Energy Science & Engineering最新文献

{"title":"Multi-Physics Pinhole Size Tolerance Analysis on the Leakage Characteristics and Performance of Proton Exchange Membrane Fuel Cells","authors":"Junyi Chen,&nbsp;Yuxuan Luo,&nbsp;Lan Zhang,&nbsp;Trevor Hocksun Kwan,&nbsp;Qinghe Yao","doi":"10.1002/ese3.70183","DOIUrl":"https://doi.org/10.1002/ese3.70183","url":null,"abstract":"<p>This study delves into exploring how pinhole size affects both the electrochemical efficiency and hydrogen leakage within proton exchange membrane fuel cells (PEMFCs). The researchers devised a comprehensive multiphysics field model for the PEMFC and employed the finite element method to simulate various pinhole diameters, evaluating their impact. Our findings highlight that the influence of pinholes on fuel cell performance heavily relies on the inlet pressure. When maintaining a constant inlet pressure, pinholes smaller than 0.37 mm diameter exhibit minimal impact on fuel cell performance, maintaining hydrogen utilization rate above 90%. Conversely, the pressure disparity across the membrane notably amplifies hydrogen leakage rates, leading to reduced current density due to the oxidation of escaping hydrogen. Consequently, this decline affects hydrogen and oxygen concentrations downstream of the pinhole. Specifically, sustaining a 90% hydrogen utilization rate necessitates a pinhole diameter of 0.027 mm at an inlet pressure differential of 500 Pa. Establishing the acceptable pinhole size crucially informs the operational strategy for PEM fuel cells.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 9","pages":"4402-4416"},"PeriodicalIF":3.4,"publicationDate":"2025-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://scijournals.onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70183","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145038473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantitative Evaluation of Sand Body Connectivity Based on the Support Vector Machine Algorithm: A Case Study of the Putaohua Oil Reservoir in the Daqing Oil Field, Songliao Basin, China","authors":"Hui He,&nbsp;Chang Liu,&nbsp;Lin Xie,&nbsp;Xianming Li,&nbsp;Chuixian Kong,&nbsp;Pengshan Ma,&nbsp;Shiyuan Li","doi":"10.1002/ese3.70186","DOIUrl":"https://doi.org/10.1002/ese3.70186","url":null,"abstract":"<p>Taking the braided river reservoir of Pu-I Member of the Putaohua Oil Reservoir in the Daqing Lamadian Oil Field as an example, this study integrates data from field outcrops, well logging, and cores. Based on a precise characterization of the sand body structure, the contact relationships of the braided river reservoir sand bodies were systematically summarized. Three connectivity patterns of the braided river reservoir sand body in the lateral, longitudinal, and internal directions were established. The support vector machine (SVM) method was employed to quantitatively predict the connectivity of the reservoir sand bodies. Research findings indicate that by categorically optimizing the evaluation parameters of sand body connectivity and applying the SVM algorithm, the connectivity of sand bodies can be rapidly and accurately evaluated. Through mutual validation of dynamic and static data, the prediction accuracy reached 88%, compared with 81% for BP neural networks and 79% for fuzzy comprehensive evaluations. On this basis, a target-based geological modeling approach was adopted to establish a single sand body model controlled by 3rd to 4th level configuration interfaces. Leveraging the characterization of interlayers, the quantitative evaluation results of sand body connectivity obtained using the SVM method were utilized as deterministic data to assign conductivities to sand bodies across different zones and categories, thereby guiding the refined numerical simulation of oil reservoirs. This approach achieved the quantitative characterization and simulation of sand body connectivity coupled with interlayers and conductivities, and the numerical simulation results better reflect actual production conditions. These outcomes provide a new technical foundation for optimizing and adjusting oil field development in subsequent stages.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 9","pages":"4445-4460"},"PeriodicalIF":3.4,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://scijournals.onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70186","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145037921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Techno-Economic Assessment of Biofuels Production From Sugarcane Bagasse","authors":"Ayanda S. Buthelezi,&nbsp;Manimagalay Chetty,&nbsp;Amir H. Mohammadi","doi":"10.1002/ese3.70178","DOIUrl":"https://doi.org/10.1002/ese3.70178","url":null,"abstract":"<p>The cooperative effect of climate change, rising fossil fuel prices and global fossil fuel depletion necessitates the production and use of renewable energy nationally and globally. The need for more energy-producing methods is growing as energy consumption rises. A techno-economic assessment (TEA) delivers an in-depth analysis of the financial feasibility of these processes, informing investment choices and policy development for biofuel advancement. Three biological biomass-to-fuel conversion routes were investigated in this study: fermentation for bioethanol production, anaerobic digestion (AD) for biogas production and dark fermentation (DF) for biohydrogen production. Aspen Plus software simulations were performed to process 51840 kg/h sugarcane bagasse (SCB). The discounted cash flow method was used for economic assessment using the tax rate of 28% and the discount rate of 12%, with a straight-line depreciation of 20% for 5 years. The plant life was assumed to be 25 years. The most profitable method was DF with an net present value (NPV) of 67.41 million USD, a payback period (PBP) of 3.3 years, an ROI of 1.51 and a PI of 7.95. Biogas production ranked second with an NPV of 37.57 million USD, a PBP of 4.4 years, an ROI of 1.16 and a PI of 5.85. Under conditions assumed in the study, bioethanol production was not feasible at all with the negative NPV. The project will not be able to recover its initial investment at the end of the plant's life.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 9","pages":"4270-4286"},"PeriodicalIF":3.4,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://scijournals.onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70178","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145037851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Joint Estimation of Lithium-Ion Battery Health Status and Remaining Service Life by Transfer Learning Based on PatchTST and Dynamic Weighted MSE Loss Function","authors":"Kaiyi Zhang,&nbsp;Xingzhu Wang","doi":"10.1002/ese3.70177","DOIUrl":"https://doi.org/10.1002/ese3.70177","url":null,"abstract":"<p>This study proposes a transfer learning estimation method based on dynamic weighted kernel MSE (DWKMSE) loss function and PatchTST model for the joint estimation of lithium-ion battery health state (SOH) and remaining useful life (RUL). The PatchTST model divides battery aging characteristics into independent features through channel-independent operations, sharing the parameter weights and biases of the transformer backbone to reduce information redundancy and capture key information in each aging feature. The dynamic weighted kernel MSE loss function guides the PatchTST model to update parameter weights, enabling the model to fully learn the nonlinear characteristics of the degradation process and reduce the impact of outliers on the model during training. The effectiveness of the PatchTST model and DWKMSE loss function in the joint estimation of battery SOH and RUL was verified on different battery aging data sets. Finally, transfer learning was performed on two different battery aging data sets to validate the estimation performance of the proposed method under different usage conditions and materials. The experimental index showed that the average MAE value for SOH is 0.421, with an average <i>R</i>² value of 0.953; the average MAE value for RUL is 16.788, with an average <i>R</i>² value of 0.987. Experimental results show that compared with direct training methods, the MAE metric for SOH estimation based on transfer learning decreased by 17.1%, while the <i>R</i>² metric improved by 2.3%; the MAE metric for SOH estimation decreased by 18.6%, and the <i>R</i>² metric improved by 0.1%.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 9","pages":"4371-4386"},"PeriodicalIF":3.4,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://scijournals.onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70177","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145037808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing of Integrated Energy Systems With CCHP-P2G on FTS Operation Strategy Using a Matrix Modeling Approach","authors":"Hui Lu,&nbsp;Hongzhi Lu,&nbsp;Zhuojia Xu,&nbsp;Wendong Huang,&nbsp;Heng Wu,&nbsp;Huiwen Zhang,&nbsp;Aoli Wang,&nbsp;Yufang Chang","doi":"10.1002/ese3.70049","DOIUrl":"https://doi.org/10.1002/ese3.70049","url":null,"abstract":"<p>With carbon peaking and carbon neutrality goals, the integrated energy system (IES) is an effective way to achieve energy transition. To improve energy efficiency and reduce carbon dioxide emissions of the IES, a model of IES with CCHP-P2G and the FTS operation strategy is proposed. Firstly, a matrix modeling method is adopted in this model. This effectively improves the accuracy of system modeling. Meanwhile, a correction matrix is used to describe uncertain factors such as energy storage and renewable energy. Besides, this paper proposes the FTS operation strategy to avoid heating waste problems in traditional operation strategy, such as FEL and FTL. In the end, a method akin to a per-unit value is applied to structure evaluation criteria. The superiority of the proposed method is verified by the simulation results. The results demonstrate that the proposed model using CCHP-P2G and FTS operation strategy can improve the utilization of renewable energy, and reduce carbon emissions and thus achieve reductions in total operation costs and carbon emissions.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 7","pages":"3491-3502"},"PeriodicalIF":3.5,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70049","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144614976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A New Add-On Flap for Performance Improvement of Small Horizontal Axis Wind Turbines","authors":"Nima Alizadeh,&nbsp;Alireza Jahangirian","doi":"10.1002/ese3.70168","DOIUrl":"https://doi.org/10.1002/ese3.70168","url":null,"abstract":"<p>In the present study, two types of add-on flaps tangential to the camber line of small horizontal axis wind turbine blade are introduced and their performances on the production power are investigated. The wind turbine of Berlin University (TU-BERT) is used as the base turbine and the flaps' length, angle, and their locations on the blade are selected as geometric variables. The generated turbine power is calculated numerically by solving three-dimensional Navier–Stokes equations with a finite volume method using SST <i>k</i>–ω turbulence model. After parametric study considering the effects of flap geometric variables on the production power, a proper arrangement of flaps is proposed. Results show that the straight and curved flaps with the best flap arrangement are able to increase the power coefficient of the wind turbine by 5.8% and 10.5%, respectively, at the rated wind speed of 5.5 m/s and tip speed ratio of 4.5.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 8","pages":"4230-4240"},"PeriodicalIF":3.4,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://scijournals.onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70168","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144805835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Front Cover Image","authors":"Goran Shirzad,&nbsp;Mehdi Assareh","doi":"10.1002/ese3.70181","DOIUrl":"https://doi.org/10.1002/ese3.70181","url":null,"abstract":"<p>COVER CAPTION:</p><p>The cover image is based on the article <i>Dual Porosity Simulation of Gravity Drainage Mechanism Induced by Geological Acid Gas Storage in Naturally Fractured Reservoirs</i> by Mehdi Assareh et al., https://doi.org/10.1002/ese3.70094.\u0000\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 6","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70181","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144244384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Regional Distributed Photovoltaic Power Forecasting Method Based on Cluster Division and Selection of Representative Plants","authors":"Honglu Zhu,&nbsp;Xi Zhang,&nbsp;Yuhang Wang,&nbsp;Huang Ding","doi":"10.1002/ese3.70171","DOIUrl":"https://doi.org/10.1002/ese3.70171","url":null,"abstract":"<p>As the proportion of distributed photovoltaic (DPV) power generation in the energy structure increases, accurate forecasting of its power output is crucial for ensuring the stability and reliability of the power grid. The crux of DPV power forecasting lies in the effective division of DPV plant clusters and the selection of representative plants. To address these issues, the geographical location distribution information and power characteristics of DPV plants are utilized for cluster division to ensure that the power characteristics of DPV plants within the clusters are similar. Following this, the maximum difference algorithm is used to identify representative plants from each cluster, thereby reducing calculational load and enhancing forecasting efficiency. Subsequently, a Convolutional Neural Network (CNN)- Bidirectional Gated Recurrent Unit model (BiGRU) is constructed, which combines meteorological data and historical power data, to forecast the power of selected representative plants, and then aggregates these forecasts to get the overall forecasting results for the region. This model leverages the strengths of CNN in capturing spatial features and BiGRU in capturing temporal dynamics, thereby significantly improving forecasting accuracy compared to traditional methods. The proposed method demonstrated a high coefficient of determination (<i>R</i>² &gt; 0.91) across all four seasons, highlighting its superior forecasting performance. Compared to CNN-GRU, the proposed CNN-BiGRU model achieves higher accuracy of 4.5%. The main innovation of this paper is the systematic division of regional DPV plants cluster and the selection of representative plants. This approach offers an efficient and dependable technical solution for the power forecasting of DPV plants, advancing the field with its innovative methodology.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 9","pages":"4314-4329"},"PeriodicalIF":3.4,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://scijournals.onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70171","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145037972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental Simulation Investigation on Mechanism and Criterion of Impact-Induced Rockburst in Gaoloushan Deep Tunnel","authors":"Chao Ren,&nbsp;Xiaoming Sun,&nbsp;Manchao He,&nbsp;DongQiao liu,&nbsp;JinKun Yang,&nbsp;Kunbo Zhang","doi":"10.1002/ese3.70160","DOIUrl":"https://doi.org/10.1002/ese3.70160","url":null,"abstract":"<p>During the excavation of a deep-buried tunnel by the drilling and blasting method, the dynamic stress of blasting may cause the disorderly release of high energy in the rock mass during the blasting process of deep high-energy rock. Blasting vibration is one of the main factors inducing dynamic disasters (such as rockbursts) in the surrounding rock. An impact-induced rockburst occurred in the Gaoloushan deep-buried tunnel. In this paper, the simulation experiment of this type of rockburst was carried out by using the impact rockburst experimental system. The two rockbursts that occurred during the experiment formed “V” type pits, which were consistent with the on-site rockburst situation; therefore, it proved the rationality of this experiment. The results showed that the total displacement characteristics of impact-induced rockbursts had obvious suddenness, and the intensity of impact-induced rockbursts showed characteristics from weak to strong. In addition, it was also found that the rupture parameters of the rock mass in rockbursts showed a compound exponential growth relationship with time. As a typical mode of instantaneous rockburst failure, the mechanism of impact-induced rockburst could be regarded as the result of the combined action of shear crack and tension-shear crack, which played a dominant role, reflecting the characteristics of sudden fracture development. The generation of impact-induced rockbursts occurred when the peak value of static load and disturbance stress wave reached a certain value. On this basis, the rockburst criterion was proposed.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 8","pages":"4252-4266"},"PeriodicalIF":3.4,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://scijournals.onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70160","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144811363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance-Emission Optimization of a Diesel Engine Blended With Biodiesel and Pentanol","authors":"Geetesh Goga,&nbsp;Deepam Goyal,&nbsp;Tarun Goyal,&nbsp;Krupakaran Radhakrishnan Lawrence,&nbsp;P. V. Elumalai,&nbsp;Sunil Kumar Mahla,&nbsp;Anil Singh Yadav,&nbsp;Subhendu Chakroborty,&nbsp;Nasim Hasan","doi":"10.1002/ese3.70164","DOIUrl":"https://doi.org/10.1002/ese3.70164","url":null,"abstract":"<p>The quest for novel alternative fuel blends is fueled by the urgent need to address the inadequacy of fossil fuels and the escalating environmental concerns. While previous studies have primarily explored base fuel and minimally diluted alcohol content since the late 20th century, a significant research gap exists in the comparative analysis of biodiesel and alcohol blends. In this article, an attempt has been made to bridge that gap by investigating fuel mixtures containing varying proportions (5%–20%) of Jatropha oil-based biodiesel (JOBD) and Pentanol, evaluated across different Engine load (EL), JOBD, and Pentanol concentrations. Experimentation was conducted on a 4-stroke, single cylinder, direct injection vertical engine. A comprehensive experimental analysis was performed using the Taguchi approach and ANOVA by MINITAB17®, to assess key engine performance and emission characteristics—namely hydrocarbons (HC) emissions, brake-specific fuel consumption (BSFC), carbon monoxide (CO) emissions, and brake thermal efficiency (BTE). The higher values of raw data and S/N ratio for BTE were observed in the order of A3B1C1 and lower raw data and higher S/N values were achieved for BSFC, CO and HC as A3B1C1, A3B3C3 and A3B3C3 respectively. The higher values of S/N ratios for higher raw data values of BTE and lower values of BSFC, CO and HC were found to be in complete agreement to each other. The findings contribute the potential of biodiesel-pentanol blends as sustainable alternatives, promoting environmentally friendly solutions for the automotive industry.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 8","pages":"4190-4198"},"PeriodicalIF":3.4,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://scijournals.onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70164","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144811308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}