Applied Energy最新文献

{"title":"Digital twin-enabled dynamic 4E-S multi-objective optimization framework for intelligent gas turbine operation with flexible loads","authors":"Juxi Hu ,&nbsp;Rui Wang ,&nbsp;Dakuan Xin ,&nbsp;Siyuan Liu ,&nbsp;Kai Cao ,&nbsp;Ke Zhao","doi":"10.1016/j.apenergy.2025.127236","DOIUrl":"10.1016/j.apenergy.2025.127236","url":null,"abstract":"<div><div>Mature gas turbines effectively address challenges from renewable intermittency to grid reliability. However, current gas turbine flexible-load operating strategies often neglect dynamic environmental factors and performance degradation's impact on the 4E-S (energy, exergy economics, emissions, and sustainability) framework, potentially compromising energy-saving and emissions reduction targets. Rooted in digital twin, this study presents a comprehensive lifecycle framework for intelligent, optimal gas turbine operation. Initially, a source domain hybrid model is developed. Subsequently, leveraging transfer learning principles, a hybrid transfer learning methodology is implemented for modeling the target domain. The gas turbine operating window is then constructed, and a thorough 4E-S analysis is performed. Further, a novel dynamic multi-objective evolutionary algorithm with reward-normalized stochastic selection (DMOEA-RNSS) is introduced to optimize performance within the defined operating window, generating dynamic Pareto fronts (PFs) and Pareto sets (PSs). Ultimately, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is applied to evaluate the PFs and determine the optimal operating strategy. The framework has been successfully applied to the optimal operational decision-making for a M701F gas turbine. The experimental results show that the Root Mean Squared Errors (RMSEs) between the predicted gas turbine performance state parameters and the actual operating measurement data are all less than 0.5 %. Furthermore, the variable load path from empirical gas turbine data remains within the established operating window's feasible boundaries, confirming window feasibility. Relative to the variable load path, the optimized strategy achieves a 0.1871 improvement in relative comprehensive energy efficiency (1.92 % in real), a 0.3652 reduction in relative emissions (28.34 g/s in real), and a 0.0674 reduction in relative economic indicators (0.7803$/s in real).</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"407 ","pages":"Article 127236"},"PeriodicalIF":11.0,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145882808","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":"Learning-based optimal power bidding of an overseas photovoltaic-battery storage plant in Singapore electricity market","authors":"Yang Xia,&nbsp;Yan Xu","doi":"10.1016/j.apenergy.2025.127328","DOIUrl":"10.1016/j.apenergy.2025.127328","url":null,"abstract":"<div><div>Singapore power grid is planning to import clean power such as photovoltaic (PV) power generation from overseas through subsea cables. To participate in the Singapore electricity market, the power output from PV plants is required to be constant during each bidding period and hence battery storage systems (BSSs) need to be deployed to compensate PV power fluctuations. This paper proposes a learning-based bidding strategy to maximize the expected profit of such a PV-BSS plant. The overall bidding process is modelled as a Markov Decision Process (MDP) and the optimal bidding strategy is acquired through deep reinforcement learning (DRL), considering PV power revenues, penalty payments for power shortage, and battery health degradation cost of the BSS. To more accurately characterize the actual operational behavior of the BSS, a detailed BSS model is built to estimate the state of power (SoP) and state of health (SoH) of the BSS. Numerical case studies are carried out to demonstrate that the proposed method can achieve promising profits compared to classic optimization-based methods and preserve BSS with less SoH degradation.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"407 ","pages":"Article 127328"},"PeriodicalIF":11.0,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145882810","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 review of underground energy storage: Modeling, experiments, and challenges","authors":"Bodu Zhang ,&nbsp;Guosheng Jiang ,&nbsp;Ting Bao ,&nbsp;Xuanming Ding ,&nbsp;Zhendong Cao ,&nbsp;Lin Zhang","doi":"10.1016/j.apenergy.2025.127319","DOIUrl":"10.1016/j.apenergy.2025.127319","url":null,"abstract":"<div><div>As the global demand for clean and reliable energy increases, technologies such as compressed air energy storage, underground gas storage, and geothermal energy storage have emerged as critical solutions to mitigate the intermittency and instability of renewable energy sources. These Underground Energy Storage (UES) systems are governed by complex interactions between thermal, hydraulic, and mechanical processes, which play a pivotal role in determining the safety, stability, and operational efficiency of UES systems. This paper presents a comprehensive review of UES to summarize recent research developments and challenges of multiphysics modeling and experiments across multiple spatial scales. The review examines the practical engineering applications of major UES technologies and provides an analysis of how the multiphysics phenomena and physico-mechanical properties of geological formations affect UES system performance from microscales to macroscales. The experimental work from lab-scale experiments and field-scale measurements is also summarized to highlight key considerations for designing and managing effective storage systems, mainly including system mechanical stability, gas tightness, and thermodynamic responses under different operational conditions. Lastly, this review underscores key challenges and outlines future research directions, with particular attention given to the role of chemical interactions in multiphysics coupling and the need for integrated, cross-scale modeling approaches to support the continued development of UES technologies.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"407 ","pages":"Article 127319"},"PeriodicalIF":11.0,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145876801","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":"Integrated design for underwater thermoelectric generator (TEG) based on fully coupled multiphysics fields analysis method","authors":"Yimeng Yang ,&nbsp;Ligeng Li ,&nbsp;Jie Yang ,&nbsp;Hua Tian ,&nbsp;Gequn Shu","doi":"10.1016/j.apenergy.2025.127317","DOIUrl":"10.1016/j.apenergy.2025.127317","url":null,"abstract":"<div><div>Based on the compact and quiet operation characteristics of TEG systems, this study proposes its application in power supply for underwater equipment, utilizing the stable temperature difference between the seawater cold source and the lead‑bismuth fluid heat source to generate electricity. First, three basic integrated structures are designed and compared in terms of temperature uniformity and electrical performance under the same operating conditions to select the most suitable structure for this application. The results show that the sandwich structure has the best temperature uniformity with a coefficient exceeding 0.95, the highest output power of 524.7 W and a medium power density. Therefore, the sandwich structure is selected as the applicable structure. Additionally, a fully coupled multiphysics calculation method is proposed, which comprehensively considers thermoelectric conversion and thermo-mechanical reliability. Using this method, an analysis of the fluid-thermal-electric-mechanical and off-design condition characteristics of the structure revealed that: under the same temperature difference, reducing the cold-side temperature can improve power generation performance more effectively than increasing the hot-side temperature. For every 15 °C decrease in the cold-side temperature, the conversion efficiency increases by approximately 5 %, while the maximum stress on the structure is reduced. Furthermore, all structures have an optimal external load that maximizes the output power, power density, and conversion efficiency. Finally, the accuracy of this fully coupled calculation method is verified through experiments. This study provides important insights into the expanded application of TEG systems in underwater equipment, as well as for performance analysis and optimization under multiphysics coupling conditions.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"407 ","pages":"Article 127317"},"PeriodicalIF":11.0,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145876964","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":"Internet data centers and industrial parks as flexibility providers in modern power systems: An ADMM-based coordination mechanism","authors":"Seyed Amir Mansouri ,&nbsp;Emad Nematbakhsh ,&nbsp;Andrés Ramos ,&nbsp;Jose Pablo Chaves-Avila ,&nbsp;Javier García-González ,&nbsp;José A. Aguado","doi":"10.1016/j.apenergy.2025.127320","DOIUrl":"10.1016/j.apenergy.2025.127320","url":null,"abstract":"<div><div>Smart prosumers with Distributed Generation (DGs) and controllable loads can provide cost-effective grid services. However, realizing this potential requires distributed optimization mechanisms that ensure market efficiency, participant privacy, and compliance with electricity market regulations. This paper presents a bi-level distributed optimization mechanism to maximize flexibility services from industrial parks and Internet Data Centers (IDCs) in distribution-level Congestion Management (CM) markets. The upper-level models the Distribution System Operator (DSO), which identifies congested lines using linear AC power flow analysis on pre-settled energy market results and sends corrective signals to prosumers. The lower level allows prosumers to adjust their operations accordingly and communicate updated transactions back to the DSO. A novel proxy-driven algorithm is proposed to facilitate service-sharing among geo-distributed IDCs, considering congestion issues. Additionally, an adaptive Alternating Direction Method of Multipliers (ADMM) algorithm enables decentralized coordination among market agents, achieving 74.52 % faster convergence than the standard ADMM. A real-world case study from Spain demonstrates that the proposed mechanism enables the grid operator to maximize grid services from prosumers, reducing congestion alleviation costs by 35.27 %. Moreover, IDCs reduced daily costs by 11.07 % through service-sharing and task-shifting aligned with CM market signals, while industrial parks achieved a 13.68 % cost reduction by aligning material production processes with CM market signals, both enabled by the proposed bi-level mechanism.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"407 ","pages":"Article 127320"},"PeriodicalIF":11.0,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145876965","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":"The Effective Energy Shift (EfES) algorithm: A non-iterative piece-wise linear method for mapping storage capacity to self-sufficiency and self-consumption","authors":"Jonathan Fellerer,&nbsp;Daniel Scharrer,&nbsp;Reinhard German","doi":"10.1016/j.apenergy.2025.127241","DOIUrl":"10.1016/j.apenergy.2025.127241","url":null,"abstract":"<div><div>The Renewable Energy Sources wind and solar are key drivers for the transition to a greenhouse gas neutral economy. However, they pose the inherent problem of high fluctuation in their availability, thereby affecting the consistency of energy generation. Energy Storage System (ESS) are a key technology for solving many of the emerging challenges. As these entail their own investment costs, the added benefit of these systems has to be calculated. Typical energetic measures are self-sufficiency, self-consumption and the loss-of-load probability. The considered energy system possesses some form of renewable energy generation, an intrinsic energy demand and a potential ESS. This paper presents a deterministic efficient algorithm that uses time series for the demand and renewable generation to construct an exact mapping by a closed-form expression and its parameters for the named energetic measures as a function of the usable capacity of the ESS. To enable these closed-form mappings we introduce the <em>effectiveness</em> of the storage, a precise, loss-agnostic operational/usage metric that generalizes the familiar equivalent full cycles (EFC). For comparability, we report both the internal EFC and the delivered EFC. This clarifies where discharge losses are applied and resolves inconsistent “cycle count” conventions in the literature. Power limits, charging and discharging efficiencies, and efficiencies for the direct use of generation by the system can be considered. Since no simulation or optimization is required to perform the analysis, it is computationally efficient and easy to set up with a relatively small amount of input data.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"407 ","pages":"Article 127241"},"PeriodicalIF":11.0,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145882809","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 carbon-negative solar fuel production method with enhanced solar contribution and superior CO2 reduction capacity: Experimental and system investigation","authors":"Zhulian Li ,&nbsp;Taixiu Liu ,&nbsp;Yu Fang ,&nbsp;Shuo Gao ,&nbsp;Qibin Liu","doi":"10.1016/j.apenergy.2025.127337","DOIUrl":"10.1016/j.apenergy.2025.127337","url":null,"abstract":"<div><div>With the continuous growth in energy demand, multi-energy hybrid utilization plays a significant role in optimizing energy structures and promoting low-carbon transformation. Solar energy and natural gas thermochemical hybrid utilization, by converting concentrated solar thermal energy into high-quality fuel chemical energy, helps mitigate the impact of solar irradiation variability on energy supply stability and reliability. Existing research primarily focuses on solar-driven dry/steam reforming of methane (DRM/SRM), converting solar energy into chemical energy in the form of syngas. However, these processes are fundamentally constrained by the thermodynamic properties of reforming and reaction thermal effects, resulting in low solar contribution, limited fossil fuel substitution, and insufficient CO₂ utilization capacity. To address these challenges, this study proposes an innovative carbon-negative solar fuel production method with enhanced solar share and CO₂ reduction capacity via chemical looping conversion. In this approach, oxygen carriers are employed to mediate the chemical looping reactions, restructuring the conventional CH₄–CO₂ reforming process into two separate steps, CH₄ oxidation and CO₂ reduction, enabling the production of high-purity CO. Concentrated solar energy is utilized to provide the heat required for reduction reaction. This pathway significantly increases the overall reaction thermal demand, enabling a higher fraction of solar energy to be converted into chemical energy stored in product CO-rich syngas. Experimental validation of the feasibility of this method is conducted in this study. Based on this approach, a carbon-negative solar fuel production system is developed and its performance is systematically evaluated through thermodynamic modeling and parametric analysis. Promising results show that the proposed system increases the solar share to 28.44 %, representing a 7.19 percentage point improvement over the most efficient solar-driven SRM system reported in literature. Furthermore, the system enhances the CO₂ reduction per unit of CH₄ to 2.84, which is 2.12 times higher than that of the conventional DRM process (0.91 mol-CO₂/mol-CH₄). Life-cycle assessment further confirms the carbon-negative characteristics of the SE-CL system, with total emissions of −0.69 kg CO₂-eq/kg-CO. These findings offer an effective solution to enhance the share of renewable energy in the energy structure and provide new pathways for utilizing CO₂ with high value.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"407 ","pages":"Article 127337"},"PeriodicalIF":11.0,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145876966","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":"Techno-economic analysis of hydrogen-to-power, ammonia-to-power pathway with biomass-to-power integration","authors":"Mou Wu ,&nbsp;Jiakun Fang ,&nbsp;Rujing Yan ,&nbsp;Jing Zhang ,&nbsp;Shichang Cui ,&nbsp;Yihan Zhang ,&nbsp;Shiqian Wang ,&nbsp;Xiaomeng Ai ,&nbsp;Jinyu Wen","doi":"10.1016/j.apenergy.2025.127327","DOIUrl":"10.1016/j.apenergy.2025.127327","url":null,"abstract":"<div><div>Biopower stands as a pivotal component of renewable energy, enabling stable electricity output and serving as a dispatchable resource. Nevertheless, its techno-economic viability as a long-term energy storage (LTES) solution for grid regulation remains underexplored. To address this, this study proposes utilizing biomass as a sustainable energy carrier and deploying the biomass-to-power (B2P) pathway for LTES. Considering the inherent limitations of B2P, it further puts forward operation strategies that integrate B2P with H2P (hydrogen-to-power) and A2P (ammonia-to-power) pathways. Then, the techno-economic model of six scenarios and long-term operation strategies is designed. The techno-economic performance of each pathway is assessed on monthly and yearly timescales. Results show that A2P achieves the highest average energy (61.23 %) and exergy (60.46 %) efficiencies, stemming from the inherently higher electrical efficiency of the direct ammonia-solid oxide fuel cell. Neither pathway of H2P nor A2P achieves lifecycle profitability. For the hybrid way of A2P with B2P integration, the overall average efficiency and exergy efficiency stand at 52.70 % and 44.30 %, respectively. Notably, the scenario exhibits the most favorable economic performance, achieving profitability in the 6th year with a net present value of 5.63 MUSD, and maintaining a superior positive discounted cash flow throughout the lifecycle. Moreover, it yields the levelized cost of electricity of 0.05–0.11 USD/kWh. Accordingly, the hybrid way of A2P with B2P integration demonstrates advantages both in technical and economic performance. It best balances technical and economic, making it suitable for large-scale deployment, especially in regions with high ammonia demand.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"407 ","pages":"Article 127327"},"PeriodicalIF":11.0,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145882807","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 method for chiller performance modeling via SKR-based neural network under physical constraints","authors":"Zhiwen Chen ,&nbsp;Yufei Liu ,&nbsp;Qiao Deng ,&nbsp;Ketian Liang ,&nbsp;Linlin Li ,&nbsp;Steven X. Ding ,&nbsp;Yalin Wang ,&nbsp;Weihua Gui","doi":"10.1016/j.apenergy.2025.127335","DOIUrl":"10.1016/j.apenergy.2025.127335","url":null,"abstract":"<div><div>The chiller is a critical component in heating, ventilation, and air conditioning (HVAC) systems, and its operating efficiency has a major impact on the overall energy performance of buildings. As a key performance indicator, accurately modeling the coefficient of performance (COP) of the chiller is critical. However, COP is significantly affected by system dynamics and uncertainties, which limit traditional neural network-based modeling methods due to their neglect of temporal dependencies in state evolution. To solve this problem, this paper proposes an SKR-based neural network (SKRNN) for COP modeling based on stable kernel representation framework. Firstly, a feature selection strategy is designed, which integrates minimum redundancy maximum relevance and autocorrelation/cross-lagged correlation analysis to distinguish between input and state features and eliminate redundancies. Secondly, an SKRNN modeling architecture is developed, which explicitly characterizes the nonlinear dynamic process of COP as a function of internal and external factors via an observer. Finally, a physically informed constraint loss function based on thermodynamic mechanisms is introduced to enhance the modeling performance of the model. SKRNN combines the strengths of state-space modeling and nonlinear fitting of neural networks, and achieves dynamic real-time COP modeling through output feedback. Its effectiveness has been validated with operational data from an actual building chiller system, comparative experiments with mainstream modeling methods demonstrate that the proposed method can effectively improve COP modeling accuracy.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"406 ","pages":"Article 127335"},"PeriodicalIF":11.0,"publicationDate":"2025-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145881280","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":"TOMATOES: Topology and material optimization for latent heat thermal energy storage devices","authors":"Rahul Kumar Padhy ,&nbsp;Krishnan Suresh ,&nbsp;Aaditya Chandrasekhar","doi":"10.1016/j.apenergy.2025.127322","DOIUrl":"10.1016/j.apenergy.2025.127322","url":null,"abstract":"<div><div>Latent heat thermal energy storage (LHTES) systems are compelling candidates for energy storage, primarily owing to their high storage density. Improving their performance is crucial for developing the next-generation efficient and cost effective devices. Topology optimization (TO) has emerged as a powerful computational tool to design LHTES systems by optimally distributing a high-conductivity material (HCM) and a phase change material (PCM). However, conventional TO typically limits itself to optimizing the geometry for fixed, pre-selected materials. This approach does not leverage the large and expanding databases of novel materials. Consequently, the co-design of material and geometry for LHTES remains a challenge and is largely unexplored.</div><div>To address this limitation, we present an automated design framework for the concurrent optimization of material choice and topology. A key challenge is the discrete nature of material selection, which is incompatible with the gradient-based methods used for TO. We overcome this by using a data-driven variational autoencoder (VAE) to project discrete material databases for both the HCM and PCM onto continuous and differentiable latent spaces. These continuous material representations are integrated into an end-to-end differentiable, transient nonlinear finite-element solver that accounts for phase change. We demonstrate this framework on a problem aimed at maximizing the discharged energy within a specified time, subject to cost constraints. The effectiveness of the proposed method is validated through several illustrative examples.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"406 ","pages":"Article 127322"},"PeriodicalIF":11.0,"publicationDate":"2025-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145881284","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}