Processes最新文献

{"title":"An Analysis of Hybrid Renewable Energy-Based Hydrogen Production and Power Supply for Off-Grid Systems","authors":"Yahya Z. Alharthi","doi":"10.3390/pr12061201","DOIUrl":"https://doi.org/10.3390/pr12061201","url":null,"abstract":"Utilizing renewable energy sources to produce hydrogen is essential for promoting cleaner production and improving power utilization, especially considering the growing use of fossil fuels and their impact on the environment. Selecting the most efficient method for distributing power and capacity is a critical issue when developing hybrid systems from scratch. The main objective of this study is to determine how a backup system affects the performance of a microgrid system. The study focuses on power and hydrogen production using renewable energy resources, particularly solar and wind. Based on photovoltaics (PVs), wind turbines (WTs), and their combinations, including battery storage systems (BSSs) and hydrogen technologies, two renewable energy systems were examined. The proposed location for this study is the northwestern coast of Saudi Arabia (KSA). To simulate the optimal size of system components and determine their cost-effective configuration, the study utilized the Hybrid Optimization Model for Multiple Energy Resources (HOMER) software (Version 3.16.2). The results showed that, when considering the minimum cost of energy (COE), the integration of WTs, PVs, a battery bank, an electrolyzer, and a hydrogen tank brought the cost of energy to almost 0.60 USD/kWh in the system A. However, without a battery bank, the COE increased to 0.72 USD/kWh in the same location because of the capital cost of system components. In addition, the results showed that the operational life of the fuel cell decreased significantly in system B due to the high hours of operation, which will add additional costs. These results imply that long-term energy storage in off-grid energy systems can be economically benefited by using hydrogen with a backup system.","PeriodicalId":506892,"journal":{"name":"Processes","volume":"117 45","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141351792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Distriformer: Research on a Distributed Training Rockburst Prediction Method","authors":"Yu Zhang, Kongyi Fang, Zhengjia Guo","doi":"10.3390/pr12061205","DOIUrl":"https://doi.org/10.3390/pr12061205","url":null,"abstract":"The precise forecasting of rockburst is fundamental for safeguarding human lives and property, upholding national energy security, and protecting social welfare. Traditional methods for predicting rockburst suffer from poor accuracy and extended model training durations. This paper proposes a distributed training rockburst prediction method called Distriformer, which uses deep learning technology combined with distributed training methods to predict rockburst. To assess the efficacy of the Distriformer rockburst model proposed herein, five datasets were used to compare the proposed method with Transformer and Informer. The experimental results indicate that, compared with Transformer, the proposed method reduces the absolute error by 44.4% and the root mean square error by 30.7% on average. In terms of training time, the proposed method achieves an average speedup ratio of 1.72. The Distriformer rockburst model enhances the accuracy of rockburst prediction, reduces training time, and serves as a reference for developing subsequent real-time prediction models for extensive rockburst data.","PeriodicalId":506892,"journal":{"name":"Processes","volume":"32 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141354564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Economic Dispatch of Combined Cycle Power Plant: A Mixed-Integer Programming Approach","authors":"Octavio López Hernández, David Romero Romero, M. Badaoui","doi":"10.3390/pr12061199","DOIUrl":"https://doi.org/10.3390/pr12061199","url":null,"abstract":"In this article, we present a modification to the Economic Dispatch (ED) model that addresses the non-convex nature of the cost curves associated with a Combined Cycle Power Plant (CCPP). Incorporating a binary variable provides greater precision in solving the combinatorial problem in only one simulation and, most importantly, demonstrates cost minimization among the three different cost curve models for dispatching the CCPP. Our results highlight the importance of considering different demand scenarios based on a reference forecast for one day ahead. Therefore, piecewise modeling is more feasible for solving the non-convex problem, showing greater accuracy regarding the operational state of the CCPP and avoiding the cost overestimation that occurs with traditional models. Moreover, it allows the operators to manage costs better and optimize generation potential, ultimately showing economic benefits for the system operator.","PeriodicalId":506892,"journal":{"name":"Processes","volume":"48 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141350522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Thermal Transportation in Heat Generating and Chemically Reacting MHD Maxwell Hybrid Nanofluid Flow Past Inclined Stretching Porous Sheet in Porous Medium with Solar Radiation Effects","authors":"M. B. Jeelani, Amir Abbas, Nouf Abdulrahman Alqahtani","doi":"10.3390/pr12061196","DOIUrl":"https://doi.org/10.3390/pr12061196","url":null,"abstract":"The emerging concept of hybrid nanofluids has grabbed the attention of researchers and scientists due to improved thermal performance because of their remarkable thermal conductivities. These fluids have enormous applications in engineering and industrial sectors. Therefore, the present research study examines thermal and mass transportation in hybrid nanofluid past an inclined linearly stretching sheet using the Maxwell fluid model. In the current problem, the hybrid nanofluid is engineered by suspending a mixture of aluminum oxide Al2O3 and copper Cu nanoparticles in ethylene glycol. The fluid flow is generated due to the linear stretching of the sheet and the sheet is kept inclined at the angle ζ = π/6 embedded in porous medium. The current proposed model also includes the Lorentz force, solar radiation, heat generation, linear chemical reactions, and permeability of the plate effects. Here, in the current simulation, the cylindrical shape of the nanoparticles is considered, as this shape has proven to be excellent for the thermal performance of the nanomaterials. The governing equations transformed into ordinary differential equations are solved using MATLAB bvp4c solver. The velocity field declines with increasing magnetic field parameter, Maxwell fluid parameter, volume fractions of nanoparticles, and porosity parameter but increases with growing suction parameter. The temperature drops with increasing magnetic field force and suction parameter values but increases with increasing radiation parameter and volume fraction values. The concentration profile increases with increasing magnetic field parameters, porosity parameters, and volume fractions but reduces with increasing chemical reaction parameters and suction parameters. It has been noted that the purpose of the inclusion of thermal radiation is to augment the temperature that is serving the purpose in the current work. The addition of Lorentz force slows down the speed of the fluid and raises the boundary layer thickness, which is visible in the current study. It has been concluded that, when heat generation parameters increase, the temperature field increases correspondingly for both nanofluids and hybrid nanofluids. The increase in the volume fraction of the nanoparticles is used to enhance the thermal performance of the hybrid nanofluid, which is evident in the current results. The current results are validated by comparing them with published ones.","PeriodicalId":506892,"journal":{"name":"Processes","volume":"124 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141360504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of the Effects of Structural Parameters on the Thermal Performance and System Stability of Ventilation Air Methane-Fueled Reverse-Flow Oxidation Reactors","authors":"Zhigang Zhang, Jiaze Yang, Shanshan Shao, Tao Cai, Aikun Tang, Lu Xiao","doi":"10.3390/pr12061193","DOIUrl":"https://doi.org/10.3390/pr12061193","url":null,"abstract":"Ventilation air methane (VAM) from coal mining is a low-grade energy source that can be used in combustion systems to tackle the energy crisis. This work presents a numerical analysis of the thermal and stabilization performance of a VAM-fueled thermal reversal reactor with three fixed beds. The effects of the combustion chamber/regenerator height ratio (β), heat storage materials, and porosity on the oxidation characteristics are evaluated in detail. It is shown that the regenerator temperature tends to vary monotonically with β due to the coupling effect of the gas residence time and heat transfer intensity. The optimal β is determined to be 4/6, above which the system may destabilize. Furthermore, it is found that regardless of the methane volume fraction, the regenerator with mullite inserted has the highest temperature among the heat storage materials investigated. In contrast, the temperature gradually decreases and the system becomes unstable as SiC is adopted, signifying the importance of choosing proper thermal diffusivity. Further analysis reveals that the porosity of the heat storage materials has little effect on the system stability. Decreasing the porosity can effectively reduce the oscillation amplitude of the regenerator temperature, but it also results in greater pressure losses.","PeriodicalId":506892,"journal":{"name":"Processes","volume":"59 16","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141358206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exopolysaccharides Synthesized by Lacticaseibacillus rhamnosus ŁOCK 0943: Structural Characteristics and Evaluation of Biological and Technological Properties","authors":"Magdalena Oleksy-Sobczak, Sabina Górska, Lidia Piekarska-Radzik, Sylwia Ścieszka, E. Klewicka","doi":"10.3390/pr12061192","DOIUrl":"https://doi.org/10.3390/pr12061192","url":null,"abstract":"Lactic acid bacteria can synthesize extracellular exopolysaccharides (EPSs) that have versatile physicochemical and biological properties. In this paper, the EPSs synthesized by Lacticaseibacillus rhamnosus ŁOCK 0943 were characterized. Their structure, biological, and technological activity, as well as application potential, were analyzed. Chemical analysis showed that this strain produces mannan and β-1,6-glucan. Their emulsifying, antagonistic, and antioxidant properties, along with their prebiotic potential, were assessed. The analysis of the tested polymers’ ability to create a stable emulsion showed that their emulsifying activity depends mainly on the type of oily substance used. The analysis of the antagonistic activity revealed that these EPSs can inhibit the growth of yeasts (e.g., Candida albicans ATCC 10231) and potentially pathogenic bacteria (e.g., Clostridium acetobutylicum ŁOCK 0831, Enterococcus faecalis ATCC 29212). Moreover, EPSs positively influenced the growth of all tested probiotic bacteria. Furthermore, EPSs can be successfully used as a preservative in cosmetic products. The most effective results were obtained with the use of a 0.05% solution of a chemical preservative (bronopol) and 0.25 mg/mL of the EPSs.","PeriodicalId":506892,"journal":{"name":"Processes","volume":"70 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141358090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of Single-Well Production Rate after Hydraulic Fracturing in Unconventional Gas Reservoirs Based on Ensemble Learning Model","authors":"Fan Ye, Xiaobo Li, Nan Zhang, Feng Xu","doi":"10.3390/pr12061194","DOIUrl":"https://doi.org/10.3390/pr12061194","url":null,"abstract":"To address the significant challenges in determining the single-well production of tight gas and shale gas after hydraulic fracturing, artificial intelligence (AI) methods were implemented. Machine learning (ML) algorithms such as random forest (RF), extremely randomized trees (ET), lightweight gradient boosting machines (LightGBM), gradient boosting regression (GBR), and linear regression (LR) were utilized in conjunction with reservoir geology, engineering parameters, and production data to develop several foundational models for forecasting the production of unconventional gas wells. The accuracy of these models was evaluated. Based on this, improvements in the models’ predictive accuracy and generalizability were achieved through the ensemble of machine learning models. Furthermore, this paper selected two representative tight and shale gas reservoirs to demonstrate the application of the ensemble model for well production forecasting, and a comparative analysis with actual production data was conducted. For tight gas reservoir A, the blending model achieved an MAE of 0.8419 and an MSE of 1.0930, with an R2 score of 0.8812. For shale gas reservoir B, the blending model achieved an MAE of 1.4841 and an MSE of 3.1629, with an R2 score of 0.9524. The results of the case studies indicate that the ensemble model approach employed in this study has a higher predictive accuracy and reliability than a single machine learning algorithm, and is capable of handling high-dimensional, large-scale, and imbalanced data, offering scientific validation and technical support for the assessment of the well productivity in tight and shale gas wells.","PeriodicalId":506892,"journal":{"name":"Processes","volume":"1 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141356949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Probabilistic Fuzzy System for Evaluation and Classification in Failure Mode and Effect Analysis","authors":"José Jovani Cardiel-Ortega, Roberto Baeza-Serrato","doi":"10.3390/pr12061197","DOIUrl":"https://doi.org/10.3390/pr12061197","url":null,"abstract":"Failure Mode and Effect Analysis (FMEA) is an essential risk analysis tool that is widely applicable in various industrial sectors. This structured technique allows us to identify and assign priority levels to potential failures that violate the reliability of a system or process. Failure evaluation occurs in a decision-making environment with uncertainty. This study proposes a probabilistic fuzzy system that integrates linguistic and stochastic uncertainty based on a Mamdani-type model to strengthen the FMEA technique. The system is based on analyzing the frequency of failures and obtaining the parameters to determine the probability of occurrence through the Poisson distribution. In addition, the severity and detection criteria were evaluated by the experts and modeled using the Binomial distribution. The evaluation result is a discrete value analogous to the process of obtaining the success or failure of the expert generating the evaluation of 10 Bernoulli experiments. Three fuzzy inference expert systems were developed to combine multiple experts’ opinions and reduce linguistic subjectivity. The case study was implemented in the knitting area of a textile company in the south of Guanajuato to validate the proposed approach. The potential failure of the knitting machinery, which compromises the top tension subsystem’s performance and the product’s quality, was analyzed. The proposed system, which is based on a robust mathematical model, allows for reliable fault evaluation with a simple scale. The classification performed by the system and the one performed by the experts has similar behavior. The results show that the proposed approach supports decision-making by prioritizing failure modes.","PeriodicalId":506892,"journal":{"name":"Processes","volume":"94 25","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141359460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Green Adsorbents for Environmental Remediation: Synthesis Methods, Ecotoxicity, and Reusability Prospects","authors":"Yanju Liu, B. Biswas, Masud Hassan, Ravi Naidu","doi":"10.3390/pr12061195","DOIUrl":"https://doi.org/10.3390/pr12061195","url":null,"abstract":"Adsorbent materials have long been used for remediating environmental contaminants. There is an increasing focus on developing sustainable adsorbent materials for long-term use in environmentally friendly and cost-effective remediation. “Green” or “eco-friendly” sorbent materials are generally prepared from renewable or recycled resources, have minimal toxic effects, involve synthesis processes with minor chemical or energy footprints, have high reusability, and do not contribute to additional waste or contamination. Thus, it is essential for materials to have high sorption capacity, high stability, and reusability. The literature focuses on using low-cost or waste materials to produce sorbent materials for the immobilization of contaminants from soil and water systems. The regeneration possibilities of adsorbents are used to evaluate their cost effectiveness and long-term environmental impact once they are applied at field-scale. This review evaluates sustainable sorbent materials, highlighting their green and eco-friendly qualities for a circular economy, and their contribution to the United Nations Sustainable Development Goals (UNSDG). The synthesis techniques, ecotoxicity, and prospect of reusing adsorbents are highlighted. Further, the review provides insights for researchers and practitioners interested in developing and applying green adsorbents, including bio-based carbon, char, and fibrous materials for soil and water remediation.","PeriodicalId":506892,"journal":{"name":"Processes","volume":"2 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141357837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Drying Kinetics of Industrial Pineapple Waste: Effective Diffusivity and Thermodynamic Properties Resulting from New Mathematical Models Derived from the Fick Equation","authors":"M. Cavalcanti‐Mata, Maria Elita Duarte, Manoel Tolentino, Francisco Assis Mendes, Leonardo Batista, Janaína Maria de Lima, Alexandre Lúcio, Amanda Nascimento, Rafaela D. Almeida, Hugo M. Lisboa","doi":"10.3390/pr12061198","DOIUrl":"https://doi.org/10.3390/pr12061198","url":null,"abstract":"This research focuses on the drying kinetics of industrial pineapple processing waste on a flat plate, revealing a two-phase drying process: an initial phase with a constant drying rate followed by a phase with a decreasing drying rate. During the constant rate phase, the convective mass transfer coefficient, influenced by temperature variations from 40 to 70 °C, ranged from 5.69 × 10−7 to 2.79 × 10−7 m s−1. The study introduced a novel approach to modeling the decreasing drying rate phase, applying equations derived from the Fick equation. This process involved determining the activation energy and thermodynamic properties of drying using an experimental forced convection dryer at temperatures of 40, 50, 60, and 70 °C, and an air velocity of 1.5 m/s. Data were fitted to several mathematical models, including Fick’s with four series terms, and versions of the Henderson–Pabis and Page models modified by Cavalcanti-Mata, among others. The Cavalcanti-Mata and modified Page models provided the most accurate fit to the experimental data. Results showed that diffusion coefficients vary per model yet align with literature values. Additionally, enthalpy (ΔH) and entropy (ΔS) values decreased with temperature, while Gibbs free energy (ΔG) increased, indicating that drying is an energy-dependent, non-spontaneous process.","PeriodicalId":506892,"journal":{"name":"Processes","volume":"37 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141357105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}