Journal Description
Processes
Processes
is an international, peer-reviewed, open access journal on processes/systems in chemistry, biology, material, energy, environment, food, pharmaceutical, manufacturing, automation control, catalysis, separation, particle and allied engineering fields published monthly online by MDPI. The Systems and Control Division of the Canadian Society for Chemical Engineering (CSChE S&C Division) and the Brazilian Association of Chemical Engineering (ABEQ) are affiliated with Processes and their members receive discounts on the article processing charges. Please visit Society Collaborations for more details.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), Ei Compendex, Inspec, AGRIS, and other databases.
- Journal Rank: JCR - Q2 (Engineering, Chemical) / CiteScore - Q2 (Chemical Engineering (miscellaneous))
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 13.7 days after submission; acceptance to publication is undertaken in 2.8 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
3.5 (2022);
5-Year Impact Factor:
3.4 (2022)
Latest Articles
Selected Micropollutant Removal from Municipal Wastewater
Processes 2024, 12(5), 888; https://doi.org/10.3390/pr12050888 (registering DOI) - 27 Apr 2024
Abstract
Micropollutants belong to various groups of chemicals. One of the most diverse and large group of them are pharmaceuticals. The presence of pharmaceutical residues in wastewater poses a significant challenge to water quality and environmental health. This paper provides an overview of recent
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Micropollutants belong to various groups of chemicals. One of the most diverse and large group of them are pharmaceuticals. The presence of pharmaceutical residues in wastewater poses a significant challenge to water quality and environmental health. This paper provides an overview of recent advancements in the removal of pharmaceuticals from water, focusing on various treatment processes and their effectiveness in eliminating micropollutants. Through a review of the literature, including studies on ozonation, UV irradiation, sulfate radical-based technologies, and photocatalytic processes, insights into degradation mechanisms and optimal conditions for their removal are synthesized. Additionally, with new legislation mandating the monitoring of selected micropollutants and the implementation of quaternary treatment in wastewater treatment plants, the paper discusses prospects for future research and recommendations for effective pharmaceutical removal. Key actions include conducting comprehensive laboratory and pilot trials, implementing quaternary treatment of wastewater, continuously monitoring water quality, investing in research and development, and promoting collaboration and knowledge sharing among stakeholders. By embracing these strategies, we can work towards safeguarding water resources and protecting public health from the adverse effects of pharmaceutical contamination.
Full article
(This article belongs to the Special Issue Eco-Friendly Advanced Processes for Efficient Removal of Emerging Contaminants from the Environment)
Open AccessArticle
Electrochemical Processes Used to Degrade Thiamethoxam in Water and Toxicity Analyses in Non-Target Organisms
by
Juliane C. Forti, Pedro E. M. Robles, Yasmin S. Tadayozzi, Maiara A. F. Demori, Felipe A. Santos, Fernando F. Putti and Eduardo F. Vicente
Processes 2024, 12(5), 887; https://doi.org/10.3390/pr12050887 (registering DOI) - 27 Apr 2024
Abstract
Pesticides ensure greater productivity in less time; however, they spread beyond the perimeters to which they are applied to reach non-target organisms, thereby affecting plant, animal, and human health. Thiamethoxam (TMX) is considered to be one of the main agents responsible for poisoning
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Pesticides ensure greater productivity in less time; however, they spread beyond the perimeters to which they are applied to reach non-target organisms, thereby affecting plant, animal, and human health. Thiamethoxam (TMX) is considered to be one of the main agents responsible for poisoning bees and potentially contaminating surface and groundwater. Conventional water-treatment protocols are unable to degrade thiamethoxam; therefore, electrochemically advanced oxidative processes (EAOPs) have become promising alternatives owing to their ease of operation and cost-effectiveness. Herein, we examined the use of EAOPs to oxidize thiamethoxam in commercial Actara® and analyzed treatment efficiencies through phytotoxicity studies using cucumber and maize seeds as bioindicators. In addition, the cost of each process was analyzed based on the resulting current efficiency. The treated solutions were used to germinate seeds that were analyzed for total protein, hydrogen peroxide, lipid peroxidation (MDA), superoxide dismutase (SOD), and catalase (CAT) activities. EAOPs were found to effectively oxidize TMX, with more than 50% degraded and 80% COD removed under all treatment conditions, even when the commercial product was used. The photoelectro-Fenton process using 10 mg L−1 FeSO4 and 100 mg L−1 H2O2 exhibited the best results, with 79% of the TMX degraded and 83% of the COD removed, additionally exhibiting the lowest estimated operating cost (USD 1.01 dm−3). Higher enzymatic SOD and CAT activities, total protein content, and H2O2 concentration were observed; however, no significant changes in MDA were recorded. This treatment protocol effectively oxidizes TMX and reduces its phytotoxicity in maize and cucumber seedlings.
Full article
(This article belongs to the Special Issue The Role of Electrochemical Technology in Wastewater Treatment)
Open AccessArticle
Numerical Simulation of Stress Disturbance Mechanism Caused by Hydraulic Fracturing of Shale Formation
by
Yinghui Zhu, Heng Zheng, Yi Liao and Ruiquan Liao
Processes 2024, 12(5), 886; https://doi.org/10.3390/pr12050886 (registering DOI) - 27 Apr 2024
Abstract
Characterizing changes in rock properties is essential for the hydraulic fracture and re-fracture parameter optimization of shale formations. This paper proposed a hydraulic fracturing model to investigate the changes in rock properties during hydraulic fracturing using SPH, and the changes in the stress
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Characterizing changes in rock properties is essential for the hydraulic fracture and re-fracture parameter optimization of shale formations. This paper proposed a hydraulic fracturing model to investigate the changes in rock properties during hydraulic fracturing using SPH, and the changes in the stress field and rock properties were quantitatively characterized. The simulation results indicated that the minimum horizontal principal stress increased by 10 MPa~15 MPa during fracture propagation, which is the main reason for the uneven propagation in multi-fracture propagation. Affected by the stress disturbance, the stimulated area was divided into four parts based on the changes in Young’s modulus and permeability; the more seriously the stress disturbance was affected, the higher the permeability of the stimulated zone was, and the smaller the stimulated zone was. Meanwhile, a zone with reduced permeability appeared due to the compression effect caused by the high injection pressure, and this increased with the increase in stress disturbance. The main reason for this was that strain formed because of the compression effect from the high injection pressure. The higher the stress disturbance, the higher the accumulated strain. This new model provides a new method for fracture parameter optimization, which also provides a foundation for the re-fracture parameter optimization of shale formations.
Full article
(This article belongs to the Special Issue Advanced Fracturing Technology for Oil and Gas Reservoir Stimulation)
Open AccessFeature PaperArticle
Computational Insights into the Interaction between Neprilysin and α-Bisabolol: Proteolytic Activity against Beta-Amyloid Aggregates in Alzheimer’s Disease
by
Jonathan Elias Rodrigues Martins, José Ednésio da Cruz Freire, Francisco Sérgio Lopes Vasconcelos-Filho, Diego da Silva de Almeida, Vânia Marilande Ceccatto and Bruno Lopes de Sousa
Processes 2024, 12(5), 885; https://doi.org/10.3390/pr12050885 (registering DOI) - 27 Apr 2024
Abstract
(1) Background: Alzheimer’s disease (AD) is an irreversible disorder of the central nervous system associated with beta-amyloid protein (Aβ) deposition and accumulation. Current treatments can only act on symptoms and not the etiologic agent. Neprilysin and α-bisabolol have been shown to reduce the
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(1) Background: Alzheimer’s disease (AD) is an irreversible disorder of the central nervous system associated with beta-amyloid protein (Aβ) deposition and accumulation. Current treatments can only act on symptoms and not the etiologic agent. Neprilysin and α-bisabolol have been shown to reduce the aggregation of Aβ, suggesting a potential interaction between both molecules, leading to increased proteolytic activity on Aβ aggregates. (2) Methods: Computational simulations were conducted to explore the interaction between murine neprilysin [NEP(m)] and α-bisabolol and their effects on enzymatic activity. NEP(m) structure was predicted using comparative modeling, and the binding pattern to α-bisabolol and its effects on leu-enkephalin binding were explored through docking calculations and molecular dynamics simulations, respectively. (3) Results: The findings suggest that α-bisabolol stabilizes the Val481-Pro488 segment of NEP2(m), which directly interacts with the peptide substrate, enabling an optimized alignment between the catalytic residue Glu525 and leu-enkephalin. (4) Conclusions: This computational evidence strongly supports the notion that α-bisabolol stabilizes peptide substrates at the NEP2(m) catalytic site, leading to the positive modulation of enzymatic activity.
Full article
(This article belongs to the Section Pharmaceutical Processes)
Open AccessArticle
Experimental Research of Ultrasonic Cavitation Evolution Mechanism and Model Optimization of RUREMM on Cylindrical Surface
by
Wenjun Tong and Lin Li
Processes 2024, 12(5), 884; https://doi.org/10.3390/pr12050884 (registering DOI) - 27 Apr 2024
Abstract
Micro-pits are widely used in the aerospace and tribology sectors on cylindrical surfaces and electrochemical micromachining which are of great significance for the high material removal rate, absence of tool wear, and mechanical stress, while facing significant challenges such as stray corrosion and
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Micro-pits are widely used in the aerospace and tribology sectors on cylindrical surfaces and electrochemical micromachining which are of great significance for the high material removal rate, absence of tool wear, and mechanical stress, while facing significant challenges such as stray corrosion and low machining efficiency. Aiming at the above problems, this paper proposes a comprehensive method called radial ultrasonic rolling electrochemical micromachining (RUREMM) in which an ultrasonic field has been added onto the cylindrical surface. First, a theoretical model was created to gain the rules of the formation and collapse of bubbles in the liquid medium. Second, to analyze the optimal size of the cathode electrode, the COMSOL5.2 simulation software was proposed to research the influence of the electric field on the different dimensions, and the influences of different parameters in RUREMM on material depth/diameter ratio and roughness are explored through processing experiments. Research results found that the cavitation bubble undergoes expansion, compression, collapse and oscillation, where the max deviation is less than 12.5%. The optimized size was chosen as 200 × 200 μm2 and an electrode spacing of 800 μm through a series of electric field model simulation analyses. Relevant experiments show that the minimum pits with a width of 212.4 μm, a depth of 21.8 μm, and a surface roughness (Ra) of 0.253 μm were formed due to the optimized parameters. The research results can offer theoretical references for fabricating micro-pits with enhanced surface quality and processing precision on cylindrical surfaces.
Full article
(This article belongs to the Section Manufacturing Processes and Systems)
Open AccessArticle
Numerical Simulation of the Mixing and Salt Washing Effects of a Static Mixer in an Electric Desalination Process
by
Yuhang Liu, Mengmeng Gao, Zibin Huang, Hongfu Wang, Peiqing Yuan, Xinru Xu and Jingyi Yang
Processes 2024, 12(5), 883; https://doi.org/10.3390/pr12050883 (registering DOI) - 27 Apr 2024
Abstract
Electric desalination units in the crude oil refining process are becoming increasingly important with the growing trend towards heavy and poor crude oils. The oil–water mixing effect of the static mixer plays a crucial role in the electric desalination process. The present study
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Electric desalination units in the crude oil refining process are becoming increasingly important with the growing trend towards heavy and poor crude oils. The oil–water mixing effect of the static mixer plays a crucial role in the electric desalination process. The present study investigated the effect of various variables, such as mixer type, number of mixing elements, washing water consumption, and oil viscosity and density on the oil–water mixing efficiency of a static mixer. In addition, this study also analyzed the effect of these variables on the salt washing process that occurs during mixing using a kinetic equation for the dissolution of inorganic salts. The results showed that the number of mixing elements was the most significant variable, followed by the amount of washing water injected. The density of the crude oil had a negligible effect. Based on these results, the use of four mixing elements in the SMX static mixer was recommended. The injection of washing water should be controlled at about 8%, while ensuring that the interfacial tension between oil and water remains below 0.01 N/m. Under these conditions, the salt washing efficiency reached 46.3%. This study provides a theoretical basis for designing static mixers and optimizing their operation in electric desalination processes.
Full article
(This article belongs to the Section Separation Processes)
Open AccessArticle
Novel Triplet Loss-Based Domain Generalization Network for Bearing Fault Diagnosis with Unseen Load Condition
by
Bingbing Shen, Min Zhang, Le Yao and Zhihuan Song
Processes 2024, 12(5), 882; https://doi.org/10.3390/pr12050882 - 26 Apr 2024
Abstract
In the real industrial manufacturing process, due to the constantly changing operational loads of equipment, it is difficult to collect data from all load conditions as the source domain signal for fault diagnosis. Therefore, the appearance of unseen load vibration signals in the
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In the real industrial manufacturing process, due to the constantly changing operational loads of equipment, it is difficult to collect data from all load conditions as the source domain signal for fault diagnosis. Therefore, the appearance of unseen load vibration signals in the target domain presents a challenge and research hotspot in fault diagnosis. This paper proposes a triplet loss-based domain generalization network (TL-DGN) and then applies it to an unseen domain bearing fault diagnosis. TL-DGN first utilizes a feature extractor to construct a multi-source domain classification loss. Furthermore, it measures the distance between class data from different domains using triplet loss. The introduced triplet loss can narrow the distance between samples of the same class in the feature space and widen the distance between samples of different classes based on the action of the cross-entropy loss function. It can reduce the dependency of the classification boundary on bearing operational loads, resulting in a more generalized classification model. Finally, two comparative experiments with fault diagnosis models without triplet loss and other classification models demonstrate that the proposed model achieves superior fault diagnosis performance.
Full article
(This article belongs to the Special Issue Machine Learning, Control, and Optimization in Manufacturing and Industry 4.0)
Open AccessArticle
Trajectory Tracking Control of Mobile Manipulator Based on Improved Sliding Mode Control Algorithm
by
Shuwan Cui, Huzhe Song, Te Zheng and Penghui Dai
Processes 2024, 12(5), 881; https://doi.org/10.3390/pr12050881 - 26 Apr 2024
Abstract
Research on trajectory tracking control for climbing welding robots holds significant importance in the field of automated welding. However, existing trajectory tracking methods suffer from issues such as jitter and slow speed. In this paper, an improved sliding mode control strategy is proposed
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Research on trajectory tracking control for climbing welding robots holds significant importance in the field of automated welding. However, existing trajectory tracking methods suffer from issues such as jitter and slow speed. In this paper, an improved sliding mode control strategy is proposed based on the self-designed wall-climbing welding mobile manipulator. Firstly, a new adaptive sliding mode control strategy is proposed for the mobile platform based on the kinematic model. By introducing a new approach law, the controller is designed when the distance between the center of mass is unknown. Secondly, regarding the manipulator, we analyze simplified dynamic equations, extract uncertain components, and utilize a CNN for compensation. This compensation strategy is integrated into the sliding mode control law, achieving precise control over the manipulator and effectively resolving issues like slow tracking speeds, large errors, and chattering. The stability of the robot control system is proved by the Lyapunov function. Through simulation analysis and experimental validation, the proposed control method is confirmed to be feasible and superior.
Full article
(This article belongs to the Section Automation Control Systems)
Open AccessArticle
Oil–Water Hydrodynamics Model during Oil Displacement by Water in Down-Hill Mobile Pipeline
by
Guang Li, Gang Fang, Zhi Kou, Shiming Chen, Jimiao Duan and Yan Chen
Processes 2024, 12(5), 880; https://doi.org/10.3390/pr12050880 - 26 Apr 2024
Abstract
In the process of water displacing oil within mobile pipelines, it is common that the oil tends to accumulate at the elevated sections of inclined pipelines, leading to an issue of residual oil accumulation. In this paper, the mechanism of carrying accumulated oil
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In the process of water displacing oil within mobile pipelines, it is common that the oil tends to accumulate at the elevated sections of inclined pipelines, leading to an issue of residual oil accumulation. In this paper, the mechanism of carrying accumulated oil out of the pipeline with water flow is discussed. Taking the residual oil layer in down-hill pipelines as a research object, a hydrodynamic model of the water-oil displacement process is established based on the theory of liquid–liquid two-phase flow and the application of the momentum transfer equation. It has been found that the use of this model can enhance the computational speed by 15% without affecting the accuracy of the calculations. Subsequently, the model is used to analyze the impact of different initial water-phase velocities, inclination angles, initial oil-phase heights, and pipeline diameters on the oil-carrying process of water flow. The results indicate that increasing the initial water-phase velocity, the angle of inclination, and the initial oil-phase height all enhance the fluctuation in the oil–water interface, making it easier for the oil phase to be carried away from the pipeline. Conversely, when all other parameters are held constant, an increase in the pipeline diameter tends to stabilize the oil–water interface, thereby making it more difficult for the residual oil to be carried away by the water flow.
Full article
(This article belongs to the Section Energy Systems)
Open AccessArticle
Flow Characterization in Fractured Shale Oil Matrices Using Advanced Nuclear Magnetic Resonance Techniques
by
Sichen Li, Jing Sun, Yang Gao, Dehua Liu, Zhengyang Zhang and Pan Ma
Processes 2024, 12(5), 879; https://doi.org/10.3390/pr12050879 - 26 Apr 2024
Abstract
The evaluation of flow dynamics in fractured shale oil reservoirs presents significant challenges due to the complex pore configurations and high organic material concentration. Conventional methods for petrophysical and fluid dynamic evaluations are insufficient in addressing these complexities. However, nuclear magnetic resonance (NMR)
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The evaluation of flow dynamics in fractured shale oil reservoirs presents significant challenges due to the complex pore configurations and high organic material concentration. Conventional methods for petrophysical and fluid dynamic evaluations are insufficient in addressing these complexities. However, nuclear magnetic resonance (NMR) technology is an effective technique for quantitatively delineating fluid micro-transport properties across the reservoir core. This study presents an experimental methodology rooted in NMR technology to quantify the flow capabilities within the shale oil matrix. This approach incorporates high-pressure saturation flow experiments across seven distinct core samples to gauge the micro-transport phenomena of fluids across various pore dimensions. The results revealed that under high-pressure saturation, shale cores devoid of fractures demonstrated an average crude oil saturation rate of merely 19.44%. Cores with evident stratification exhibited a 16.18% increase in flow capacity compared to their non-stratified counterparts. The flow dynamics within these shale reservoirs exhibited a range of behaviors, from non-linear to linear. In lower-permeability zones, non-linear patterns became increasingly apparent. An NMR T2 spectrum analysis was used to identify the minimum effective pore size conducive to shale oil flow within the matrix, which was between 8 and 10 nanometers. These insights provide a foundation for a deeper understanding of the mechanisms behind oil and gas migration in fractured shale oil matrices, offering valuable insight into their extractive potential.
Full article
(This article belongs to the Section Energy Systems)
Open AccessArticle
Forecasting Gas Well Classification Based on a Two-Dimensional Convolutional Neural Network Deep Learning Model
by
Chunlan Zhao, Ying Jia, Yao Qu, Wenjuan Zheng, Shaodan Hou and Bing Wang
Processes 2024, 12(5), 878; https://doi.org/10.3390/pr12050878 - 26 Apr 2024
Abstract
In response to the limitations of existing evaluation methods for gas well types in tight sandstone gas reservoirs, characterized by low indicator dimensions and a reliance on traditional methods with low prediction accuracy, therefore, a novel approach based on a two-dimensional convolutional neural
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In response to the limitations of existing evaluation methods for gas well types in tight sandstone gas reservoirs, characterized by low indicator dimensions and a reliance on traditional methods with low prediction accuracy, therefore, a novel approach based on a two-dimensional convolutional neural network (2D-CNN) is proposed for predicting gas well types. First, gas well features are hierarchically selected using variance filtering, correlation coefficients, and the XGBoost algorithm. Then, gas well types are determined via spectral clustering, with each gas well labeled accordingly. Finally, the selected features are inputted, and classification labels are outputted into the 2D-CNN, where convolutional layers extract features of gas well indicators, and the pooling layer, which, trained by the backpropagation of CNN, performs secondary dimensionality reduction. A 2D-CNN gas well classification prediction model is constructed, and the softmax function is employed to determine well classifications. This methodology is applied to a specific tight gas reservoir. The study findings indicate the following: (1) Via two rounds of feature selection using the new algorithm, the number of gas well indicator dimensions is reduced from 29 to 15, thereby reducing the computational complexity of the model. (2) Gas wells are categorized into high, medium, and low types, addressing a deep learning multi-class prediction problem. (3) The new method achieves an accuracy of 0.99 and a loss value of 0.03, outperforming BP neural networks, XGBoost, LightGBM, long short-term memory networks (LSTMs), and one-dimensional convolutional neural networks (1D-CNNs). Overall, this innovative approach demonstrates superior efficacy in predicting gas well types, which is particularly valuable for tight sandstone gas reservoirs.
Full article
(This article belongs to the Special Issue Data-Based Prediction Models in Energy Systems: From Principles to Applications)
Open AccessArticle
Business Process Reengineering with a Circular Economy PDCA Model from the Perspective of Manufacturing Industry
by
Milena Nebojša Rajić, Zorana Zoran Stanković, Marko V. Mančić, Pedja Miroslav Milosavljević and Rado Maksimović
Processes 2024, 12(5), 877; https://doi.org/10.3390/pr12050877 (registering DOI) - 26 Apr 2024
Abstract
In times of increasing awareness of sustainability and the need for efficient business processes, this study explores the integration of business process reengineering with circular economy principles within Serbian manufacturing organizations. Addressing the need for sustainable development, the research aims to propose and
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In times of increasing awareness of sustainability and the need for efficient business processes, this study explores the integration of business process reengineering with circular economy principles within Serbian manufacturing organizations. Addressing the need for sustainable development, the research aims to propose and validate a model that harmonizes business process reengineering with the circular economy to improve environmental and organizational performance. The study conducted an extensive survey and analysis across 135 manufacturing organizations in Serbia, assessing their readiness and current practices in adopting circular economy strategies through business process reengineering, utilizing the Plan-Do-Check-Act (PDCA) model. The findings reveal a moderate level of integration, with an average implementation score of 44.70% across surveyed organizations. Notably, organizations with ISO 9001 and ISO 14001 certifications demonstrated higher levels of model implementation. The study highlights the potential of integrating business process reengineering with circular economy principles as a path to sustainable manufacturing. It also highlights the need for targeted strategies to improve management commitment, resource allocation, and participation in sustainable practices. The research contributes valuable insights for policymakers, industry stakeholders, and academic discourse, advocating for a more systematic approach to embedding circular economy principles within organizational processes for a sustainable future.
Full article
(This article belongs to the Section Manufacturing Processes and Systems)
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Open AccessArticle
Fiber Solidification Treatment of River and Lake Wastewater and Sediments: Deformation Characteristics and Microscopic Mechanism Research
by
Aiwu Yang, Jian Xu, Yuhao Gu, Fengjun Li, Xiaoqiang Liu and Jinfang Hou
Processes 2024, 12(5), 876; https://doi.org/10.3390/pr12050876 - 26 Apr 2024
Abstract
River and lake dredging projects inevitably produce significant quantities of wastewater and sediment. This accumulation results in dredged soil with high moisture content, characterized by low strength, rendering it unsustainable for use. To facilitate environmentally friendly utilization of wastewater and sediment, solidifying agents
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River and lake dredging projects inevitably produce significant quantities of wastewater and sediment. This accumulation results in dredged soil with high moisture content, characterized by low strength, rendering it unsustainable for use. To facilitate environmentally friendly utilization of wastewater and sediment, solidifying agents and basalt fibers are introduced to solidify the wastewater within the dredged sediment. This process transforms the wastewater, sediment, solidifying agents, and basalt fibers into a novel, strengthened material. This transformation allows for their application as stabilized soil for engineering endeavors. Indoor experiments and scanning electron microscope analyses were performed to examine the deformation characteristics of fiber-stabilized soil and analyze its micro-mechanisms. Research findings suggest that as the curing age increases, the curing agent’s reaction becomes more comprehensive. Fibers have the potential to ameliorate soil damage. The proposed binary-medium model’s applicability and accuracy were validated through the analysis of triaxial test results employing the reinforcement principle. These findings establish a theoretical foundation for the resourceful utilization of wastewater and sediment.
Full article
(This article belongs to the Special Issue Advanced Technologies and Process Optimizations of Wastewater Treatment)
Open AccessArticle
Investigation on Aerodynamic Performance of a Centrifugal Compressor with Leaned and Bowed 3D Blades
by
Zhehong Li, Wanmin Kong, Genqiang Shao, Fujian Zhu, Chaowei Zhang, Feiyue Kong and Yifan Zhang
Processes 2024, 12(5), 875; https://doi.org/10.3390/pr12050875 - 26 Apr 2024
Abstract
The application of centrifugal compressors is extensive in industries such as aerospace and energy. The blade is the primary factor affecting the aerodynamic performance of compressors. In this paper, the aerodynamic performance of a centrifugal compressor with leaned and bowed 3D blades is
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The application of centrifugal compressors is extensive in industries such as aerospace and energy. The blade is the primary factor affecting the aerodynamic performance of compressors. In this paper, the aerodynamic performance of a centrifugal compressor with leaned and bowed 3D blades is investigated. The spanwise section profiles of the blade in the circumferential direction are deflected at different angles, resulting in four compressors with distinct leaned and bowed 3D blades based on the original model. There is a significant change in isentropic efficiency of the modified models under design conditions. Specifically, models 1, 3, and 4 experienced an increase of 0.97%, 1.04%, and 0.79%, respectively, while model 2 experienced a decrease of 0.70%. The profile of the blade tip and 50% spanwise section are shifted towards the suction surface, resulting in a geometric structure where the blade is concave towards the pressure surface. This structure gradually lifts the flow from the blade root to the blade tip downstream to the outlet area of the flow channel, reducing the load on the trailing edge of the blade and making the flow more closely aligned with the blade. At the same time, the larger radial velocity gradient near the blade tip suppresses the backflow on the shroud side, making the flow at the impeller outlet more stable. The outlet velocity of the impeller is more evenly distributed along the spanwise and circumferential directions, which improves the flow at the inlet of the diffuser and enhances the efficiency of the diffuser. Due to the high spanwise height of the leading edge of the blade, this bowed blade structure has little effect on the spanwise curvature upstream of the blade, resulting in negligible influence on the flow of the upstream channel.
Full article
(This article belongs to the Section Manufacturing Processes and Systems)
Open AccessFeature PaperReview
Energy Performance of Buildings for Incentivisation in Energy-Efficient Structures: An Analysis of Secondary Data in Malta
by
Joseph Falzon, Rebecca Dalli Gonzi, Simon Grima and Edward Vella
Processes 2024, 12(5), 874; https://doi.org/10.3390/pr12050874 - 26 Apr 2024
Abstract
High-performance green buildings mitigate the adverse environmental effects of energy consumption and carbon emissions while simultaneously demonstrating that sustainability does not mean compromising utility, productivity, or comfort. We need to address the identified gap in the evolution of energy-efficient structures facilitated in building
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High-performance green buildings mitigate the adverse environmental effects of energy consumption and carbon emissions while simultaneously demonstrating that sustainability does not mean compromising utility, productivity, or comfort. We need to address the identified gap in the evolution of energy-efficient structures facilitated in building applications to enhance energy usage without mitigating comfort. The aim of this study was to provide a review of the current methods used to assess energy efficiency in buildings in Malta through secondary data and to supplement this with qualitative data from interviews. The study investigated the importance of certification, compulsory legislation, and regulations implemented by local authorities and the European Union to incentivise energy performance measures. The findings, supplemented with qualitative data from representatives of public entities, show that most participants agreed that the current method of assessing needs requires a complete overhaul in order to promote a proactive approach to sustainable development. Recent public awareness has highlighted the limited understanding of sustainable practices implemented in buildings to capture and conserve energy. However, it is widely recognised that the building industry has significant potential for energy savings, which applies to both new constructions and existing structures, but the current level falls short of what is necessary in Malta. The study findings emphasise the primary energy users and pinpoint the obstacles in the implementation process. In conclusion, the use of software EPRDM, which may be applied to raise the importance of energy performance in building standards, lacks a value-driven focus, resulting in its full utilisation and potential being unexplored. Future applications of this study include the categorisation of old buildings for a possible bid in energy retrofit; campaigns to promote responsiveness; and the utilisation of advanced technological tools, such as DESIGNBUILDER and related software, to enable the simulation of an optimal building envelope. While increased energy efficiency may result in elevated rental and sale prices for buildings, this knowledge, when disseminated to prospective purchasers via the energy performance certificate (EPC) system, can catalyse investments in structures that are more energy efficient for the end user.
Full article
(This article belongs to the Special Issue Optimal Design for Renewable Power Systems)
Open AccessArticle
Optimization of Integrated Energy System Considering Electricity and Hydrogen Coordination in the Context of Carbon Trading
by
Xiaofeng Li, Bing Wang, Duoyu Pan, Xiong Yu, Yanling Che, Qianye Lei, Lijia Yang, Baofeng Wang and Hao Lu
Processes 2024, 12(5), 873; https://doi.org/10.3390/pr12050873 - 26 Apr 2024
Abstract
In order to improve the consumption of renewable energy and reduce the carbon emissions of integrated energy systems (IESs), this paper proposes an optimal operation strategy for an integrated energy system considering the coordination of electricity and hydrogen in the context of carbon
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In order to improve the consumption of renewable energy and reduce the carbon emissions of integrated energy systems (IESs), this paper proposes an optimal operation strategy for an integrated energy system considering the coordination of electricity and hydrogen in the context of carbon trading. The strategy makes full use of the traditional power-to-gas hydrogen production process and establishes a coupling model comprising cogeneration and carbon capture equipment, an electrolytic cell, a methane reactor, and a hydrogen fuel cell. Taking a minimum daily operating cost and minimal carbon emissions from the system as objective functions, a mixed-integer nonlinear optimal scheduling model is established. This paper designs examples based on MATLAB R2021b and uses the GUROBI solver to solve them. The results show that compared with the traditional two-stage operation process, the optimization method can reduce the daily operation cost of an IES by 26.01% and its carbon emissions by 90.32%. The results show that the operation mode of electro-hydrogen synergy can significantly reduce the carbon emissions of the system and realize a two-way flow of electro-hydrogen energy. At the same time, the addition of carbon capture equipment and the realization of carbon recycling prove the scheduling strategy’s ability to achieve a low-carbon economy of the scheduling strategy.
Full article
(This article belongs to the Section Energy Systems)
Open AccessArticle
Research on Dynamic Reactive Power Cost Optimization in Power Systems with DFIG Wind Farms
by
Qi Xu, Yuhang Wang, Xi Chen and Wensi Cao
Processes 2024, 12(5), 872; https://doi.org/10.3390/pr12050872 - 26 Apr 2024
Abstract
As the power market system gradually perfects, the increasingly fierce competition not only drives industry development but also brings new challenges. Reactive power optimization is crucial for maintaining stable power grid operation and improving energy efficiency. However, the implementation of plant–grid separation policies
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As the power market system gradually perfects, the increasingly fierce competition not only drives industry development but also brings new challenges. Reactive power optimization is crucial for maintaining stable power grid operation and improving energy efficiency. However, the implementation of plant–grid separation policies has kept optimization costs high, affecting the profit distribution between power generation companies and grid companies. Therefore, researching how to effectively reduce reactive power optimization costs, both technically and strategically, is not only vital for the economic operation of the power system but also key to balancing interests among all parties and promoting the healthy development of the power market. Initially, the study analyzes and compares the characteristic curves of synchronous generators and DFIGs, establishes a reactive power pricing model for generators, and considering the randomness and volatility of wind energy, establishes a DFIG reactive power pricing model. The objective functions aimed to minimize the cost of reactive power purchased by generators, the price of active power network losses, the total deviation of node voltages, and the depreciation costs of discrete variable actions, thereby establishing a dynamic reactive power optimization model for power systems including doubly-fed wind farms. By introducing Logistic chaotic mapping, the CSA is improved by using the highly stochastic characteristics of chaotic systems, which is known as the Chaotic Cuckooing Algorithm. Meanwhile, the basic cuckoo search algorithm was improved in terms of adaptive adjustment strategies and global convergence guidance strategies, resulting in an enhanced cuckoo search algorithm to solve the established dynamic reactive power optimization model, improving global search capability and convergence speed. Finally, using the IEEE 30-bus system as an example and applying the improved chaotic cuckoo search algorithm for solution, simulation results show that the proposed reactive power optimization model and method can reduce reactive power costs and the number of discrete device actions, demonstrating effectiveness and adaptability. When the improved chaotic cuckoo algorithm is applied to optimize the objective function, the optimization result is better than 7.26% compared to the standard cuckoo search algorithm, and it is also improved compared to both the PSO algorithm and the GWO algorithm.
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(This article belongs to the Section Energy Systems)
Open AccessArticle
Study on the Adaptability Evaluation of Micro-Dispersed-Gel-Strengthened-Alkali-Compound System and the Production Mechanism of Crude Oil
by
Teng Wang, Tianjiang Wu, Yunlong Liu, Chen Cheng and Guang Zhao
Processes 2024, 12(5), 871; https://doi.org/10.3390/pr12050871 - 26 Apr 2024
Abstract
A novel micro-dispersed-gel (MDG)-strengthened-alkali-compound flooding system was proposed for enhanced oil recovery in high-water-cut mature oilfields. Micro-dispersed gel has different adaptability and application schemes with sodium carbonate and sodium hydroxide. The MDG-strengthened-alkali flooding system can reduce the interfacial tension to an ultra-low interfacial-tension
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A novel micro-dispersed-gel (MDG)-strengthened-alkali-compound flooding system was proposed for enhanced oil recovery in high-water-cut mature oilfields. Micro-dispersed gel has different adaptability and application schemes with sodium carbonate and sodium hydroxide. The MDG-strengthened-alkali flooding system can reduce the interfacial tension to an ultra-low interfacial-tension level of 10−2 mN/m, which can reverse the wettability of rock surface. After 30 days aging, the MDG-strengthened-Na2CO3 flooding system has good viscosity retention of 74.5%, with an emulsion stability of 79.13%. The enhanced-oil-recovery ability of the MDG-strengthened-Na2CO3 (MDGSC) flooding system is 43.91%, which is slightly weaker than the 47.78% of the MDG-strengthened-NaOH (MDGSH) flooding system. The crude-oil-production mechanism of the two systems is different, but they all show excellent performance in enhanced oil recovery. The MDGSC flooding system mainly regulates and seals micro-fractures, forcing subsequent injected water to enter the low-permeability area, and it has the ability to wash the remaining oil in micro-fractures. The MDGSH flooding system mainly removes the remaining oil on the rock wall surface in the micro-fractures by efficient washing, and the MDG particles can also form weak plugging of the micro-fractures. The MDG-strengthened-alkali flooding system can be used as an alternative to enhance oil recovery in high-water-cut and highly heterogeneous mature oilfields.
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(This article belongs to the Special Issue Phase Change, Interphase Coupling, and Multiphase Transport in Porous Structures)
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Open AccessArticle
Numerical Study of Three-Dimensional Models of Single- and Two-Phase Nanofluid Flow through Corrugated Channels
by
Elhadi Kh Abugnah, Wan Saiful-Islam Wan Salim, Abdulhafid M. A. Elfaghi, Sami Al-Alimi, Yazid Saif and Wenbin Zhou
Processes 2024, 12(5), 870; https://doi.org/10.3390/pr12050870 - 26 Apr 2024
Abstract
This study delves into computational fluid dynamics (CFDs) predictions for SiO2–water nanofluids, meticulously examining both single-phase and two-phase models. Employing the finite volume approach, we tackled the three-dimensional partial differential equations governing the turbulent mixed convection flow in a horizontally corrugated
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This study delves into computational fluid dynamics (CFDs) predictions for SiO2–water nanofluids, meticulously examining both single-phase and two-phase models. Employing the finite volume approach, we tackled the three-dimensional partial differential equations governing the turbulent mixed convection flow in a horizontally corrugated channel with uniform heat flux. The study encompasses two nanoparticle volume concentrations and five Reynolds numbers (10,000, 15,000, 20,000, 25,000, and 30,000) to unravel these intricate dynamics. Despite previous research on the mixed convection of nanofluids using both single-phase and two-phase models, our work stands out as the inaugural systematic comparison of their predictions for turbulent mixed convection flow through this corrugated channel, considering the influences of temperature-dependent properties and hydrodynamic characteristics. The results reveal distinct variations in thermal fields between the two-phase and single-phase models, with negligible differences in hydrodynamic fields. Notably, the forecasts generated by three two-phase models—Volume of Fluid (VOF), Eulerian Mixture Model (EMM), and Eulerian Eulerian Model (EEM)—demonstrate remarkable similarity in the average Nusselt number, which are 24% higher than the single-phase model (SPM). For low nanoparticle volume fractions, the average Nusselt number predicted by the two-phase models closely aligns with that of the single-phase model. However, as the volume fraction increases, differences emerge, especially at higher Reynolds numbers. In other words, as the volume fraction of the nanoparticles increases, the nanofluid flow becomes a multi-phase problem, as depicted by the findings of this study.
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(This article belongs to the Special Issue Dynamics Analysis and Intelligent Control in Industrial Engineering)
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Open AccessReview
A Systematic Review of Multi-Objective Evolutionary Algorithms Optimization Frameworks
by
Andrei Pătrăușanu, Adrian Florea, Mihai Neghină, Alina Dicoiu and Radu Chiș
Processes 2024, 12(5), 869; https://doi.org/10.3390/pr12050869 - 26 Apr 2024
Abstract
The study of evolutionary algorithms (EAs) has witnessed an impressive increase during the last decades. The need to explore this area is determined by the growing request for design and the optimization of more and more engineering problems in society, such as highway
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The study of evolutionary algorithms (EAs) has witnessed an impressive increase during the last decades. The need to explore this area is determined by the growing request for design and the optimization of more and more engineering problems in society, such as highway construction processes, food and agri-technologies processes, resource allocation problems, logistics and transportation systems, microarchitectures, suspension systems optimal design, etc. All of these matters refer to specific highly computational problems with a huge design space, hence the obvious need for evolutionary algorithms and frameworks, or platforms that allow for the implementing and testing of such algorithms and methods. This paper aims to comparatively analyze the existing software platforms and state-of-the-art multi-objective optimization algorithms and make a review of what features exist and what features might be included next as further developments in such tools, from a researcher’s perspective. Additionally, it is essential for a framework to be easily extendable with new types of problems and optimization algorithms, metrics and quality indicators, genetic operators or specific solution representations and results analysis and comparison features. After presenting the most relevant existing features in these types of platforms, we suggest some future steps and the developments we have been working on.
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(This article belongs to the Special Issue Advances in Smart Industrial Engineering Techniques for Optimizing and Controlling Processes)
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