Applied Energy最新文献

{"title":"A novel solar spectrum splitting PV-CPT hybrid conversion system based on linear Fresnel filter-concentrator structure: Experimental device and application analysis","authors":"Jialu Tian,&nbsp;Guijia Zhang,&nbsp;Haojin Wu,&nbsp;Shiquan Shan,&nbsp;Leyi Miao,&nbsp;Ziying Cheng,&nbsp;Zhijun Zhou,&nbsp;Kefa Cen","doi":"10.1016/j.apenergy.2025.126300","DOIUrl":"10.1016/j.apenergy.2025.126300","url":null,"abstract":"<div><div>This study investigates the solar energy efficient conversion of photovoltaic-concentrated photothermal (PV-CPT), integrating the multilayer selective filter into a Linear Fresnel concentrating structure for full-spectrum splitting and residual-spectrum concentration. The optical filter designed for Si PV cell achieves high transmittance in the respond waveband, transmitting 60.7 % solar energy for PV power generation. The residual spectrum is reflected and concentrated by the Linear-Fresnel selective filter field to the thermal receiver. Three typical thermal utilization methods, Organic Rankine Cycle (ORC), Methanol Decomposition (MD) and coupling with Steam Rankine Cycle (SRC) are analyzed for CPT conversion. The exergy efficiencies of these processes are evaluated to understand the mechanism of irreversible losses. The power generation efficiencies of hybrid systems based on ORC, MD, and coupling with SCR are 31.56 %, 31.73 % and 32.65 %, respectively. The coupling with SRC method achieves a higher CPT exergy efficiency of 21 % while having the highest hybrid system efficiency, making it the optimal for residual-spectrum CPT conversion. An experimental device and a thermo-physical model of the system are developed to evaluate system performance, with the receiver tube reaching 435 K at a concentration ratio of 9.8. This study provides valuable insights for the implementation of high-efficiency solar full-spectrum energy conversion.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"396 ","pages":"Article 126300"},"PeriodicalIF":10.1,"publicationDate":"2025-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144281158","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}

{"title":"Uncertain operation region of electricity-hydrogen virtual power plant: Concept and description method","authors":"Hong Tan ,&nbsp;Ao Yang ,&nbsp;Zhenjia Lin ,&nbsp;Leijiao Ge ,&nbsp;Qiujie Wang ,&nbsp;Yuan Gao","doi":"10.1016/j.apenergy.2025.126210","DOIUrl":"10.1016/j.apenergy.2025.126210","url":null,"abstract":"<div><div>The Electric-Hydrogen Virtual Power Plant aggregates internal distributed energy resources to achieve joint electricity and hydrogen output, providing a new pathway for accommodating surplus renewable energy generation. However, precise modeling methods for the uncertain operating region of EH-VPP remain challenging. In this regard, this paper first defines the uncertain operating region of EH-VPP and constructs its internal optimization model. Then, based on multi-parameter programming theory and the cutting-plane method, the mapping relationship of the EH-VPP electricity‑hydrogen joint output curve is analytically derived. Based on this, the probability density function of the projection points of the electricity‑hydrogen joint curve onto the hydrogen production rate axis is derived, incorporating the known probability distributions of input random variables, thereby enabling probabilistic modeling of the uncertain operating region boundary. Finally, the opportunity constraint method is applied to construct the uncertain operating region of EH-VPP, which is then used in the coordinated scheduling optimization of the electric‑hydrogen integrated energy system. Simulation results show that the proposed method efficiently characterizes the uncertain operating region with an error of less than 0.05 %, supports flexible modeling based on confidence levels, and ensures both scheduling security and computational efficiency in large-scale collaborative scheduling scenarios.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"396 ","pages":"Article 126210"},"PeriodicalIF":10.1,"publicationDate":"2025-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144281162","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}

{"title":"Synerging closed-loop sustainable waste legislation with turquoise hydrogen in electric supply chain","authors":"Binoy Krishna Giri ,&nbsp;Sankar Kumar Roy","doi":"10.1016/j.apenergy.2025.126250","DOIUrl":"10.1016/j.apenergy.2025.126250","url":null,"abstract":"<div><div>The indisputable concerns about the environment are compelled the rapid spread of electric vehicles (EVs), turquoise hydrogen (TH) and renewable energy facilities (REFs). TH production is environmentally friendly and less harmful than conventional hydrogen, but further research is needed to make its eventual use feasible. Thus, this study explores India’s potential organic waste for pyrolysis, highlighting potential challenges in maintaining supply–demand equilibrium in the electric distribution system (EDS) due to unpredictable and variable sources. The study proposes a distributionally robust optimization approach for waste legislation-based multi-objective mixed-integer sustainable closed-loop supply chain in integrated natural gas and electricity distribution networks (INEDNs) in order to overcome these issues. The method not only simplifies waste separation in TH manufacturing but also significantly diverts recyclable waste to recycling facilities. Furthermore, EDS utilizes demand response activities (DRAs) to prevent peak load hours from overlapping with natural gas distribution system (NGDS), and utilizes linepack technology to store natural gas in NGDS pipes for short-term versatility. Next, the proposed multi-objective model is solved using a novel approach called utility function based multi-volition conic goal programming. A 123-EDS and a 40-NGDS are used for the simulations. The analysis of hydrogen’s closed-loop supply chain using flexible energy sources, DRA, linepack technology, and smart charging simulations shows potential for an 11.22 % reduction in emissions. Linepack technology reduces operating expenses for natural gas pipelines by 6.5 % in <span><math><msub><mi>S</mi><mn>2</mn></msub></math></span>, to EDS responsive loads 4.2 % in <span><math><msub><mi>S</mi><mn>3</mn></msub></math></span>, and 9.49 % in <span><math><msub><mi>S</mi><mn>4</mn></msub></math></span> lower than those of <span><math><msub><mi>S</mi><mn>1</mn></msub></math></span> when all energy sources are used.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"396 ","pages":"Article 126250"},"PeriodicalIF":10.1,"publicationDate":"2025-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144279762","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}

{"title":"Latching control of a point absorber wave energy converter in irregular wave environments coupling computational fluid dynamics and deep reinforcement learning","authors":"Hao Qin ,&nbsp;Haowen Su ,&nbsp;Zhixuan Wen ,&nbsp;Hongjian Liang","doi":"10.1016/j.apenergy.2025.126282","DOIUrl":"10.1016/j.apenergy.2025.126282","url":null,"abstract":"<div><div>This paper proposes a novel latching control model coupling Computational fluid dynamics (CFD) and Deep Reinforcement Learning (DRL) to improve the wave energy capture performance of a point absorber wave energy converter (WEC). Firstly, a numerical wave flume (NWF) is built to generate unpredicted irregular waves. That simulates the two-way coupling interaction between the WEC and waves based on CFD, which creates the nonlinear environmental state space for the DRL input. In the meanwhile, a training method based on the Soft Actor-Critic (SAC) algorithm without explicit parameter adjustment is designed to implement a non-predictive latching control agent. Secondly, using the CFD-DRL coupling model, training for the latching control strategy is conducted in parallel irregular wave environments, and three state space configurations are evaluated to enhance the agent's generalization ability. Lastly, the wave energy capture performance using the proposed latching control model is compared with a traditional real-time latching method, and comparative analysis of two different training approaches is carried out. Simulation results show that the proposed latching control model outperforms the traditional real-time latching method in tests under irregular waves with different wave heights and frequencies, stably achieving more than 30 % wave energy conversion efficiency. This paper highlights the applicability and advancement of the DRL method applied in intelligent control of WECs, which may provide new insights for the wave energy and ocean engineering industries.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"396 ","pages":"Article 126282"},"PeriodicalIF":10.1,"publicationDate":"2025-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144281150","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}

{"title":"Collaborative planning of hydrogen refuelling stations and DRGs in ADN for distributed energy consumption and flexibility enhancement","authors":"Menghao Peng ,&nbsp;Yuxuan Zhao ,&nbsp;Jiarong Li ,&nbsp;Zhaoxia Jing","doi":"10.1016/j.apenergy.2025.126293","DOIUrl":"10.1016/j.apenergy.2025.126293","url":null,"abstract":"<div><div>Integrating hydrogen refuelling stations (HRSs) equipped with the on-site electrolyser and fuel cell into the active distribution network (ADN) enhances both the consumption of distributed renewable generators' (DRGs) power generation and the operational flexibility of the ADN. To achieve this goal, a two-stage robust model is proposed for the collaborative planning of HRSs and DRGs within the ADN, encompassing investment and operation stages. In the investment stage, the site selection and component capacity determination of HRSs and DRGs are collaboratively determined. In the operation stage, the optimal scheduling of the ADN considering the relationship between the ADN and the transportation network (TN) is derived based on the planning results from the investment stage. By simulating the operation of the ADN with HRSs and DRGs in the operation stage, the optimal collaborative planning results that minimizes the total costs is determined. A user equilibrium (UE) traffic flow model is introduced to describe the travel and refuelling behaviours of hydrogen fuel cell vehicles (HFCVs) in the TN and to estimate their hydrogen refuelling demands. The two-stage robust collaborative planning model (TRCPM) is derived using robust optimisation to manage uncertainty and some linearisation techniques as well as the Nested Column-and-Constraint Generation (NC&amp;CG) algorithm are introduced to make it tractable. Simulations on a hybrid 33-bus power distribution network and 24-node transportation network demonstrate the effectiveness of the proposed collaborative planning model.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"396 ","pages":"Article 126293"},"PeriodicalIF":10.1,"publicationDate":"2025-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144280851","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}

{"title":"Experimental investigation on the impact of ambient temperature and current load rate on the cold start behavior of a short PEMFC stack","authors":"Pu He ,&nbsp;Qianxi Zhang ,&nbsp;Yutong Mu ,&nbsp;Zhiguo Qu ,&nbsp;Jinzhou Yin ,&nbsp;Ziai Li ,&nbsp;Weiwei Yang ,&nbsp;Saijie Cai ,&nbsp;Junhong Chen ,&nbsp;Wenquan Tao","doi":"10.1016/j.apenergy.2025.126317","DOIUrl":"10.1016/j.apenergy.2025.126317","url":null,"abstract":"<div><div>Enhancing the cold start performance of short stacks at low temperatures, which is largely attributed to their significant end-plate effect, proves essential for advancing commercialization. The constant current control strategy remains the most prevalent approach during startup operations. In this study, a 12-cell short stack was employed to investigate experimentally the effects of ambient temperatures and current load rates on cold start behavior. Results demonstrate that decreasing ambient temperatures intensifies the end-plate effect, while implementing lower current load rates effectively prolongs cold-start duration. At elevated ambient temperatures, the generated heat predominates over potential freezing risks for successful rapid startups. The current-controlled cold start process can be divided into three stages: initial performance recovery, moderate membrane water adsorption, and icing onset, which are primarily associated with the hydration state of the membrane electrode assembly. Variations in high frequency resistance evolution and reverse polarity characteristics emerge across these stages. Membrane electrode assembly damage induced by reverse polarity and icing leads to substantial increases in both high frequency resistance and membrane resistance, accompanied by a marginal reduction in the roughness factor of catalyst layer. The protective voltage strategy sustains stable stack performance, demonstrating high consistency at −10 °C. However, significant performance degradation manifests below −20 °C, particularly near end-plates, emphasizing the critical requirement for maintaining internal thermal uniformity under extreme low-temperature conditions.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"396 ","pages":"Article 126317"},"PeriodicalIF":10.1,"publicationDate":"2025-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144281159","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}

{"title":"Advancing calcium-based thermochemical heat storage: Impact of a dual-reaction strategy on the system performance","authors":"Haocheng Sun ,&nbsp;Zhiwei Ge ,&nbsp;Zhihan Yao ,&nbsp;Liang Wang ,&nbsp;Xipeng Lin ,&nbsp;Yakai Bai ,&nbsp;Shuang Zhang ,&nbsp;Haisheng Chen","doi":"10.1016/j.apenergy.2025.126299","DOIUrl":"10.1016/j.apenergy.2025.126299","url":null,"abstract":"<div><div>Thermochemical heat storage technology offers immense potential owing to its high energy storage density and low heat loss, making it ideal for long-duration and large-scale energy storage applications. However, challenges persist in terms of the reactor scalability, heat release efficiency, and comprehensive system evaluation. This study proposes a sequential dual-reaction strategy for calcium-based thermochemical heat storage using a flexible and scalable shell-and-tube reactor. The multi-physical coupling mechanisms and key factors influencing the kinetics of a fundamental single-reaction heat release process are explored in this study. In addition to demonstrating the superior heat transfer capabilities of the shell-and-tube design, our findings revealed a significant increase in irreversible entropy generation. Under ideal constant-pressure conditions, we also identified the key parameters governing the basic single-reaction heat release process, achieving a remarkable efficiency of up to 97.01 %. To further optimize the thermochemical heat storage system, a cascaded dual-reaction heat release strategy was proposed, which reduced irreversible entropy generation by 15 % compared to the basic single-reaction process. This strategy simultaneously enhanced the rates of both energy conversion and heat transfer. Finally, the detailed examination and optimization of the multi-reaction coupling mechanisms yielded a 30.60 % improvement in the comprehensive energy efficiency evaluation metric compared to the baseline model. This study offers valuable guidance for the design and control of thermochemical heat storage systems, presenting new solutions for achieving long-term, low-entropy energy conversion.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"396 ","pages":"Article 126299"},"PeriodicalIF":10.1,"publicationDate":"2025-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144281160","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}

{"title":"Advanced ultrasonic detection of lithium-ion battery thermal runaway under various heating powers","authors":"Hyuk Lee ,&nbsp;Yun-Ho Seo ,&nbsp;Pyung-Sik Ma","doi":"10.1016/j.apenergy.2025.126328","DOIUrl":"10.1016/j.apenergy.2025.126328","url":null,"abstract":"<div><div>Lithium-ion batteries (LIBs) are essential in modern technologies, including energy storage systems and electric vehicles, owing to their high efficiency and compact design. However, their vulnerability to thermal runaway (TR) triggered by overheating, particularly without effective early safety warnings, significantly limits their broader adoption. In this study, we systematically examine TR progression in LIBs under various heating powers by integrating ultrasonic diagnostics with conventional parameters, such as the force, voltage, and temperature. Using Floquet-Bloch analysis regarding internal periodic multi-layers, we employ a wide frequency range of ultrasonic waves covering a highly dispersive region near 2 MHz. This, in turn, enhances sensitivity to microstructural changes within the LIB during the early stages of TR. In particular, this method demonstrates superior performance compared to conventional indicators, such as the expansion force, providing early warnings of venting by 282 s–953.8 s and TR by 377 s–851 s under various heating powers ranging from 600 W to 1200 W. Furthermore, we present a comprehensive safety metric that incorporates early warning ultrasonic features along with multidimensional parameters. These findings establish a robust framework for using ultrasonic diagnostics to enhance the safety and reliability of LIBs for critical applications.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"396 ","pages":"Article 126328"},"PeriodicalIF":10.1,"publicationDate":"2025-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144281163","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}

{"title":"MapVC: Map-based deep learning for real-time current prediction in eco-driving electric vehicles","authors":"Zhuoer Wang ,&nbsp;Xiaowen Zhu ,&nbsp;Qingbo Wang ,&nbsp;Jian Zhou ,&nbsp;Bijun Li ,&nbsp;Baohan Shi ,&nbsp;Chenming Zhang","doi":"10.1016/j.apenergy.2025.126313","DOIUrl":"10.1016/j.apenergy.2025.126313","url":null,"abstract":"<div><div>The operating current prediction of power batteries is crucial for ensuring the working performance of Electric Vehicle (EV). However, complex real-world eco-driving scenarios—particularly the common engagement of regenerative braking systems (RBS) that produce negative current values—have introduced strong randomness into power system data. To overcome the limitations of conventional data-driven models in capturing such complexity, we propose the MapVC framework. First, a map-based encoder is introduced, which deduces the operation of the RBS via estimating the vehicle's motion state, greatly reinforcing prediction performance of data from complex real-world driving conditions. Additionally, a decoder leveraging multi-head self-attention is employed to extract multi-scale temporal features, enabling comprehensive modeling of intrinsic battery state changes. Moreover, a bidirectional gated recurrent network is integrated, which manages to address long-term dependency loss and exploit both past and future information for robust sequential modeling. To further mitigate overfitting problem caused by high-dimensional parameters, we introduce the Improved Hippopotamus Optimization (IHO) algorithm for efficient network tuning. Trained on real-world data from electric buses with RBS in Wuhan, China, our model achieves an MSE of 0.0709, MAE of 0.1859 and MAPE of 1.81 %, representing up to 93 % reduction in MSE and a 5.6-fold improvement in MAPE over prior work while maintaining outstanding computational efficiency. It outperforms its precursor in predicting key parameters of operating data and provides significant guidance for the application of geographic information to vehicle operating condition prediction.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"396 ","pages":"Article 126313"},"PeriodicalIF":10.1,"publicationDate":"2025-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144281164","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}

{"title":"A comparative sustainability assessment of several grid energy storage technologies","authors":"Roque Aguado Molina ,&nbsp;Juan José Cartelle Barros ,&nbsp;María del Pilar de la Cruz López ,&nbsp;Manuel Lara Coira ,&nbsp;Alfredo del Caño Gochi","doi":"10.1016/j.apenergy.2025.126248","DOIUrl":"10.1016/j.apenergy.2025.126248","url":null,"abstract":"<div><div>The global energy transition toward a low-carbon economy is driving increasing penetration of variable energy sources into electricity markets. This unprecedented deployment of intermittent renewables confronts decision-makers in the electricity sector with the challenge of selecting among different energy storage technologies, a choice that must be made on the basis of sustainability criteria. Existing studies present shortcomings, including the absence of the social dimension, the use of weights against sustainable development, or the application of methodologies affected by the rank reversal issue, among others. To address gaps in current knowledge, this study presents a novel probabilistic model for assessing the global sustainability of grid energy storage technologies. The model is based on the MIVES (<em>Modelo Integrado de Valor para una Evaluación Sostenible</em>)–Monte Carlo method, which combines requirement trees, value functions, the analytic hierarchy process, and probabilistic simulations. It consists of 19 indicators and makes it possible to obtain a sustainability index (<em>SI</em>), as well as partial economic, social, environmental, and technical indices for each technology. Data from an extensive literature review were integrated with expert input and estimations based on linear correlations to address challenges in assessing social and environmental indicators. The model was applied to six technologies: pumped hydroelectric energy storage (PHES), compressed air energy storage (CAES), liquid air energy storage (LAES), vanadium redox flow batteries (VRFB), sodium-sulfur batteries (NaSB), and hydrogen energy storage (HES). A comprehensive sensitivity analysis is also included. To the best of the authors’ knowledge, no existing study has utilized the innovative methodology presented in this paper, nor has any related research achieved the scope and depth proposed here. The top-performing technologies identified for the economic, social, environmental, and technical dimensions of sustainability are CAES, VRFB, LAES, and PHES, respectively. In terms of global sustainability, VRFB, LAES and PHES are the best options, while HES consistently ranks last. NaSB and CAES occupy intermediate positions.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"396 ","pages":"Article 126248"},"PeriodicalIF":10.1,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144281148","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}