Applied Energy最新文献_第7页

Deep learning-based distributionally robust joint chance constrained distribution networks PV hosting capacity assessment 基于深度学习的分布式鲁棒联合机会约束配电网光伏托管容量评估

IF 10.1 1区工程技术

Applied Energy Pub Date : 2025-05-22 DOI: 10.1016/j.apenergy.2025.126130

Zihui Wang , Yanbing Jia , Xiaoqing Han , Peng Wang , Jiajie Liu

{"title":"Deep learning-based distributionally robust joint chance constrained distribution networks PV hosting capacity assessment","authors":"Zihui Wang , Yanbing Jia , Xiaoqing Han , Peng Wang , Jiajie Liu","doi":"10.1016/j.apenergy.2025.126130","DOIUrl":"10.1016/j.apenergy.2025.126130","url":null,"abstract":"<div><div>As distributed photovoltaic (PV) penetration in distribution networks (DNs) is increasing, it is essential to assess the PV hosting capacity (PVHC) to ensure the safe operation of DNs. This paper proposes a data-driven distributionally robust joint chance constrained (DRJCC) distribution networks PVHC assessment framework. Firstly, the spatiotemporal attention, projection, supervision, and Transformer architecture-based generative adversarial blocks are introduced to develop an augmented time series generative adversarial network (ATS-GAN), which, by integrating both supervised and unsupervised learning during the joint training process, better captures the spatiotemporal characteristics of PV and load power. Subsequently, leveraging the ATS-GAN, a Wasserstein metrics-based ambiguity set of PV and load power probability distributions is constructed, centered on the distributions induced by the generator neural network. Secondly, the DRJCC PVHC assessment model is proposed. A combination of the Bonferroni inequality and conditional value-at-risk approximation is adopted to transform the multivariate DRJCC model into a tractable conic formulation for efficient computation. Numerical results demonstrate that the proposed method effectively captures the spatiotemporal characteristics and uncertainties of multivariate distributions under multiple constraints, significantly reducing the conservatism typically associated with distributionally robust individual chance constraints.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"394 ","pages":"Article 126130"},"PeriodicalIF":10.1,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117063","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

Perceived complexity and effectiveness of dynamic electricity rate designs for smart markets 智能市场动态电价设计的感知复杂性和有效性

IF 10.1 1区工程技术

Applied Energy Pub Date : 2025-05-22 DOI: 10.1016/j.apenergy.2025.126042

Philipp Staudt , David Dann

引用次数: 0

Improving cross-temporal forecasts reconciliation accuracy and utility in energy market 提高能源市场跨时间预测对账准确性和实用性

IF 10.1 1区工程技术

Applied Energy Pub Date : 2025-05-22 DOI: 10.1016/j.apenergy.2025.126053

Mahdi Abolghasemi , Daniele Girolimetto , Tommaso Di Fonzo

{"title":"Improving cross-temporal forecasts reconciliation accuracy and utility in energy market","authors":"Mahdi Abolghasemi , Daniele Girolimetto , Tommaso Di Fonzo","doi":"10.1016/j.apenergy.2025.126053","DOIUrl":"10.1016/j.apenergy.2025.126053","url":null,"abstract":"<div><div>Wind power forecasting is essential for managing daily operations at wind farms and enabling market operators to manage power uncertainty effectively in demand planning. Traditional reconciliation methods rely on in-sample errors for forecast reconciliation, which may not generalize well to future performance. Additionally, conventional aggregation structures do not always align with the decision-making requirements in practice, and evaluation metrics often neglect the economic impact of forecast errors. To address these challenges, this paper explores advanced cross-temporal forecasting models and their potential to enhance forecasting accuracy and decisions. First, we propose a novel approach that leverages validation errors, rather than traditional in-sample errors, for covariance matrix estimation and forecast reconciliation. Second, we introduce decision-based aggregation levels for forecasting and reconciliation, where certain horizons are tailored to the specific decisions required in operational settings. Third, we assess model performance not only by traditional accuracy metrics but also by their ability to reduce decision costs, such as penalties in ancillary services. Our results show that using validation errors improves the accuracy by more than 7 % across different temporal levels. We also demonstrate that statistical-based hierarchies tend to adopt less conservative forecasts and reduce revenue losses. On the other hand, decision-based reconciliation offers a more balanced compromise between accuracy and decision cost, while saving computational time by 2 %–3 % for simpler models and up to 93 % for more advanced models, making them attractive for practical use.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"394 ","pages":"Article 126053"},"PeriodicalIF":10.1,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144107927","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

Modelling and economic assessment of organic Rankine cycle integration into an inter-plant heat exchanger network 有机朗肯循环集成到厂间热交换器网络的建模和经济评估

IF 10.1 1区工程技术

Applied Energy Pub Date : 2025-05-22 DOI: 10.1016/j.apenergy.2025.126126

La Verne Ramir D.T. Certeza , Aloisius Rabata Purnama , Aniq Ahsan , Jonathan S.C. Low , Wen F. Lu

{"title":"Modelling and economic assessment of organic Rankine cycle integration into an inter-plant heat exchanger network","authors":"La Verne Ramir D.T. Certeza , Aloisius Rabata Purnama , Aniq Ahsan , Jonathan S.C. Low , Wen F. Lu","doi":"10.1016/j.apenergy.2025.126126","DOIUrl":"10.1016/j.apenergy.2025.126126","url":null,"abstract":"<div><div>Establishing energy-based industrial symbiosis networks (EISNs) through inter-plant heat integration is a collaborative energy efficiency initiative to reduce industrial energy consumption. Its benefits can be improved through organic Rankine cycle (ORC) integration into an inter-plant heat exchanger network (HEN) to generate electricity. In this study, a novel nonlinear programming (NLP) model is formulated for inter-plant HEN-ORC integration optimization. It improves the computational performance of conventional mixed-integer nonlinear programming (MINLP) models and the accuracy of total EISN cost computation by using chemical engineering plant cost indices (CEPCIs) to adjust capital cost values to a common time. Furthermore, this study also proposes an EISN economic viability assessment methodology based on Shapley value computation and based on social welfare, Rawlsian welfare, and Nash allocation schemes to determine the new individual cost of each plant if it joins an EISN. The model and methodology have been applied to two case studies. Results reveal that Nash allocation can minimize the total EISN cost while maximizing the savings attained by each plant, thereby making it the superior cost allocation method among the four. Furthermore, results show that inter-plant HEN-ORC integration can increase an EISN's economic viability. However, this depends on whether there is a significant difference between the cold and hot utility prices. Lastly, results indicate that limiting the number of superstructure stages to just one can result in a more realistically implementable EISN configuration. Overall, the proposed model and methodology have been demonstrated to yield pragmatic insights on the cost-effectiveness of inter-plant HEN-ORC integration.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"394 ","pages":"Article 126126"},"PeriodicalIF":10.1,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144107924","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

A record fast ACP self-heating for lithium-ion batteries without capacity loss based on electrochemical-thermal coupling model 基于电化学-热耦合模型的锂离子电池无容量损失快速ACP自热

IF 10.1 1区工程技术

Applied Energy Pub Date : 2025-05-21 DOI: 10.1016/j.apenergy.2025.126153

Zixian Zhuang , Sijie Gu , Weiling Luan , Jun Li , Haofeng Chen

{"title":"A record fast ACP self-heating for lithium-ion batteries without capacity loss based on electrochemical-thermal coupling model","authors":"Zixian Zhuang , Sijie Gu , Weiling Luan , Jun Li , Haofeng Chen","doi":"10.1016/j.apenergy.2025.126153","DOIUrl":"10.1016/j.apenergy.2025.126153","url":null,"abstract":"<div><div>Lithium-ion batteries exhibit a notable decline in performance at low temperatures, including capacity reduction and impedance growth. Therefore, adopting an alternating current pulse (ACP) self-heating is a viable approach for improving battery performance at low temperatures. However, improper selection of ACP amplitude and frequency may induce capacity loss during heating. To overcome this challenge, a novel electrochemical-thermal coupling (ETC) model has been constructed by simultaneously considering the double layer and lithium plating, and combining model accelerated computation. The model can efficiently and accurately calculate capacity loss and temperature rise of batteries under high-frequency (> 10 Hz) currents. The effects of ACP self-heating on the batteries are analyzed using the model, revealing the mechanism by which the combined effects of ACP frequency and amplitude contribute to lithium plating during self-heating. Furthermore, a Bayesian optimization framework is established by combining the model to effectively identify the optimal ACP parameters at different temperatures, accompanied by the proposal of a self-heating strategy that adapts to temperature variations. The self-heating strategy can enhance the temperature rise rate while eliminating capacity loss due to lithium plating. The experimental validation illustrates that batteries can be rapidly heated from −20 °C to 11.1 °C within five minutes via the optimized strategy without capacity loss after 90 heating cycles. The proposed self-heating strategy achieves a record fast battery temperature rise compared to other studies.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"393 ","pages":"Article 126153"},"PeriodicalIF":10.1,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144106128","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

A multi-stage review framework for AI-driven predictive maintenance and fault diagnosis in photovoltaic systems 光伏系统人工智能预测性维护与故障诊断的多阶段评审框架

IF 10.1 1区工程技术

Applied Energy Pub Date : 2025-05-21 DOI: 10.1016/j.apenergy.2025.126108

Ali Hamza , Zunaib Ali , Sandra Dudley , Komal Saleem , Muhammad Uneeb , Nicholas Christofides

{"title":"A multi-stage review framework for AI-driven predictive maintenance and fault diagnosis in photovoltaic systems","authors":"Ali Hamza , Zunaib Ali , Sandra Dudley , Komal Saleem , Muhammad Uneeb , Nicholas Christofides","doi":"10.1016/j.apenergy.2025.126108","DOIUrl":"10.1016/j.apenergy.2025.126108","url":null,"abstract":"<div><div>The photovoltaic (PV) sector encounters challenges such as high initial costs, reliance on weather, susceptibility to faults, irregularities in the grid, and degradation of components. Predictive maintenance (PdM) aims to proactively identify issues, thereby enhancing reliability and efficiency but may lack specific fault details without additional diagnostic efforts. This research presents an advanced PdM and fault diagnosis framework that integrates fault pattern analysis, severity assessments, and critical fault predictions. It aims to improve the functionality of PV systems, minimize downtime, and enhance reliability by identifying and analyzing specific fault patterns. Consequently, our article provides a critical review of current Artificial Intelligence (AI) methodologies for PdM and fault diagnosis in PV systems. Moreover, this study highlights the significance of data standardization and offers recommendations on how PdM, when combined with fault diagnosis, can utilize various data sources to anticipate faults in advance, assess their severity, and optimize system performance and maintenance activities. To the best of the authors’ knowledge, no such review study exists.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"393 ","pages":"Article 126108"},"PeriodicalIF":10.1,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144098808","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

Dynamic reconfiguration method and performance optimization of 3D curved photovoltaic modules under non-uniform illumination conditions based on improved simulated annealing algorithm (ISAA) 基于改进模拟退火算法（ISAA）的非均匀光照条件下三维弯曲光伏组件动态重构方法及性能优化

IF 10.1 1区工程技术

Applied Energy Pub Date : 2025-05-21 DOI: 10.1016/j.apenergy.2025.126162

Jingyong Cai , Jianxiao Fang , Mengyao Liang , Zhengrong Shi , Lijie Xu , Tao Zhang , Wenzhu Huang

{"title":"Dynamic reconfiguration method and performance optimization of 3D curved photovoltaic modules under non-uniform illumination conditions based on improved simulated annealing algorithm (ISAA)","authors":"Jingyong Cai , Jianxiao Fang , Mengyao Liang , Zhengrong Shi , Lijie Xu , Tao Zhang , Wenzhu Huang","doi":"10.1016/j.apenergy.2025.126162","DOIUrl":"10.1016/j.apenergy.2025.126162","url":null,"abstract":"<div><div>Three-dimensional curved photovoltaic (PV) modules offer flexible integration on irregular surfaces such as building facades, vehicles, and wearable devices, but it faces severe power losses from non-uniform irradiance and current mismatch. This study develops an Improved Simulated Annealing Algorithm (ISAA) for real-time electrical topology reconfiguration of a 6 × 6 curved PV module. The ISAA reconfiguration method embeds facet-level irradiance feedback into the annealing search, integrates a global-best current-mismatch index into its acceptance criterion to overcome local optima, and executes parallel, parameter-free cell-swap trials for rapid convergence. This paper compares the performance of ISAA, TCT, and SDS reconfiguration methods under various illumination distribution conditions and evaluates the adaptability under dynamic irradiance environments. Results show ISAA maintains a current mismatch index below one in all cases, smooths I–V/P–V characteristics. In addition, ISAA effectively reduces the cumulative effect of current mismatch and maintains relatively stable performance improvement under both sunny and cloudy weather conditions. ISAA reduces daily mismatch losses by up to 52 %, boosts daily energy yield by 42 % ∼ 44 % compared to TCT and SDS, and enhances fill factor and operational stability under rapidly changing irradiance. Overall, ISAA handles complex irradiance, dynamic shading, and weather fluctuations, enabling optimized 3D PV performance.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"393 ","pages":"Article 126162"},"PeriodicalIF":10.1,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144098809","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

A review on thermal management strategy for liquid-cooling proton exchange membrane fuel cells: Temperature regulation and cold start 液冷质子交换膜燃料电池热管理策略综述：温度调节与冷启动

IF 10.1 1区工程技术

Applied Energy Pub Date : 2025-05-21 DOI: 10.1016/j.apenergy.2025.126142

Hongye Su , Haisong Xu , Lei Wang , Zhiyang Liu , Lei Xie

{"title":"A review on thermal management strategy for liquid-cooling proton exchange membrane fuel cells: Temperature regulation and cold start","authors":"Hongye Su , Haisong Xu , Lei Wang , Zhiyang Liu , Lei Xie","doi":"10.1016/j.apenergy.2025.126142","DOIUrl":"10.1016/j.apenergy.2025.126142","url":null,"abstract":"<div><div>Effective thermal management strategies are crucial for optimizing the performance and durability of proton exchange membrane fuel cells (PEMFCs). This paper presents a comprehensive review of thermal management strategies for liquid-cooling PEMFCs, with a particular emphasis on temperature regulation and cold start operations. Firstly, the fundamental thermal characteristics of PEMFCs under both above-freezing and sub-freezing temperatures are introduced, followed by an overview of both offline and online identification methods for thermal system models. Subsequently, considering the intrinsic nonlinearity and coupling characteristics of PEMFC thermal systems, along with the presence of diverse internal and external disturbances, various temperature control strategies are reviewed and classified from four perspectives: (1) exploring the relationship between optimal operational temperature and overall performance of PEMFCs, (2) managing the coupling effects in multiple input multiple output cooling systems, (3) enhancing system robustness against disturbances and uncertainties, and (4) reducing the parasitic power consumption of the cooling system. Strategies can be classified into categories such as model-based, data-driven, and adaptive types, based on their underlying mechanisms. From the perspective of cold start strategies, the review explores the efficient and rapid start-up techniques that ensure temperature uniformity and voltage consistency within the fuel cell stack. The importance of shutdown purging for water removal is highlighted as a critical measure to prevent ice formation and facilitate subsequent start-ups. In conclusion, current research status on PEMFC thermal management strategies is summarized. Furthermore, future directions for advancing thermal management systems in PEMFCs are provided.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"393 ","pages":"Article 126142"},"PeriodicalIF":10.1,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144099378","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

A review on Lithium-ion battery failure risks and mitigation indices for electric vehicle applications 电动汽车锂离子电池失效风险及缓解指标研究进展

IF 10.1 1区工程技术

Applied Energy Pub Date : 2025-05-21 DOI: 10.1016/j.apenergy.2025.126139

K. Kalaikkanal, N. Gobinath

{"title":"A review on Lithium-ion battery failure risks and mitigation indices for electric vehicle applications","authors":"K. Kalaikkanal, N. Gobinath","doi":"10.1016/j.apenergy.2025.126139","DOIUrl":"10.1016/j.apenergy.2025.126139","url":null,"abstract":"<div><div>Electric vehicles (EVs) are leading the way towards a more sustainable and eco-friendly future, helping the transportation sector moving closer to the carbon neutrality. Batteries hold a pivotal role in EVs due to their substantial influence on the vehicles' cost, performance, and safety. Lithium-ion batteries (LIBs), commonly used in EVs, are valued for their relatively longer lifespan, high energy storage density and no memory-effects; however, these batteries can pose safety risks in case of their failure. This study comprehensively overviews various LIBs used in EVs. It focuses primarily on the internal faults within LIBs covering their types, abusive scenarios, key feature indicators, safety enhancements, and fire characteristics. Any of the mechanical or electrical or thermal abusive scenarios is observed to eventually cause internal short circuit and hence, thermal runaway in LIBs. Overcharging is found to alter the porosity of cathode, anode and separators of LIBs whereas, over dis-charging is reported to degrade its capacity. LIBs, when exposed to abnormal working scenarios would face increase in temperature, swelling and gas release; Analysing these vent gases is reported as an effective way to corroborate the failure mechanism of LIBs. This work sheds light on LIB failure mechanisms behind the specific fault cases, highlights the battery characteristics that signal faults, and their instrumentation techniques. Furthermore, this review reports several challenges in the existing literature, provides insights and guidance for researchers to create safer and more durable EV batteries.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"393 ","pages":"Article 126139"},"PeriodicalIF":10.1,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144106127","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

Multi-stage portfolio optimization for GenCo considering multi-correlation between electricity and carbon markets 考虑电力和碳市场多重相关性的发电公司多阶段投资组合优化

IF 10.1 1区工程技术

Applied Energy Pub Date : 2025-05-21 DOI: 10.1016/j.apenergy.2025.126052

Xiaocong Sun , Minglei Bao , Yi Ding , Xinyu Ouyang , Yonghua Song

{"title":"Multi-stage portfolio optimization for GenCo considering multi-correlation between electricity and carbon markets","authors":"Xiaocong Sun , Minglei Bao , Yi Ding , Xinyu Ouyang , Yonghua Song","doi":"10.1016/j.apenergy.2025.126052","DOIUrl":"10.1016/j.apenergy.2025.126052","url":null,"abstract":"<div><div>Under the electricity and carbon (E&C) markets, generation companies (Gencos) need to trade among multiple options including forward contract markets and spot markets for electricity and carbon emission allowance (CEA), a process known as portfolio optimization. However, there exists a complicated multi-correlation between E&C markets, i.e., quantity and temporal correlation, which is seldom considered in the previous studies. This paper for the first time proposes a multi-stage portfolio optimization framework that determines the optimal composition of electricity and CEA in contract and spot markets to maximize revenue. The multi-stage framework is formulated as yearly, monthly, and spot stages: The yearly stage decides on the forward contract signing and allocation strategies to various monthly stages; The monthly stage adjusts contract signing and allocation strategies to spot stages; The spot stage considers the bidding strategies of electricity and CEA in two respective spot markets while integrating with the clearing processes. Then, the multi-stage portfolio optimization model is formulated as a multi-stage nonlinear stochastic programming with bilevel problems in the substage. To improve the solution efficiency, the alternating stochastic dual dynamic programming (A-SDDP) algorithm is innovatively proposed to cope with it. Finally, the case study demonstrates the importance of modeling the multi-correlation between E&C markets in Genco's portfolio optimization. Compared to the models that either only consider the carbon tax in the objective functions or models that ignore the temporal correlation, the proposed framework significantly improves profit for Genco.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"393 ","pages":"Article 126052"},"PeriodicalIF":10.1,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144106126","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