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
Study of Methane Solubility Calculation Based on Modified Henry’s Law and BP Neural Network
Processes 2024, 12(6), 1091; https://doi.org/10.3390/pr12061091 (registering DOI) - 26 May 2024
Abstract
Methane (CH4), a non-polar molecule characterized by a tetrahedral structure, stands as the simplest organic compound. Predominantly constituting conventional natural gas, shale gas, and combustible ice, it plays a pivotal role as a carbon-based resource and a key raw material in
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Methane (CH4), a non-polar molecule characterized by a tetrahedral structure, stands as the simplest organic compound. Predominantly constituting conventional natural gas, shale gas, and combustible ice, it plays a pivotal role as a carbon-based resource and a key raw material in the petrochemical industry. In natural formations, CH4 and H2O coexist in a synergistic system. This interplay necessitates a thorough examination of the phase equilibrium in the CH4-H2O system and CH4’s solubility under extreme conditions of temperature and pressure, which is crucial for understanding the genesis and development of gas reservoirs. This study synthesizes a comprehensive solubility database by aggregating extensive solubility data of CH4 in both pure and saline water. Utilizing this database, the study updates and refines the key parameters of Henry’s law. The updated Henry’s law has a prediction error of 22.86% at less than 40 MPa, which is an improvement in prediction accuracy compared to before the update. However, the modified Henry’s law suffers from poor calculation accuracy under certain pressure conditions. To further improve the accuracy of solubility prediction, this work also trains a BP (Back Propagation) neural network model based on the database. In addition, MSE (Mean-Square Error) is used as the model evaluation index, and pressure, temperature, compression coefficient, salinity, and fugacity are preferred as input variables, which finally reduces the mean relative error of the model to 16.32%, and the calculation results are more accurate than the modified Henry’s law. In conclusion, this study provides a novel and more accurate method for predicting CH4 solubility by comparing modified Henry’s law to neural network modeling.
Full article
(This article belongs to the Section Energy Systems)
Open AccessArticle
Optimization of Energy Consumption in Oil Fields Using Data Analysis
by
Xingyuan Liang, Zhisheng Xing, Zhenduo Yue, He Ma, Jin Shu and Guoqing Han
Processes 2024, 12(6), 1090; https://doi.org/10.3390/pr12061090 (registering DOI) - 26 May 2024
Abstract
In recent years, companies have employed numerous methods to lower expenses and enhance system efficiency in the oilfield. Energy consumption has constituted a significant portion of these expenses. This paper introduces a normalized consumption factor to effectively evaluate energy consumption in the oilfield.
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In recent years, companies have employed numerous methods to lower expenses and enhance system efficiency in the oilfield. Energy consumption has constituted a significant portion of these expenses. This paper introduces a normalized consumption factor to effectively evaluate energy consumption in the oilfield. Statistical analysis has been conducted on nearly 45,000 wells from six fields in China. Critical factors such as lifting method, daily production, pump depth, gas–oil ratio (GOR), and well deviation angle were evaluated individually. Results revealed that higher production could lead to lower normalized consumption for beam pumps, progressive cavity pumps, and electric submersible pump systems, thus enhancing system efficiency. Additionally, a higher GOR might result in lower normalized consumption for the beam pump system, while the deviation angle of the well showed negligible impact on the normalized consumption factor. This manuscript offers a method to assess the impacts of artificial lift methods on production and discusses suggestions for reducing consumption associated with each lifting method in the oilfield.
Full article
(This article belongs to the Special Issue Artificial Intelligent Techniques in the Optimal Operation of Oil and Gas Production Systems)
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Open AccessArticle
Analysis of Rock Mass Energy Characteristics and Induced Disasters Considering the Blasting Superposition Effect
by
Lu Chen, Xiaocong Yang, Lijie Guo and Shibo Yu
Processes 2024, 12(6), 1089; https://doi.org/10.3390/pr12061089 (registering DOI) - 26 May 2024
Abstract
Upon reaching deeper levels of extraction, dynamic hazards such as rockburst become more pronounced, with the high energy storage characteristics of rock masses in high-stress environments being the fundamental factor behind rockburst disasters. Additionally, deep-seated mineral extraction commonly involves drilling and blasting methods,
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Upon reaching deeper levels of extraction, dynamic hazards such as rockburst become more pronounced, with the high energy storage characteristics of rock masses in high-stress environments being the fundamental factor behind rockburst disasters. Additionally, deep-seated mineral extraction commonly involves drilling and blasting methods, where the vibrational energy generated by mining explosions combines with the elastic energy of rock masses, leading to a sudden growth in the risk and intensity of rockburst disasters. This paper, with deep mining at Sanshandao Gold Mine as the focal point, systematically investigates the impact of blasting vibrations on rockburst disasters in deep mines. Initially, based on extensive data on measured geostress considering the tri-arch cross-section form of deep tunnels, the elastic energy storage of the surrounding rocks in deep tunnels was calculated. The results indicate that the maximum energy storage of the surrounding rocks occurs at the bottom of the tunnel, with the peak accumulation position located at a distance of five times the tunnel radius. On this basis, the Map3D numerical simulation analysis was adopted to systematically capture the accumulation behavior and distribution characteristics of disturbance energy. Subsequently, by conducting the dynamic impact experiments with an improved Split Hopkinson pressure bar (SHPB) and monitoring vibration signals at various locations, the paper provides insights into the propagation patterns of impact energy in a long sample (400 mm in length and 50 mm in diameter). Analysis of the scattering behavior of vibrational energy reveals that the combined portion of blasting vibration energy constitutes 60% of the total vibrational energy. Finally, a rockburst disaster evaluation model based on energy accumulations was proposed to analyze the rockburst tendencies around deep tunnels. The results indicated that the disaster-driven energy increased by 19.9% and 12.2% at different places on the roadway. Also, the probability and intensity of a rockburst would be raised.
Full article
(This article belongs to the Special Issue Numerical Simulation and Application of Process in Deep Mining Engineering and Petroleum Engineering)
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Open AccessArticle
Construction Method and Practical Application of Oil and Gas Field Surface Engineering Case Database Based on Knowledge Graph
by
Taiwu Xia, Zhixiang Dai, Yihua Zhang, Feng Wang, Wei Zhang, Li Xu, Dan Zhou and Jun Zhou
Processes 2024, 12(6), 1088; https://doi.org/10.3390/pr12061088 (registering DOI) - 25 May 2024
Abstract
To address the challenge of quickly and efficiently accessing relevant management experience for a wide range of ground engineering construction projects, supporting project management with information technology is crucial. This includes the establishment of a case database and an application platform for intelligent
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To address the challenge of quickly and efficiently accessing relevant management experience for a wide range of ground engineering construction projects, supporting project management with information technology is crucial. This includes the establishment of a case database and an application platform for intelligent search and recommendations. The article leverages Optical Character Recognition (OCR) technology, knowledge graph technology, and Natural Language Processing (NLP) technology. It explores the mechanisms for classifying construction cases, methods for constructing a case database, structuring case data, intelligently retrieving and matching cases, and intelligent recommendation methods. This research forms a complete, feasible, and scalable method for deconstructing, storing, intelligently retrieving, and recommending construction cases, providing a theoretical basis for the establishment of a construction case database. It aims to meet the needs of digital project management and intelligent decision-making support in the oil and gas sector, thereby enhancing the efficiency and accuracy of project construction. This work offers a theoretical foundation for the development of an intelligent management platform for ground engineering projects in the oil and gas industry, supporting the sector’s digital transformation and intelligent development.
Full article
(This article belongs to the Special Issue Green Manufacturing Processes: Data Modelling and Fusion-Driven Optimization Control)
Open AccessArticle
Recognition of Longitudinal Cracks on Slab Surfaces Based on Particle Swarm Optimization and eXtreme Gradient Boosting Model
by
Yu Liu, Lai Jiang, Jing Shi, Jiabin Liu, Guohui Li, Zhaofeng Wang and Zhi Zhang
Processes 2024, 12(6), 1087; https://doi.org/10.3390/pr12061087 (registering DOI) - 25 May 2024
Abstract
Longitudinal cracks are a common defect on the surface of continuous casting slabs, and cause increases in additional processing costs or long-time interruptions. The accurate identification of surface longitudinal cracks is helpful to ensure the casting process is adjusted in time, which significantly
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Longitudinal cracks are a common defect on the surface of continuous casting slabs, and cause increases in additional processing costs or long-time interruptions. The accurate identification of surface longitudinal cracks is helpful to ensure the casting process is adjusted in time, which significantly improves the quality of slabs. In this research, the typical temperature characteristics of thermocouples at the position of longitudinal cracks and their adjacent locations were extracted. The principal component analysis (PCA) method was used to reduce the dimensions of these characteristics to remove the redundant information. The particle swarm optimization (PSO) method was introduced to optimize the parameter. On this basis, a recognition model of surface longitudinal cracks was established, based on a particle swarm optimization–eXtreme gradient boosting (XGBOOST) model. Finally, this model was trained and tested using longitudinal crack and non-longitudinal crack samples and compared with the decision tree, the gradient boosting decision tree (GBDT) and XGBOOST models. The test results showed that PSO-XGBOOST had the best identification performance in all evaluation indexes. The accuracy, F1 score and alarm rate results were 95.8%, 92.3% and 100%, respectively, and the false alarm rate was as low as 5.5%. The research results provide a theoretical basis and a reliable model for surface longitudinal crack identification.
Full article
(This article belongs to the Section Materials Processes)
Open AccessArticle
Strength and Contaminant Toxicity Leaching Characteristics of MgO-Solidified Silt
by
Shi Shu, Xiaohuan Zhou, Yujie Gong, Haohui Wang, Yan Tang and Junhao Chen
Processes 2024, 12(6), 1086; https://doi.org/10.3390/pr12061086 (registering DOI) - 25 May 2024
Abstract
Abstract: In this study, MgO as an environmentally friendly silt-solidifying material was first mixed with silt and then carbonized by injection with CO2. The strength and contaminant leaching characteristics of the MgO-solidified silt were studied using unconfined compressive
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Abstract: In this study, MgO as an environmentally friendly silt-solidifying material was first mixed with silt and then carbonized by injection with CO2. The strength and contaminant leaching characteristics of the MgO-solidified silt were studied using unconfined compressive strength and toxicity leaching tests, and the results were compared with those of cement-solidified silt. The unconfined compressive strength of the silt reached 111 kPa with 9% MgO content and a 14 d curing time. The CO2 injection further increased the unconfined compressive strength of the MgO-solidified silt by approximately 25%: the values for MgO-solidified silts without and with a CO2 injection were approximately 60% and 80%, respectively, of those of the cement-solidified silts with the same additive additions. The leaching concentrations of nutrient salts and heavy metal pollutants in the silt decreased with increased MgO content. Compared with the dredged silt, MgO solidification with carbonization reduced the leaching of total nitrogen and total phosphorus by more than 10% and 50%, respectively: these values were approximately 5% points higher than those of cement-solidified silt. Of the heavy metals, the leaching concentration of Ni was reduced the most. This study provides a theoretical basis and technical support for low-carbon treatment and green resource utilization of dredging silt.
Full article
(This article belongs to the Section Environmental and Green Processes)
Open AccessArticle
Effect of Cross-Well Natural Fractures and Fracture Network on Production History Match and Well Location Optimization in an Ultra-Deep Gas Reservoir
by
Dong Chen, Yuwei Jiao, Fenglai Yang, Chuxi Liu, Min Yang, Joseph Leines Artieda and Wei Yu
Processes 2024, 12(6), 1085; https://doi.org/10.3390/pr12061085 (registering DOI) - 25 May 2024
Abstract
Understanding subsurface natural fracture systems is crucial to characterize well production dynamics and long-term productivity potential. In addition, the placement of future wells can benefit from in-depth fracture network connectivity investigations, vastly improving new wells’ profitability and life cycles if they are placed
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Understanding subsurface natural fracture systems is crucial to characterize well production dynamics and long-term productivity potential. In addition, the placement of future wells can benefit from in-depth fracture network connectivity investigations, vastly improving new wells’ profitability and life cycles if they are placed in dense, well-connected natural fracture zones. In this study, a novel natural fracture calibration workflow is proposed. This workflow starts with the extraction of sector geology and a natural fracture model from the pre-built full-field model. Then, a cross wellbore discrete fracture network (CW-DFN) is created using a novel CW-DFN generation tool, based on image log data. An innovative fracture network identification tool is developed to detect the interconnected regional fracture network (IcFN) with CW-DFN. The non-intrusive embedded discrete fracture model (EDFM) is utilized to numerically incorporate the complex IcFN and CW-DFN in a reservoir simulation, and it is history-matched by tuning their conductivities. This workflow is applied to a single vertical well within a natural fracture carbonate reservoir in Northwest China. The study results show that the number of CW-DFNs is 11, and the number of IcFNs is 72. The non-intersected natural fractures only account for 5.5% of the production, and thus can be removed to improve simulation efficiency. The history-matching absolute average relative deviation (AARD) is 15.16%. The calibrated effective fracture permeability is 280 millidarcy, with an aperture of 0.001 m, equating to a conductivity of 0.28 millidarcy-meter. The 30-year gas production forecast is estimated to be 1.66 billion cubic meters based on a history-matched model. Finally, if the well is drilled to the east of the sector, 30-year production declines to 1.33 billion cubic meters (a reduction of 20%). However, if the well is drilled to the west of the sector, 30-year production increases to 2 billion cubic meters (an improvement of 20.5%).
Full article
(This article belongs to the Special Issue Advances in Improving Oil Recovery in Low-Permeability Hydrocarbon Resources)
Open AccessArticle
Classification Strategy for Power Quality Disturbances Based on Variational Mode Decomposition Algorithm and Improved Support Vector Machine
by
Le Gao, Jinhao Wang, Min Zhang, Shifeng Zhang, Hanwen Wang and Yang Wang
Processes 2024, 12(6), 1084; https://doi.org/10.3390/pr12061084 (registering DOI) - 25 May 2024
Abstract
With the continuous improvement in production efficiency and quality of life, the requirements of electrical equipment for power quality are also increasing. Accurate detection of various power quality disturbances is an effective measure to improve power quality. However, in practical applications, the dataset
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With the continuous improvement in production efficiency and quality of life, the requirements of electrical equipment for power quality are also increasing. Accurate detection of various power quality disturbances is an effective measure to improve power quality. However, in practical applications, the dataset is often contaminated by noise, and when the dataset is not sufficient, the computational complexity is too high. Similarly, in the recognition process of artificial neural networks, the local optimum often occurs, which ultimately leads to low recognition accuracy for the trained model. Therefore, this article proposes a power quality disturbance classification strategy based on the variational mode decomposition (VMD) and improved support vector machine (SVM) algorithms. Firstly, the VMD algorithm is used for preprocessing disturbance denoising. Next, based on the analysis of typical fault characteristics, a multi-SVM model is used for disturbance classification identification. In order to improve the recognition accuracy, the improved Grey Wolf Optimization (IGWO) algorithm is used to optimize the penalty factor and kernel function parameters of the SVM model. The results of the final case study show that the classification accuracy of the proposed method can reach over 98%, and the recognition accuracy is higher than that of the other models.
Full article
(This article belongs to the Section Energy Systems)
Open AccessArticle
A Hierarchical Axiomatic Evaluation of Additive Manufacturing Equipment and the 3D Printing Process Based on Sustainability and Human Factors
by
Ismael Mendoza-Muñoz, Mildrend Ivett Montoya-Reyes, Aidé Aracely Maldonado-Macías, Gabriela Jacobo-Galicia and Olivia Yessenia Vargas-Bernal
Processes 2024, 12(6), 1083; https://doi.org/10.3390/pr12061083 (registering DOI) - 25 May 2024
Abstract
As interest in additive manufacturing (AM) continues to increase, it has become more important to have a robust method to help potential users select the AM process that best suits their technological needs while providing the greatest potential benefits in terms of sustainability
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As interest in additive manufacturing (AM) continues to increase, it has become more important to have a robust method to help potential users select the AM process that best suits their technological needs while providing the greatest potential benefits in terms of sustainability and its effect on people. This paper presents the development of a framework for selecting the best AM process for a given application by considering both sustainability and human factors through the combination of axiomatic design and the analytic hierarchy process. Thirty-one participants with varying levels of expertise (novice and advanced users) were involved in the study, considering the frequency of 3D printer usage (novice users: never, rarely; expert users: sometimes, almost always, always) for prototyping parts. They employed fused deposition modeling (FDM) and stereolithography (SLA) (both 3D desktop printers) and collected data on five evaluation criteria. The participation of experts helped establish a novel methodology, with material cost deemed most important (49.8%), followed by cycle time (28%), energy consumption (11.7%), error rate (6.6%), and equipment noise (3.9%). The results showed that FDM was the optimal equipment option for advanced users. By examining the information content of the other options, it was found that FDM demanded less information than SLA, regardless of the user’s level of expertise. The proposed method is appropriate to assess the sustainability aspect of FDM and SLA; however, it can be further improved by adding indicators such as environmental impact, recyclability, and ergonomic and occupational health factors.
Full article
(This article belongs to the Special Issue Innovations in Manufacturing Processes and Systems for Sustainable Practices)
Open AccessArticle
Surfactant–Polymer Flooding: Chemical Formula Design and Evaluation for High-Temperature and High-Salinity Qinghai Gasi Reservoir
by
Jinlong Sun, Yifeng Liu, Xiuyu Zhu, Futang Hu, Yuanyuan Wang, Xiaoling Yi, Zhuoyan Zhu, Weidong Liu, Youyi Zhu and Qingfeng Hou
Processes 2024, 12(6), 1082; https://doi.org/10.3390/pr12061082 - 24 May 2024
Abstract
The Gasi reservoir in the Qinghai oilfield is a typical high-temperature and high-salinity reservoir, with an average temperature and average salinity of 70.0 °C and 152,144 mg/L, respectively. For over 30 years since 1990, water flooding has been the primary method for enhancing
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The Gasi reservoir in the Qinghai oilfield is a typical high-temperature and high-salinity reservoir, with an average temperature and average salinity of 70.0 °C and 152,144 mg/L, respectively. For over 30 years since 1990, water flooding has been the primary method for enhancing oil recovery. Recently, the Gasi reservoir has turned into a mature oilfield. It possesses a high water cut of 76% and a high total recovery rate of 47%. However, the main developing enhanced oil recovery (EOR) technology for the development of the Gasi reservoir in the next stage is yet to be determined. Surfactant–polymer (SP) flooding, which can reduce the oil–water interfacial tension and increase the viscosity of the water phase, has been widely applied to low-temperature and low-salinity reservoirs across China in the past few decades, but it has rarely been applied to high-temperature and high-salinity reservoirs such as the Gasi reservoir. In this study, the feasibility of SP flooding for high-temperature and high-salinity reservoirs was established. Thanks to the novel surfactant and polymer products, an SP flooding formula with surfactants ZC-2/B2 and polymer BRH-325 was proposed for Gasi. The formula showed a low interfacial tension of 10−2 mN/m and a high viscosity of 18 mPa·s in simulated reservoir conditions. The oil displacement experiment demonstrated that this formula can enhance the oil recovery rate by 26.95% upon water flooding at 64.64%. This study provides a feasible EOR candidate technology for high-temperature and high-salinity reservoirs, as exemplified by the Qinghai Gasi reservoir.
Full article
(This article belongs to the Special Issue Advanced Reservoir Simulation and Modelling, Thermal and Enhanced Oil Recovery Processes)
Open AccessArticle
Static Characteristics and Energy Consumption of the Pressure-Compensated Pump
by
David Kolář, Adam Bureček, Lumír Hružík, Marian Ledvoň, Tomáš Polášek, Jana Jablonská and Richard Lenhard
Processes 2024, 12(6), 1081; https://doi.org/10.3390/pr12061081 - 24 May 2024
Abstract
The motivation of this research was to assess the possibility of speed control for the selected pressure-compensated pump. Measured static characteristics of an axial piston pump with pressure compensation are presented in the paper. Based on these characteristics, the pump efficiencies are determined.
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The motivation of this research was to assess the possibility of speed control for the selected pressure-compensated pump. Measured static characteristics of an axial piston pump with pressure compensation are presented in the paper. Based on these characteristics, the pump efficiencies are determined. The characteristics and efficiencies are determined for the different pump outlet pressures, pump speeds, relative displacements and for the different pressures set at the pressure compensator. In addition, the different methods of pump control were compared. These are displacement control, speed control and both controls. The efficiency of each control method was compared based on the determined mechanical input power at the pump drive shaft. By comparing these control methods, it was found that the combination of both control methods can achieve up to 93% savings of mechanical power in the controlled state (stand-by state). Also, the adverse effects resulting from each control method that reduces pump efficiency were defined.
Full article
(This article belongs to the Section Manufacturing Processes and Systems)
Open AccessArticle
Numerical Investigation of Heat Transfer Characteristics of Trapezoidal Fin Phase Change Thermal Energy Storage Unit
by
Haobing Luo, Changchuan Yang, Meng Xu and Ying Zhang
Processes 2024, 12(6), 1080; https://doi.org/10.3390/pr12061080 - 24 May 2024
Abstract
Abstract: In order to enhance the heat transfer performance of a phase change thermal energy storage unit, the effects of trapezoidal fins of different sizes and arrangement modes were studied by numerical simulation in the heat storage and release processes. The optimal
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Abstract: In order to enhance the heat transfer performance of a phase change thermal energy storage unit, the effects of trapezoidal fins of different sizes and arrangement modes were studied by numerical simulation in the heat storage and release processes. The optimal enhancement solution was obtained by comparing the temperature distribution, instantaneous liquid-phase ratio, solid–liquid phase diagram and comprehensive heat storage and release performance of the thermal energy storage unit under different fin sizes. During the heat storage process, the results show that when the ratio of the length of the upper and lower base of the trapezoid h1/h2 is 1:9, the heat storage time is shortened by 9.03% and 18.21% compared with h1/h2 = 3:7 and 5:5, respectively. During the heat release process, the optimal heat transfer effect is achieved when h1/h2 = 5:5. To further improve the heat transfer effects, the energy storage unit is placed upside down; then, the least time is achieved when h1/h2 = 2:8. When heat storage and release are considered together, the energy storage unit with h1/h2 = 2:8 takes the shortest time to melt in upright placement and then to solidify in upside-down placement.
Full article
(This article belongs to the Special Issue Progresses in Electrochemical Energy Conversion and Storage—Materials, Structures and Simulation)
Open AccessArticle
Heat Transfer and Entropy Generation for Mixed Convection of Al2O3–Water Nanofluid in a Lid-Driven Square Cavity with a Concentric Square Blockage
by
M. Özgün Korukçu
Processes 2024, 12(6), 1079; https://doi.org/10.3390/pr12061079 - 24 May 2024
Abstract
The present numerical investigation is focused on analyzing the characteristics of steady laminar mixed convection flow in a lid-driven square cavity, specifically considering the utilization of Al2O3–water nanofluid. The Al2O3–water nanofluid is assumed to be
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The present numerical investigation is focused on analyzing the characteristics of steady laminar mixed convection flow in a lid-driven square cavity, specifically considering the utilization of Al2O3–water nanofluid. The Al2O3–water nanofluid is assumed to be Newtonian and incompressible. Within the cavity, a square blockage is positioned at its center, which is subjected to isothermal heating. The blockage ratio of the square is B = 1/4, and the Grashof number is Gr = 100. The walls of the cavity are maintained at a constant temperature, Tc, while the square blockage remains at a constant temperature, Th. The primary objective of this study is to investigate the flow and heat transfer mechanisms, as well as the entropy generation within the cavity. This investigation is conducted for a range of Richardson numbers (0.01 ≤ Ri ≤ 100) and volume fractions of the nanofluid (0 ≤ ϕ ≤ 0.05). Several parameters are obtained and analyzed, including streamlines, isotherms, velocity variations on the vertical and horizontal midplanes, local Nusselt number variations on the surfaces of the square blockage, the average Nusselt number on the square blockage, and the total dimensionless entropy generation of the system. The results of the investigation revealed that both the average Nusselt number on the square blockage and the total dimensionless entropy generation of the system exhibit an increasing trend with an increasing volume fraction of the nanofluid and a decreasing Richardson number. Furthermore, correlations for the average Nusselt number and the total dimensionless entropy generation with the Richardson number, and the nanofluid volume fraction are derived.
Full article
(This article belongs to the Special Issue New Trends and Processes in Nanofluids and Carbon-Based Nanoparticles)
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Open AccessArticle
Advancing Decarbonization Efforts in the Glass Manufacturing Industry through Mathematical Optimization and Management Accounting
by
Wen-Hsien Tsai, Shuo-Chieh Chang and Xiang-Yu Li
Processes 2024, 12(6), 1078; https://doi.org/10.3390/pr12061078 - 24 May 2024
Abstract
This study explores the integration of activity-based costing (ABC) and the theory of constraints (TOC) with carbon tax policies to drive decarbonization in the Taiwanese glass industry. Employing a mathematical programming approach, four distinct models are developed to assess the impact of different
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This study explores the integration of activity-based costing (ABC) and the theory of constraints (TOC) with carbon tax policies to drive decarbonization in the Taiwanese glass industry. Employing a mathematical programming approach, four distinct models are developed to assess the impact of different carbon tax structures, carbon trading mechanisms, and recycled material utilization on corporate profitability and carbon emissions. The findings reveal that strategically applying ABC and the TOC with well-designed carbon tax policies can effectively incentivize emission reduction while maintaining industrial competitiveness. The models incorporating carbon trading and tax allowances demonstrate the potential for creating win–win situations, where companies can increase profitability by investing in cleaner technologies and processes. This study contributes to the literature on sustainable manufacturing and provides actionable insights for policymakers and industry leaders seeking to implement effective carbon pricing mechanisms that drive economic growth and environmental sustainability in tandem.
Full article
(This article belongs to the Topic Multiple Roads to Achieve Net-Zero Emissions by 2050)
Open AccessArticle
The Impact of Installation Angle on the Wind Load of Solar Photovoltaic Panels
by
Hai-Bing Jiang, Hui-Fan Huang, Yu-Liang Zhang, Xiao-Wei Xu and Yan-Juan Zhao
Processes 2024, 12(6), 1077; https://doi.org/10.3390/pr12061077 - 24 May 2024
Abstract
In order to explore the wind load characteristics acting on solar photovoltaic panels under extreme severe weather conditions, based on the Shear Stress Transport (SST) κ-ω turbulence model, numerical calculations of three-dimensional incompressible viscous steady flow were performed for four installation
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In order to explore the wind load characteristics acting on solar photovoltaic panels under extreme severe weather conditions, based on the Shear Stress Transport (SST) κ-ω turbulence model, numerical calculations of three-dimensional incompressible viscous steady flow were performed for four installation angles and two extreme wind directions of the solar photovoltaic panels. The wind load characteristics on both sides of the photovoltaic panels were obtained, and the vortex structure characteristics were analyzed using the Q criterion. The results indicate that, under different installation angles, the windward side pressure of the solar photovoltaic panel is generally higher than the leeward side. The leeward side is prone to forming larger vortices, increasing the fatigue and damage risk of the material, which significantly impacts the solar photovoltaic panel. As the installation angle increases, the windward side pressure of the solar photovoltaic panel also gradually increases. Therefore, optimal installation methods include installing the panel facing the wind at angles of 30° and 45°, or installing it facing away from the wind at a 60° angle, to minimize the impact of wind load on the solar photovoltaic panel.
Full article
(This article belongs to the Section Energy Systems)
Open AccessArticle
An Experimental Study on the Flash Boiling Characteristics of Liquid Ammonia Spray in a Constant Volume Chamber under High Injection Pressure
by
Haibin He, Jie Wu, Lei Wang, Hua Lou, Songfeng Li, Lvmeng Huang and Zhanming Chen
Processes 2024, 12(6), 1076; https://doi.org/10.3390/pr12061076 - 24 May 2024
Abstract
The spray characteristics of liquid ammonia under various ambient pressures and temperatures were analyzed in a constant volume chamber to cover a wide range of superheat degrees. The injection pressure was set as 70 and 80 MPa with ambient pressure ranging from 0.2
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The spray characteristics of liquid ammonia under various ambient pressures and temperatures were analyzed in a constant volume chamber to cover a wide range of superheat degrees. The injection pressure was set as 70 and 80 MPa with ambient pressure ranging from 0.2 to 4 MPa. The ambient temperature was 500 K. The results showed that the higher the injection pressure, the greater the kinetic energy obtained. The droplet fragmentation was enhanced, and the phenomenon of gradual separation of the gas–liquid region occurred with increasing injection pressure. Under flash boiling spray conditions, the spray developed faster than non-flash boiling and transition flash boiling spray under the same injection pressure. In addition, the flash boiling spray tip penetration of the gas and liquid increased more than that of cold spray, and the fluctuation of the late stage of the injection was relatively large. Therefore, the injection pressure has a greater effect on the spray tip penetration of flash boiling spray. Moreover, ambient pressure greatly influences the flare flash boiling spray. The spray resistance phenomenon was found during the spray development in the flare flash boiling condition. With the increase in ambient pressure, the spray tip penetration of flash boiling spray decreases due to the reduction in the pressure difference inside and outside the spray hole and the restriction of ambient gas. Meanwhile, owing to the low ambient pressure and ambient density, the liquid penetration in the initial phase of the flare flash boiling spray will be abnormally shorter than that of the non-flash boiling spray.
Full article
(This article belongs to the Special Issue Green Fuels: Utilization, Production and Processing Technologies)
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Open AccessArticle
An Efficient Multi-Label Classification-Based Municipal Waste Image Identification
by
Rongxing Wu, Xingmin Liu, Tiantian Zhang, Jiawei Xia, Jiaqi Li, Mingan Zhu and Gaoquan Gu
Processes 2024, 12(6), 1075; https://doi.org/10.3390/pr12061075 - 24 May 2024
Abstract
Sustainable and green waste management has become increasingly crucial due to the rising volume of waste driven by urbanization and population growth. Deep learning models based on image recognition offer potential for advanced waste classification and recycling methods. However, traditional image recognition approaches
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Sustainable and green waste management has become increasingly crucial due to the rising volume of waste driven by urbanization and population growth. Deep learning models based on image recognition offer potential for advanced waste classification and recycling methods. However, traditional image recognition approaches usually rely on single-label images, neglecting the complexity of real-world waste occurrences. Moreover, there is a scarcity of recognition efforts directed at actual municipal waste data, with most studies confined to laboratory settings. Therefore, we introduce an efficient Query2Label (Q2L) framework, powered by the Vision Transformer (ViT-B/16) as its backbone and complemented by an innovative asymmetric loss function, designed to effectively handle the complexity of multi-label waste image classification. Our experiments on the newly developed municipal waste dataset “Garbage In, Garbage Out”, which includes 25,000 street-level images, each potentially containing up to four types of waste, showcase the Q2L framework’s exceptional ability to identify waste types with an accuracy exceeding 92.36%. Comprehensive ablation experiments, comparing different backbones, loss functions, and models substantiate the efficacy of our approach. Our model achieves superior performance compared to traditional models, with a mean average precision increase of up to 2.39% when utilizing the asymmetric loss function, and switching to ViT-B/16 backbone improves accuracy by 4.75% over ResNet-101.
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(This article belongs to the Section Advanced Digital and Other Processes)
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Analysis of Microwave Effects on the MnO2-Catalyzed Toluene Oxidation Pathway
by
Fengming Yang, Yi Ye, Lili Ding, Huacheng Zhu, Jianhong Luo, Long Gao, Yunfei Song and Shumeng Yin
Processes 2024, 12(6), 1074; https://doi.org/10.3390/pr12061074 - 24 May 2024
Abstract
Microwave radiation has become an effective catalytic combustion method, especially in the degradation of volatile organic compounds (VOCs) such as toluene using catalysts like MnO2. In this study, a spine waveguide microwave reactor was designed to investigate the influence of different
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Microwave radiation has become an effective catalytic combustion method, especially in the degradation of volatile organic compounds (VOCs) such as toluene using catalysts like MnO2. In this study, a spine waveguide microwave reactor was designed to investigate the influence of different microwave processing conditions on the degradation of toluene catalyzed by MnO2. An experimental system for microwave-assisted catalytic degradation of toluene was established to explore the relationship between microwave power, catalyst conductivity, and toluene degradation rate. The results showed that the efficiency of MnO2 catalyzing toluene degradation had a nonlinear relationship with microwave power, first increasing to a peak and then decreasing. Additionally, the experiment found that the degradation rate of toluene was positively correlated with the conductivity of MnO2. Subsequent characterization analyses using X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy (SEM) further verified the changes in the microstructure and properties of MnO2 under microwave heating. The characterization results showed that with the increase in microwave power, the relative content of Mn3+ on the surface of MnO2 increased, and the relative content of adsorbed oxygen also increased accordingly. At a microwave power of 100 W, the treated MnO2 displayed the optimal ratio of manganese oxidation state and oxide, both close to 1:1, which was more conducive to the degradation of toluene. Based on these findings, this study hypothesized that the microwave-enhanced catalytic degradation of toluene by MnO2 may be attributed to changes in the surface electron transfer kinetics of MnO2, providing new insights into the field of microwave-enhanced catalysis.
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(This article belongs to the Special Issue Microwave Applications in Chemistry and Industry)
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A Predictive Model for Wellbore Temperature in High-Sulfur Gas Wells Incorporating Sulfur Deposition
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Qiang Fang, Jinghong He, Yang Wang, Hong Pan, Hongming Ren and Hao Liu
Processes 2024, 12(6), 1073; https://doi.org/10.3390/pr12061073 - 24 May 2024
Abstract
HSG (high-sulfur gas) reservoirs are prevalent globally, yet their exploitation is hindered by elevated levels of hydrogen sulfide. A decrease in temperature and pressure may result in the formation of sulfur deposits, thereby exerting a notable influence on gas production. Test instruments are
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HSG (high-sulfur gas) reservoirs are prevalent globally, yet their exploitation is hindered by elevated levels of hydrogen sulfide. A decrease in temperature and pressure may result in the formation of sulfur deposits, thereby exerting a notable influence on gas production. Test instruments are susceptible to significant corrosion due to the presence of hydrogen sulfide, resulting in challenges in obtaining bottom hole temperature and pressure test data. Consequently, a WTD (wellbore temperature distribution) model incorporating sulfur precipitation was developed based on PPP (physical property parameter), heat transfer, and GSTP (gas–solid two-phase) flow models. The comparison of a 2.53% temperature error and a 4.80% pressure error with actual field test data indicates that the established model exhibits high accuracy. An analysis is conducted on the impact of various factors, such as production, sulfur layer thickness, reservoir temperature, and reservoir pressure, on the distribution of the wellbore temperature field and pressure field. Increased gas production leads to higher wellhead temperatures. The presence of sulfur deposits reduces the flow area and wellhead pressure. A 40% concentration of hydrogen sulfide results in a 2 MPa pressure drop compared to a 20% concentration. Decreased reservoir pressure and temperature facilitate the formation of sulfur deposits at the wellhead.
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(This article belongs to the Special Issue Advances in Numerical Analysis of Heat Transfer and Fluid Flow)
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An Online Energy-Saving Control Allocation Strategy Based on Self-Updating Loss Estimation for Multi-Motor Drive Systems
by
Yujie Chen, Tao Peng, Yansong Xu, Junze Luo and Jinqiu Gao
Processes 2024, 12(6), 1072; https://doi.org/10.3390/pr12061072 - 23 May 2024
Abstract
In this paper, an online energy-saving control allocation strategy based on self-updating loss estimation for multi-motor drive systems is proposed, where the impact of variations in motor parameters and distribution coefficients is considered. Firstly, a drive system model for multi-motor drive systems incorporating
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In this paper, an online energy-saving control allocation strategy based on self-updating loss estimation for multi-motor drive systems is proposed, where the impact of variations in motor parameters and distribution coefficients is considered. Firstly, a drive system model for multi-motor drive systems incorporating iron loss in permanent magnet synchronous motor (PMSM) is established. Then, a self-updating PMSM loss estimation method based on dynamic torque–current mapping is proposed. The torque–current mapping is initially identified based on the conv-fusion curve, and iteratively updated by optimal estimation. Subsequently, an online control allocation method based on line search is proposed, which mitigates the adverse effects caused by variations in distribution coefficients and reduces the total motor loss. Finally, the effectiveness of the proposed strategy is verified on the hardware-in-the-loop (HIL)-based platform. The results demonstrate that the strategy effectively enhances energy efficiency while maintaining the original control performance of the system.
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(This article belongs to the Topic Energy Management and Efficiency in Electric Motors, Drives, Power Converters and Related Systems)
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