Energy Conversion and Management最新文献_第9页

Dairy-farm micro-energy system optimal planning and operation: Driven by dynamic coordination approach to material output and energy demand 奶牛场微能源系统优化规划与运行：以物料产出和能源需求为驱动的动态协调方法

IF 9.9 1区工程技术

Energy Conversion and Management Pub Date : 2025-03-26 DOI: 10.1016/j.enconman.2025.119728

Chen Wang , Rui Liang , Kaize Liang , Honghang Zhang , Le Zhang , Hongxu Huang , Zehua Tang , Chaoxian Lv

{"title":"Dairy-farm micro-energy system optimal planning and operation: Driven by dynamic coordination approach to material output and energy demand","authors":"Chen Wang , Rui Liang , Kaize Liang , Honghang Zhang , Le Zhang , Hongxu Huang , Zehua Tang , Chaoxian Lv","doi":"10.1016/j.enconman.2025.119728","DOIUrl":"10.1016/j.enconman.2025.119728","url":null,"abstract":"<div><div>With the modernization progress of large-scale dairy farms, the demands for eco-friendly operation are becoming increasingly stringent. Some existing farms and those in the early development stages, characterized by underutilized manure, imbalances in electricity supply and demand, and potentially insufficiently considered scalability, are particularly sensitive to these requirements. To address these issues, this paper presents a model characterizing the dynamic coordinated material and energy by analyzing the various cattle growth stages influence, based on specific energy-material requirements in dairy farm. Furthermore, the energy-material cycle of farms is studied to reveal its impacts on the performance of dairy farm micro-energy system(DFMES). Integrating these findings, an optimized planning and operational method for DFMES is proposed, aiming to enhance the initial setup and meet long-term efficiency goals. Case studies from dairy farm in East and Northeast China validate the method, highlighting its effective support for low-carbon operations and efficient energy conversion in dairy farms.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119728"},"PeriodicalIF":9.9,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhanced Carnot battery for high-efficiency energy storage: Feasibility analysis 增强型卡诺电池用于高效储能：可行性分析

IF 9.9 1区工程技术

Energy Conversion and Management Pub Date : 2025-03-26 DOI: 10.1016/j.enconman.2025.119754

Ce Zhang , Minxia Li , Chaobin Dang , Xun Chen , Xiuming Li , Zongwei Han

{"title":"Enhanced Carnot battery for high-efficiency energy storage: Feasibility analysis","authors":"Ce Zhang , Minxia Li , Chaobin Dang , Xun Chen , Xiuming Li , Zongwei Han","doi":"10.1016/j.enconman.2025.119754","DOIUrl":"10.1016/j.enconman.2025.119754","url":null,"abstract":"<div><div>The widespread application of renewable energy generation technologies poses a serious challenge to grid stability. It is essential to develop advanced energy storage technologies. The Carnot battery has advantages such as low construction cost and high installation flexibility. However, the low round-trip efficiency of conventional Carnot battery limits its widespread application. In this study, the enhanced Carnot battery is constructed to achieve high-efficiency energy storage, and the performance of various enhanced technologies is discussed. Taking three cities in China as the application sites, the feasibility of the enhanced Carnot battery is analyzed by selecting industrial low-grade waste heat recovery as the application scenario. The results show that the overall performance is optimal when the heat pump module applies the vapor injection technology, and the organic Rankine cycle module applies the dual-pressure evaporation technology. Compared with conventional Carnot battery, the payback period of the enhanced Carnot battery can be shortened by 76.8%, and the levelized cost of storage can be reduced by 26.7%.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119754"},"PeriodicalIF":9.9,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Performance analysis and optimization of Tesla turbine based on comprehensive operational and structural parameters 基于综合运行和结构参数的特斯拉涡轮性能分析与优化

IF 9.9 1区工程技术

Energy Conversion and Management Pub Date : 2025-03-25 DOI: 10.1016/j.enconman.2025.119757

Yang Zhao , Shiyang Teng , Dou An , Huan Xi

{"title":"Performance analysis and optimization of Tesla turbine based on comprehensive operational and structural parameters","authors":"Yang Zhao , Shiyang Teng , Dou An , Huan Xi","doi":"10.1016/j.enconman.2025.119757","DOIUrl":"10.1016/j.enconman.2025.119757","url":null,"abstract":"<div><div>The Tesla turbine shows great potential in small-scale energy utilization systems. Consequently, it is crucial to investigate methods for enhancing the Tesla turbine’s output performance. In response to the current situation of incomplete performance optimization process of Tesla turbine, a comprehensive analysis of its operational and structural parameters is conducted. To identify the optimal parameters and structure of the Tesla turbine in operation, a three-dimensional simulation model is developed, and the computational fluid dynamics method is employed for analysis. Additionally, a prototype of Tesla turbine is designed and manufactured, and experiments are conducted using compressed air to drive the Tesla turbine, thereby validating the reliability of the simulation model. In the study, output power and isentropic efficiency are regarded as optimization objective parameters, while key operational parameters including rotational speed, inlet pressure, and mass flow rate are also considered. The fundamental operating characteristics of the Tesla turbine are initially examined, followed by sequential analyses of the structural parameters including nozzle height, nozzle width, disc spacing, disc thickness, disc diameter, and the number of discs. Through the comprehensive optimization process, the Tesla turbine achieves significant performance improvements, resulting in an output power of 787 W and an efficiency of 32.1 %.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119757"},"PeriodicalIF":9.9,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143703914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Aging-aware real-time multi-layer co-optimization approach for hybrid vehicles: across configuration, parameters, and control 混合动力汽车的实时多层协同优化方法：跨配置、参数和控制

IF 9.9 1区工程技术

Energy Conversion and Management Pub Date : 2025-03-24 DOI: 10.1016/j.enconman.2025.119748

Yunge Zou , Yalian Yang , Yuxin Zhang , Xiaolin Tang

{"title":"Aging-aware real-time multi-layer co-optimization approach for hybrid vehicles: across configuration, parameters, and control","authors":"Yunge Zou , Yalian Yang , Yuxin Zhang , Xiaolin Tang","doi":"10.1016/j.enconman.2025.119748","DOIUrl":"10.1016/j.enconman.2025.119748","url":null,"abstract":"<div><div>The powertrain configuration, parameters, and control of hybrid vehicles are intertwined. All of these factors have a significant impact on acceleration, fuel economy, and battery degradation. However, research on the impact of the multi-layer co-optimization of the powertrain physical configuration and control on battery life has been neglected. Therefore, to fill this gap, an innovative aging-aware real-time multi-layer co-optimization method is proposed in this study. In the topology layer, a novel and improved multi-mode multi-gear configuration is proposed, and the performance differences and the intrinsic mechanism of different powertrain types are analyzed quantitatively and qualitatively. In the control layer, an advanced aging-aware fast real-time control strategy (AFRCS) is proposed. In the AFRCS, the offline optimization layer works in combination with Pareto optimization, battery life aging optimization (BLAO), and parallel computation to speed up the computational efficiency. The online mode coordination layer is used for real-time control, which improves the computational efficiency by approximately 20,000 times, and the battery life optimization is in the range of 10.22 %–12.9 %. During real-world driving cycles, the proposed configuration improves the acceleration and the battery life by an average of 50 % and 22.67 %, respectively, compared to a Toyota Prius, and it improves fuel saving by 8.82 % compared to a Honda Accord. Finally, the proposed AFRCS is verified with a hardware-in-the-loop (HIL) experiment. This study provides guidance for the selection, optimization, and real-time control of next-generation electrified transmissions.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119748"},"PeriodicalIF":9.9,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143678188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhanced energy conversion in a concentrated photovoltaic/thermal system using phase change material as a spectral beam filter 利用相变材料作为光谱光束滤波器增强聚光光伏/热系统的能量转换

IF 9.9 1区工程技术

Energy Conversion and Management Pub Date : 2025-03-22 DOI: 10.1016/j.enconman.2025.119751

Yue Yang , Mostafa M. Abd El-Samie , Ahmed M.I. Abutalib , Mohamed I. Hassan Ali , Lei Zhou

引用次数: 0

Integration of direct air capture with Allam cycle: Innovative pathway in negative emission technologies 直接空气捕获与Allam循环的集成：负排放技术的创新途径

IF 9.9 1区工程技术

Energy Conversion and Management Pub Date : 2025-03-22 DOI: 10.1016/j.enconman.2025.119746

Alireza Ghorbani , Ayat Gharehghani , Jabraeil Ahbabi Saray , Amin Mahmoudzadeh Andwari , Tohid N. Borhani

{"title":"Integration of direct air capture with Allam cycle: Innovative pathway in negative emission technologies","authors":"Alireza Ghorbani , Ayat Gharehghani , Jabraeil Ahbabi Saray , Amin Mahmoudzadeh Andwari , Tohid N. Borhani","doi":"10.1016/j.enconman.2025.119746","DOIUrl":"10.1016/j.enconman.2025.119746","url":null,"abstract":"<div><div>The advancement of negative emission technologies (NETs) is crucial for addressing climate change by reducing atmospheric carbon dioxide levels. This study presents a comprehensive evaluation of a High Temperature Direct Air Capture (HT-DAC) system integrated with a supercritical CO<sub>2</sub> (S-CO<sub>2</sub>) cycle, representing a significant advancement in carbon capture, energy optimization, and NET systems. Given to significant energy demands of HT-DAC, the primary objective of this research is to address the process’s energy intensity by focusing on the development of a more efficient power island. Specifically, this study investigates the energy demands of the Air Separation Unit (ASU) to minimize energy consumption and improve the overall efficiency of the Allam cycle when coupled with the ASU. Additionally, the study examines the thermal integration of the system using pinch analysis to assess the impact of this innovative power island on energy efficiency. Key results indicate that the proposed system is capable of capturing 0.99 million tons of CO<sub>2</sub> per year directly from the air, achieving a capture efficiency of 75 %. The specific energy requirement for the process is initially 3.19 kWh per kg of captured CO<sub>2</sub>, which is reduced to 2.21 kWh/kgCO<sub>2</sub> following process optimization and heat integration. Through this optimization, hot and cold utility demands are reduced by 69.7 % and 36.9 %, respectively, while 110.1 MW of heat is recovered through the design of heat exchangers network, resulting in an 9.66 % reduction in overall energy demand compared to the base case. Furthermore, the integration of captured and regenerated CO<sub>2</sub> (135.1 tons per hour with a purity of 98.1 mol%) offers substantial potential for synthetic fuel production and underground storage.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119746"},"PeriodicalIF":9.9,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143678194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Advanced power curve modeling for wind turbines: A multivariable approach with SGBRT and grey wolf optimization 风力涡轮机的高级功率曲线建模：基于SGBRT和灰狼优化的多变量方法

IF 9.9 1区工程技术

Energy Conversion and Management Pub Date : 2025-03-20 DOI: 10.1016/j.enconman.2025.119680

Wenliang Yin , Mengqian Jia , Lin Liu , Ming Li , Youguang Guo , Gang Lei , Jian Guo Zhu

{"title":"Advanced power curve modeling for wind turbines: A multivariable approach with SGBRT and grey wolf optimization","authors":"Wenliang Yin , Mengqian Jia , Lin Liu , Ming Li , Youguang Guo , Gang Lei , Jian Guo Zhu","doi":"10.1016/j.enconman.2025.119680","DOIUrl":"10.1016/j.enconman.2025.119680","url":null,"abstract":"<div><div>Accurate power curve modeling is crucial for improving the operational efficiency and performance of grid-connected wind turbines (WTs). To enhance the modeling quality and eliminate input variable interactions, this paper proposes a novel multivariable power curve prediction approach that integrates advanced machine learning techniques, namely stochastic gradient boosting regression tree (SGBRT) and grey wolf optimization (GWO), with innovative data preprocessing and feature selection methods. The specific works and novelties are as follows. 1) The raw data is cleaned in a two-dimensional Copula space, using wind wheel speed as an auxiliary criterion and a probabilistic description, to handle data uncertainties and nonlinear dependencies. 2) A partial mutual information (PMI) method is presented for data characteristics analysis, based on which eight significant parameters are selected as modeling input variables, reducing computational complexity while enhancing prediction accuracy. 3) A power curve prediction model considering multiple input variables is established using SGBRT, and its hyperparameters are optimized through a GWO algorithm, guided by a fitness function combining the indicators of root mean square error (RMSE), mean absolute error (MAE) and R squared (R<sup>2</sup>). 4) Validated with real SCADA data from WTs in service, the proposed model achieves superior performance, with the smallest standardized residuals (6.56 %), RMSE (around 27 kW), MAE (19.27 kW), and superior average R<sup>2</sup> (98.61 %) for all speed regions. Comparative studies indicate that the proposed approach outperforms existing methods, offering significant improvements in accuracy, efficiency, robustness and adaptability for WT power curve modeling.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119680"},"PeriodicalIF":9.9,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143681935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Selection of oxygen carrier for chemical looping combustion of natural gas and syngas fuels – A machine learning approach 天然气和合成气燃料化学环燃烧氧载体的选择-机器学习方法

IF 9.9 1区工程技术

Energy Conversion and Management Pub Date : 2025-03-19 DOI: 10.1016/j.enconman.2025.119745

Bilal Ahmed , Atta Ullah , Rehan Zubair Khalid , Muhammad Shahid , Liang Zeng , Xubin Zhang , Muhammad Zaman

{"title":"Selection of oxygen carrier for chemical looping combustion of natural gas and syngas fuels – A machine learning approach","authors":"Bilal Ahmed , Atta Ullah , Rehan Zubair Khalid , Muhammad Shahid , Liang Zeng , Xubin Zhang , Muhammad Zaman","doi":"10.1016/j.enconman.2025.119745","DOIUrl":"10.1016/j.enconman.2025.119745","url":null,"abstract":"<div><div>This research focuses on selecting suitable oxygen carriers (OCs) using data driven modeling in order to prevent operational issues such as agglomeration, attrition, and sintering, which are challenges in chemical looping combustion (CLC) operations. The complexity of choosing effective OCs arises from the diverse compositions of natural ores and synthetic compounds used in the process. In this work, eight machine learning techniques were employed to predict the performance of oxygen carriers using a parameter known as gas yield under different operating temperatures for gaseous fuels primarily natural gas and syngas. A comprehensive dataset including experimental data from the literature for various carriers were used to train multiple machine learning models. The models predicted gas yield with knowledge of reactor operating temperature, fuel composition, and the elemental makeup of oxygen carriers. Cross-validation and bootstrap techniques were employed to ensure model robustness and minimize prediction error. The results demonstrate that the GBR and CatBoost have been the best-performing model achieving a high coefficient of determination 0.820 and 0.822 value respectively and same low mean error value of 0.015. It was observed that Fe and Mn based mixed oxide performed as good OCs with their reactivity increasing with Fe to Mn ratio. This study highlights the potential of machine learning in optimizing oxygen carrier performance and accelerating advancements in CLC technology.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119745"},"PeriodicalIF":9.9,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143681936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improving energy efficiency through forecast-driven control in hybrid heat pumps 通过混合热泵预测驱动控制提高能源效率

IF 9.9 1区工程技术

Energy Conversion and Management Pub Date : 2025-03-18 DOI: 10.1016/j.enconman.2025.119737

Marco Bizzarri, Paolo Conti, Eva Schito, Daniele Testi

{"title":"Improving energy efficiency through forecast-driven control in hybrid heat pumps","authors":"Marco Bizzarri, Paolo Conti, Eva Schito, Daniele Testi","doi":"10.1016/j.enconman.2025.119737","DOIUrl":"10.1016/j.enconman.2025.119737","url":null,"abstract":"<div><div>Hybrid heat pumps (HHPs) are increasingly used for residential space heating, especially where stand-alone heat pumps (HPs) are inefficient. Typically, HHPs and HVAC systems controls rely on simple rule-based approaches. Smart controllers that employ building-system modeling can improve energy efficiency by determining which heat generation unit to activate and setting the supply water temperature according to actual building heat demand. Data-driven models are particularly suitable for widespread use, as they can self-learn building thermal characteristics and optimize system operation. In this study, we employed an autoregressive model to forecast short-term hourly energy demand and the corresponding water supply temperature to the heat emitters. These predictions helped to estimate generators performance and select the optimal unit to minimize energy costs while meeting heat demand. The predictive control procedure was tested on various case studies, both simulated and field-monitored, representative of the Italian housing stock. Results showed that in non-renovated buildings with radiators, the predictive control strategy can reduce operating costs by up to 20% compared to current commercial HHP controls. This improvement was mainly due to better supply temperature set-point evaluation and increased HP use. Similar benefits were observed in environmental and primary energy metrics. Conversely, in newer, well-insulated houses with low-temperature emitters, current controls are already efficient. Finally, we showed that the proposed control strategy deviates less than 3% from an ideal prediction and control in realistic on-field monitored test cases, representing a valuable trade-off between achievable benefits, data requirements, computational efforts, and implementation feasibility in real industrial HHP devices.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119737"},"PeriodicalIF":9.9,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143643348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Toward a green steel production powered by a hybrid renewable energy system: Techno-economic and environmental assessment 迈向以混合可再生能源系统为动力的绿色钢铁生产：技术经济和环境评估

IF 9.9 1区工程技术

Energy Conversion and Management Pub Date : 2025-03-18 DOI: 10.1016/j.enconman.2025.119716

Pouriya Nasseriyan , Saeed Jafari , Hossein Khajehpour , Saeed Edalati

{"title":"Toward a green steel production powered by a hybrid renewable energy system: Techno-economic and environmental assessment","authors":"Pouriya Nasseriyan , Saeed Jafari , Hossein Khajehpour , Saeed Edalati","doi":"10.1016/j.enconman.2025.119716","DOIUrl":"10.1016/j.enconman.2025.119716","url":null,"abstract":"<div><div>The steel supply chain consists of several stages, with the most energy-demanding phase being the direct reduction iron process. Syngas, used in this stage, is typically produced from fossil fuels like natural gas, which leads to substantial greenhouse gas emissions. In this study, the direct reduction iron production stage was replaced with a proposed process aimed at reducing both energy consumption and emissions while maintaining economic viability. The proposed process (Solid Oxide Electrolyzer − Direct Reduction Iron) was introduced as a potential solution and was compared technically, environmentally, and economically with the conventional (Steam Methane Reforming − Direct Reduction Iron) process. In the proposed process, solid oxide electrolysis cells are used to produce syngas, with the required electrical and thermal energy supplied from renewable sources, solar power and biogas. The results were validated after modeling the process and performing an economic analysis. The comparison between key performance indicators of the two processes highlighted three main findings: first, energy consumption per unit of production decreased by 17 %, from 3.06 MWh/ton<sub>DRI</sub> to 2.53 MWh/ton<sub>DRI</sub>, while energy efficiency improved by 33 %, rising from 52 % to 85 %. Second, the proposed process resulted in near-zero emissions (Green Steel) production due to the use of renewable energy sources. Third, from an economic perspective, considering the carbon emission penalty, the levelized cost of production for the conventional process was 245 $/ton<sub>DRI</sub>, making it comparable to the 249 $/ton<sub>DRI</sub> cost for the proposed process.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"332 ","pages":"Article 119716"},"PeriodicalIF":9.9,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143643349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0