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
Numerical Simulation Study of Gas-Liquid Two-Phase Flow in a Pressurized Leaching Stirred Tank
Processes 2024, 12(5), 896; https://doi.org/10.3390/pr12050896 (registering DOI) - 28 Apr 2024
Abstract
The gas-liquid flow and oxygen content in a pressurized leaching stirred tank significantly influence the chemical reaction rates, while the specific dynamics of gas-liquid flow in the sulfuric acid system remain largely unexplored. In this study, a mathematical model of gas-liquid flow within
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The gas-liquid flow and oxygen content in a pressurized leaching stirred tank significantly influence the chemical reaction rates, while the specific dynamics of gas-liquid flow in the sulfuric acid system remain largely unexplored. In this study, a mathematical model of gas-liquid flow within a stirred tank is developed using the Euler-Euler approach, with the turbulence and drag force models being validated against experimental data. Utilizing this validated and reliable model, this study investigates the impacts of the sulfuric acid concentration, baffles, air inlet velocity, and bubble diameter on the flow field and gas holdup in a two-phase system consisting of a sulfuric acid solution and oxygen. The findings indicate that introducing a specific concentration of sulfuric acid decreases the solution velocity and increases the gas holdup within the tank. However, once the sulfuric acid concentration reaches a certain threshold, further increases have a diminished effect on the gas-liquid phases. The installation of baffles enhances the turbulent kinetic energy and increases the gas holdup while only resulting in a minimal 1.2% increase in power consumption. Additionally, the inlet velocity and bubble diameter have a relatively minor impact on the tank’s flow field. However, increasing the inlet velocity significantly boosts the gas holdup, whereas an increase in the bubble diameter marginally reduces it. Furthermore, introducing a sulfuric acid solution into the tank can enhance the gas holdup when the gas inlet velocity is low. Conversely, when the gas inlet velocity is high, the addition of sulfuric acid results in a decrease in the gas holdup. The conclusions from this study contribute to enhancing the mixing effectiveness and oxygen content within the tank, providing a substantial theoretical basis for optimizing the design and operating conditions of pressurized leaching stirred tanks.
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(This article belongs to the Section Chemical Processes and Systems)
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Open AccessArticle
Effect of Acid Fluid on Deep Eocene Sweet Spot Reservoir of Steep Slope Zone in Lufeng Sag, Pearl River Mouth Basin, South China Sea
by
Kai Zhong, Lihao Bian, Shijie Zhao and Kailong Feng
Processes 2024, 12(5), 895; https://doi.org/10.3390/pr12050895 (registering DOI) - 28 Apr 2024
Abstract
The Paleogene system of the Zhuyi Depression exhibits a pronounced mechanical compaction background. Despite this compaction, remarkable secondary porosity is observed in deep clastic rocks due to dissolution processes, with well-developed hydrocarbon reservoirs persisting in deeper strata. We conducted a comprehensive study utilising
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The Paleogene system of the Zhuyi Depression exhibits a pronounced mechanical compaction background. Despite this compaction, remarkable secondary porosity is observed in deep clastic rocks due to dissolution processes, with well-developed hydrocarbon reservoirs persisting in deeper strata. We conducted a comprehensive study utilising various analytical techniques to gain insights into the dissolution and transformation mechanisms of deep clastic rock reservoirs in the steep slope zone of the Lufeng Sag. The study encompassed the collection and analysis of the rock thin sections, XRD whole-rock mineralogy, and petrophysical properties from seven wells drilled into the Eocene. Our findings reveal that the nature of the parent rock, tuffaceous content, dominant sedimentary facies, and the thickness of individual sand bodies are crucial factors that influence the development of high-quality reservoirs under intense compaction conditions. Moreover, the sustained modification and efficient expulsion of organic–inorganic acidic fluids play a main role in forming secondary dissolution porosity zones within the En-4 Member of the LF X transition zone. Notably, it has been established that the front edge of the fan delta, the front of the thin layer, and the near margin of the thick layer of the braided river delta represent favorable zones for developing deep sweet-spot reservoirs. Furthermore, we have identified the LF X and LF Y areas as favourable exploration zones and established an Eocene petroleum-accumulation model. These insights will significantly aid in predicting high-quality dissolution reservoirs and facilitate deep oil and gas exploration efforts in the steep slope zone of the Zhuyi Depression.
Full article
(This article belongs to the Special Issue Organic–Inorganic Interactions and Their Significance for Hydrocarbon Generation in Deep Formations)
Open AccessReview
Nutrient Removal and Recovery from Municipal Wastewater
by
Ján Derco, Andreja Žgajnar Gotvajn, Patrícia Guľašová, Angelika Kassai and Nikola Šoltýsová
Processes 2024, 12(5), 894; https://doi.org/10.3390/pr12050894 (registering DOI) - 28 Apr 2024
Abstract
With the ongoing amendment of the EU legislation on the treatment of urban wastewater, stricter requirements for the removal of pollutants are expected, which calls for the need for innovative wastewater treatment technologies. Biological systems are still the first choice. A survey of
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With the ongoing amendment of the EU legislation on the treatment of urban wastewater, stricter requirements for the removal of pollutants are expected, which calls for the need for innovative wastewater treatment technologies. Biological systems are still the first choice. A survey of typical bioreactors applied in wastewater treatment is presented. The wastewater treatment objective, biochemical environment, and microbial growth are selected as the main criteria for the classification of these bioreactors. Hydraulic and kinetic aspects are considered, along with the advantages and drawbacks of these bioreactors regarding the selection of the appropriate type of reactor; as well, details regarding the operation of reactors are mentioned. The aim of this paper is to provide operators and designers with a brief overview of the selected traditional and advanced processes, reactors, and technologies for nutrient removal from municipal wastewater. The possibilities and limitations in complying with more strict effluent standards are also discussed. Methods of nutrient recovery are added value. From the evaluation of the published papers, we determine that the currently applied traditional methods for nutrient removal have the potential to also convey the expected stricter limits.
Full article
(This article belongs to the Special Issue Municipal Wastewater Treatment and Removal of Micropollutants)
Open AccessArticle
Understanding Plugging Agent Emplacement Depth with Polymer Shear Thinning: Insights from Experiments and Numerical Modeling
by
Shanbin He, Chunqi Xue, Chang Du, Yahui Mao, Shengnan Li, Jianhua Zhong, Liwen Guo and Shuoliang Wang
Processes 2024, 12(5), 893; https://doi.org/10.3390/pr12050893 (registering DOI) - 28 Apr 2024
Abstract
Polymer-plugging agents are widely employed in profile control and water-plugging measures, serving as a crucial component for efficient reservoir development. However, quantitatively monitoring the emplacement depth of polymer-plugging agents in low-permeability and high-permeability layers remains a challenging bottleneck. Presently, insufficient attention on shear
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Polymer-plugging agents are widely employed in profile control and water-plugging measures, serving as a crucial component for efficient reservoir development. However, quantitatively monitoring the emplacement depth of polymer-plugging agents in low-permeability and high-permeability layers remains a challenging bottleneck. Presently, insufficient attention on shear thinning, a critical rheological property for water shut-off and profile control, has limited our understanding of polymer distribution laws. In this study, polymer shear-thinning experiments are firstly conducted to explore polymer variations with flow rate. The novelty of the research is that varying polymer viscosity is implemented instead of the fixed-fluid viscosity that is conventionally used. The fitted correlation is then integrated into the 2D and 3D heterogeneous numerical models for simulations, and a multivariate nonlinear regression analysis is performed based on the simulation results. The results show that lower polymer emplacement depth ratios corresponded to higher viscosity loss rates under the same flow rate. An increase in the initial permeability ratio corresponds to a decrease in the emplacement ratio, along with a reduction in the fraction of the plugging agent penetrating the low permeability formations. The model was applied to the Kunan Oilfield and demonstrated a polymer reduction of approximately 3000 tons compared to traditional methods. Despite the slightly complex nature of the multivariate nonlinear mathematical model, it presents clear advantages in controlling plugging agent distribution and estimating dosage, laying good theoretical ground for the effective and efficient recovery of subsurface resources.
Full article
(This article belongs to the Special Issue Quantitative Evaluation, Efficient Development, Seepage, and Simulation of Geo-Energy Resources)
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Open AccessArticle
Piece-Wise Droop Controller for Enhanced Stability in DC-Microgrid-Based Electric Vehicle Fast Charging Station
by
Mallareddy Mounica, Bhooshan A. Rajpathak, Mohan Lal Kolhe, K. Raghavendra Naik, Janardhan Rao Moparthi and Sravan Kumar Kotha
Processes 2024, 12(5), 892; https://doi.org/10.3390/pr12050892 (registering DOI) - 28 Apr 2024
Abstract
The need for public fast electric vehicle charging station (FEVCS) infrastructure is growing to meet the zero-emission goals of the transportation sector. However, the large charging demand of the EV fleet may adversely impact the grid’s stability and reliability. To improve grid stability
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The need for public fast electric vehicle charging station (FEVCS) infrastructure is growing to meet the zero-emission goals of the transportation sector. However, the large charging demand of the EV fleet may adversely impact the grid’s stability and reliability. To improve grid stability and reliability, the development of a DC microgrid (MG) leveraging renewable energy sources to supply the energy demands of FEVCSs is the sustainable solution. Balancing the intermittent EV charging demand and fluctuating renewable energy generation with the stable DC bus voltage of a DC MG is a challenging objective. To address this objective, a piece-wise droop control strategy is proposed in this work. The proposed scheme regulates DC bus voltage and power sharing with droop value updating in a region-based load current distribution. Voltage compensation in individual regions is carried out to further improve the degree of freedom. In this paper, the performance of the proposed strategy is evaluated with the consideration of real-time solar PV dynamics and EV load dynamics. Further, to showcase the effectiveness of the proposed strategy, a comparative analysis with a maximum power point tracking (MPPT) controller against various dynamic EV load scenarios is carried out, and the results are validated through a hardware-in-loop experimental setup. Despite the intermittent source and EV load dynamics, the proposed piece-wise droop control can maintain voltage regulation with less than 1% deviation.
Full article
(This article belongs to the Special Issue Clean Energy Conversion Processes)
Open AccessArticle
The Fracture Evolution Mechanism of Tunnels with Different Cross-Sections under Biaxial Loading
by
Lexin Jia, Shili Qiu, Yu Cong and Xiaoshan Wang
Processes 2024, 12(5), 891; https://doi.org/10.3390/pr12050891 (registering DOI) - 28 Apr 2024
Abstract
Biaxial compression tests based on an elliptical tunnel were conducted to study the failure characteristics and the meso-crack evolution mechanism of tunnels with different cross-sections constructed in sandstone. The progressive crack propagation process around the elliptical tunnel was investigated using a real-time digital
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Biaxial compression tests based on an elliptical tunnel were conducted to study the failure characteristics and the meso-crack evolution mechanism of tunnels with different cross-sections constructed in sandstone. The progressive crack propagation process around the elliptical tunnel was investigated using a real-time digital image correlation (DIC) system. Numerical simulations were performed on egg-shaped, U-shaped, and straight-walled arched tunnels based on the mesoscopic parameters of the elliptical tunnel and following the principle of an equal cross-sectional area. The meso-crack evolution and stress conditions of the four types of tunnels were compared. The results show that (1) fractures around an elliptical tunnel were mainly distributed at the end of the long axis and mainly induce slabbing failure, and the failure mode is similar to a V-shaped notch; (2) strain localization is an important characteristic of rock fracturing, which forebodes the initiation, propagation, and coalescence paths of macro-cracks; and (3) the peak loads of tunnels with egg-shaped, U-shaped, and straight-walled arched cross-sections are 98.76%, 97.56%, and 90.57% that of an elliptical cross-section. The elliptical cross-section shows the optimal bearing capacity.
Full article
(This article belongs to the Special Issue Process Safety and Monitoring of Intelligent and Green Mining Technology)
Open AccessArticle
Data-Driven-Based Intelligent Alarm Method of Ultra-Supercritical Thermal Power Units
by
Xingfan Zhang, Lanhui Ye, Cheng Zhang and Chun Wei
Processes 2024, 12(5), 889; https://doi.org/10.3390/pr12050889 (registering DOI) - 28 Apr 2024
Abstract
In order to ensure the safe operation of the ultra-supercritical thermal power units (USCTPUs), this paper proposes an intelligent alarm method to enhance the performance of the alarm system. Firstly, addressing the issues of slow response and high missed alarm rate (MAR
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In order to ensure the safe operation of the ultra-supercritical thermal power units (USCTPUs), this paper proposes an intelligent alarm method to enhance the performance of the alarm system. Firstly, addressing the issues of slow response and high missed alarm rate (MAR) in traditional alarm systems, a threshold optimization method is proposed by integrating kernel density estimation (KDE) and convolution optimization algorithm (COA). Based on the traditional approach, the expected detection delay (EDD) indicator is introduced to better evaluate the response speed of the alarm system. By considering the false alarm rate (FAR), and EDD, a threshold optimization objective function is constructed, and the COA is employed to obtain the optimal alarm threshold. Secondly, to address the problem of excessive nuisance alarms, this paper reduces the number of nuisance alarms by introducing an adaptive delay factor into the existing system. Finally, simulation results demonstrate that the proposed method significantly reduces the MAR and EDD, improves the response speed and performance of the alarm system, and effectively reduces the number of nuisance alarms, thereby enhancing the quality of the alarms.
Full article
(This article belongs to the Special Issue Industrial IoT-Enabled Modeling and Optimization for the Process Industry)
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Open AccessArticle
Analysis of the Influence Mechanism of Nanomaterials on Spontaneous Imbibition of Chang 7 Tight Reservoir Core
by
Xiaoxiang Wang, Yang Zhang, Xinmeng Wu, Xin Fan, Desheng Zhou and Jinze Xu
Processes 2024, 12(5), 890; https://doi.org/10.3390/pr12050890 (registering DOI) - 27 Apr 2024
Abstract
This study investigates the impact of nanomaterials on different surfactant solutions. By measuring the parameters (including emulsification property, zeta potential, DLS, CA, IFT, etc.) of imbibition liquid system with nanoparticles and without nanoparticles, combining with imbibition experiments, the law and mechanism of improving
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This study investigates the impact of nanomaterials on different surfactant solutions. By measuring the parameters (including emulsification property, zeta potential, DLS, CA, IFT, etc.) of imbibition liquid system with nanoparticles and without nanoparticles, combining with imbibition experiments, the law and mechanism of improving the imbibition recovery of nanomaterials were obtained. The findings demonstrate that the nano-silica sol enhances the emulsification and dispersion of crude oil in the surfactant system, resulting in smaller and more uniform particle sizes for emulsified oil droplets. Non-ionic surfactant AEO-7 has the best effect under the synergistic action of nanomaterials. Zeta potential and DLS tests also showed that AEO-7 exhibits smaller particle sizes due to their insignificant electrostatic interaction with nanoparticles. Furthermore, the addition of nanomaterials enhances the hydrophilicity of core and reduces the interfacial tension. Under the synergistic action of nanoparticles, AEO-7 still showed the best enhanced core hydrophilicity (CA 0.61° after imbibition) and the lowest interfacial tension (0.1750 mN·m−1). In the imbibition experiment, the imbibition recovery of the system with nanomaterials is higher than that of the non-nanomaterials. The mixed system of AEO-7 and nano-silica sol ZZ-1 has the highest imbibition recovery (49.27%). Combined with the experiments above, it shows that nanomaterials have a good effect on enhancing the recovery rate of tight core, and the synergistic effect of non-ionic surfactant AEO-7 with nanomaterials is the best. Moreover, nanomaterials reduce adhesion work within the system while improving spontaneous imbibition recovery. These findings provide theoretical guidance for better understanding the mechanism behind nanomaterial-induced imbibition enhancement as well as improving tight oil’s imbibition recovery.
Full article
(This article belongs to the Section Energy Systems)
Open AccessReview
Selected Micropollutant Removal from Municipal Wastewater
by
Ján Derco, Andreja Žgajnar Gotvajn, Patrícia Guľašová, Nikola Šoltýsová and Angelika Kassai
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.
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(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.
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(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.
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(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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