineering (PSE) is a multidisciplinary research field that aims to address engineering problems related to the design, operation, control, and management of process systems [...]
]]>Processes doi: 10.3390/pr12030603
Authors: Jiaxiang Peng Chenxi Hui Ziwei Zhao Ying Fang
This article explores the impact of operating parameters on the classification efficiency of a rotor classifier. Based on the experimental data of calcined petroleum coke classification, a single-factor experimental analysis is conducted to find the relationship between operating parameters and classification performance. The cut size becomes progressively smaller as the rotor speed and feeding speed increase, and progressively larger as the inlet air volume increases. Newton’s classification efficiency and classification accuracy decreased with the increase in feeding speed. The range analysis of the orthogonal experiment shows that the rotor speed and inlet air volume have significant effects on the classification performance, but the effect of feed speed is relatively weak. In addition, the optimal combination of operating parameters is obtained by optimizing the operating parameters. Newton’s classification efficiency under this combination is estimated, and the estimated value is 82%. The verification experiment reveals that the Newton’s classification efficiency is 83.5%, which is close to the estimated value. Meanwhile, the classification accuracy is 0.626. This study provides theoretical guidance for the industrial production of calcined petroleum coke and accumulates basic experimental data for the development of air classifiers.
]]>Processes doi: 10.3390/pr12030605
Authors: Huifang Dang Yongqiang Han
In this paper, a waste heat recovery compound system for series hybrid electric vehicles is established. The existing components of vehicle air conditioning are used in the organic Rankine cycle (ORC) to realize miniaturization. The waste heat recovery compound system is constructed using GT-SUITE, and the objective of the analysis is to increase the power output and engine thermal efficiency increase ratio (ETEIR). The effects of the expander speed, pump speed, working fluid mass flow rate, and working fluid type on the waste heat recovery compound system are analyzed. The simulation results show that the optimal schemes for the ORC system and compound system corresponding to the expander speed and pump speed are 1000 pm, 2500 rpm, 1200 rpm, and 2500 rpm, respectively. Compared with the ORC system, the maximum power output of the compound system with the same working fluid in three states (1500 rpm, 2500 rpm, and 3500 rpm) of the engine is increased by 21.67%, 24.05%, and 28.23%, respectively. Working fluid supplies of 0.4 kg/s, 0.4 kg/s, and 0.6 kg/s in the three engine states are also considered the best solutions. The working fluid R1234yf and R1234ze are the preferred choices for a waste heat recovery compound system, which have a high system power output and ETEIR and are environmentally friendly.
]]>Processes doi: 10.3390/pr12030606
Authors: Jun Li Taotao Luo Tingting Cheng Ying Lei Yameng Xing Bin Pan Xiao Fu
Large-scale volumetric fracturing is generally used during shale gas development. The return rate of fracturing fluid is low, and a large amount of slickwater is retained in the reservoir. The adsorption and desorption of partially hydrolyzed polyacrylamide (HPAM), an additive commonly used in slickwater, on the surface of shale was studied using Longmaxi shale from the Sichuan Basin. The experimental results showed that the mass ratio of the HPAM solution to shale reached saturation adsorption at 20:1 when the concentration of HPAM solution was 1000 mg/L and 25:1 when the concentration of HPAM solution was 500 mg/L. The mass ratio of the HPAM solution to shale was fixed at 25:1, and the adsorption equilibrium was reached at a HPAM concentration of 1000 mg/L when the aqueous solution temperature was 30 °C and 800 mg/L when the aqueous solution temperature was 60 °C. The Langmuir adsorption model yielded a better fit than the Freundlich adsorption model. The adsorption equilibrium time at 30 °C was at 60 min for a HPAM concentration of 500 mg/L, while for a concentration of 1000 mg/L, it was at 90 min. The adsorption equilibrium time at 60 °C was 40 min for a HPAM concentration of 500 mg/L, whereas it was 60 min for a HPAM concentration at 1000 mg/L. The pseudo-second order (PSO) kinetics model yielded better fits than the pseudo-first order (PFO) kinetics model. The adsorption of HPAM on shale was strong, and the adsorbed HPAM resembled cobwebs adhering to the shale surface. HPAM on the surface of shale after adsorption was able to resist the desorption capacity of water. However, when the amount of adsorbed HPAM on shale increased significantly, the amount of residual HPAM on the surface of the shale decreased rapidly during desorption in deionized water. The desorption of HPAM on the shale surface followed a modified desorption model. The higher the concentration of HPAM adsorbed on the shale surface was, the easier it was to desorb and the easier it was to be removed from the shale.
]]>Processes doi: 10.3390/pr12030604
Authors: Chao Yu Mingzhen Shao Wenbao Zhang Guangyi Wang Mian Huang
An efficient and accurate method for optimizing capsule-type plate heat exchangers is proposed in this paper. This method combines computational fluid dynamics simulation, a backpropagation algorithm and multi-objective optimization to obtain better heat transfer performance of heat exchanger structures. For plate heat exchangers, the heat transfer coefficient j and friction coefficient f are a pair of contradictory objectives. The optimization of capsule-type plate heat exchangers is a multi-objective optimization problem. In this paper, a backpropagation neural network was used to construct an approximate model. The plate shape was optimized by a multi-objective genetic algorithm. The optimized capsule-type plate heat exchanger has lower flow resistance and higher heat exchange efficiency. After optimization, the heat transfer coefficient is increased by 8.3% and the friction coefficient is decreased by 14.3%, and the heat transfer effect is obviously improved. Further, analysis of flow field characteristics through field co-ordination theory provides guidance for the further optimization of plates.
]]>Processes doi: 10.3390/pr12030602
Authors: Shunxi Liu Jie Yang Yi Jin Huibo Song Baoyu Wang Jiabin Dong Junling Zheng
The parameters of coalbed methane reservoirs have large differences, and the precise values cannot represent the resource and production characteristics of the whole block. In order to address these problems, an index system for evaluating the production potential of coalbed methane blocks was constructed, the weights of evaluation parameters were determined, and a model for the preferential selection of coalbed methane blocks based on the subjective–objective combination of weights method was established. The main coal seams (No. 2-1 and No. 4-2) of the Pingdingshan-Shoushan I Mine Block were taken as the research objects to rank the development potential of CBM blocks in a preferential way. The results show that the six resource and production parameters of No. 2-1 coal are gas content, top and bottom rock properties, coal seam thickness, coal seam depth, coal body structure, and tectonic conditions, in descending order of importance, and the parameters of No. 4-2 coal are gas content, coal body structure, coal seam thickness, top and bottom rock properties, coal seam depth, and tectonic conditions, in descending order of importance. It is predicted that the favorable CBM gas development sweet spot areas of the No. 2-1 coal seam and No. 4-2 coal seam will be located along the exploration wells W15–W29 and W31, respectively. This paper aims to make a multi-dimensional and more comprehensive evaluation of coalbed methane mining potential in the Shoushan I mine, and provide a technical basis for the next step of coalbed methane mining in the study area.
]]>Processes doi: 10.3390/pr12030601
Authors: Tianjian Li Jiale Ren Qingping Yang Long Chen Xizhi Sun
To address the issue of low accuracy in detecting defects of battery cell casings with low space ratio and small object characteristics, the low space ratio feature and small object feature are studied, and an object detection algorithm based on dual-coordinate attention and small object loss feedback is proposed. Firstly, the EfficientNet-B1 backbone network is employed for feature extraction. Secondly, a dual-coordinate attention module is introduced to preserve more positional information through dual branches and embed the positional information into channel attention for precise localization of the low space ratio features. Finally, a small object loss feedback module is incorporated after the bidirectional feature pyramid network (BiFPN) for feature fusion, balancing the contribution of small object loss to the overall loss. Experimental comparisons on a battery cell casing dataset demonstrate that the proposed algorithm outperforms the EfficientDet-D1 object detection algorithm, with an average precision improvement of 4.23%. Specifically, for scratches with low space ratio features, the improvement is 13.21%; for wrinkles with low space ratio features, the improvement is 9.35%; and for holes with small object features, the improvement is 3.81%. Moreover, the detection time of 47.6 ms meets the requirements of practical production.
]]>Processes doi: 10.3390/pr12030600
Authors: Giulia Cestonaro Rodrigo Gonzalez-Ortega Antonella L. Grosso Ksenia Morozova Giovanna Ferrentino Matteo Scampicchio Enrico Costanzo
Driven by growing concerns about food supply and the environment, research on alternative protein sources has become increasingly important. In this context, de-oiled seed cakes, particularly soybean cakes, have emerged as a promising option. However, the conventional methods, such as organic solvent extraction, from which these cakes are obtained present several limitations. This study aims to evaluate the efficiency of supercritical fluid extraction (SFE) as an alternative method for de-oiling soybean seeds and obtaining related protein isolates. By using SFE for de-oiling, it was possible to achieve 19% more protein isolates from soybean cakes than the conventional de-oiling method using hexane. Moreover, protein isolates from the SFE de-oiled cake reported significantly improved (p < 0.05) emulsifying abilities and water absorption capacity. Gel electrophoresis and differential scanning calorimetry indicated the presence of a higher concentration of proteins in their native state in the SFE de-oiled flour. Finally, results from the sulfhydryl group content, surface hydrophobicity, and protein dispersibility index also supported these conclusions. The SFE process produced de-oiled soybean cakes with superior functional characteristics and lower environmental impact. Thus, this study provided important information for the food industry to develop more sustainable and healthier production methods.
]]>Processes doi: 10.3390/pr12030599
Authors: Wei-Jen Chen Chi-Jie Lu Pei-Ti Hsu Chih-Te Yang
The equipment in a factory will gradually deteriorate during production, leading to the production of defective products. Without appropriate maintenance, the defect rate will increase over time. Consequently, the production cost will rise, the inventory quality will be affected, the profit will decrease, and the risk of carbon emissions will increase, leading to more customer complaints and damaging the corporate image. In addition to focusing on preventive maintenance to ensure the quality of products, companies should also take carbon emissions into consideration. Furthermore, the frequency of maintenance must be carefully considered, as both carbon emissions and maintenance costs will increase if the frequency is too high; conversely, if the maintenance frequency is too low or non-existent, the defect rate may increase cumulatively, or production may be suspended due to equipment failure. Therefore, this research explores preventive maintenance and inventory management issues within an imperfect production system and develops an extended economic production quantity model that incorporates defective products as well as taking carbon tax and preventive maintenance into consideration. The main purpose is to determine the optimal maintenance frequency, production, and replenishment cycle length, so as to maximize the total profit under the carbon tax policy. This study demonstrates a computing process with relatively impractical product data based on the actual business situation of a disposable diaper manufacturer. Furthermore, a sensitivity analysis is implemented to the model parameters in the proposed model. The managemental insights are illustrated based on the results of theoretical analysis to provide a reference to policy makers during decision making, hence, to secure the sustainability and green transitions of corporates. The results of this study not only help to reduce environmental impact but can also improve the competitiveness and sustainable development of enterprises.
]]>Processes doi: 10.3390/pr12030598
Authors: Liyi He Xue Hu Lixin Zhang Feng Chen Xinwang Zhang
Heat-transfer enhancement and entropy generation were investigated for a double-helical-type-channel heat sink with different rib structures set on the upper wall. Based on available experimental data, a series of simulations with various turbulence models were conducted to find the best numerical model. Five different rib structures were considered, which were diamond (FC-DR), rectangular (FC-RR), drop-shaped (FC-DSR), elliptic (FC-ER) and frustum (FC-FR). The research was carried out under turbulent flow circumstances with a Reynolds number range of 10,000–60,000 and a constant heat-flow density. The numerical results show that the thermal performance of the flow channel set with a rib structure is better than that of the smooth channel. FC-ER offers the lowest average temperature and the highest temperature uniformity, with a Nusselt number improvement percentage ranging from 15.80% to 30.77%. Overall, FC-ER shows the most excellent performance evaluation criteria and lowest augmentation entropy-generation number compared with the other reinforced flow channels.
]]>Processes doi: 10.3390/pr12030597
Authors: Alexander S. Behr Julia Surkamp Elnaz Abbaspour Max Häußler Stephan Lütz Jürgen Pleiss Norbert Kockmann Katrin Rosenthal
The importance of biocatalysis for ecologically sustainable syntheses in the chemical industry and for applications in everyday life is increasing. To design efficient applications, it is important to know the related enzyme kinetics; however, the measurement is laborious and error-prone. Flow reactors are suitable for rapid reaction parameter screening; here, a novel workflow is proposed including digital image processing (DIP) for the quantification of product concentrations, and the use of structured data acquisition with EnzymeML spreadsheets combined with ontology-based semantic information, leading to rapid and smooth data integration into a simulation tool for kinetics evaluation. One of the major findings is that a flexibly adaptive ontology is essential for FAIR (findability, accessibility, interoperability, reusability) data handling. Further, Python interfaces enable consistent data transfer.
]]>Processes doi: 10.3390/pr12030596
Authors: Hamid Reza Rahimpour Jafar Zanganeh Behdad Moghtaderi
Fugitive methane emissions from the mining industry, particularly so-called ventilation air methane (VAM) emissions, are considered among the largest sources of greenhouse gas (GHG) emissions. VAM emissions not only contribute to the global warming but also pose a significant hazard to mining safety due to the risk of accidental fires and explosions. This research presents a novel approach that investigates the capture of CH4 in a controlled environment using 1-butyl-3-methylimidazolium bis (trifluoromethylsulfonyl) imide [BMIM][TF2N] ionic liquid (IL), which is an environmentally friendly solvent. The experimental and modelling results confirm that CH4 absorption in [BMIM][TF2N], in a packed column, can be a promising technique for capturing CH4 from point sources, particularly the outlet streams of ventilation shafts in underground coal mines, which typically accounts for <1% v/v of the flow. This study assessed the effectiveness of CH4 removal in a packed bed column by testing various factors such as absorption temperature, liquid and gas flow rates, flow pattern, packing size, desorption temperature, and desorption pressure. According to the optimisation results, the following parameters can be used to achieve a CH4 removal efficiency of 23.8%: a gas flow rate of 0.1 L/min, a liquid flow rate of 0.5 L/min, a packing diameter of 6 mm, and absorption and desorption temperatures of 303 K and 403.15 K, respectively. Additionally, the experimental results indicated that ILs could concentrate CH4 in the simulated VAM stream by approximately 4 fold. It is important to note that the efficiency of CH4 removal was determined to be 3.5-fold higher compared to that of N2. Consequently, even though the VAM stream primarily contains N2, the IL used in the same stream shows a notably superior capacity for removing CH4 compared to N2. Furthermore, CH4 absorption with [BMIM][TF2N] is based on physical interactions, leading to reduced energy requirements for regeneration. These findings validate the method’s effectiveness in mitigating CH4 emissions within the mining sector and enabling the concentration of VAM through a secure and energy-efficient procedure.
]]>Processes doi: 10.3390/pr12030595
Authors: Antreas Kantaros Theodore Ganetsos Florian Ion Tiberiu Petrescu Liviu Marian Ungureanu Iulian Sorin Munteanu
Additive manufacturing (AM) has revolutionized production across industries, yet challenges persist in achieving optimal part quality. This paper studies the enhancement of post-processing techniques to elevate the overall quality of AM-produced components. This study focuses on optimizing various post-processing methodologies to address prevalent issues such as surface roughness, dimensional accuracy, and material properties. Through an extensive review, this article identifies and evaluates a spectrum of post-processing methods, encompassing thermal, chemical, and mechanical treatments. Special attention is given to their effects on different types of additive manufacturing technologies, including selective laser sintering (SLS), fused deposition modeling (FDM), and stereolithography (SLA) and their dedicated raw materials. The findings highlight the significance of tailored post-processing approaches in mitigating inherent defects, optimizing surface finish, and enhancing mechanical properties. Additionally, this study proposes novel post-processing procedures to achieve superior quality while minimizing fabrication time and infrastructure and material costs. The integration of post-processing techniques such as cleaning, surface finishing, heat treatment, support structure removal, surface coating, electropolishing, ultrasonic finishing, and hot isostatic pressing (HIP), as steps directly within the additive manufacturing workflow can immensely contribute toward this direction. The outcomes displayed in this article not only make a valuable contribution to the progression of knowledge regarding post-processing methods but also offer practical implications for manufacturers and researchers who are interested in improving the quality standards of additive manufacturing processes.
]]>Processes doi: 10.3390/pr12030594
Authors: Changxiong Li Yihuai Hu Hao Guo
As a clean alternative fuel oil for marine engines, methanol has received increasing attention, but its low cetane number requires diesel ignition, which increases the difficulty of retrofitting existing engine fuel injection systems. Polymethoxy dimethyl ether (PODEn) is an ether fuel mixture whose chemical structural formula can be expressed as CH3O(CH2O)nCH3 (n≥2). PODE3 is the predominant component in the blend, and its properties are representative of the blend. PODE is a low-carbon fuel with a high cetane number and is easy to compression ignite, and, as such, can be used to ignite methanol in a marine diesel engine. This article explores the combustion mechanism of mixed methanol–PODE fuel using the characteristics of PODE that can be easily mixed with methanol for combustion. Taking methanol and PODE3 as representative fuels, the detailed combustion mechanism of PODE3 and the detailed combustion mechanism of methanol are simplified using a DRGEPSA (direct relationship graph with error propagation (DRGEP) and sensitivity analysis (SA)) method. Based on the target engine cylinder combustion environment, a simplified mechanism for mixed methanol–PODE fuel is obtained, and the new mechanism is validated in terms of the ignition delay period and laminar flame speed. The results indicate that the newly constructed simplified mechanism is basically consistent with the ignition delay data and flame propagation speed data measured by a rapid compression machine (RCM), laying the foundation for the application of alternative methanol fuels in marine engines.
]]>Processes doi: 10.3390/pr12030593
Authors: Claudio Urrea Daniel Saa John Kern
In this study, groundbreaking software has been developed to automate the generation of equations of motion for manipulator robots with varying configurations and degrees of freedom (DoF). The implementation of three algorithms rooted in the Lagrange–Euler (L-E) formulation is achieved through the utilization of .m files in MATLAB R2020a software.This results in the derivation of a symbolic dynamic model for industrial manipulator robots. To comprehend the unique features and advantages of the developed software, dynamic simulations are conducted for two 6- and 9-DoF redundant manipulator robots as well as for a 3-DoF non-redundant manipulator robot equipped with prismatic and rotational joints, which is used to simplify the dynamic equations of the redundant prototypes. Notably, for the 6-DoF manipulator robot, model predictive control (MPC) is employed using insights gained from the dynamic model. This enables optimal control by predicting the future evolution of state variables: specifically, the values of the robot’s joint variables. The software is executed to model the dynamics of different types of robots, and the CPU time for a MacBook Pro with a 3 GHz Dual-Core Intel Core i7 processor is less than a minute. Ultimately, the theoretical findings are validated through response graphs and performance indicators of the MPC, affirming the accurate functionality of the developed software. The significance of this work lies in the automation of motion equation generation for manipulator robots, paving the way for enhanced control strategies and facilitating advancements in the field of robotics.
]]>Processes doi: 10.3390/pr12030592
Authors: Rachel Irankunda Pauline Jambon Alexandra Marc Jairo Andrés Camaño Echavarría Laurence Muhr Laetitia Canabady-Rochelle
Chromatography modeling for simulation is a tool that can help to predict the separation of molecules inside the column. Knowledge of sorption isotherms in chromatography modeling is a crucial step and methods such as frontal analysis or batch are used to obtain sorption isotherm parameters, but they require a significant quantity of samples. This study aims to predict Langmuir isotherm parameters from Surface Plasmon Resonance (SPR) affinity data (requiring less quantity of sample) to simulate metal chelating peptides (MCPs) separation in Immobilized Metal ion Affinity Chromatography (IMAC), thanks to the analogy between both techniques. The validity of simulation was evaluated by comparing the peptide’s simulated retention time with its experimental retention time obtained by IMAC. Results showed that the peptide affinity constant (KA) can be conserved between SPR and IMAC. However, the maximal capacity (qmax) must be adjusted by a correction factor to overcome the geometry differences between IMAC (spherical particles) and SPR (plane sensor ship). Therefore, three approaches were studied; the best one was to use qmax,IMAC imidazole determined experimentally while a correction factor was applied on qmax,SPR to obtain the qmax,IMAC of the peptide, thus minimizing the discrepancy between the experimental and simulated retention times of a peptide.
]]>Processes doi: 10.3390/pr12030591
Authors: Joanna Żandarek Małgorzata Starek Monika Dąbrowska
Cefazolin is a first-generation cephalosporin used to treat severe infections of the respiratory tract, urinary tract, skin, and soft tissues. This study presents the optimal conditions for the determination of cefazolin by thin-layer chromatography with densitometric detection. A chloroform–methanol–glacial acetic acid mixture (6:4:0.5, v/v/v) was selected as the mobile phase, while TLC silica gel 60F254 plates were used as the stationary phase. Next, the developed procedure was validated in accordance with ICH guidelines. The obtained results showed that the method is selective, precise, and accurate in a linearity range of 0.04–1.00 µg/spot (r > 0.99). Subsequently, qualitative and quantitative analyses of formulations containing cefazolin were performed. It was found that the amount of antibiotic is highly consistent with the content declared by manufacturers. The suitability of the developed method for stability testing under varying environmental conditions was also verified. It was found that under the tested conditions, the degradation process follows first-order kinetics. The lowest stability was registered in an alkaline environment and in the presence of an oxidizing agent, and the highest stability was recorded in water, and these results were confirmed by the calculated kinetic parameters. The developed method can be used in qualitative and quantitative analyses and stability studies of the analyzed antibiotic.
]]>Processes doi: 10.3390/pr12030590
Authors: Dahlia Byles Patrick Kuretich Salman Mohagheghi
The problem of power grid capacity expansion focuses on adding or modernizing generation and transmission resources to respond to the rise in demand over a long-term planning period. Traditionally, the problem has been mainly viewed from technical and financial perspectives. However, with the rise in the frequency and severity of natural disasters and their dire impacts on society, it is paramount to consider the problem from a nexus of resilience, sustainability, and equity. This paper presents a novel multi-objective optimization framework to perform power grid capacity planning, while balancing the cost of operation and expansion with the life cycle impacts of various technologies. Further, to ensure equity in grid resilience, a social vulnerability metric is used to weigh the energy not served based on the capabilities (or lack thereof) of communities affected by long-duration power outages. A case study is developed for part of the bulk power system in the state of Colorado. The findings of the study show that, by considering life cycle impacts alongside cost, grid expansion solutions move towards greener alternatives because the benefits of decommissioning fossil-fuel-based generation outweigh the costs associated with deploying new generation resources. Furthermore, an equity-based approach ensures that socially vulnerable populations are less impacted by disaster-induced, long-duration power outages.
]]>Processes doi: 10.3390/pr12030588
Authors: Sandro Guadalupe Perez Grajales Angel Horacio Hernández David Juárez-Romero Guadalupe Lopez Lopez Gustavo Urquiza-Beltran
In this experimental work, a prototype of a hybrid solar–thermal–photovoltaic (HE-PV/T) heat exchanger has been designed, built, and characterized, with rectangular geometry and 12 fins inside, to obtain better heat flow and higher performance in order to achieve a better heat transfer coefficient, reducing and optimizing the working area. The heat exchanger contains 12 photovoltaic cells connected in series, with an angle of inclination of approximately 18° towards the south and a surface area of 0.22 m2, smaller than those available on the market, which individually capture 147.05 W/m2 as a photovoltaic panel and 240 W/m2 as a solar collector. Mathematical models found in the literature from previous work were used for the electrical and thermal evaluations. The temperature of the PV cells was reduced to 13.2 °C and the thermal level of the water was raised to a temperature above 70 °C, with a photovoltaic–thermal coupling power of 307.11 W and a heat transfer coefficient of 5790 W/m2 °C. The efficiencies obtained were as follows: thermal up to 0.78 and electrical up to 0.095. The novelty of these results was achieved in a reduced space of 40% less than those reported and available on the market.
]]>Processes doi: 10.3390/pr12030589
Authors: Zhouqing Tan Yuanyuan Li Feifei Chen Jiashu Liu Jianxiong Zhong Li Guo Ran Zhang Rong Chen
The pyrolysis process is a thermochemical conversion reaction that encompasses an intricate array of simultaneous and competitive reactions occurring in oxygen-depleted conditions. The final products of biomass pyrolysis are bio-oil, biochar, and some gases, with their proportions determined by the pyrolysis reaction conditions and technological pathways. Typically, low-temperature slow pyrolysis (reaction temperature below 500 °C) primarily yields biochar, while high-temperature fast pyrolysis (reaction temperature 700–1100 °C) mainly produces combustible gases. In the case of medium-temperature rapid pyrolysis (reaction temperature around 500–650 °C), conducted at very high heating rates and short vapor residence times (usually less than 1 s), the maximum liquid yield can reach up to 85 wt% (on a wet basis) or achieve 70 wt% (on a dry basis), with bio-oil being the predominant product. By employing the pyrolysis technique, valuable utilization of tobacco stem waste enriched with lignin can be achieved, resulting in the production of desired pyrolysis products such as transportation fuels, bio-oil, and ethanol. The present review focuses on catalytic pyrolysis, encompassing catalytic hydropyrolysis and catalytic co-pyrolysis, and meticulously compares the impact of catalyst structure on product distribution. Initially, we provide a comprehensive overview of the recent pyrolysis mechanism of lignin and tobacco waste. Subsequently, an in-depth analysis is presented, elucidating how to effectively design the catalyst structure to facilitate the efficient conversion of lignin through pyrolysis. Lastly, we delve into other innovative pyrolysis methods, including microwave-assisted and solar-assisted pyrolysis.
]]>Processes doi: 10.3390/pr12030587
Authors: Zhe Fan Xiusen Liu Zuoqian Wang Pengcheng Liu Yanwei Wang
Petroleum production forecasting involves the anticipation of fluid production from wells based on historical data. Compared to traditional empirical, statistical, or reservoir simulation-based models, machine learning techniques leverage inherent relationships among historical dynamic data to predict future production. These methods are characterized by readily available parameters, fast computational speeds, high precision, and time–cost advantages, making them widely applicable in oilfield production. In this study, time series forecast models utilizing robust and efficient machine learning techniques are formulated for the prediction of production. We have fused the two-stage data preprocessing methods and the attention mechanism into the temporal convolutional network-gated recurrent unit (TCN-GRU) model. Firstly, the random forest (RF) algorithm is employed to extract key dynamic production features that influence output, serving to reduce data dimensionality and mitigate overfitting. Next, the mode decomposition algorithm, complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), is introduced. It employs a decomposition–reconstruction approach to segment production data into high-frequency noise components, low-frequency regular components and trend components. These segments are then individually subjected to prediction tasks, facilitating the model’s ability to capture more accurate intrinsic relationships among the data. Finally, the TCN-GRU-MA model, which integrates a multi-head attention (MA) mechanism, is utilized for production forecasting. In this model, the TCN module is employed to capture temporal data features, while the attention mechanism assigns varying weights to highlight the most critical influencing factors. The experimental results indicate that the proposed model achieves outstanding predictive performance. Compared to the best-performing comparative model, it exhibits a reduction in RMSE by 3%, MAE by 1.6%, MAPE by 12.7%, and an increase in R2 by 2.6% in Case 1. Similarly, in Case 2, there is a 7.7% decrease in RMSE, 7.7% in MAE, 11.6% in MAPE, and a 4.7% improvement in R2.
]]>Processes doi: 10.3390/pr12030586
Authors: He Li Yizhuo Wang Yujie Luo Chang Jiang Ziheng Yang
Aiming at the problem of low pollutant concentration in the sewage treatment plant due to external water intrusion into the sewage collection system, which in turn leads to low pollutant reduction efficiency. A sewage system in Zhenjiang City is taken as an example. Analyze the situation of external water intrusion in the sewage pipe network and determine the external water intrusion proportion based on the water quality and quantity method. First, the dry season flow rate of the sewage pipe is obtained according to the monitoring data of the flowmeter. Then, the key research areas are screened out based on the changes in the concentration of water quality characteristic factors. Furthermore, chemical oxygen demand and electrical conductivity are used as water quality characteristic indicators to characterize shallow groundwater and river water. In addition, the proportions of groundwater and river water intrusion in the sewage pipe network are quantitatively analyzed based on the chemical mass balance equation. At the same time, the dredging detection method is used to assist in the investigation, and finally, the engineering rectification of the problems found in the drainage is carried out. The results show that the water quality and quantity method can effectively identify the types of external water and analyze the proportion of external water intrusion, which is of exemplary significance for the evaluation of sewage collection systems.
]]>Processes doi: 10.3390/pr12030585
Authors: Meiqi Yu Hongliang Luo Beini Zhou Yang Liu Chang Zhai Keiya Nishida Jun-Cong Ge
Renewable natural gas (RNG) is attractive for energy policy goals in the world. Therefore, a regional system is designed to explore RNG combustion for power generation in localities. This study investigates a direct injection (DI) engine fueled with hydrogen (H2) blended into the simulated renewable natural gas, which consists of 50% methane (CH4) and 50% carbon dioxide (CO2) in volume. In order to obtain higher efficiency, comparisons between DI and port fuel injection (PFI) of H2 addition were made. Then, the volume percentage of H2 was changed from 20% to 100% by keeping the volume ratio of CH4 and CO2 at 1:1. Finally, results of power output, brake mean effective pressure (BMEP), brake thermal efficiency (BTE) and brake specific fuel consumption (BSFC) were discussed. Results showed that in contrast to PFI, H2 DI injection could increase efficiency by 4%. Additionally, H2 DI could retard the MBT ignition timing at 5 °CA. Compared with CH4/CH4 + CO2 combustion, under stoichiometric combustion, BMEP increases with H2 addition but BTE decreases significantly. However, by enlarging the excess air ratio (λ) to 1.24, both BMEP and BTE increase obviously with H2 addition. Moreover, when λ < 1.3, the MBT ignition timing should be advanced from −10 to 15 °CA top dead center (TDC). But the MBT ignition timing is fixed at −25 °CA TDC when λ is larger than 1.3. Furthermore, if efficiency is the priority, 30% H2 addition with λ at 1.24 (−15 °CA TDC) should be selected. If higher BMEP is preferred, 20% H2 addition with λ at 0.99 (−10 °CA TDC) should be selected.
]]>Processes doi: 10.3390/pr12030584
Authors: Serkan Çaşka Mete Özbaltan
In engineering, cost minimization, especially in Computer Numerical Control (CNC) machining like pocket milling, is crucial. Existing tool path definition software often lacks optimization, particularly at critical starting and ending points. This study optimizes CNC machine tool paths for energy-efficient multi-pocket milling, utilizing the Symbolic Discrete Control Synthesis (SDCS) method for formal correctness. In our work, the tool path generation is formulated as a traveling salesman problem. We introduce a modeling framework to adapt SDCS to multi-pocket-milling processes, aiming to enhance precision and efficiency for potential cost savings, including energy and time, in engineering applications. This study reports experimental and comparative results, where comparative evaluations were made using metaheuristic algorithms. Our proposed approach improves CNC machining processes for multi-pocket milling. We experimentally evaluate our control algorithms and demonstrate and validate our approach through case studies.
]]>Processes doi: 10.3390/pr12030583
Authors: Milica Karadžić Banjac Strahinja Kovačević Sanja Podunavac-Kuzmanović
In this review, papers published in the chemometrics field were selected in order to gather information and conduct a systematic review regarding food science and technology; more precisely, regarding the domain of bioactive compounds and the functional properties of foods. More than 50 papers covering different food samples, experimental techniques and chemometric techniques were selected and presented, focusing on the chemometric methods used and their outcomes. This study is one way to approach an overview of the current publications related to this subject matter. The application of the multivariate chemometrics approach to the study of bioactive compounds and the functional properties of foods can open up even more in coming years, since it is fast-growing and highly competitive research area.
]]>Processes doi: 10.3390/pr12030581
Authors: Athanasia Kourelatou Theodoros Chatzimitakos Vassilis Athanasiadis Konstantina Kotsou Ioannis Makrygiannis Eleni Bozinou Stavros I. Lalas
The dried flowers of Hibiscus sabdariffa (HS), available worldwide, have various applications in both non-medicinal and medicinal fields. The growing global interest in the health benefits of HS is linked to its potential prevention or management of non-communicable diseases. The aim of this research was to find the optimal extraction method that ensures the maximum yield of multiple beneficial bioactive components, such as polyphenols, anthocyanins, vitamin C, β-carotene, antioxidant activity, free radical scavenging activity DPPH and ferric reducing antioxidant power (FRAP). To this end, stirring, pulsed electric field, and ultrasound-assisted extraction were evaluated, either alone or in combination. Under optimized extraction conditions, the obtained extract exhibited an elevated total polyphenol content (37.82 mg of gallic acid equivalents/g dry weight (dw)), total anthocyanin content (610.42 μg of cyanidin equivalents/g dw), total carotenoids content (921.84 μg of β-carotene equivalents/g dw), and ascorbic acid content (507.44 mg/100 g dw). Remarkably, the extracts exhibited strong antioxidant properties (487.51 μmol of ascorbic acid equivalents (AAE)/g dw and 243.42 μmol AAE/g dw as evidenced by FRAP and DPPH assays, respectively). This research advances the parameters that should be employed to produce the optimal and nutritionally enhanced HS flower extracts, that can be used in the commercial sector.
]]>Processes doi: 10.3390/pr12030582
Authors: Andrea Špačková Katarína Hroboňová Michal Jablonský
In this study, adsorbents based on molecularly imprinted polymers (MIPs) in two solid-phase extraction application forms, pipette tip and magnetic extraction, were used for the selective extraction of coumarins. The pipette-tip solid-phase extraction reduced solvent volumes; the magnetic MIP extraction was simple and effective for phase separation. Parameters affecting extraction, such as the amount of adsorbent, type of washing solvent, volume of the elution solvent, and extraction times for magnetic extraction, were optimized. The MIP-based adsorbents displayed high selectivity and extraction efficiency, resulting in recoveries ranging from 70.3 to 102.0% (RSD % less than 5.5%) for five coumarins under study, 6,7-dihydroxycoumarin-6-β-D-glucoside, coumarin, 7-methoxycoumarin, 6-methylcoumarin, and dicoumarol. The extracts were analyzed by high-performance liquid chromatography with diode array (DAD) and fluorescence (FLD) detectors, reaching limits of quantification of 0.5 and 0.9 µg·mL−1 for coumarin and dicoumarol detected by DAD and 0.001–0.012 µg·mL−1 for the other prohibited simple coumarins when used as a fragrance (detected by FLD). The proposed method was validated and its applicability was shown for the analysis of cosmetic samples like shower gel and perfume.
]]>Processes doi: 10.3390/pr12030579
Authors: Lin Guo Xiao Wang Weili Yang Jing Lv
The steel industry in China, the world’s largest, contributes to about 15% of the nation’s total carbon emissions. Instead of direct combustion, the technology of converting off-gas from the steel industry into liquid fuels not only enhances the added value of this byproduct but also helps alleviate carbon emissions. This study, for the first time, integrates the specific circumstances of China to evaluate the carbon emissions of Ethanol to Jet (ETJ) and Fischer–Tropsch to Jet (FTJ) fuel technologies utilizing Basic Oxygen Furnace Gas (BOFG) and Coke Oven Gas (COG) as feedstocks. Six cases were examined using Aspen Plus (V11) for mass and energy balance: Case 1: BOFG/ETJ, Case 2: BOFG/FTJ, Case 3: COG/ETJ, Case 4: COG/FTJ, Case 5: (COG + BOFG)/ETJ, and Case 6: (COG + BOFG)/FTJ. The analysis underscores that the FTJ pathway exhibits superior carbon reduction efficiency relative to ETJ. Compared to traditional petroleum-based aviation fuels (86.65 g CO2eq/MJ), the FTJ pathways utilizing COG or COG + BOFG as feedstocks exhibit significant advantages in greenhouse gas (GHG) emission reductions, with carbon emissions of 23.60 g CO2eq/MJ and 41.48 g CO2eq/MJ, respectively, representing reductions of 72.76% and 52.13%. Furthermore, employing uncertainty analysis based on the Monte Carlo method establishes the credibility of the findings. Finally, sensitivity analysis for parameter optimization and process improvements demonstrates the significant impact of the life cycle assessment (LCA) allocation method on computational results for exhaust gas feedstocks. Given the limited coverage of lifecycle assessments for Ethanol to Jet and Fischer–Tropsch to Jet pathways in China, this study could assist policymakers in determining the development trajectory of sustainable aviation fuel (SAF) in China.
]]>Processes doi: 10.3390/pr12030580
Authors: Marcus Rothhaupt Lucas Vogt Leon Urbas
Mass customization, small batch sizes, high variability of product types and a changing product portfolio during the life cycle of an industrial plant are current trends in the industry. Due to an increasing decoupling of the development of software and hardware components in an industrial context, compatibility problems within industrial control systems arise more and more frequently. In this publication, a strategy concept for compatibility testing is derived and discussed by means of a literature review and applied research. This four-phase strategy concept identifies incompatibilities between software and hardware components in the industrial control environment and enables test engineers to detect problems at an early stage. By automating the compatibility test on an external I-PC, the test can be run both when new software is installed on the industrial controller and when the controller is restarted. Thus, changes to the components are constantly detected and incompatibilities are avoided. Furthermore, early incompatibility detection can ensure that a system remains permanently operational. Based on a discussion, additional strategies are identified to consolidate the robustness and applicability of the presented concept.
]]>Processes doi: 10.3390/pr12030578
Authors: Ruixue Jia Liang Zhu Xiaoping Song Jian Chen
Both domestic and international scholars have conducted in-depth research on wellbore stability issues. They have established various empirical models, analytical models, and numerical simulation methods. However, there is relatively little research on the impact of the uncertainty of input parameters on wellbore stability, and the understanding of this aspect remains unclear. To address this, this paper introduces a probability distribution method. It is based on a wellbore stability mechanical analytical model and, using reliability theory, establishes a method for evaluating wellbore instability risks. By employing the Monte Carlo random simulation method, this study investigates the sensitivity of input parameters to wellbore stability, clarifying that ground stress is the main controlling factor affecting wellbore stability. Combining the analysis of the “felt layer” ground stress profile, this study utilizes two-dimensional simulation experiments to validate the accurate determination of ground stress magnitude in wellbore stability analysis. It also examines the impact of reducing its uncertainty. The results show that this approach significantly reduces the risk of wellbore instability, addressing the challenging issue of identifying wellbore instability in the Qiu Dong Depression’s “felt layer” within the TH Basin.
]]>Processes doi: 10.3390/pr12030577
Authors: Maja Repajić Ivona Elez Garofulić Nina Marčac Duraković Marta Balun Karla Cegledi Ena Cegledi Erika Dobroslavić Verica Dragović-Uzelac
In this study, fennel essential oil (EO) was spray-dried, varying the wall material type (two-component blends of maltodextrin (MD), β-cyclodextrin (β-CD) and gum arabic (GA)), the wall material ratio (1:1, 1:3 and 3:1) and the drying temperature (120, 160 and 200 °C). A total of 27 powders were analyzed for their moisture content, solubility, hygroscopicity, bulk density and particle size, while powder recovery and oil retention were determined in terms of encapsulation efficiency. The morphology and chemical composition of the powder obtained under optimal conditions were additionally analyzed by scanning electron microscopy and gas chromatography-mass spectrometry. The results showed that all of the powders had generally good properties, exhibiting a low moisture content, high powder recovery and high oil retention. A 1:3 MD:GA mixture and a drying temperature of 200 °C were found to be optimal for the spray-drying of fennel EO, producing a powder with a low moisture content (3.25%) and high solubility (56.10%), while achieving a high powder recovery (72.66%) and oil retention (72.11%). The chemical profiles of the initial and encapsulated fennel EO showed quantitative differences without qualitative changes, with an average 24.2% decrease in the volatiles in the encapsulated EO. Finally, spray-drying proved to be a successful tool for the stabilization of fennel EO, at the same time expanding the possibilities for its further use.
]]>Processes doi: 10.3390/pr12030576
Authors: Boliang Xu Qi Liu Zuchao Zhu Yongcao Gao Chuancang Li Yuanding Zhang
A gear pump is a key rotary-displacement pump for aircraft fuel transportation in the aerospace industry. Due to the great ratio of power-to-weight condition demanded for gear pumps in aircraft fuel transportation systems, the parameter of the rotation speed is a matter of extreme concern affecting internal flow characteristics that determines the adverse effects of cavitation, fuel trapping, and vibration. However, the flow characteristics of an aircraft fuel gear pump influenced by the rotation speed have not been elaborated upon on yet. In this research, the flow characteristics of an aircraft fuel gear pump were studied by considering the influence of the rotation speed. An experiment for testing the external performance of an aircraft fuel gear pump was performed, and a corresponding numerical simulation of a gas–liquid two-phase flow was employed. Distributions of the velocity and pressure at the central cross-sections and their monitored transient developments were comparatively analyzed for different rotation speeds. It was found that a greater pressure oscillational amplitude accompanied by a higher frequency could be induced by a higher rotation speed, especially in the region of gear engagement. Additionally, cavitation evolution characteristics affected by the rotation speed in the fuel gear pump were discussed. The mechanism of cavitation generation in the region of gear engagement to withdrawal was revealed to be the quick release of a great amount of pressure. Furthermore, a dimensionless cavitation area was employed to quantify the periodic cavitation evolution, and the natural exponential development of the maximum dimensionless cavitation area with the rotation speed was determined through curve fitting. This study should be helpful for creating a deeper understanding of the internal flow characteristics of an aircraft fuel gear pump in scientific research and the external performance in aerospace industrial applications.
]]>Processes doi: 10.3390/pr12030575
Authors: Lanxia Zhang Xuexing Ding Shipeng Wang Shuai Zhang Junhua Ding
Concerning the application of high-precision, enormous rotating equipment under harsh working conditions, the advantages of dry gas sealing technology are increasingly obvious. Herein, research on the dynamic stability of dry gas seals is reviewed based upon their operating mechanisms. The influence of the dry gas seal structure, vibration response, and dynamic followability on the reliability of the shaft end sealing system of rotating machinery is the focus of current dry gas sealing technology. This work reviews the research history; analyzes the key coefficient of the instability of the sealing system under external disturbances, and the existing research on stability models; discusses the influence of starting and stopping characteristics, working conditions, and groove parameters on the stability of dry gas seals; and points out the shortcomings in the existing research. In addition, potential developments in dynamic stability are proposed, including improving model accuracy, improving experimental techniques, or applying intelligent control and optimization methods to enhance the dynamic stability of the sealing system. Finally, the development prospects for dry gas sealing technology in intelligent monitoring and wide temperature range adaptations are discussed, and theoretical guidance for improving a dry gas seal system is provided.
]]>Processes doi: 10.3390/pr12030574
Authors: Wenqi Zhu Yu Liang Lv Zhao
Oil casings and premium threaded connections play vital roles in the oil and gas extraction industry. The present work establishes an integrated modeling framework for the sealability assessment of premium threaded connections which can be easily implemented and employed by engineers. The framework incorporates a part-scale finite element analysis of the make-up process, a micro-scale simulation of the contact behavior, and a mechanism-informed gap flow model. It is found that complete sealing can be achieved when the contact pressure exceeds 1540 MPa for Gaussian rough surfaces presenting a roughness of 1.6 μm. The seal surface fit is revealed to be critical for sealing performance, as it slightly changes the optimum make-up torque (up to 4%) but significantly changes contact pressure (up to 22%). At an optimum make-up torque, the connection with the loosest seal surface tolerance fit is prone to gas leakage when considering an inlet pressure of 110 MPa. The proposed modeling framework can be extended to other types of threaded connections with metal–metal contact sealing.
]]>Processes doi: 10.3390/pr12030573
Authors: Mustafa Kemal Gümüş Mykola Yu. Gorobets Nesimi Uludag
The effect of the molar ratio between reagents, reaction time and temperature on the yield of 5-substituted 3-amino-1,2,4-triazoles obtained by the direct condensation of carboxylic acids with aminoguanidine bicarbonate under acid catalysis conditions was studied. As a result, a general green straightforward synthesis of the title compounds bearing aliphatic substituents or a phenyl ring was developed using sealed reaction vials under controlled microwave synthesis conditions that are suitable for the application of volatile starting carboxylic acids. Our straightforward synthetic method proposed in this work increases the synthetic accessibility of these widely used building blocks and therefore is able to significantly expand the structural diversity of compounds containing a triazole moiety for the needs of drug discovery.
]]>Processes doi: 10.3390/pr12030572
Authors: Hongyang Zhang Junzhen Gong Xiaori Liu Wen Sun Ke Sun Shuzhan Bai
The arrangement of a pit-shaped surface texture on the surface of a cylinder liner significantly affects reductions in piston ring friction, and the influence of the structural parameters and spatial distribution on piston ring friction power consumption is unclear. In this paper, the diameter, depth, axial spacing distance, and radial spacing distance of the pits on the inner surface of a cylinder liner were used as variable parameters to process the surface textures of different schemes, and then a friction and wear test was carried out on UMT piston ring–cylinder liner specimens, several texture schemes with the best anti-friction effect were selected, an engine bench test was carried out by comparing these texture schemes with non-texture schemes, and the frictional torque and fuel consumption of the engine were studied at different oil temperatures. The results show that the depth of the pits in the surface texture of a cylinder liner has a greater influence on the friction reduction effect, followed by the radius. The higher the oil temperature in the engine bench test, the greater the impact of the surface texture. The reduction in fuel consumption was greater in the lower-speed region after structuring the textured cylinder liner compared to the non-textured cylinder liner. Specifically, the friction coefficient was mainly affected by the depth of the pits, and the depths of the pits in the texture schemes with good friction reduction effect were all 17–19 μm. The best friction reduction could be achieved when the pit radius is around 50 μm, with little difference in pit depth. When the oil temperature was 95 °C, the average drag torque reduction was about 1.69 Nm; when the oil temperature was 105 °C, the decrease was about 2.54 Nm; and when the oil temperature was 105 °C, the decrease was about 4.53 Nm. After adding the surface texture of the cylinder liner, the fuel consumption rate of the engine equipped with the structured cylinder liner was generally reduced compared with that of the original cylinder liner engine. Among them, the average and subsequent consumption rate of surface assembly scheme 11 decreased the most, with a value of 1.3 g/kwh.
]]>Processes doi: 10.3390/pr12030571
Authors: Heng Zhang Mibang Wang Wenqi Ke Xiaolong Li Shengjun Yang Weihua Zhu
Kazakhstan has abundant resources of low-permeability oil reservoirs, among which the KKM low-permeability oil reservoir has geological reserves of 3844 × 104 t and a determined recoverable reserve of 1670 × 104 t. However, the water flooding efficiency is only 68%, and the recovery efficiency is as low as 32%. The development of the reservoir faces challenges such as water injection difficulties and low oil production from wells. In order to further improve the oil recovery rate of this reservoir, our team developed micro-pressure-driven development technology based on pressure-driven techniques by integrating theories of fluid mechanics and artificial intelligence. We also combined this with subsequent artificial lift schemes, resulting in a complete set of micro-pressure-driven process technology. The predicted results indicate that after implementing micro-pressure-driven techniques, a single well group in the KKM oilfield can achieve a daily oil production increase of 32.08 t, demonstrating a good development effect.
]]>Processes doi: 10.3390/pr12030569
Authors: Nawaf S. Alqahtani Turki A. Alrefai Abdulaziz M. Almutlaq Saeed M. Alzahrani Ahmed E. Abasaeed
In this research work, an attempt has been made to address the heat and power integration opportunities for the process of the chlorination of benzene. This process produces a mixture of chlorobenzenes. To increase the production of the dichlorobenzene portion, the ratio of chlorine to benzene is typically 2:1. A process simulation model is designed using Aspen Plus for the production of 70,000 tons/year of dichlorobenzene via the reaction of liquid benzene with gaseous chlorine. Energy analysis is performed for the effective utilization of the utilities by networking the heat exchangers. This modification reduced the process heating and cooling requirements by 56.7% and 12.7%, respectively, and a reduction by 35.4% in the operating costs is achieved, while the annualized fixed cost increased by 9.6%; these changes resulted in savings in the total annual costs of about 10.9%.
]]>Processes doi: 10.3390/pr12030570
Authors: Subbu Venkata Satyasri Harsha Pathapati Rahulkumar Sunil Singh Michael L. Free Prashant K. Sarswat
Rare earth elements (REEs including Sc, Y) are critical minerals for developing sustainable energy sources. The gradual transition adopted in developed and developing countries to meet energy targets has propelled the need for REEs in addition to critical metals (CMs). The rise in demand which has propelled REEs into the spotlight is driven by the crucial role these REEs play in technologies that aim to reduce our carbon footprint in the atmosphere. Regarding decarbonized technologies in the energy sector, REEs are widely applied for use in NdFeB permanent magnets, which are crucial parts of wind turbines and motors of electric vehicles. The underlying motive behind exploring the energy and carbon footprint caused by REEs production is to provide a more complete context and rationale for REEs usage that is more holistic. Incorporating artificial intelligence (AI)/machine learning (ML) models with empirical approaches aids in flowsheet validation, and thus, it presents a vivid holistic picture. The energy needed for REEs production is linked with the source of REEs. The availability of REEs varies widely across the globe. REEs are either produced from ores with associated gangue or impurities. In contrast, in other scenarios, REEs can be produced from the waste of other mineral deposits or discarded REEs-based products. These variations in the source of feed materials, and the associated grade and mineral associations, vary the process flowsheet for each type of production. Thus, the ability to figure out energy outcomes from various scenarios, and a knowledge of energy requirements for the production and commercialization of multiple opportunities, is needed. However, this type of information concerning REEs production is not readily available as a standardized value for a particular material, according to its source and processing method. The related approach for deciding the energy and carbon footprint for different processing approaches and sources relies on the following three sub-processes: mining, beneficiation, and refining. Some sources require incorporating all three, whereas others need two or one, depending on resource availability. The available resources in the literature tend to focus on the life cycle assessment of REEs, using various sources, and they focus little on the energy footprint. For example, a few researchers have focused on the cumulative energy needed for REE production without making assessments of viability. Thus, this article aims to discuss the energy needs for each process, rather than on a specific flowsheet, to define process viability more effectively regarding energy need, availability, and the related carbon footprint.
]]>Processes doi: 10.3390/pr12030568
Authors: Piao Long Bin Shi Yunxing Cao Yufei Qi Xinyi Chen Liuyang Li
The wettability of coal is an important factor influencing hydraulic stimulation. Field-trial data has proven that high-pressure N2 injection plays a positive role in increasing the coalbed methane (CBM) production rate. For the purpose of investigating the mechanism by which N2 promotes the gas rate, multiple experiments were conducted sequentially on the wettability of anthracite under different N2 pressures. Testing of the coal surface contact angle was conducted under 0.1–8 MPa nitrogen pressure using a newly built contact angle measuring device. The coal samples were collected from the Xinjing Coal Mine in the Qinshui Basin, China. The test results revealed that the contact angle increased with increasing N2 pressure. That is, the contact angle was 77.9° at an N2 pressure of 0.1 MPa and gradually increased to 101.4° at an infinite N2 pressure. In contrast, the capillary pressure decreased with an increasing N2 pressure, from 0.298 MPa to −0.281 MPa. The relationship between the contact angle and N2 pressure indicates a reversal of the wettability, at 5.26 MPa, with a contact angle of 90° and a capillary pressure of 0 MPa. The capillary pressure reversed to a negative value as the N2 pressure increased. At the microlevel, a high N2 pressure increases the surface roughness of coal, which improves the ability of the coal matrix to adsorb N2, forming the gas wall that hinders the intrusion of water into the pores of the coal matrix. The results of this study provide laboratory evidence that high-pressure N2 injection can prevent water contamination and reduce the capillary pressure, thus benefiting coalbed methane production.
]]>Processes doi: 10.3390/pr12030566
Authors: Yuqiang Yang Yu Wang Zhaoyang Xu Baojiang Xie Yong Hu Jiatao Yu Yehong Chen Ting Zhang Zhenneng Lu Yulie Gong
In order to develop a highly efficient and stable high-temperature heat pump to realize high-efficient electrification in the industrial sector, performance of high-temperature heat pumps with a flash tank vapor injection and sub-cooler vapor injection are compared under different evaporation temperatures, condensation temperatures, compressor suction superheat degrees, subcooling degrees and compressor isentropic efficiencies. The results show that the COP, injection mass flow ratio and VHC of the FTVC are higher than those of the SVIC-0, SVIC-5, SVIC-10 and SVIC-20 under the same working conditions, while the discharge temperature of the FTVC is approximately equal to that of the SVIC-0 and lower than those of the SVIC-5, SVIC-10 and SVIC-20. When the evaporation temperature, the condensation temperature and injection pressure are 55 °C, 125 °C and 921.4 kPa, respectively, the system COP of the FTVC is 4.49, which is approximately 6.7%, 7.3%, 7.8% and 8.9% higher than those of the SVIC-0, SVIC-5, SVIC-10, and SVIC-20, respectively.
]]>Processes doi: 10.3390/pr12030567
Authors: Kochakon Moonsub Phisit Seesuriyachan Dheerawan Boonyawan Wassanai Wattanutchariya
The use of integrated plasma-activated water (PAW) with micro/nanobubbles (MNBs), ultraviolet (UV) photolysis, and ultrasonication (US) for the synergistic efficiency of Escherichia coli inactivation in chicken meat was investigated. A 2k factorial design was employed to optimize the combined treatment parameters for pathogen disinfection in Design of Experiments (DOE) techniques. Its effectiveness was evaluated based on electrical conductivity (EC), oxidation–reduction potential (ORP), hydrogen peroxide (H2O2) concentration, and E. coli inactivation. The most significant impact on E. coli reduction was observed for MNBs, UV treatment time, and their interaction (MNBs and UV). Optimal E. coli inactivation (6 log10 CFU/mL reduction) was achieved by combining PAW with MNB and UV for 10 and 20 min, respectively. Integrating PAW with appropriate supplementary technologies enhanced E. coli inactivation by 97% compared to PAW alone. This novel approach provides a promising alternative for pathogen control in chicken meat, potentially improving food safety and shelf life in the poultry industry.
]]>Processes doi: 10.3390/pr12030564
Authors: Chao Huang Xuewei Chao Weiji Zhou Lijiao Gong
To achieve effective and accurate segmentation of photovoltaic panels in various working contexts, this paper proposes a comprehensive image segmentation strategy that integrates an improved Meanshift algorithm and an adaptive Shi-Tomasi algorithm. This approach effectively addresses the challenge of low precision in segmenting target regions and boundary contours in routine photovoltaic panel inspection. Firstly, based on the image information of photovoltaic panels collected under different environments by cameras, an improved Meanshift algorithm based on platform histogram optimization is used for preliminary processing, and images containing target information are cut out; then, the adaptive Shi-Tomasi algorithm is used to extract and screen feature points from the target area; finally, the extracted feature points generate the segmentation contour of the target photovoltaic panel, achieving accurate segmentation of the target area and boundary contour of the photovoltaic panel. Experiments verified that in photovoltaic panel images under different background environments, the method proposed in this paper enhances the accuracy of segmenting the target area and boundary contour of photovoltaic panels.
]]>Processes doi: 10.3390/pr12030565
Authors: Rafal Kozdrach
This study shows the experimental data obtained by Raman spectroscopy to evaluate the structural changes of vegetable lubricants modified with montmorillonite after tribological tests. The analysis of the friction factor and limiting load of wear in the test for the examined grease compound shows a substantial effect on this parameter for grease. A change in the evaluated tribo-parameter results in a modification of the structure of the tested lubricant and changes in the protection efficiency of the tribological system. The amount of thickener, oil base and additive in the grease structure has an influence on the value of anti-wear properties, as shown by the data obtained in the tribological test described in this paper. The Raman spectroscopy tests showed that, in the tribological processes, some of the ingredients undergo an oxidative reaction, which leads to the formation of oxygenated organic substances that form an organic layer on the metal surface and counteract the wear of the lubricated contact surfaces. Other compounds come into close contact with the tribological layer, which increases its ability to resist wear and shear. The efficiency of the used additive is based on the formation (during friction) of a low-shear and high-plastic-strength thin film which is chemically highly bonded to the material and has a high level of durability against wear processes. As a consequence of the thermal decomposition of the additive, chemical interactions occur among the ingredients of the material of the substrate and the lubricants.
]]>Processes doi: 10.3390/pr12030562
Authors: Jiayu Qian Jubin Zhang Ting Lei Silin Li Chen Sun Guanghua He Bin Wen
Polymerization products are indispensable for our daily life, and the relevant modeling process plays a vital role in improving product quality. However, the model identification of the related process is a difficult point in industry due multivariate, nonlinear and time-varying characteristics. As for the conventional offline subspace identification methods, the identification accuracy may be not satisfying. To handle such a problem, an enhanced on-line recursive subspace identification method is presented on the basis of principal component analysis and sliding window (RSIMPCA-SW) in this paper to obtain the state space model for polymerization. In the proposed on-line subspace identification approach, the initial L-factor is acquired by the LQ decomposition of the sampled historical data, firstly, and then it is updated recursively through the bona fide method after the new data have been handled by the sliding window rule. Subsequently, principal component analysis (PCA) is introduced to calculate the extended observation matrix, and finally the on-line model parameters are extracted. Compared with the traditional subspace schemes, smaller computation complexity and higher identification precision are anticipated in the proposed method. A case study on the modeling of the ethylene polymerization verifies the effectiveness of the developed approach, in which the related statistical indexes of the obtained identification model are better.
]]>Processes doi: 10.3390/pr12030563
Authors: Abdulaziz Y. Alammar Seung-Hak Choi Maria Giovanna Buonomenna
Hollow fiber (HF) organic solvent nanofiltration (OSN) membranes have recently attracted significant interest in the field of membrane technology. Their popularity stems from comparative advantages, such as high packing density, fouling resistance, and easier scalability for larger applications, unlike flat-sheet/spiral-wound OSN membranes, which may present challenges in these aspects. The combination of interfacial polymerization (IP) and HF configuration has opened up new opportunities for developing advanced membranes with enhanced separation performance that can be tailored for various OSN applications. The objective of this review is to discuss the latest advancements in developing thin film composite (TFC) HF membranes, with a focus on the IP method. Novel materials and processes are discussed in detail, emphasizing the fabrication of greener, interfacially polymerized HF OSN membranes. In addition, the commercial viability and limitations of TFC HF membranes are highlighted, providing perspectives on future research directions.
]]>Processes doi: 10.3390/pr12030560
Authors: Caio Henrique da Silva Thiago Peixoto de Araújo Alexandre Teixeira de Souza Mara Heloisa Neves Olsen Scaliante Wardleison Martins Moreira
Moringa oleifera seeds, in particular, have been used for water and wastewater treatment due to their ability to remove many pollutants. Therefore, the present work aims to produce bioadsorbent materials by pyrolysis using biomass from the seed shell of Moringa oleifera to remove the drug Metronidazole present in an aqueous medium. The biochars produced were activated with phosphoric acid (H3PO4) and potassium hydroxide (KOH) to compare the material’s modifications and adsorption mechanisms with the biochar in nature (BCM). The biochars were characterized by Point-of-zero charges (pHpzc), Scanning Electron Microscopy (SEM), X-ray Diffractometry (XRD), Fourier transform infrared spectroscopy (FTIR), and Raman spectroscopy. The studies showed that the adsorption behavior varied with the pH of the solution. The adsorption study verified that the activated biochars presented better results, so in the kinetic study, the adsorption behavior occurred rapidly in the initial minutes until stabilizing within 3–4 h, better fitting the Elovich model. Isotherm models were tested, where the experimental data were adjusted to the Sips model, with an adsorption capacity of 18 mg g−1 for acid-activated biochar (BCH3PO4) and KOH-activated biochar (BCKOH) with 366.49 mg g−1. The results showed that biochars, especially BCKOH, become viable for production because they are a low-cost material and highly effective in removing drugs.
]]>Processes doi: 10.3390/pr12030561
Authors: Mahmoud Ahmednooh Brenno Menezes
A major operation in petroleum refinery plants, blend scheduling management of stocks and their mixtures, known as blend-shops, is aimed at feeding process units (such as distillation columns and catalytic cracking reactors) and production of finished fuels (such as gasoline and diesel). Crude-oil, atmospheric residuum, gasoline, diesel, or any other stream blending and scheduling (or blend scheduling) optimization yields a non-convex mixed-integer nonlinear programming (MINLP) problem to be solved in ad hoc propositions based on decomposition strategies. Alternatively, to avoid such a complex solution, trial-and-error procedures in simulation-based approaches are commonplace. This article discusses solutions for blend scheduling (BS) in petroleum refineries, highlighting optimization against simulation, continuous (simultaneous) and batch (sequential) mixtures, continuous- and discrete-time formulations, and large-scale and complex-scope BS cases. In the latter, ordinary least squares regression (OLSR) using supervised machine learning can be utilized to pre-model blending of streams as linear and nonlinear constraints used in hierarchically decomposed blend scheduling solutions. Approaches that facilitate automated decision-making in handling blend scheduling in petroleum refineries must consider the domains of quantity, logic, and quality variables and constraints, in which the details and challenges for industrial-like blend-shops, from the bulk feed preparation for the petroleum processing until the production of finished fuels, are revealed.
]]>Processes doi: 10.3390/pr12030559
Authors: Qiuchen Zhang Yu Tang Lupeng Wang
Thermal efficiency is one of the important indices used to evaluate the operational energy efficiency of hot blast stoves. In this study, a method for calculating the thermal efficiency of hot blast stoves was developed based on simulation results. The working process of top combustion hot blast stoves was numerically simulated through the established 3D fluid flow heat transfer model. The system thermal efficiency of hot blast stoves was calculated according to the simulation data, referring to the Chinese national standard, “measurement and calculation method of the heat balance of blast furnace hot blast stove” (GB/T 32287-2015). In particular, a “segmented calculation and accumulate by time” method was proposed based on the air supply curve to more precisely calculate the heat carried away by the hot blast. The results indicate that when the burning air supply cycles increased from 120 to 240 min, the thermal efficiency showed a trend of first decreasing and then increasing, with the value ranging between 70.39% and 72.48%. The reason for the decrease in thermal efficiency at a burning cycle of 150 min is explained based on heat transfer theory combined with the structural characteristics of hot blast stoves. This study provides a convenient and effective method for calculating the thermal efficiency of hot blast stoves, which helps us to evaluate and improve the operating process of hot blast stoves.
]]>Processes doi: 10.3390/pr12030558
Authors: Afonso Fontes Ricardo Francisco Frederico Castelo Ferreira Nuno Torres Faria Susana Marques Alberto Reis Patrícia Moura Rafal Lukasik José Santos Teresa Lopes da Silva
Microbial oils can be used as an alternative sustainable and renewable feedstock to fossil reserves for producing lubricants and polyurethane materials. Two oleaginous yeasts were grown on non-detoxified corn stover hydrolysate supplemented with corn steep liquor and mineral medium in shake flasks. Trichosporon oleaginosus DSM 11815 displayed the highest lipid production. This strain was further cultivated in a bench bioreactor, using the same culture medium, under a batch regime. Flow cytometry was used to monitor the T. oleaginosus culture using the dual staining technique (SYBR Green and PI) for cell membrane integrity detection. Values of 42.28% (w/w) and 0.06 g/Lh lipid content and lipid productivity, respectively, were recorded for T. oleaginosus cultivated in the bench bioreactor operated under a batch regime. During the cultivation, most of the yeast cells maintained their integrity. T. oleaginosus has the potential to be used as an oil microbial source for a wide range of industrial applications. In addition, it is robust in adverse conditions such as lignocellulosic hydrolysate exposure and oxygen-limiting conditions. Flow cytometry is a powerful and useful tool for monitoring yeast cultivations on lignocellulosic hydrolysates for cell count, size, granularity, and membrane integrity detection.
]]>Processes doi: 10.3390/pr12030557
Authors: Taixia Zhao Yongshi Hua Yuanyuan Zhou Haixia Xu Wenxin Tian Zhongbao Luo Baoqin Huang Lanming Chen Li Fan
This study aimed to investigate the antioxidant activity and antibacterial effect of total flavonoids from Persicaria hydropiper (L.) Spach (TFs-Ph) and to provide a theoretical basis for the development of drugs for the treatment of pathogenic Escherichia coli and Salmonella spp. of broiler origin. Firstly, the response surface optimization heating reflux method was used to extract TFs-Ph, and the effects of ethanol concentration, solid–liquid ratio, heating reflux time, heating reflux temperature, and number of extraction times on the extraction yield of TFs-Ph were analyzed to determine the optimal extraction conditions. The antioxidant activity of TFs-Ph was determined by measuring the scavenging ability against hydroxyl radicals (•OH), 1,1-diphenyl-2-picrylhydrazyl (DPPH), superoxide anion (•O2−), and 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS). The antibacterial effect of TFs-Ph was determined by the disk diffusion method. The results showed that the optimal extraction parameters of TFs-Ph were as follows: ethanol concentration of 51%, solid-liquid ratio of 1:24 g/mL, heating reflux time of 74 min, heating reflux temperature of 70 °C, and three extraction times; in this case, the extraction yield of TFs-Ph was 6.37%. TFs-Ph had a strong scavenging ability against the free radicals of •OH, DPPH, •O2−, and ABTS, and the antioxidant activity was better than that of vitamin C (Vc). In addition, it showed a better antibacterial effect against pathogenic Escherichia coli and Salmonella of broiler origin compared with ampicillin (AMP). Therefore, TFs-Ph have a certain potential to replace antibiotics.
]]>Processes doi: 10.3390/pr12030556
Authors: Valentina Zhukova Paula Corte-Leon Ahmed Talaat Mihail Ipatov Alfonso García-Gomez Alvaro González Juan Maria Blanco Arcady Zhukov
Magnetic microwires with amorphous structures can present a unique combination of excellent magnetic softness and giant magnetoimpedance (GMI) effects together with reduced dimensions and good mechanical properties. Such unique properties make them suitable for various technological applications. The high GMI effect, observed in as-prepared Co-rich microwires, can be further optimized by postprocessing. However, unexpected magnetic hardening and a transformation of the linear hysteresis loop into a rectangular loop with a coercivity on the order of 90 A/m were observed in several Co-rich microwires upon conventional annealing. Several routes to improve magnetic softness and GMI effect in Fe- and Co-rich magnetic microwires are provided. We observed that stress annealing could remarkably improve the magnetic softness and GMI ratio of Co-rich microwires. Thus, almost unhysteretic loops with a coercivity of 2 A/m and a magnetic anisotropy field of about 70 A/m are achieved in Co-rich microwires stress annealed at appropriate conditions. The observed change in hysteresis loops and the GMI effect is explained by stress-annealing-induced anisotropy, which is affected by the stresses applied during annealing and by the annealing temperature. While as-prepared Fe-rich amorphous microwires present a low GMI effect, appropriate postprocessing (annealing and stress annealing) allows for a remarkable GMI ratio improvement (an order of magnitude). The evaluated dependence of the maximum GMI ratio on frequency allows the identification of the optimal frequency band for the studied samples. The origin of stress-annealing-induced anisotropy and related changes in hysteresis loops and the GMI effect are discussed in terms of the relaxation of internal stresses, “back-stresses”, as well as structural anisotropy.
]]>Processes doi: 10.3390/pr12030555
Authors: Michaela Sudová Martin Sisol Maria Kanuchova Michal Marcin Jakub Kurty
This paper focuses on the environmental leaching of antimony, a critical mineral, using deep eutectic solvents. Mining residues often contain embedded antimony, posing environmental risks. Deep eutectic solvents, known for being low in toxicity, cost-effective, and environmentally friendly, present a promising avenue for sustainable antimony extraction. The study focuses on optimizing the leaching process through experimental analysis by considering variables such as temperature, time, and percentage of solids. Different deep eutectic solvent (DES) compositions are being studied, including choline chloride with malonic acid, thiourea, and ethylene glycol in different molar ratios, to identify the most effective solvent system for antimony extraction. A sample, originally obtained from mining waste produced via the flotation of antimonite ore, was used to test these three types of DESs. By optimizing the leaching process by changing the ratio of solid and liquid components, as well as the amount of oxidizing agent up to 3 g, iodine, yields of up to 100% were achieved after leaching for 4 h at 100 °C. The aim of the study is to advance sustainable resource management by providing knowledge on an ecological and feasible method of extracting antimony from mine waste, leading to more conscious and efficient resource practices in the mining sector.
]]>Processes doi: 10.3390/pr12030554
Authors: Guxing Tong Xiaolei Zhu Yang Liu Fuxiang Lv Xiaofeng Lu
Hydrogen storage is a crucial factor that limits the development of hydrogen energy. This paper proposes using a split liner for the inner structure of a hydrogen storage cylinder. A self-tightening seal is employed to address the sealing problem between the head and the barrel. The feasibility of this structure is demonstrated through hydraulic pressure experiments. The influence laws of the O-ring compression rate, the distance from the straight edge section of the head to the sealing groove, and the thickness of the head on the sealing performance of gas cylinders in this sealing structure are revealed using finite elements analysis. The results show that when the gas cylinder is subjected to medium internal pressure, the maximum contact stress on the O-ring extrusion deformation sealing surface is greater than the medium pressure. There is sufficient contact width, that is, the arc length of the part where the stress on the O-ring contact surface is greater than the medium pressure, so that it can form a good sealing condition. At the same time, increasing the compression ratio of the O-ring and the head’s thickness will help improve the sealing performance, and reducing the distance from the straight edge section of the head to the sealing groove will also improve the sealing performance.
]]>Processes doi: 10.3390/pr12030553
Authors: Qingmiao Ding Xiaoman Li Yanyu Cui Junda Lv Yunlong Shan Yongqiang Liu
Cavitation bubbles commonly exist in shipbuilding engineering, ocean engineering, mechanical engineering, chemical industry, and aerospace. Asymmetric deformation of the bubble occurs near the boundary and then has strong destructiveness, such as high amplitude loading. Therefore, the research on non-spherical deformation is of great significance, and the objective of this paper is to investigate the non-spherical collapse dynamics of laser-induced cavitation bubbles when near different boundaries. In this study, experimental data, such as the bubble pulsation process and bubble surface velocity distribution, were obtained by high-speed camera techniques and full-field velocity calculations. Near the different boundaries, the results show that the bubbles appeared to have different collapse shapes, such as near-hemispherical, near-ellipsoidal, near-cone, and near-pea shapes, and the surface velocity distribution is extremely non-uniform. When the bubble near the free surface or rigid boundary collapses, the smaller the stand-off r is, the more obvious the repulsive effect of the free surface or the attractive effect of the rigid boundary is. As the stand-off r decreases, the larger the Bjerknes force and the bubble surface velocity difference and the more pronounced the non-spherical shape becomes.
]]>Processes doi: 10.3390/pr12030552
Authors: Antoni Sánchez
In 2019, one of the Editorial Staff of the MDPI journal Processes, sent me an email informing me that I was being invited to join the Editorial Board of the journal, a proposal that I accepted [...]
]]>Processes doi: 10.3390/pr12030551
Authors: Mingzhe Li Yizhong Zhang Maolin Zhang Bin Ju Long Yang Xu Guo
In gas cap reservoirs underlain by bottom water, the connection between the reservoir and the aquifer leads to an increasing invasion of bottom water as reservoir development progresses. The average formation pressure of the reservoir will change, and the separated phase recovery of the gas cap reservoir with bottom water will be affected by the change in the average formation pressure. The traditional average formation pressure calculation formulas do not consider the water influx, so the accurate calculation of separated recovery cannot be obtained by those calculation methods. The development of gas cap reservoirs with bottom water presents several challenges, including the simultaneous production of oil and gas, undetermined rates of bottom water influx, and uncertain formation pressure and gas-to-oil ratios. These factors contribute to substantial discrepancies between theoretical calculations and actual observations. A more accurate and comprehensive approach is required to address these issues and enable a precise determination of the phase separated recovery in gas cap reservoirs with bottom water. The volume-deficit method is integrated with the Fetkovich quasi-steady state method for water influx. The water-influx prediction is incorporated into the material balance equation, which is further refined by introducing the Fetkovich model to enhance the estimation of the average formation pressure. The average formation pressure, once determined, is utilized in conjunction with the established relationships among this pressure, surface oil production, gas production, and the dissolved gas–oil ratio. Through the application of mass conservation principles, the varying degree of phase recovery, as influenced by fluctuations in the average formation pressure, is calculated. The precision of this refined method has been validated by a comparison with outcomes generated by simulation software. The results reveal a commendable accuracy: an error in the average formation pressure calculation is found to be merely 2.61%, while the errors in recovery degrees for gas cap gas, dissolved gas, and oil-rim oil are recorded at 2.73%, 2.94%, and 1.28%, respectively. These minor discrepancies indicate a good level of consistency and affirm the reliability of this advanced methodology, as demonstrated by passive assessments. This paper provides a method to accurately calculate the phase recovery without some oil- and gas-production data, which provides accurate data support for the actual production evaluation and subsequent development measures.
]]>Processes doi: 10.3390/pr12030549
Authors: Ibrahim T. Teke Ahmet H. Ertas
Nodular iron plays a crucial role in various industries, especially in large-scale applications such as gearboxes. Ensuring that nodular iron remains free from oil leakage and that contact surfaces are properly aligned is essential, given its operational requirements. Achieving flat contact faces through precise machining is therefore of utmost importance. As surface roughness and flatness are closely linked, it is vital to investigate the machining process parameters involved. This study focuses on addressing surface quality issues with EN-GJS-600-3 cast iron by optimizing machining parameters. CMM measurements were utilized to analyze the relationship between surface roughness and flatness, with a surface profile used to assess flatness. Furthermore, a new 2D surface roughness estimation method (2D-SRET) was created and tested with experimental data in order to improve the precision of assessing the discrete flat surface machining procedure.
]]>Processes doi: 10.3390/pr12030550
Authors: Hongbo Zhang Shaowu Jiu Qianwen Gao Sijun Zhao Yanxin Chen Feng Cheng Ding Han Ruihong Shi Kaixin Yuan Jiacheng Li Yuxin Li Zichun Wang Bo Zhao
Although the calcination-based activation of coal gangue is important for its valorization in the form of cementitious materials, the related works mainly focus on high-quality coal gangue, neglecting its low-quality counterpart. To bridge this gap, we herein conducted the pilot-scale suspension calcination of low-quality coal gangue; explored the effects of calcination temperature, particle size, and O2 content on the phase composition of the calcined product, kaolinite decomposition, decarbonization, and silica/alumina dissolution; and evaluated calcination-product-based cementitious materials. Under optimal conditions (temperature = 875–900 °C; particle size = 39.71–46.84 μm; and O2 content = 12–14%), the carbon content of the calcined product equaled 1.24–1.87 wt%, and the dissolution rates of activated alumina and silica were 77.6–79.5% and 49.4–51.1%, respectively. The 28 d compressive strength (50.8–55.7 MPa) and true activity index (98.8–108.4%) of the cementitious material prepared at a calcination product dosage of 30–38 wt% met the standard of 42.5 grade cement. This study demonstrated the suitability of suspension calcination for the preparation of high-performance low-carbon cementitious materials from low-quality coal gangue, thus providing a basis for further industrialization and technological development.
]]>Processes doi: 10.3390/pr12030546
Authors: Md. Samin Safayat Islam Puja Ghosh Md. Omer Faruque Md. Rashidul Islam Md. Alamgir Hossain Md. Shafiul Alam Md. Rafiqul Islam Sheikh
The inherent volatility of PV power introduces unpredictability to the power system, necessitating accurate forecasting of power generation. In this study, a machine learning (ML) model based on Gaussian process regression (GPR) for short-term PV power output forecasting is proposed. With its benefits in handling nonlinear relationships, estimating uncertainty, and generating probabilistic forecasts, GPR is an appropriate approach for addressing the problems caused by PV power generation’s irregularity. Additionally, Bayesian optimization to identify optimal hyper-parameter combinations for the ML model is utilized. The research leverages solar radiation intensity data collected at 60-min and 30-min intervals over periods of 1 year and 6 months, respectively. Comparative analysis reveals that the data set with 60-min intervals performs slightly better than the 30-min intervals data set. The proposed GPR model, coupled with Bayesian optimization, demonstrates superior performance compared to contemporary ML models and traditional neural network models. This superiority is evident in 98% and 90% improvements in root mean square errors compared to feed-forward neural network and artificial neural network models, respectively. This research contributes to advancing accurate and efficient forecasting methods for PV power output, thereby enhancing the reliability and stability of power systems.
]]>Processes doi: 10.3390/pr12030548
Authors: Ke Han Shuai He Yue Yu
In response to the urgent need for efficient pneumonia diagnosis—a significant health challenge that has been intensified during the COVID-19 era—this study introduces the RCGAN-CTL model. This innovative approach combines a coupled generative adversarial network (GAN) with relativistic and conditional discriminators to optimize performance in contexts with limited data resources. It significantly enhances the efficacy of small or incomplete datasets through the integration of synthetic images generated by an advanced RCGAN. Rigorous evaluations using a wide range of lung X-ray images validate the model’s effectiveness. In binary classification tasks that differentiate between normal and pneumonia cases, RCGAN-CTL demonstrates exceptional accuracy, exceeding 99%, with an area under the curve (AUC) of around 95%. Its capabilities extend to a complex triple classification task, accurately distinguishing between normal, viral pneumonia, and bacterial pneumonia, with precision scores of 89.9%, 95.5%, and 90.5%, respectively. A notable improvement in sensitivity further evidences the model’s robustness. Comprehensive validation underscores RCGAN-CTL’s superior accuracy and reliability in both binary and triple classification scenarios. This advancement is pivotal for enhancing deep learning applications in medical diagnostics, presenting a significant tool in addressing the challenges of pneumonia diagnosis, a key concern in contemporary healthcare.
]]>Processes doi: 10.3390/pr12030547
Authors: Chenglong Zhang Yujie Diao Lei Fu Xin Ma Siyuan Wang Ting Liu
CO2 geological storage combined with deep saline water recovery technology (CO2-EWR) is one of the most effective ways to reduce carbon emissions. Due to the complex structural features, it is difficult to use CO2-EWR technology in Huaiyin Sag, Subei basin, East China. In this study, the multi-source information superposition evaluation technology of GIS was utilized for the selection of CO2 storage sites and water displacement potential target areas in this area, which mainly focused on the sandstone reservoirs of Cretaceous Pukou Formation. Based on the results, a three-dimensional injection–extraction model was established. Various scenarios with different production/injection well ratios (PIR) were simulated. Research has shown that the suitability of the surrounding site of Huaiyin Power Plant can be divided into two levels: relatively suitable and generally suitable; the area in the generally suitable level accounts for more than 80%. At a PIR of 1, CO2 is distributed asymmetrically, whereas at PIRs of 2 or 4, CO2 is distributed symmetrically. When the number of production wells is constant, a higher injection rate results in a faster expansion rate of the CO2 plume. This means that the time taken for the CO2 plume to reach the production wells is shorter. Reservoir pressure increases rapidly after more than 60 years of CO2 injection at lower PIR values, while at higher PIRs, reservoir pressure eventually stabilizes. Higher PIR values correspond to higher gas saturation, indicating a greater capacity for CO2 sequestration with more producing wells. When PIR = 4, the total CO2 injection increased by 55.73% compared to PIR = 1. However, the extraction of saline decreases with an increase in the number of producing wells, resulting in a decrease in replacement efficiency. This study provides a theoretical basis and technical support for the implementation of large-scale CO2-EWR engineering and technology demonstration in this region.
]]>Processes doi: 10.3390/pr12030545
Authors: Tomislav Domanovac Dajana Kučić Grgić Monika Šabić Runjavec Marija Vuković Domanovac
Biowaste, which often accounts for more than 50% of municipal waste, is an environmental problem if disposed of improperly in landfills but has great potential to achieve the recycling targets set out in Directive (EU) 2018/851. Despite the knowledge in theory and practice about the processing of biowaste and the benefits of recycling, there is a lack of methodological approaches in describing the process of aerobic biodegradation in a concise and suitable way for decision makers, environmental engineers, and project designers. This paper presents how basic data on the properties of biowaste can be used, using theoretical models, to determine basic indicators of the dynamics and material balance of the process. The maximum rate of CO2 generation on the 4th day was Rm = 45.3 g/d, with the potential of available, readily biodegradable components of the biowaste sample of P = 526 g CO2/kg VS. A substrate conversion of 51.7% was achieved in the bioreactor by the 17th day of treatment. The results of this analysis, together with future analyses of sensitivity and boundary conditions of the process, are useful for rapidly sizing a biological treatment system for municipal solid waste in a given area.
]]>Processes doi: 10.3390/pr12030544
Authors: Violeta Bozhanova Plamena Marinova Maria Videva Spasimira Nedjalkova Evgenia Benova
Cold atmospheric pressure plasma (CAP) has attracted increased interest in recent years for possible biomedical, environmental and agricultural applications. A wide range of cold plasma treatment effects is observed in agricultural applications, like effects on the seed germination and seedling growth, but more systematic investigations are needed. The aim of this study was to identify the most appropriate combinations of the plasma source and duration of treatment positively affecting seed germination. In addition, the effect of cold plasma on the seedling growth and osmotic stress tolerance was studied. The seeds of three Bulgarian durum wheat cultivars were treated with cold plasma in twelve variants. The results obtained were processed statistically via two-way ANOVA. The treatment of seeds with a plasma torch for 20 s and the treatment with underwater diaphragm discharge for 5 min when the seeds were placed in both cameras in two different positions (relative to the electrodes between which the plasma is supplied, “+” and “−”) have the greatest positive effect on the all traits related to germination. The analysis of variance reveals that the variation in germination energy, shoot length and root length after the cold plasma treatment of seeds is mainly due to the interaction between the genotype and treatment variant and to a small degree due to the genotype. The treatment of seeds with cold plasma improves the osmoregulation ability of cells and therefore increases the drought resistance of genotypes.
]]>Processes doi: 10.3390/pr12030543
Authors: Jiaping Wang Chao Wang Jie Wu
The pressure distribution characteristics of an apple subjected to compressive loading were investigated using the pressure-sensitive film (PSF) technique combined with apple bruise measurements. Pressure was unevenly distributed in the elliptical contact region. The average pressure had no effect on bruising because it changed slightly in the range of 0.26–0.31 MPa with increasing load. Pressures of 0.20–0.40 MPa accounted for 72% of the total pressure area. Comparatively, the area where pressure over 0.50 MPa was distributed could be ignored and showed little contribution to the bruise area. The contact edge subjected to pressure below 0.10 MPa showed that no bruising occurred. As a result, the relationship between the ≥0.10 MPa pressure area strongly correlated with the bruise area according to a linear equation, with a correlation coefficient of ≥0.99. When this relationship was applied to determine the bruise area with FE, satisfactory predicted results were obtained with minor error rates of 0–7.89% for loads of 54–80 N. But larger prediction errors occurred when the load was above 90 N, suggesting that the linear elastic FE model may not be appropriate for accurately predicting apple bruising.
]]>Processes doi: 10.3390/pr12030542
Authors: Fenghe Cui Lei Pan Yi Pang Jianwei Chen Fan Shi Yin Liang
In the traditional C3MR process (T-C3MR), the boiling gas (BOG) output from the last stage of the gas–liquid separator is directly discharged, in which the excellent low-temperature capability is not utilized, and the system efficiency is decreased. In liquefied natural gas (LNG), single-objective optimization methods are commonly used to optimize system parameters, which may result in incomplete system analysis. To solve the above problems, this paper proposes a multi-objective optimization strategy for the improved C3MR process(I-C3MR) based on a new multi-objective optimization algorithm called EHR-GWO-GA. Firstly, the main work proposes an I-C3MR structure. Secondly, an optimization strategy of the I-C3MR with the maximization of liquefaction amount, minimization of unit energy consumption and minimization of exergy loss as objective functions are proposed. Based on the optimization results, the influence of decision variables on liquefaction amount, unit energy consumption and exergy loss are analyzed, and the results show that the decision variables have good adaptability. Finally, a detailed exergy analysis of the equipment used is made, and the results show that the main exergy losses come from the water coolers and compressors, accounting for 32% and 34%, respectively. Compared to the T-C3MR, the improved C3MR based on EHR-GWO-GA(E-C3MR) has an approximate 8% increase in liquefaction amount—a roughly 23% decrease in unit energy consumption and a decrease of nearly 24% in exergy loss.
]]>Processes doi: 10.3390/pr12030541
Authors: Tao Shi Libo Gu Zeyan Xu Jialin Sheng
This study focuses on a renewable energy power plant equipped with electrolytic hydrogen production system, aiming to optimize energy management to smooth renewable energy generation fluctuations, participate in peak shaving auxiliary services, and increase the absorption space for renewable energy. A multi-objective energy management model and corresponding algorithms were developed, incorporating considerations of cost, pricing, and the operational constraints of a renewable energy generating unit and electrolytic hydrogen production system. By introducing uncertain programming, the uncertainty issues associated with renewable energy output were successfully addressed and an improved particle swarm optimization algorithm was employed for solving. A simulation system established on the Matlab platform verified the effectiveness of the model and algorithms, demonstrating that this approach can effectively meet the demands of the electricity market while enhancing the utilization rate of renewable energies.
]]>Processes doi: 10.3390/pr12030540
Authors: Ting-An Lin Yi-Chen Lee Wen-Jer Chang Yann-Horng Lin
This paper proposes an observer-based proportional Derivative (O-BPD) fuzzy controller for uncertain discrete-time nonlinear descriptor systems (NDSs). Representing NDSs with the Takagi–Sugeno fuzzy model (T-SFM), the proportional derivative (PD) feedback method can be utilized in the fuzzy controller design via the Parallel Distributed Compensation (PDC) concept, such that the noncausal problem and impulse behavior are avoided. A fuzzy observer is proposed to obtain unmeasured states to fulfill the PD fuzzy controller. Moreover, uncertainties and transient response performances are taken into account for the NDSs. Then, a stability analysis process and corresponding stability conditions are derived from the Lyapunov theory with the robust control method and the pole constraint. Different from existing research, the Singular Value Decomposition (SVD) and the projection lemma are utilized to transfer the stability conditions into the Linear Matrix Inequation (LMI) form. Because of this reason, the conservatism of the analysis process can be reduced by eliminating the restriction on the positive definite matrix in the Lyapunov function. By giving the proper center and radius parameters of the pole constraint in the O-BPD fuzzy controller design process, the expected transient responses can be obtained for different designers and different practical applications. Finally, the effectiveness and applicability of the proposed O-BPD fuzzy controller are demonstrated by two examples of the simulation.
]]>Processes doi: 10.3390/pr12030539
Authors: Claudio A. Faúndez Elías N. Fierro Ariana S. Muñoz
In this work, four hundred and forty experimental solubility data points of 14 systems composed of methane and ionic liquids are considered to train a multilayer perceptron model. The main objective is to propose a simple procedure for the prediction of methane solubility in ionic liquids. Eight machine learning algorithms are tested to determine the appropriate model, and architectures composed of one input layer, two hidden layers, and one output layer are analyzed. The input variables of an artificial neural network are the experimental temperature (T) and pressure (P), the critical properties of temperature (Tc) and pressure (Pc), and the acentric (ω) and compressibility (Zc) factors. The findings show that a (4,4,4,1) architecture with the combination of T-P-Tc-Pc variables results in a simple 45-parameter model with an absolute prediction deviation of less than 12%.
]]>Processes doi: 10.3390/pr12030538
Authors: Junping Cheng Yongmei Hao Zhixiang Xing Rui Song Fan Wu Sunqi Zhuang
In order to explore the influence of the side duct position and venting position on the premixed combustion and explosion characteristics of methane/air, a premixed combustion and explosion experiment of methane/air and a simulation of an explosion of the same size were carried out in a tube with an internal size of 2000 mm × 110 mm × 110 mm. The results showed that the side duct could change the flame structure and accelerate the flame inside the tube. The maximum increase ratio of the flame propagation speed was 106.1%. The side duct had a certain venting effect on the explosion pressure. For different position cases, when the venting film was placed over the bottom section, the maximum overpressure first decreased and then increased. When the venting film was placed over the middle section and the top section, the maximum overpressure first increased and then decreased, and the change trend of the top section was stronger. Turbulence mostly occurred inside the side duct when the venting film of the side duct ruptured. There is no linear relationship between the maximum flame propagation velocity within the tube and the maximum turbulent kinetic energy inside the side duct. The two had a relationship that could be fitted to the Gauss function; the correlation coefficient R2 was 0.836, and the minimum value was at (4767.72, 17.918), suggesting that the side duct had the best venting effect on the flame inside the duct at this maximum turbulent kinetic energy. The analysis results of the influence of the location of the vent on the maximum flame propagation velocity inside the tube are helpful for optimizing the layout design of the underground space, reducing the combustion efficiency, and ensuring the safety of the process.
]]>Processes doi: 10.3390/pr12030537
Authors: Xiaoping Lin Bing Ni Fangqin Shangguan
In the context of carbon reduction and emission reduction, the new process of electric arc furnace (EAF) steelmaking based on direct hydrogen reduction is an important potential method for the green and sustainable development of the steel industry. Within an electric furnace for the hydrogen-based direct reduction of iron, after hydrogen-based directly reduced iron (HDRI) is produced through a shaft furnace, HDRI is melted or smelted in an EAF to form final products such as high-purity iron or high-end special steel. As smelting proceeds in the electric furnace, it is easy for pieces of HDRI to bond to each other and become larger pieces; they may even form an “iceberg”, and this phenomenon may then worsen the smelting working conditions. Therefore, the melting of HDRI is the key to affecting the smelting cycle and energy consumption of EAFs. In this study, based on the basic characteristics of HDRI, we established an HDRI melting model using COMSOL Multiphysics 6.0 and studied the HDRI melting process, utilizing pellets with a radius of 8 mm. The results of our simulation show that the HDRI melting process can be divided into three different stages: generating a solidified steel layer, melting the solidified steel layer, and melting HDRI bodies. Moreover, multiple HDRI processes are prone to bonding in the melting process. Increasing the spacing between pieces of HDRI and increasing the preheating temperature used on the HDRI can effectively reduce the aforementioned bonding phenomenon. When the melting pool temperature is 1873 K, increasing the spacing of HDRI to 10 mm and increasing the initial HDRI temperature to 973 K was shown to effectively reduce or eliminate the bonding phenomenon among pieces of HDRI. In addition, with the increase in the melting pool temperature, the time required for melting within the three stages of the HDRI melting process shortened, and the melting speed was accelerated. With the increase in the temperature used to preheat the HDRI, the duration of the solidified steel layer’s existence was also shortened, but this had no significant impact on the time required for the complete melting of HDRI. This study provides a theoretical basis for the optimization of the HDRI process within EAFs.
]]>Processes doi: 10.3390/pr12030536
Authors: Guanchen Zong Cunfeng Kang Shujun Chen Xiaoqing Jiang
Robotic friction stir welding (RFSW), with its wide application range, ample working space, and task flexibility, has emerged as a vital development in friction stir welding (FSW) technology. However, the low stiffness of serial industrial robots can lead to end-effector deviations and vibrations during FSW tasks, adversely affecting the weld quality. This paper proposes a dynamic dual particle swarm optimization (DDPSO) algorithm through a new comprehensive stability index that considers both the stiffness and vibration stability of the robot to optimize the installation position of complex space curve weldments, thereby enhancing the robot’s stability during the FSW process. The algorithm employs two independent particle swarms for exploration and exploitation tasks and dynamically adjusts task allocation and particle numbers based on current results to fully utilize computational resources and enhance search efficiency. Compared to the standard particle swarm optimization (PSO) algorithm, the DDPSO approach demonstrated superior search capabilities and stability of optimization results. The maximum fitness value improved by 4.2%, the average value increased by 12.74%, and the concentration level of optimization results rose by 72.91% on average. The new optimization method pioneers fresh perspectives for optimizing the stability of RFSW, providing significant grounds for the process optimization and offline programming of complex spatial curve weldments.
]]>Processes doi: 10.3390/pr12030535
Authors: Meijun Zhu Shuai Zhou Yang Liu Zhehong Li Ziyun Chen
A scramjet engine consisting of several components is a highly coupled system that urgently needs a universal performance metric. Exergy is considered as a potential universal currency to assess the performance of scramjet engines. In this paper, a control-volume-based exergy method for the Reynolds-averaged Navier–Stokes solution of truncated and corrected Busemann inlets was proposed. An exergy postprocessing code was developed to achieve this method. Qualitative and quantitative analyses of exergies in the Busemann inlets were performed. A complete understanding of the evolution process of anergy and the location where anergy occurs in the inlet at various operation conditions was also obtained. The results show that the exergy destroyed in the Busemann inlet can be decomposed into shock wave anergy, viscous anergy and thermal anergy. Shock wave anergy accounts for less than 4% of the total exergy destroyed while thermal anergy and viscous anergy, in a roughly equivalent magnitude, contribute to almost all the remaining. The vast majority of inflow exergy is converted into boundary pressure work and thermal exergy. Some of the thermal exergy excluded by the computation of the total pressure recovery coefficient belongs to the available energy, as this partial energy will be further converted into useful work in combustion chambers.
]]>Processes doi: 10.3390/pr12030534
Authors: Zhifan Zhang Ruijin Zhu
With the continuous expansion of grid-connected wind, photovoltaic, and other renewable energy sources, their volatility and uncertainty pose significant challenges to system peak regulation. To enhance the system’s peak-load management and the integration of wind (WD) and photovoltaic (PV) power, this paper introduces a distributionally robust optimization scheduling strategy for a WD–PV thermal storage power system incorporating deep peak shaving. Firstly, a detailed peak shaving process model is developed for thermal power units, alongside a multi-energy coupling model for WD–PV thermal storage that accounts for carbon emissions. Secondly, to address the variability and uncertainty of WD–PV outputs, a data-driven, distributionally robust optimization scheduling model is formulated utilizing 1-norm and ∞-norm constrained scenario probability distribution fuzzy sets. Lastly, the model is solved iteratively through the column and constraint generation algorithm (C&CG). The outcomes demonstrate that the proposed strategy not only enhances the system’s peak-load handling and WD–PV integration but also boosts its economic efficiency and reduces the carbon emissions of the system, achieving a balance between model economy and system robustness.
]]>Processes doi: 10.3390/pr12030533
Authors: Georgiana Cătălina Neacşu (Dobrişan) Eduard Laurenţiu Niţu Ana Cornelia Gavriluţă Georgica Gheorghiţa Vlad Elena Mădălina Dobre Marian Gheorghe Maria Magdalena Stan
Strong competition in the automotive industry has required manufacturers to implement lean production, both with methods and techniques specific to Industry 4.0. At the same time, universities must provide graduates with specific skills for applying these new production methods and techniques. In this context, a lean learning factory was developed in the Pitesti University Center that allows students to learn about, experiment with, and research new lean manufacturing methods and techniques as well as Industry 4.0 in an environment similar to that of enterprises. The research presented in this study aimed to identify the minimum number of repetitions necessary to train operators to perform the same assembly operation while working at two differently organized workstations: one classic and the other including digital techniques. Several indicators were considered in our analysis, such as the number of errors, the number of stops, the effective duration of the work cycle, and the percentage ratio between the standard duration of cyclical activities and the effective duration of the work cycle. The evolution of these indicators was mathematically modelled by regression functions, using the least squares method. The obtained results also highlight the usefulness of applying the DOJO method as a lean-manufacturing-specific learning technique and the efficiency of implementing digital techniques in work organization.
]]>Processes doi: 10.3390/pr12030532
Authors: Tianyu Ying Edward S. Spang
This study explores the existing literature on specific energy consumption (SEC) use for paddy drying and consolidates all relevant data for comparisons across technologies. Energy consumption data for a range of drying technologies are consolidated from published literature and normalized to enable comparison. A large proportion of the source data are generated from operational performance in industrial or laboratory settings, while the remainder is derived from computer simulations. The SEC of paddy drying is driven primarily by technology type; however, operational factors (such as the system size, temperature, and airflow) and external factors (such as the local climate and paddy moisture content) also heavily influence system energy use. The results of our analysis show that the industrial drying technologies explored in this study have an average SEC of 5.57 ± 2.21 MJ/kg, significantly lower than the 20.87 ± 14.97 MJ/kg observed in a laboratory setting, which can potentially be attributed to differences in processing capacity. Multi-stage drying typically has higher energy efficiency when tempering stages are incorporated. The self-circulating design of some drying systems may provide additional opportunities for heat exchange, leading to efficient drying performance without the need for a separate tempering stage. Beyond traditional methods, we have observed a notable shift towards solar-assisted and infrared drying technologies in laboratory settings, reflecting an increasing interest in sustainable and efficient drying solutions. In summary, this review consolidates SEC data for rice drying technologies, analyzes the energy intensity and performance of each drying technology, and identifies data gaps that might be addressed in future research.
]]>Processes doi: 10.3390/pr12030531
Authors: Beata Szulc-Musioł Piotr Duda Michał Meisner Beata Sarecka-Hujar
This study aimed to assess the changes occurring during the storage of tablets of three effervescent preparations available in Polish pharmacies containing calcium and quercetin from various manufacturers under stressful conditions (45 °C, UV radiation) using a hyperspectral Specim IQ camera (Finland), X-ray microtomography (Germany), and selected pharmacopoeial parameters. All measurements were made three times at the beginning of the experiment (day 0) and then on days 3 and 10. In general, for all analyzed preparations, the values of reflectance (within a range from visible light to near-infrared) were significantly higher on day 0 than after 10 days of heat and UV (p < 0.001 each). The hardness of the tablets of all analysed preparations was higher on days 3 and 10 compared to day 0. Significant differences were found in the density of the internal structure of the tested preparations (p < 0.001), but in Preparations 1 and 2 on day 10, the density was higher compared to the initial density. In contrast, the porosity was lower on day 10 than on day 0 for Preparations 1 and 2, while in Preparation 3, it remained the same. In conclusion, lower reflectance values indicate that more light passes through/into the tablet, and the increase in density and decrease in porosity may indicate changes in the microstructure of the tablets.
]]>Processes doi: 10.3390/pr12030530
Authors: Urszula Domańska Anna Wiśniewska Zbigniew Dąbrowski
The recycling of metals from waste printed circuit boards (WPCBs) has been presented as a solid–liquid extraction process using two deep eutectic solvents (DESs) and four ionic liquids (ILs). The extraction and separation of Cu(II), Ag(I), and other metals, such as Al(III), Fe(II), and Zn(II), from the solid WPCBs (after the physical, mechanical, and thermal pre-treatments) with different solvents are demonstrated. Two popular DESs were used to recover valuable metal ions: (1) choline chloride + malonic acid, 1:1, and (2) choline chloride + ethylene glycol, 1:2. The extraction efficiencies of DES 1 after two extraction and two stripping stages were only 15.7 wt% for Cu(II) and 17.6 wt% for Ag(I). The obtained results were compared with those obtained with four newly synthetized ILs as follows: didecyldimethylammonium propionate ([N10,10,1,1][C2H5COO]), didecylmethylammonium hydrogen sulphate ([N10,10,1,H][HSO4]), didecyldimethylammonium dihydrogen phosphate ([N10,10,1,1][H2PO4]), and tetrabutylphosphonium dihydrogen phosphate ([P4,4,4,4][H2PO4]). Various additives, such as didecyldimethyl ammonium chloride surfactant, DDACl; hydrogen peroxide, H2O2; trichloroisocyanuric acid, TCCA; and glycine or pentapotassium bis(peroxymonosulphate) bis(sulphate), PHM, were used with ILs during the extraction process. The solvent concentration, quantity of additivities, extraction temperature, pH, and solid/liquid, as well as organic/water ratios, and the selectivity and distribution ratios were described for all of the systems. The utilization of DESs and the new ILs with different additives presented in this work can serve as potential alternative extractants. This will help to compare these extractants, additives, extraction efficiency, temperature, and time of extraction with those of others with different formulas and procedures. The metal ion content in aqueous and stripped organic solutions was determined by the ICP-MS or ICP-OES methods. The obtained results all show that solvent extraction can successfully replace traditional hydrometallurgical and pyrometallurgical methods in new technologies for the extraction of metal ions from a secondary electronic waste, WPCBs.
]]>Processes doi: 10.3390/pr12030529
Authors: Guanwei Zhou Henrik Saxén Olli Mattila Yaowei Yu
The conditions in the combustion zones, i.e., the raceways, are crucial for the operation of the blast furnace. In recent years, advancements in tuyere cameras and image processing and interpretation techniques have provided a better means by which to obtain information from this region of the furnace. In this study, a comprehensive approach is proposed to visually monitor the status of the pulverized coal cloud at the tuyeres based on a carefully designed processing strategy. Firstly, tuyere images are preprocessed to remove noise and enhance image quality, applying the adaptive Otsu algorithm to detect the edges of the coal cloud, enabling precise delineation of the pulverized coal region. Next, a Swin–Unet model, which combines the strengths of Swin Transformer and U-Net architecture, is employed for accurate segmentation of the coal cloud area. The extracted pulverized coal cloud features are analyzed using RGB super-pixel weighting, which takes into account the variations in color within the cloud region. It is demonstrated that the pulverized coal injection rate shows a correlation with the state of the cloud detected based on the images. The effectiveness of this visual monitoring method is validated using real-world data obtained from a blast furnace of SSAB Europe. The experimental results align with earlier research findings and practical operational experience.
]]>Processes doi: 10.3390/pr12030528
Authors: Lin Zhang Zhili Du Xiao Jin Jian Li Bin Lu
To investigate the characteristics and generation potential of gas generated from over-mature shale, hydrous and anhydrous pyrolysis experiments were carried out on the Longmaxi Formation in the Anwen 1 well of the Sichuan Basin of China at temperatures of 400–598 °C and pressures of 50 Mpa, with (hydrous) and without (anhydrous) the addition of liquid water. The results show that in the presence of water, the total yield of carbon-containing gases (i.e., the sum of methane, ethane, and carbon dioxide) was increased by up to 1.8 times when compared to the total yield from the anhydrous pyrolysis experiments. The increased yield of carbon dioxide and methane accounted for 89% and 10.5% of the total increased yield of carbon-containing gases. This indicated that the participation of water could have promoted the release of carbon from over-mature shale, like we used in this study. The methane generated in the hydrous pyrolysis experiments was heavier, with a δ13C value of −21.27‰ (544 °C) compared to that generated in the anhydrous pyrolysis experiments, which showed a lighter δ13C of −33.70‰ (544 °C). It is noteworthy that the δ13C values of the methane from hydrous pyrolysis at >500 °C were even heavier than that of the kerogen from the over-mature shale, although the δ13C values of the methane show an overall increasing trend with increasing temperature both in hydrous and anhydrous pyrolysis. The carbon dioxide from hydrous pyrolysis was less enriched in 13C relative to that from anhydrous pyrolysis. Specifically, the δ 13C values of the carbon dioxide increased with the increasing temperature in anhydrous pyrolysis, whereas they remained nearly constant with increasing temperature in hydrous pyrolysis. The overall lighter δ13C values of the carbon dioxide generated in the hydrous pyrolysis experiments likely indicate that water tends to prompt the release of lighter carbon and/or suppress the release of heavier carbon from over-mature shale in the form of carbon dioxide, especially at higher temperatures, for example, of >510 °C.
]]>Processes doi: 10.3390/pr12030527
Authors: Xu Su Desheng Zhou Haiyang Wang Jinze Xu
The Sulige gas field is a typical “three lows” (low permeability, low pressure, and low abundance) tight sandstone gas reservoir, with formation pressures often characterized by abnormally high or low pressures. The complex geological features of the reservoir further deviate from conventional understanding, impacting the effective implementation of wellbore blockage removal measures. Therefore, it is imperative to establish the wellbore blockage mechanism, prediction model, and effective prevention measures for the target area. In this study, based on field data, we first experimentally analyzed the water quality and types of blockage in the target area. Subsequently, utilizing a BP neural network model, we established a model for predicting the risk of wellbore blockage and analyzing mitigation measures in the target reservoir. The model’s prediction results, consistent with on-site actual results, demonstrate its reliability and accuracy. Experimental results show that the water quality in the target area is mainly a CaCl2 type, and the predominant scales produced are CaCO3 and BaSO4. Model calculations reveal that temperature, pressure, and ion concentration all influence scaling, with BaSO4 more influenced by pressure and CaCO3 more influenced by temperature. Under the combined effect of temperature, pressure, and ion concentration, different types of scales exhibit distinct trends in scaling quantity. Combining scaling quantity calculations with wellbore contraction ratios, it was found that when the temperature, pressure, and ion concentration are within a certain range, the wellbore contraction rate can be controlled below 4%. At this point, the wellbore scaling risk is minimal, and preventive measures against wellbore scaling can be achieved by adjusting production systems, considering practical production conditions. This study investigates the mechanism of scaling in wellbores of tight sandstone gas reservoirs and proposes a cost-effective scaling prevention measure. This approach can guide the prediction of scaling risks and the implementation of scaling prevention measures for gas wells in tight sandstone reservoirs.
]]>Processes doi: 10.3390/pr12030526
Authors: Benjamin Peric Michael Engler Marc Schuler Katja Gutsche Peter Woias
This study presents a method for predicting the volume flow output of external gear pumps using neural networks. Based on operational measurements across the entire energy chain, the neural network learns to map the internal leakage of the pumps in use and consequently to predict the output volume flow over the entire operating range of the underlying dosing process. As a consequence, the previously used volumetric flow sensors become obsolete within the application itself. The model approach optimizes the higher-level dosing system in order to meet the constantly growing demands of industrial applications. We first describe the mode of operation of the pumps in use and focus on the internal leakage of external gear pumps, as these primarily determine the losses of the system. The structure of the test bench and the data processing for the neural network are discussed, as well as the architecture of the neural network. An error flow rate of approximately 1% can be achieved with the presented approach considering the entire operating range of the pumps, which until now could only be realized with multiple computationally intensive CFD simulations. The results are put into perspective by a hyperparameter study of possible neural architectures. The biggest obstacle considering the industrial scaling of this solution is the data generation process itself for various operating points. To date, an individual dataset is required for each pump because the neural architectures used are difficult to transfer, due to the tolerances of the manufactured pumps.
]]>Processes doi: 10.3390/pr12030525
Authors: Walid M. Shewakh Ibrahim M. Hassab-Allah
A new manufacturing process has been developed that involves drawing circular sheets of thin metal through a conical die to create square cups. This technique produces deep square cups with a height-to-punch-side length ratio of approximately 2, as well as high dimensional accuracy and a nearly uniform height. The study investigated how various factors, including the sheet material properties and process geometric parameters, affect the limiting drawing ratio (LDR). The researchers used finite element analysis to determine the optimal die design for achieving a high LDR and found that the proposed technique is advantageous for producing long square cups with high dimensional accuracy.
]]>Processes doi: 10.3390/pr12030524
Authors: Heidy Lorena Calambás Pulgarin Carolina Caicedo
The thermal, rheological, mechanical, and barrier properties of flat biopolymeric films processed by extrusion with different proportions of plasticizer and surfactant were evaluated. In the first stage, pellets were developed through twin-screw extrusion using a temperature profile in the ascending step process. These samples were analyzed using rotational rheology analysis to understand the viscoelastic transitions through the behavior of the storage and loss modulus, as well as the incidence of complex viscosity concerning concentration. The interaction among the components was analyzed under infrared spectroscopy after the two processing stages, revealing the miscibility of the mixture due to the action of the surfactant. The degradation temperatures increased by more than 20 °C, generating thermal stability, and the temperatures related to polymer transitions were determined. In the second stage, co-extrusion was carried out using pellets from the blend with a melt flow index (MFI) suitable for this process. The samples TPS50-PLA50-T5 and TPS75-PLA25-T5-A10 presented MFI values of 2.27 and 1.72 g/10 min, respectively. These samples were co-extruded for the production of films, impacting the physical properties. The resistance to traction, Young’s modulus, and elongation showed limited effectiveness of plasticizer and surfactant, with high resistance and elongation values (4.276 MPa and 2.63%) in the TPS50-PLA50-T5 film. Additionally, morphological analysis showed the detailed action of the plasticizer on the regular shapes of threads as a product of deformation during material processing. The barrel properties exhibited limited biopolymer–plastic–tensile miscibility, resulting in different water vapor permeability for the TPS75-PLA25-T5-A10 film on each side (a difference of two orders of magnitude). The contact angle corroborated the effect, with values in each case ranging from 103.7° to 30.3°. In conclusion, we assert that biopolymeric films, when modified with plasticizers and surfactants, can be tailored for various applications within the packaging sector while maintaining control over each film.
]]>Processes doi: 10.3390/pr12030523
Authors: Mingxing Guo Ran Lv Zexing Miao Fei Fei Zhixin Fu Enqi Wu Li Lan Min Wang
The prediction of cold load in ice-storage air conditioning systems plays a pivotal role in optimizing air conditioning operations, significantly contributing to the equilibrium of regional electricity supply and demand, mitigating power grid stress, and curtailing energy consumption in power grids. Addressing the issues of minimal correlation between input and output data and the suboptimal prediction accuracy inherent in traditional deep-belief neural-network models, this study introduces an enhanced deep-belief neural-network combination prediction model. This model is refined through an advanced genetic algorithm in conjunction with the “Statistical Products and Services Solution” version 25.0 software, aiming to augment the precision of ice-storage air conditioning load predictions. Initially, the input data undergo processing via the “Statistical Products and Services Solution” software, which facilitates the exclusion of samples exhibiting low coupling. Subsequently, the improved genetic algorithm implements adaptive adjustments to surmount the challenge of random weight parameter initialization prevalent in traditional deep-belief networks. Consequently, an optimized deep-belief neural-network load prediction model, predicated on the enhanced genetic algorithm, is established and subjected to training. Ultimately, the model undergoes simulation validation across three critical dimensions: operational performance, prediction evaluation indices, and operating costs of ice-storage air conditioners. The results indicate that, compared to existing methods for predicting the cooling load of ice-storage air conditioning, the proposed model achieves a prediction accuracy of 96.52%. It also shows an average improvement of 14.12% in computational performance and a 14.32% reduction in model energy consumption. The prediction outcomes align with the actual cooling-load variation patterns. Furthermore, the daily operational cost of ice-storage air conditioning, derived from the predicted cooling-load data, has an error margin of only 2.36%. This contributes to the optimization of ice-storage air conditioning operations.
]]>Processes doi: 10.3390/pr12030522
Authors: Hongxu Zhao Xinghua Zhang Xinchen Gao Peng Chen Kangliang Guo
During the development of condensate gas reservoirs, the phenomenon of retrograde condensation seriously affects the production of gas wells. The skin factor caused by retrograde condensation pollution is the key to measuring the consequent decrease in production. In this study, a multiphase flow model and a calculation model of retrograde condensate damage are first constructed through a dynamic simulation of the phase behavior characteristics in condensate gas reservoirs using the skin coefficient, and these models are then creatively coupled to quantitatively evaluate retrograde condensation pollution. The coupled model is solved using a numerical method, which is followed by an analysis of the effects of the selected formation and engineering parameters on the condensate saturation distribution and pollution skin coefficient. The model is verified using actual test data. The results of the curves show that gas–liquid two-phase permeability has an obvious effect on well production. When the phase permeability curve changes from the first to the third type, the skin coefficient increases from 3.36 to 26.6, and the condensate precipitation range also increases significantly. The distribution of the pollution skin coefficient also changes significantly as a result of variations in the formation and dew point pressures, well production, and formation permeability. The average error between the calculated skin of the model and the actual test skin is 3.87%, which meets the requirements for engineering calculations. These results have certain significance for guiding well test designs and the evaluation of condensate gas well productivity.
]]>Processes doi: 10.3390/pr12030521
Authors: Fandi Zeng Hongwei Diao Ji Cui Wenlong Ye Hongbin Bai Xuying Li
Precision seeding technology is an important component of agricultural mechanization production. The precise regulation of seed movement behavior is the core of precision sowing technology and the key to improving the quality of single seed precision sowing. To accurately obtain the interaction law between seeds and soil after touching the soil, it is necessary to conduct comprehensive physical experiments to determine the simulation parameters of the seed and soil. This article takes coated cotton seeds as the research object, and the basic physical parameters of coated cotton seeds are measured through biological experiments. Based on the Hertz–Mindlin with bonding V2 contact model, a simulation model of compression between coated cotton seeds and soil is established. Using peak compression force as the response value, a combination of physical experiments and simulation simulations was used to calibrate the simulation parameters of the simulation mode of coated cotton seeds and soil. Through PB testing, it was found that four factors have a significant impact on the peak compressive force, and the parameter range was obtained. The Poisson’s ratio of coated cotton seeds was 0.14–0.26. The static friction coefficient between coated cotton seeds and steel plate was 0.38–0.58. The static friction coefficient between soil and soil was 0.3–1.2. The rolling friction coefficient between soil and soil was 0.1–0.6. Through response surface experiments with four factors and three levels, regression models were established between various factors and response values, and the optimal combination of simulation parameters was determined: the Poisson’s ratio of coated cotton seeds was 0.21; the static friction coefficient between coated cotton seed and steel plate was 0.47; the static friction coefficient between soil and soil was 0.34; and the rolling friction coefficient between soil and soil was 0.59. Based on the optimal parameter combination, the simulation of compression between coated cotton seeds and soil was continued, and the variation law of soil particle bonding bonds at different positions of coated cotton seeds during the compression process was obtained. This study provides a basis for exploring the interaction mechanism between the trencher seed soil of precision seeders and optimizing the design of critical components of cotton precision seeders.
]]>Processes doi: 10.3390/pr12030520
Authors: Marija M. Vuksanović Milena Milošević Ivan Dimitrijević Gordana Milentijević Ljiljana Babincev Jelena Gržetić Aleksandar Marinković Milutin Milosavljević
The increase in waste polymer recycling has helped in promoting sustainability, and together with the use of renewable raw materials, it has become a widespread concept with positive effects on both the economy and ecology. Accordingly, the aim of this study was the synthesis of “green” plasticizers, marked as LA/PG/PET/EG/LA, formed from waste poly(ethylene terephthalate) (PET) and bio-based platform chemicals propylene glycol (PG) and levulinic acid (LA). The structure of the obtained plasticizers was complex, as confirmed by results from nuclear magnetic resonance (NMR) and Fourier-transform infrared spectroscopy (FTIR) analysis. The LA/PG/PET/EG/LA plasticizers and waste poly(vinyl chloride) (PVC) were used in an optimized technology for PVC re-granulate production. The hardness of the PVC-based material with “green” plasticizers, in comparison to commercial plasticizer dioctyl terephthalate (DOTP), increased by 11.3%, while migration decreased. An improved material homogeneity and wettability of the fibers by the matrix were observed using SEM analysis of the material’s fracture surface, with a higher efficiency of intermolecular interactions leading to better mechanical performances of the newly designed materials. Thus, LA/PG/PET/EG/LA are unique materials with good compounding and plasticizing potential for PVC, as revealed by differential scanning calorimetry (DSC) and dynamic mechanical analysis (DMA). In that manner, the use of bio-renewable resources and recycled polymers will contribute to diminishing waste polymer generation, contributing to a lower carbon footprint.
]]>Processes doi: 10.3390/pr12030519
Authors: Ahmad Raza Khan
Dynamic load balancing in cloud computing is crucial for efficiently distributing workloads across available resources, ensuring optimal performance. This research introduces a novel dynamic load-balancing approach that leverages a deep learning model combining Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) to calculate load values for each virtual machine (VM). The methodology aims to enhance cloud performance by optimizing task scheduling and stress distribution. The proposed model employs a dynamic clustering mechanism based on computed loads to categorize VMs into overloaded and underloaded clusters. To improve clustering efficiency, the approach integrates Reinforcement Learning (RL) with a sophisticated Hybrid Lyrebird Falcon Optimization (HLFO) algorithm. HLFO merges the Lyrebird Optimization Algorithm (LOA) and Falcon Optimization Algorithm (FOA), enhancing the effectiveness of load balancing. A Multi-Objective Hybrid Optimization model is introduced to optimize task scheduling while considering Quality of Service (QoS) parameters, including makespan minimization, energy consumption reduction, balanced CPU utilization, efficient memory usage, and task prioritization. The implementation, conducted in Python and CloudSim, demonstrates the model’s ability to effectively allocate work between virtual machines (VMs) and physical machines (PMs), resulting in improved resource utilization, shortened makespan, enhanced CPU usage, and rigorous assessments affirming its efficacy. This research addresses the complexity of dynamic load balancing in cloud environments by combining deep learning, reinforcement learning, and hybrid optimization techniques, offering a comprehensive solution to optimize cloud performance under varying workloads and resource conditions.
]]>Processes doi: 10.3390/pr12030518
Authors: Chao Ke Yanxiang Chen Muyang Gan Yang Liu Qunjing Ji
The design for the remanufacturing process (DFRP) is a key part of remanufacturing, which directly affects the cost, performance, and carbon emission of used product remanufacturing. However, used parts have various failure forms and defects, which make it hard to rapidly generate the remanufacturing process scheme for simultaneously satisfying remanufacturing requirements regarding cost, performance, and carbon emissions. This causes remanufactured products to lose their energy-saving and emission-reduction benefits. To this end, this paper proposes an integrated design method for the used product remanufacturing process based on the multi-objective optimization model. Firstly, an integrated DFRP framework is constructed, including design information acquisition, the virtual model construction of DFRP solutions, and the multi-objective optimization of the remanufacturing process scheme. Then, the design matrix, sensitivity analysis, and least squares are applied to construct the mapping models between performance, carbon emissions, cost, and remanufacturing process parameters. Meanwhile, a DFRP multi-objective optimization model with performance, carbon emission, and cost as the design objectives is established, and a teaching–learning based adaptive optimization algorithm is employed to solve the optimization model to acquire a DFRP solution satisfying the target information. Finally, the feasibility of the method is verified by the DFRP of the turbine blade as an example. The results show that the optimized remanufacturing process parameters reduce carbon emissions by 11.7% and remanufacturing cost by USD 0.052 compared with the original process parameters, and also improve the tensile strength of the turbine blades, which also indicates that the DFPR method can effectively achieve energy saving and emission reduction and ensure the performance of the remanufactured products. This can greatly reduce the carbon emission credits of the large-scale remanufacturing industry and promote the global industry’s sustainable development; meanwhile, this study is useful for remanufacturing companies and provides remanufacturing process design methodology support.
]]>Processes doi: 10.3390/pr12030517
Authors: Seydi Yıkmış Berna Erdal Caglar Doguer Okan Levent Melikenur Türkol Nazan Tokatlı Demirok
Onion (Allium cepa L.) juice is an important product used in gastronomy and food formulations. The first objective of this study was to optimize the content of bioactive compounds in purple onion juice (POJ) after the thermosonication process using response surface methodology (RSM) and artificial neural network (ANN) application models. Second, the anticancer, antibacterial, antihypertensive, and antidiabetic effects of POJ obtained after thermal pasteurization (P-POJ) or thermosonication (TS-POJ) were investigated after obtaining the ANN and RSM analysis reports. The optimization process for TS-POJ was carried out at 44 °C, for 13 min, with a 68% amplitude. The findings demonstrated that the angiotensin-converting enzyme (ACE) inhibition level was greater in TS-POJ samples than in the untreated control (C-POJ) sample (p > 0.05). C-POJ, TS-POJ, and P-POJ exhibited the inhibition of cell proliferation in vitro in a dose-dependent manner in lung (A549), cervical (HeLa), and colon cancer cells following 24 h incubation. Thermosonication or thermal pasteurization did not markedly affect the cell proliferation of the examined cancer cells compared to the untreated control group. While no antibacterial effect was observed with low concentrations of samples, they showed an antibacterial effect at pure concentrations (100%). The thermosonication treatment for processing purple onion juice was successful in this study’s results.
]]>Processes doi: 10.3390/pr12030515
Authors: Seyed Reza Nabavi Saheleh Ghahri Gade Pandu Rangaiah
In the catalytic ozonation process (COP), the reactions are complex, and it is very difficult to determine the effect of different operating parameters on the degradation rate of pollutants. Data-based modeling tools, such as the multilayer perceptron (MLP) neural network, can be useful in establishing the complex relationship of degradation efficiency with the operating variables. In this work, the COP of acid red 88 (AR88) with Fe3O4 nano catalyst was investigated in a semi-batch reactor and a MLP model was developed to predict the degradation efficiency (%DE) of AR88 in the range of 25 to 96%. The MLP model was trained using 78 experimental data having five input variables, namely, AR88 initial concentration, catalyst concentration, pH, inlet air flow rate and batch time (in the ranges of 150–400 mg L−1, 0.04–0.4 g L−1, 4.5–8.5, 0.5–1.90 mg min−1 and 5–30 min, respectively). Its optimal topology was obtained by changing the number of neurons in the hidden layer, the momentum and the learning rates to 7, 0.075 and 0.025, respectively. A high correlation coefficient (R2 > 0.98) was found between the experimental and predicted values by the MLP model. Simultaneous maximization of %DE and minimization of Fe3O4 concentration was carried out by multi-objective particle swarm optimization (MOPSO) and the Pareto-optimal solutions were successfully obtained. The trade-off was analyzed through multi-criteria decision making, and one Pareto-optimal solution was selected. The developed model and optimal points are useful for treatment of AR88 wastewater.
]]>Processes doi: 10.3390/pr12030516
Authors: Yuanlin Jing Chenhao Wang Qunwu Huang Yiping Wang Yangyang Yu
In this paper, under the background of low-temperature steam waste heat recovery technology, the pressure oscillation characteristics of direct-contact condensation between continuously falling droplets and saturated steam at sub-atmosphere pressure were studied. An experimental device of pressure oscillation based on an acceleration oscillation sensor was established to investigate the influence of vapor pressure and fluid velocity on the oscillation characteristics of direct-contact condensation. The results showed that as the absolute pressure increases, the peak value of oscillation decreases gradually and the time-domain periodic waveform becomes fluctuating. When the liquid flow rate is low, the condensation oscillation shows a single-peak waveform and the dominant frequency moves towards a higher frequency. When the liquid velocity increases gradually, the RMS (root mean square) of pressure oscillation remains unchanged at first and then decreases obviously. The dominant frequency of oscillation decreases from 23.68 Hz to 7.16 Hz continuously, and the amplitude of oscillation decreases in a parabolic pattern. The auto power spectrum showed that the frequencies with higher energy become unconcentrated and show fluctuation characteristics. The amplitude of the dominant frequency is about 0.0004 (m/s2)2, while that of the other peak frequencies is about 0.00010–0.00015 (m/s2)2. In practical applications, excessive flow velocity and reduced vacuum degree should be avoided to prevent low-frequency vibration, which may lead to fatigue damage or even failure of the equipment due to resonance. In addition, the direct-contact condensation state can be inferred from the vibration signal to reduce environmental noise.
]]>Processes doi: 10.3390/pr12030514
Authors: Moeka Shimada Risa Someya Yasunao Okamoto Daigo Yamamoto Akihisa Shioi
The transformation of amphiphilic molecular assemblies in response to chemical oscillations is fundamental in biological systems. The reversible transformation of a vesicular aggregate (VA) in response to a pH oscillation is presented in this study. A VA composed of the cationic surfactant didodecyldimethylammonium bromide is transformed using a pH oscillation ranging between 3 and 7. When the VA attains a stable structure at extreme pH values, the transformation reaches the irreversible stage. However, the addition of a phosphate buffer to the VA suspension changes the pH oscillation pattern from being rectangular to triangular and decreases the oscillation amplitude, successfully achieving the reversible transformation of the VA. Maintaining the non-equilibrium (transient) structures throughout the transformation and not falling into the equilibrium state with a varying pH are essential for the reversible transformation. This may be common and essential for dynamics in biological cells.
]]>Processes doi: 10.3390/pr12030513
Authors: Jinlin Zhu Xingke Gao Zheng Zhang
Traditional two-dimensional dynamic fault detection methods describe nonlinear dynamics by constructing a two-dimensional sliding window in the batch and time directions. However, determining the shape of a two-dimensional sliding window for different phases can be challenging. Samples in the two-dimensional sliding windows are assigned equal importance before being utilized for feature engineering and statistical control. This will inevitably lead to redundancy in the input, complicating fault detection. This paper proposes a novel method named attention-based two-dimensional dynamic-scale graph autoencoder (2D-ADSGAE). Firstly, a new approach is introduced to construct a graph based on a predefined sliding window, taking into account the differences in importance and redundancy. Secondly, to address the training difficulties and adapt to the inherent heterogeneity typically present in the dynamics of a batch across both its time and batch directions, we devise a method to determine the shape of the sliding window using the Pearson correlation coefficient and a high-density gridding policy. The method is advantageous in determining the shape of the sliding windows at different phases, extracting nonlinear dynamics from batch process data, and reducing redundant information in the sliding windows. Two case studies demonstrate the superiority of 2D-ADSGAE.
]]>Processes doi: 10.3390/pr12030512
Authors: Agata Lipko Anna Grzeczkowicz Magdalena Antosiak-Iwańska Marcin Strawski Monika Drabik Angelika Kwiatkowska Ewa Godlewska Ludomira H. Granicka
(1) Purpose: The aim of the study was to develop a nanocomposite with copper nanoparticles constituting a bacteriostatic surface to maintain human lung cell function. (2) Methods: A polyelectrolyte layer coating that incorporated copper nanoparticles was designed. As a bacteriostatic factor, copper nanoparticles were applied as a colloidal solution of copper nanoparticles (ColloidCuNPs) and a solution of copper nanoparticles (CuNPs). The influence of the polyelectrolytes on selected Gram (+) and Gram (−) strains was examined. The function and morphology of the human adenocarcinoma A549 cell line, comprising human epithelial lung cells cultured in the presence of nanocomposite layer coatings, were evaluated. We applied fluorescence and scanning electron microscopies, as well as flow cytometry, for these studies. Furthermore, the layer coating material was characterized by atomic force microscopy (AFM) and energy dispersive X-ray analysis (EDX). (3) Results: It was observed that the polyelectrolytes polyethyleneimine (PEI) and poly-L-lysine (PLL) did not induce proliferation of the E. coli strain. However, they did induce the proliferation of the S. aureus strain. Due to the effectiveness of the CuNPs against the E. coli strain, CuNPs were selected for further research. The designed coatings of proper NPs shared the sustained function of human lung cells within 10 days of culture. The AFM and EDX characterization confirmed the presence of copper in the layer coating nanomaterial. The presence of CuNPs in polyethyleneimine-based nanocomposite deepened the bacteriostatic effect on E. coli compared with PEI alone. Meanwhile, incorporating CuNPs in PLL allowed A549 cell maintenance but did not exert a bacteriostatic influence on the examined strain. (4) Conclusions: The platform based on polyelectrolytes, incorporated with copper nanoparticles, that ensures the growth and appropriate morphology of the human lung epithelial cells, might be considered an element of a system for medical devices used to maintain the function of human lung cells.
]]>Processes doi: 10.3390/pr12030511
Authors: Ricardo Santos Renata Assis Raquel Freitas Isabele Barbosa Vânia Ceccatto
Rapadura is a well-recognized sugar-cane-derived product with a sweet, characteristic flavor and hard texture. This product is a cultural Brazilian landmark, particularly in Ceará, Brazil, where it is usually produced by small family businesses and consumed locally. This feature contributes to the difficulties of rapadura production standardization, a requirement for the global market. Against this backdrop, this study focuses on analyzing the centesimal composition and mineral content of rapadura. Six samples from different cities in Ceará were analyzed for moisture, ash, lipids, proteins, carbohydrates, energy value, and minerals. The results ranged from 6.42–11.74% for moisture, 0.23–1.12% for ash, 0.49–0.92% for protein, 85.18–89.12% for lipids, and 352.00–391.19 Kcal for energy value. Significant variations were observed between the samples, showing a lack of standardization in the production process. The analysis of micronutrients revealed low levels, with copper and iron standing out in sample D. It can be concluded that the rapadura analyzed meets the physical-chemical parameters established by national legislation and is a food rich in carbohydrates and energy.
]]>Processes doi: 10.3390/pr12030510
Authors: Pablo Silva Ortiz Silvio de Oliveira Adriano Pinto Mariano Agnes Jocher John Posada
The aeronautical sector faces challenges in meeting its net-zero ambition by 2050. To achieve this target, much effort has been devoted to exploring sustainable aviation fuels (SAF). Accordingly, we evaluated the technical performance of potential SAF production in an integrated first- and second-generation sugarcane biorefinery focusing on Brazil. The CO2 equivalent and the renewability exergy indexes were used to assess environmental performance and impact throughout the supply chain. In addition, exergy efficiency (ηB) and average unitary exergy costs (AUEC) were used as complementary metrics to carry out a multi-criteria approach to determine the overall performance of the biorefinery pathways. The production capacity assumed for this analysis covers 10% of the fuel demand in 2020 at the international Brazilian airports of São Paulo and Rio de Janeiro, leading to a base capacity of 210 kt jet fuel/y. The process design includes sugarcane bagasse and straw as the feedstock of the biochemical processes, including diverse pre-treatment methods to convert lignocellulosic resources to biojet fuel, and lignin upgrade alternatives (cogeneration, fast pyrolysis, and gasification Fischer-Tropsch). The environmental analysis for all scenarios shows a GHG reduction potential due to a decrease of up to 30% in the CO2 equivalent exergy base emissions compared to fossil-based jet fuel.
]]>Processes doi: 10.3390/pr12030509
Authors: Antonio Vega-Galvez Luis S. Gomez-Perez Kong Shun Ah-Hen Francisca Zepeda Purificación García-Segovia Cristina Bilbao-Sainz Nicol Mejías Alexis Pasten
This study examined the convective drying of red cabbage at temperatures ranging from 50 to 90 °C. Mathematical modeling was used to describe isotherms, drying kinetics and rehydration process. The effects of drying conditions on energy consumption and microstructure were also evaluated. The Halsey model had the best fit to the isotherm data and the equilibrium moisture was determined to be 0.0672, 0.0490, 0 0.0379, 0.0324 and 0.0279 g water/g d.m. at 50, 60, 70, 80 and 90 °C, respectively. Drying kinetics were described most accurately by the Midilli and Kuçuk model. Also, the diffusion coefficient values increased with drying temperature. Lower energy consumption was found for drying at 90 °C and the rehydration process was best described by the Weibull model. Samples dehydrated at 90 °C showed high water holding capacity and better maintenance of microstructure. These results could be used to foster a sustainable drying process for red cabbage.
]]>Processes doi: 10.3390/pr12030508
Authors: Zhengkai Song Yuxuan Chen Tao Yu Xi Wang Haifeng Cao Zhiqiang Li Xiaopeng Lang Simeng Xu Shiyi Lu Chenxing Jiang
The flow field structure and pressure pulsation characteristics in two series of trailing edges of a centrifugal pump are investigated using the SST k-w turbulence model. Series 1 involves varying the impeller exit angle, and Series 2 involves varying the impeller exit shape. The entropy generation rate analysis method is used to evaluate the numerical simulation results. Vortex cores within the flow field are identified by applying the Ω criterion. The influence of different trailing edge configurations on the energy loss characteristics of the pumps is explored. The dynamic mode decomposition (DMD) method is used to analyze pressure pulsations at the volute considering unsteady flows in centrifugal pumps with different trailing edge shapes. The findings suggest that different trailing edge shapes can be used to adjust the energy loss proportions in various components of the pump. In Series 1, the efficiency remains nearly constant with changes in the outlet angle on both sides of the trailing edge. In Series 2, the efficiency is enhanced by 1.18% with the elliptical edge shape on both sides (EBS) compared to the original trailing edge (OTE) shape. In Series 1 and Series 2, greater entropy generation rates are accompanied by greater pressure pulsations at the pump outlet. The DMD results demonstrate a noticeable impact of the different trailing edges on the pressure distribution of various modes within the volute. Moreover, the impeller outlet pressure inhomogeneity coefficient changes under different modes. This study holds great significance for selecting the appropriate trailing edges for centrifugal pumps.
]]>