Processes, Volume 11, Issue 7 (July 2023) – 364 articles

The efficient development of oil reservoirs mainly depends on the comprehensive optimization of the subsurface fluid flow process. As an intelligent analysis technique, artificial intelligence provides a novel solution to multi-objective optimization (MOO) problems. In this study, an intelligent agent model based on the Transformer framework with the assistance of the multi-objective particle swarm optimization (MOPSO) algorithm has been utilized to optimize the gas flooding injection–production parameters in a well pattern in the Middle East. Firstly, 10 types of surveillance data covering 12 years from the target reservoir were gathered to provide a data foundation for model training and analysis. The prediction performance of the Transformer model reflected its higher accuracy compared to traditional reservoir numerical simulation (RNS) and other intelligent methods. The production prediction results based on the Transformer model were 21, 12, and 4 percentage points higher than those of RNS, bagging, and the bi-directional gated recurrent unit (Bi-GRU) in terms of accuracy, and it showed similar trends in the gas–oil ratio (GOR) prediction results. Secondly, the Pareto-based MOPSO algorithm was utilized to fulfil the two contradictory objectives of maximizing oil production and minimizing GOR simultaneously. After 10,000 iterations, the optimal injection–production parameters were proposed based on the generated Pareto frontier. To validate the feasibility and superiority of the developed approach, the development effects of three injection–production schemes were predicted in the intelligent agent model. In the next 400 days of production, the cumulative oil production increased by 25.3% compared to the average distribution method and 12.7% compared to the reservoir engineering method, while GOR was reduced by 27.1% and 15.3%, respectively. The results show that MOPSO results in a strategy that more appropriately optimizes oil production and GOR compared to some previous efforts published in the literature. The injection–production parameter optimization method based on the intelligent agent model and MOPSO algorithm can help decision makers to update the conservative development strategy and improve the development effect. Full article

In the past, the optimization of engineering specifications primarily included the influence of quality loss terms on product quality; however, in actual production practice, compensation quantity inevitably affects the optimization quality of engineering specifications. In this paper, the quadratic exponential quality loss and gain function was first supplemented, and the quadratic exponential quality loss and gain function was constructed under the larger-the-better characteristic and the smaller-the-better characteristic; in order to accurately represent the change in compensation amount in the process of quality control, the optimization method of engineering specification under the calculation of quality loss and compensation was given in combination with the hyperbolic tangent function. Finally, with the support of the dam construction quality acceptance assessment, the engineering specification optimization model was tested. The optimal coefficient was obtained as 0.162, and the specification range was reduced from 0.744 to 0.648, achieving the optimization goal. Full article

The recognition and growing consumption of cold-pressed rapeseed oil (CPRO) is due to by its unique, health-promoting properties; it is a rich source of omega-3 fatty acids and antioxidants. Nevertheless, the high content of unsaturated fatty acids and plant tissue particles makes CPRO more susceptible to oxidation. These pro-oxidant plant particles can be eliminated via centrifugation, thus improving the quality and stability of CPRO. Therefore, we aimed to determine whether the clarification of CPRO via centrifugation affects its quality parameters, pigment and phenolic profile, and antioxidant properties. These characteristics were analyzed and compared between centrifuged CPRO and CPRO clarified via natural decantation. Changes were monitored for 6 months of oil storage at 22 °C. Based on the results, no changes in the oxidation profile were found between centrifuged CPRO and decantated CPRO. When the storage is longer than 1 month, centrifugation is more beneficial with regard to delaying hydrolytic deterioration, while decantation provides slightly better pigment and polyphenol profiles. We did not observe that centrifugation improved the oil’s antioxidant properties. Further research should be continued to establish the effects of centrifugation on CPRO quality, including parameters such as rapeseed quality, maturity degree, varieties, and stricter storage conditions. Full article

New requirements for terminal production and operation have emerged as a result of the increase in container terminal throughput. Traditional terminals’ manufacturing capabilities fall short of the expanding service needs. By constructing a digital twin yard for container terminals, the production capacity of terminals can be effectively improved, and the production operation process can be optimized. This paper firstly constructs a digital twin yard system for container terminals, proposing that it is mainly composed of physical space, virtual space, data, services, and intelligent agents. This paper elaborates on the core technologies of digital twin yards and finally takes the container delivery and loading process as an example to solve the production bottlenecks of the yard in the container delivery business by reorganizing the operation process and targeting it, which can improve the terminal production efficiency to a certain extent. Full article

Shunbei Oilfield is a fractured carbonate reservoir with complex geological structures that are influenced by fault movements and prone to collapse and leak incidents. Precisely predicting leakage pressure is crucial for conducting fracturing operations in the later stages of production. However, current fracture-related leakage pressure prediction models mostly rely on statistical and mechanical methods, which require the consideration of factors such as fracture aperture and parameter selection, thereby leading to limitations in prediction efficiency and accuracy. To enhance the accuracy of reservoir leakage pressure prediction, this study leverages the advantages of artificial intelligence methods in dealing with complex nonlinear problems and proposes an optimized Long Short-Term Memory (LSTM) neural network prediction approach using the Particle Swarm Optimization (PSO) algorithm. Firstly, the Spearman correlation coefficient is used to evaluate the correlation between nine parameter features and leakage pressure. Subsequently, an LSTM network framework is constructed, and the PSO algorithm is applied to optimize its hyper-parameters, establishing an optimal model for leakage pressure prediction. Finally, the model’s performance is evaluated using the Coefficient of Determination ($R^2$), Root Mean Squared Error ($RMSE$), and Mean Absolute Percentage Error ($MAPE$). The evaluation results demonstrate that the PSO-optimized LSTM model achieved an $R^2$ of 0.828, $RMSE$ of 0.049, and $MAPE$ of 3.2, all of which outperformed the original model. The optimized LSTM model showed an average accuracy approximately 12.8% higher than that of the single LSTM model, indicating its higher prediction accuracy. The verification results from multiple development wells in this block further confirmed that the deep learning model established in this study surpassed traditional methods in prediction accuracy. Consequently, this approach is beneficial for drilling engineers and decision-makers to plan drilling operations more effectively and achieve accurate risk avoidance during the drilling process. Full article

A wave energy resource characterization for China’s Guangdong Coast is carried out utilizing 1-year (2020) wave data from four buoy sites. The wave heights, wave periods, wave directions, and effective wave height occurrence were analyzed using statistical methods. The wave energy spectrum methodology is used to calculate the wave power density. The wave energy level frequency and effective storage of wave energy are presented. The seasons and month variation indices are used to assess the wave power stability. The contribution of sea conditions to wave power is examined. The results indicate that the waters off Guangdong are rich in wave-related energy resources. The average wave energy density is (8.55–13.1) kW/m, and the maximum wave energy density is (94.6–624.2) kW/m. The effective reserves in winter are the largest at 1.0 × 10⁶ kW·h/m. The biggest share of wave energy is found in the sea state, with significant wave heights of 0.5–1.0 m and significant wave periods of 5–6 s. Typhoons contribute very little to yearly wave energy, yet they are significant when evaluating the dependability and durability of ocean wave energy converters. Full article

In this work, vanadium-substituted cesium phosphomolybdate salts with general formulae Cs_3+nPMo_12−nV_nO₄₀ (n = 0, 1, 2, and 3) were synthesized and evaluated in the acetalization of benzaldehyde with alkyl alcohols. All the catalysts were characterized through Raman, infrared, and ultraviolet–visible spectroscopies, powder X-ray diffraction patterns, isotherms of N₂ desorption/adsorption, and measurements of acidity strength. The catalytic activity of cesium phosphomolybdovanadate salts was evaluated in the acetalization reactions of benzaldehyde with alkyl alcohols. Among the salts tested, the Cs₄PMo₁₁V₁O₄₀ was the most active and selective catalyst in the conversion of benzaldehyde to methyl benzyl acetal and benzoic acid, which was obtained without the use of an oxidant agent. The impact of the main reaction parameters on the conversion and selectivity was evaluated by varying the content of vanadium per heteropolyanion, catalyst load, temperature, and alkyl alcohols. The greatest activity of the Cs₄PMo₁₁V₁O₄₀ salt was assigned to the highest Brønsted acidity strength, as demonstrated by the acidity measurements and analysis of their surface properties. This solid catalyst has advantages over traditional liquid homogenous catalysts, such as low corrosiveness, a minimum generation of residues and effluents, and easy recovery/reuse. In addition, its synthesis route is easier and quicker than solid-supported catalysts and comprises a potential alternative route to synthesize acetals. Full article

Worldwide, around 385 thousand babies are born each day. Many of them cannot be breastfed because of several physiological problems of the mothers. Galactogogues remain the most natural and prolific way to improve both milk quantity and quality. Various herbs are traditionally used to increase lactation, but the best known are fennel (Foeniculum vulgare L.) and anise (Pimpinella anisum L.). The main objective of the present study was to obtain some special and nutritious ready-to-eat products from pureed sweet potato (Ipomoea batatas L.) fortified with aqueous extracts from the aforementioned galactogogues herbs. Two different types of thermal treatment, steaming and baking, were investigated to obtain healthy and safe-for-consumption purees. Steam convection had a lower impact, compared with hot air convection, on the content of bioactive compounds among all samples. Among all samples, sweet potato puree with fennel aqueous extract, processed by steaming, (EFCA) showed the highest content of β-carotene (1.27 ± 0.11 mg/g DW), lycopene (0.59 ± 0.07 mg/g DW), and total carotenoids (1.38 ± 0.11 mg/g DW); the cooking loss registered statistically significantly lower values in the case of steam convection. These reports might potentially generate novel ready-to-eat foods used as meals and as well as lactation adjuvants. Full article

At present, as a new separation technology, supersonic separators have great potential in the separation of natural gases. However, their system performance is still low. In this paper, a supersonic swirl separator design is proposed with an integration approach of the discrete phase model (DPM), bi-coupling, and the random walk model, and it is used to predict the flow process of liquid droplets within the device. Such a numerical method is further employed to study the influence of key parameters on system performance. The results show that with an increase in the inlet port number and the ratio of the gas-liquid area, the separation performance decreases. As a result, the expansion, condensation effect, and economy of the separation system are greatly improved. When the deflection angle exceeds 20°, the separation temperature increases greatly. Consequently, this may ruin the condensing environment. The working pressure ranges are: (1) the boost ratio (the dry outlet pressure/total inlet pressure) is less than 0.76; (2) the wet pressure ratio (the wet outlet pressure/total inlet pressure)is less than 0.46. The increase in droplet diameter can improve the separation performance, and the droplets are completely separated as the diameter reaches 1.75 μm. Full article

In response to the problems of considerable size, loose structure, and low energy conversion efficiency of multi-energy power coupling devices, this paper makes improvements based on the mechanical–electric–hydraulic power coupler proposed by our research group. We propose a new asynchronous mechanical–electric–hydraulic power coupler (IA-MEHPC). This mechanism integrates a traditional three-phase asynchronous motor with a swashplate axial piston pump/motor to realize the mutual conversion of electrical, mechanical, and hydraulic energy. Compactness, efficiency, and adaptability are the distinguishing features of the complex. This paper builds a three-dimensional model of the IA-MEHPC and a two-dimensional theoretical model of the electrical structure (motor part). Moreover, the electrical structure parameters of the IA-MEHPC are optimized using an approximate response surface-based optimization method. The maximum motor peak torque and minimum torque fluctuation are identified as optimization objectives, and we obtain the optimal combination of parameters. The simulation results show that, compared to the pre-optimized structure, the peak motor torque of the optimized IA-MEHPC is increased by 5.78%, and the torque pulsation coefficient is reduced by 15.83%, in line with engineering practice expectations. This paper innovatively proposes and optimizes IA-MEHPC, which is significant for developing hybrid mechanical devices and subsequent research. Full article

The applicability of linear model predictive control to the 2-butene metathesis process is studied. Similarly to industrial practice, the model predictive controller is configured on a supervisory level, providing set points to basic process controllers. The development of the process model is based on open-loop identification from input–output data extracted from dynamic simulation performed in Aspen Plus Dynamics. The model predictive controller, designed using MATLAB tools, supervises a system consisting of two inputs (feed rate and reaction temperature) and two outputs (ethylene and propylene production rates). The performance of the model-based control strategy is assessed by Aspen Plus Dynamics-Simulink co-simulation and compared to regulatory control through several indexes (mean square error, integral square error, peak error, and integral absolute error). The model predictive controller outperforms the feedback controller. Considerations regarding the workflow for the implementation of model predictive control in an industrial environment are provided. Full article

The mining confrontation caused by a super-long working face is an important factor that leads to difficulties in the control of surrounding rock in facing-mining roadways. To address this issue, this study takes the 18106 working face of Xiegou Coal Mine as the engineering background. First, deformation characteristics of the surrounding rock in two stages of roadway mining are explored, and the principle of determining the time for fracturing construction is presented. Additionally, the influence of fracturing space position on the control effect of the roadway’s surrounding rock is examined. Results show that the roadway which is influenced by adjacent working face mining has obvious asymmetric deformation, and the order of deformation is as follows: pillar side > roof > coal side > floor. The roof activity in goaf is the key factor of roadway deformation, and the proportion of deformation is 60%, followed by the influence of advance stress, accounting for 38%. After fracturing, with the increase in fracturing height, the deformation of the surrounding rock decreases, and the decrease in deformation of the roof and two sides also reduces, while the decrease in deformation of the floor remains relatively stable. The reasonable fracturing height is 10 m, and the reasonable fracturing construction time is 17 days before the confrontation between the working face and the roadway. Field practice suggests that there are effective cracks in the roof after fracturing, and the deformation of the surrounding rock in facing-mining roadways is reduced by more than 60% compared to that without fracturing. Hydraulic fracturing is significant for controlling the deformation of the surrounding rock in facing-mining roadways. Full article

Rock electrical experiments are essential means of researching the conductive properties of rocks and are fundamental to interpreting resistivity logging. Carbonate rocks have more complex pore structures than sandstone, which results in more complex conductive properties. However, conducting experiments on representative rock samples from carbonate reservoirs is difficult, making it challenging to study the micro factors affecting electrical properties. Therefore, researching the conductive properties of carbonate rocks is difficult. To address this, in this paper, three-dimensional (3D) digital rock models with different porosities are generated, and conductive simulations are carried out on these models using the finite element method (FEM). Firstly, a micro-computed tomography (μ-CT) 3D image of a carbonate rock is obtained. Secondly, mathematical morphology-based methods are used on the μ-CT image to generate cores with varying porosities and fluid distributions. Then, the electrical properties are simulated using the FEM method, and the results are analyzed. The results reveal that the formation factor of the reservoir is mainly influenced by the shape and structure of the pores. The Archie equation is more suitable for carbonate reservoirs with water saturation levels greater than 60%. The wettability of the rock can alter the distribution of fluid in the reservoir space under different water saturation conditions. In pure water-wet rocks, the water phase mainly occupies small pores, while the oil phase occupies larger pores. As a result, compared to pure oil-wet rocks, water-wet rocks have more conductive channels and better conductivity. Therefore, it is important to determine the wettability of the rock when calculating water saturation using the Archie equation. The saturation index value of water-wet carbonate rock is about 2, while that of oil-wet rock is around 3–4. This research lays a foundation for studying the electrical conductivity of carbonate reservoirs using digital rocks. Full article

Plasma-activated water (PAW) is water that has been treated with atmospheric pressure plasma. Due to the presence of reactive oxygen and nitrogen species (RONS), PAW can be used in various applications such as (1) surface disinfection and food decontamination, (2) enhancement in seed germination, and (3) enhancement in surface cooling in the nucleate boiling regime. Briefly, for surface disinfection, the reactive species in PAW can induce oxidative stress on microbes; for enhancement of seed germination, the reactive species in PAW can trigger seed germination and provide nutrients; for enhancement in surface cooling, the reactive species cause a reduction in the surface tension of PAW, facilitating the phase-change heat transfer and, quite unexpectedly, minimizing the surface oxidation. Here, we review the physicochemical properties of PAW, the three commonly used techniques (plasma jet, dielectric barrier discharge, and corona discharge) for generating atmospheric pressure plasma, and the use of PAW for the above three applications. In particular, we review the recent development of the miniaturization of the plasma generator integrated with an acoustic neutralizer to produce plasma-activated aerosols, elimination of the need for storage, and the interesting physicochemical properties of PAW that lead to cooling enhancement. Full article

Stimulated by the increase in user demands and the development of intelligent driving, the automotive industry is pursuing high-bandwidth techniques, low-cost network deployment and deterministic data transmission. Time-sensitive networking (TSN) based on Ethernet provides a possible solution to these targets, which is arousing extensive attention from both academia and industry. We review TSN-related academic research papers published by major academic publishers and analyze research trends in TSN. This paper provides an up-to-date comprehensive survey of TSN-related standards, from the perspective of the physical layer, data link layer, network layer and protocol test. Then we classify intelligent driving products with TSN characteristics. With the consideration of more of the latest specified TSN protocols, we further analyze the minimum complete set of specifications and give the corresponding demo setup for the realization of TSN on automobiles. Open issues to be solved and trends of TSN are identified and analyzed, followed by possible solutions. Therefore, this paper can be an investigating basis and reference of TSN, especially for the TSN on automotive applications. Full article

The failure of managed-pressure running casing in oil and gas wells may lead to complex accidents such as overflow or leakage. The technique of using multi-density gradient drilling fluids in wellbores with negative pressure windows (NPWs) is often used to deal with this situation. Therefore, it is vital to analyze the dynamic slurry column structure and calculate the wellbore pressure during casing running. For this issue, the model of transient surge pressure is established during casing running. The calculation equation of the model is proposed, and the calculations of the wellbore pressure are carried out with the exploration of Well LT-X1, located in the Xinjiang oil field. A circulation scheme is designed as follows: Circulate 125 m³ of drilling fluid with a density of 2.45 g/cm³ and 155 m³ of drilling fluid with a density of 2.35 g/cm³ at a depth of 3560 m. From there, circulate 164 m³ of drilling fluid with a density of 2.35 g/cm³ at a depth of 5900 m. Finally, at a depth of 7050 m, circulate 250 m³ of drilling fluid with a density of 2.30 g/cm³. The casing running speeds and back-pressure values were designed as follows for the respective well sections: 0–1523 m: 0.160 m/s casing speed, 0 MPa back pressure; 1523–3560 m: 0.160 m/s casing speed, 1.641 MPa back pressure; 3560–5900 m: 0.145 m/s casing speed, 2.427 MPa back pressure; 5900–6674 m: 0.137 m/s casing speed, 4.041 MPa back pressure; 6674–7050 m: 0.124 m/s casing speed, 4.457 MPa back pressure. The results show that optimizing structure of the multi-density gradient drilling fluid with different densities and applying annular back pressure in stages, with the accurate calculation of wellbore pressure, can achieve the goals of leak-proofing and pressure-stabilization. It is concluded that this result may serve as the foundation for managed-pressure running casing technology. Full article

The Carboniferous Ha’erjiawu Formation in the Santanghu Basin represents a significant potential target for shale oil exploration, yet its characteristics remain largely unknown. This study utilizes a combination of elemental and organic geochemical analyses to investigate the paleoenvironmental conditions and shale oil potential of the Carboniferous Ha’erjiawu Formation black shales within the Santanghu Basin. The results suggest that the Ha’erjiawu Formation black shales were deposited in water columns with low salinity and dysoxic conditions, as indicated by paleosalinity and redox proxies such as Rb/K, B/Ga, B content, V/Cr, V/(V + Ni), V/Al, and Mo/Al. Furthermore, the climatic proxies (Ga/Rb, Sr/Cu and K₂O/Al₂O₃) indicate that the Santanghu Basin underwent a warm-humid/cold-dry oscillating climate during the deposition of the Ha’erjiawu Formation black shales, potentially influenced by synsedimentary volcanic activity or the Late Paleozoic glaciation. The organic geochemical analyses have revealed that the Ha’erjiawu Formation black shales are rich in type II kerogen, which is in the early mature to mature stage, indicating a significant potential for oil generation. However, there is considerable variation in the oil content of the analyzed samples, with only a few containing movable oil. Given the high abundance of brittle minerals within the Ha’erjiawu Formation black shales, it will be indispensable to meticulously evaluate and identify intervals exhibiting abundant movable oil for successful shale oil exploration and development within this geological unit. Full article

Bioadsorbents based on biopolymers modified with magnetic nanoparticles stand out for being non-toxic, effective, and easy to recover. Thus, the objective of the present work was to carry out a computer-aided environmental evaluation of the industrial-scale production of bioadsorbents from chitosan modified with iron nanoparticles and functionalized with thiourea as a chelating agent plus mass integration. The plant simulation was carried out in Aspen Plus, and for the mass integration of the process, a pinch analysis was used to determine the minimum target fresh and residual water amount, assuming two process stages: (1) the synthesis of magnetite nanoparticles, and (2) the production of chitosan-based bioadsorbents. The environmental assessment was performed using the waste reduction algorithm (WAR). The potential environmental impact (PEI) was quantified, taking into account the impact of the products and energy, obtaining a value below zero of −0.78 PEI/kg of the product. The photochemical oxidation potential (PCOP) stood out as the category with the greatest impact, mainly related to the use of ethanol during washing. The categories related to toxicological impacts (HTPI, HTPE, TTP, and ATP) had lower values than those related to atmospheric impacts (GWP, ODP, PCOP, and AP). The mass integration of the process resulted in fewer impacts in the HTPE category, as a consequence of the decrease in NaOH in the residual streams and the release of 0.297 PEI/kg of product in the ATP category caused by the presence of Al(OH)₃. It can be concluded that the mass integration managed to reduce up to 51% of the freshwater used in the processes, and it is a useful tool, as it slightly decreased the total potential impacts. Full article

In this study, we conducted a one-step photochemical synthesis to produce silver nanoparticles (AgNPs) with irregular morphology. The synthesis process involved the photoconversion of Ag nanoseeds into self-assembled Ag nanostructures of various morphologies using a high-pressure sodium lamp with a wavelength of 589 nm, corresponding to an energy of 2.1 eV. During the synthesis, the color of the colloidal Ag nanoseeds gradually changed as the irradiation time increased, transitioning from yellow to brown, juniper green, basil green, ocean green, aegean blue, and finally to true blue. We characterized the morphological evolution of the resulting AgNPs, as well as their optical properties and aggregation behavior, using transmission electron microscopy, UV-vis spectroscopy, and dynamic light scattering. Furthermore, we evaluated the impact of the self-assembled morphology of the AgNPs on their surface-enhanced Raman scattering efficiency, using R6G as the target analyte. The results revealed that the colloidal AgNPs synthesized under a visible light irradiation time of 1 h consisted of circular nanoplates, hexagonal nanoplates, trapezoid nanoplates, and triangular nanoplates. These colloidal AgNPs exhibited excellent SERS activity when used as an SERS-active substrate in the form of an aqueous solution, enabling the detection of low concentrations of R6G down to 10⁻¹² M. Full article

Carbon dioxide (CO₂) sequestration plays a crucial role in reducing the levels of atmospheric CO₂ and mitigating the harmful effects of global warming. Among the various CO₂ sequestration technologies, CO₂ marine geological sequestration emerges as a safer and more efficient alternative compared with traditional terrestrial geological sequestration. This is highly attributed to its expansive potential, safe distance from aquifers, and stable temperature and pressure conditions. This paper reviews and evaluates the main CO₂ marine geological sequestration technologies, including CO₂ sequestrations in shallow marine sediments, CO₂, sub-seabed aquifers, and CO₂-CH₄ replacement. The goal of this paper is to shed light on the mechanism, potential, and challenges of each technology. Given the importance of safety in CO₂ sequestration, this review also explores the potential adverse effects of CO₂ leakage from reservoirs, particularly its impact on marine environments. Finally, we discuss potential development trends in CO₂ marine geological technology. Full article

Coalbed methane reservoirs exhibit a low strength and high heterogeneity, rendering them susceptible to coal fines generation during hydraulic fracturing operations. The detrimental impact of coal fines on the conductivity of the propped fracture has been overlooked, leading to a substantial negative effect on the later-stage recovery of coalbed methane reservoirs. Moreover, the particle size distribution of the composite proppant also affects the conductivity of the propped fracture. To mitigate the damage caused by coal fines to the conductivity of the proppant pack in CBM reservoirs, this study conducted conductivity tests on actual coal rock fractures. The aim was to assess the effect of various particle size ratios in composite proppant blends on the conductivity of complex fractures in CBM reservoirs. The ultimate goal was to identify an optimized proppant blending approach that is suitable for hydraulic fracturing in coal seams. The results indicated that, in terms of the short-term conductivity of coalbed methane reservoirs, the conductivity of composite proppants is primarily influenced by the proportion of large or small particles. A higher proportion of large particles corresponds to a stronger conductivity (e.g., the conductivity is highest at a particle ratio of 5:1:1 for large, medium, and small particles). On the other hand, a higher proportion of small particles leads to a poorer conductivity (the conductivity is lowest when the particle ratio is 1:1:5). In the long-term conductivity of coalbed methane reservoirs, the fluid flushing of the fracture surfaces generates coal fines, and small particles can fill the gaps between larger particles, hindering the infiltration of coal fines. Therefore, it is important to control the particle size ratio of composite proppants, with a predominant proportion of larger particles. This approach can maintain long-term conductivity and prevent the excessive infiltration of coal fines, thereby avoiding fracture blockage (e.g., the conductivity is highest at a particle ratio of 5:1:5, followed by a ratio of 3:1:3). Furthermore, considering the influence of proppant placement methods and the support effect on near-wellbore opening fractures and far-end sliding fractures, segmented placement is utilized to fully fill the fractures for short-term conductivity, whereas mixed placement is employed for long-term conductivity to achieve a balance in particle gaps and hinder the infiltration of coal fines. The findings of this study contribute to the understanding of proppant selection and placement strategies for efficient hydraulic fracturing in coalbed methane reservoirs. Full article

Additive manufacturing (AM) technologies enable the production of customized and personalized medical devices that facilitate users’ comfort and rehabilitation requirements according to their individual conditions. The concept of a tailor-made orthopedic device addresses the accelerated recovery and comfort of the patient through the utilization of personalized rehabilitation equipment. Direct modeling, with an increasing number of approaches and prototypes, has provided many successful results until now. The modeling procedure for 3D-printed orthoses has emerged as the execution of steady and continuous tasks with several design selection criteria, such as cutting, thickening the surface, and engraving the shell of the orthosis. This publication takes into consideration the aforementioned criteria and proposes the creation of a holistic methodology and automated computational design process for the customization of orthotic assistive devices, considering aspects such as material properties, manufacturing limitations, recycling, and patients’ requirements. This proposal leads to the designing and manufacturing of a wrist orthopedic device based on reverse engineering, Design for AM (DfAM), and Design for Recycling (DfR) principles. The proposed methodology can be adjusted for different limbs. A dual-material approach was attained utilizing rigid, mechanically enhanced feedstock material and soft elastic material with reduced skin irritation risks to achieve both mechanical requirements and adequate cushioning for user comfort during rehabilitation. Recyclable thermoplastic matrices were selected, which also allow for the option to create washable devices for product life extension. Then, 3D scanning procedures were implemented to acquire the initial anatomic measurements for the design of the WHO and ensure and assess the dimensional accuracy of the final product. Physical mechanical testing was implemented to evaluate the WHO’s mechanical behavior and verify its functionality during basic wrist movements. The extracted dimensional data for the two main orthosis components that indicated approximately 50% and 25% of the tolerance values, respectively, were within the range (−0.1 mm, 0.1 mm). Full article

Cnidoscolus quercifolius, commonly known as “favela”, “faveleira”, “urtiga-branca”, and “cansanção”, is a plant that is native to the Caatinga biome. The species is extremely tolerant to adverse weather conditions and is of great importance for the population of the semi-arid region, as it has uses in afforestation, the recovery of degraded areas, sawmills, fuels, animal feed, and food production. In addition, the species is popularly known for its medicinal uses, and it has been scientifically tested for such purposes. The objective of the research was to compile updated information about the chemical composition, biological activities, and botanical characteristics of the species, in addition to information about its use in folk medicine. It was observed that C. quercifolius has a strong usage among people in the Brazilian Caatinga for ophthalmic and other medical conditions, including inflammation in general, scarring, and infections. Studies involving the species have shown its effectiveness as antinociceptive, cytotoxic agent, antioxidant, and insecticide, as also thanks to its anti-inflammatory, hypoglycemic, and repellent characteristics. Other tests have indicated that the vegetable oil from the seed is promising for food consumption. This work demonstrates that further investigations are still necessary to determine the chemical composition and the toxicological characteristics of the species in order to support subsidies for the possible development of new drugs. Such future investigations may include the isolation of its substances, an analysis of its pharmacological activities, and a deepening of the understanding of the mechanisms of action of its various plant products. Full article

Industrial facilities are seeking new strategies that help in providing savings mechanisms for demand charges. Demand charges are the charges incurred by industrial facilities as a result of power usage. Thermal energy storage has advanced significantly with lots of new applications, garnering the interest of many industrial facilities. These applications could be used to shave the industrial facilities’ peak electric demand and reduce their demand charges. This paper aims to demonstrate the efficacy of thermal energy storage in reducing demand charges and highlight new developments in the integration of smart control systems with thermal energy storage. The study compares energy consumption and peak demand for a facility equipped with and without thermal energy storage tanks using a fixed schedule for charging and discharging. Additionally, the paper examines the impact of incorporating a smart controller to determine when to charge and discharge the tank based on the facility’s real-time power usage and a given setpoint. The results indicate cost savings from the use of thermal energy storage tanks under two proposed scenarios, reflected in the reduced cost of power consumption for the studied facility. The incorporation of a smart controller with the thermal energy storage tank in the facility studied could provide estimated savings of 3.3% per year of power consumption charges, without considering the contribution of any incentives. The estimated savings provided by the fixed schedule scenario are 2.7% per year. Full article

Conventional downhole traction robots only provide axial traction, while coiled tubing drilling (CTD) robots must not only overcome the axial force but also overcome the reaction torque generated by the drill bit breaking the rock. Therefore, the tooth profile of the friction block of the conventional downhole traction robot cannot achieve effective support under the simultaneous action of the axial load and circumferential load. In this paper, based on the actual reaction torque conditions generated by CTD, a mechanical model of the friction block teeth of the CTD robot under the conditions of axial traction and reverse torque is established. This reveals the influence of different tooth slope angles, axial-included angles and friction coefficients on the mechanical properties. It provides guidelines for the design of the inclination of the tooth slope, the axial angle of the tooth and the friction coefficient of the friction block of the CTD robot. It has scientific and engineering significance for the promotion of downhole robots in drilling engineering. Full article

The present investigation focuses on the impact of jet nozzle orientation on mixing time in a cylindrical tank. The aim is to identify nozzle positions that improve mixing performance and to elucidate the governing parameters that influence it. A water tank was employed for the experiment. The vertical inclination angle (α) and the horizontal inclination angle (β) of the jet nozzle determined the nozzle positions. Mixing time was determined using an inert tracer and spectrophotometry measurements. The findings show that the mixing time is significantly influenced by the position of the jet nozzle position. The accuracy of existing jet turbulence and the circulation models for the prediction of mixing time was evaluated for the different nozzle positions. Our results indicate that both models provide accurate predictions for the conventional centrally aligned (β = 0°), upward-pointing jet nozzle positions only (α > 0). For the other nozzle positions where β > 0° and at varying α, the data follow the same trends as the jet turbulence and circulation models; however, the proportionality constants vary. Shorter mixing times can be attributed principally to longer jet path lengths and therefore higher fluid entrainment and circulation as well as higher dissipation rates per jet length squared. However, it is suspected that the three-dimensional nature of the flow pattern generated in the tank also plays a non-negligible role since mixing is hindered when the nozzle points more towards the tank wall. Full article

Soil is the main aggregation site of polycyclic aromatic hydrocarbons and an important pathway of migration to other media. In this paper, the adsorption behavior of pyrene and seven different types of surfactants on kaolinite surfaces was studied by molecular dynamics simulation and desorption testing. The molecular dynamics simulation results showed that pyrene was more easily adsorbed on the 001 (-) side of kaolinite. SDBS, SDS, TW80, and TX-100 had strong interactions with pyrene, encapsulating pyrene molecules in aggregates. However, when the concentration of surfactant was too high, the desorption of pyrene molecules on a kaolinite surface will be inhibited. The desorption of pyrene molecules will be inhibited in the presence of BS-12, TW80, and TX-100, while the desorption process can be promoted by using CTAC, DDBAC, SDBS, and SDS as soil remediation agents. The removal rate of pyrene gradually increased with the increase of SDS dosage, while for SDBS, the removal rate showed a trend of first increasing and then decreasing. When the concentration of SDS was 0.014 mol/L, the elution rate of pyrene reached 72.86%. The molecular dynamics simulation results were similar to the desorption test results, verifying the reliability of molecular dynamics simulation. The research results provide theoretical support for the selection of surfactants in the remediation process of pyrene-contaminated soil. Full article

The application of nanofiltration (NF) membranes in the forward osmosis (FO) process to remove heavy metal ions from wastewater is an emerging concept. Unlike NF, FO does not require an external driving force. Although the product, a dilute draw solution, must further be processed by NF to produce pure water and reconcentrate a draw solution, the feed to that NF process is “clean”, which minimizes membrane fouling. This paper examines the role of Cu²⁺ and Pb²⁺ in the feed solution on the water and the reverse solute fluxes in FO process using novel thin film nanocomposite (TFN) NF membranes. The TFN membranes were fabricated by in situ interfacial polymerization of piperazine (PIP) and 1,3,5-benzenetricarbonyl trichloride (TMC) containing different amounts of dispersed halloysite nanotubes (HNTs) nanoparticles functionalized with the first generation of poly(amidoamine) (PAMAM) dendrimers. The presence of Cu²⁺ and Pb²⁺ in the feed solution decreased the reverse flux of MgCl₂ by at least 2.5 times compared to the experiments with pure water as a feed. Simultaneously, the water flux also increased. The corresponding rejections of Cu²⁺ and Pb²⁺ in the FO process ranged from 94.5% to 98.1%. Full article

A novel four-parameter lifetime Lomax model is presented and investigated within the scope of this paper. The failure rate of the innovative model can be “monotonically decreasing failure rate,” “monotonically increasing failure rate,” or “constant failure rate,” and the density of the model can be “asymmetric right skewed,” “symmetric,” “asymmetric left skewed,” or “uniform density”. The new density is expressed as a blend of the Lomax densities that have been multiplied by an exponent. New bivariate Lomax types were created for our research. The maximum likelihood technique was utilized. We performed simulated experiments for the purpose of evaluating the finite sample behavior of maximum likelihood estimators, using “biases” and “mean squared errors” as our primary metrics of analysis. The novel distribution was evaluated based on a number of pertinent Lomax models, including Lomax extensions that were generated on the basis of odd log-logistic, Kumaraswamy, beta, gamma, and Topp–Leone families, among others. The newly developed extension demonstrated its relevance by predicting the service and failure times of datasets pertaining to aircraft windshields. Full article