Applied Energy最新文献

{"title":"Two-stage optimization scheduling strategy for virtual power plants considering the correlated uncertainty of distributed energy storage in extreme scenarios","authors":"Runxin Chen ,&nbsp;Liqing Liao ,&nbsp;Dongran Song ,&nbsp;Chuxi Wei ,&nbsp;Jian Yang ,&nbsp;M. Talaat ,&nbsp;M.H. Elkholy","doi":"10.1016/j.apenergy.2026.127477","DOIUrl":"10.1016/j.apenergy.2026.127477","url":null,"abstract":"<div><div>Under extreme scenarios, virtual power plants (VPPs) are subjected to multiple impacts such as abrupt changes in source-load power and mismatched coordinated operation of distributed energy storage (DES) clusters, which significantly increases the difficulty of balancing scheduling security and economic efficiency. Considering the correlated uncertainty of DES, this article proposes a two-stage optimization scheduling strategy for VPPs to address the issue of enhancing system resilience in extreme disaster events. Firstly, K-means clustering is performed on the wind and load data, and based on typical scenario screening, an extreme scenario optimization selection mechanism is proposed with the principle of maximizing scenario dissimilarity. Secondly, based on cross correlation analysis, the correlated uncertainty of DES power changes in extreme scenarios is characterized, and a correlated matrix is constructed. Then, the two-stage optimization scheduling strategy is proposed. In the first stage, the total cost of purchasing electricity and operation and maintenance expenses is minimized. In the second stage, based on the output of each DES obtained in the first stage, the correlated uncertainty between DES and their own response deviation are reduced. Finally, the effectiveness of the strategy is verified through numerical analysis. The results show that compared to existing methods, the proposed strategy can reduce 30.91% of the power gap and 68.77% of the total cost in extreme scenarios of the distribution network. Therefore, the proposed method effectively balances the risk resistance ability and scheduling economy in extreme scenarios, providing a new technical path for the safe and efficient operation of VPP under extreme working conditions.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"409 ","pages":"Article 127477"},"PeriodicalIF":11.0,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146171573","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":"High-resolution dynamic modeling and techno-economic optimization of off-grid PV–electrolysis–BESS systems for green hydrogen production","authors":"Haeseong Shin ,&nbsp;Dohyung Jang ,&nbsp;Hee-Sun Shin ,&nbsp;Sungtae Park ,&nbsp;Sanggyu Kang","doi":"10.1016/j.apenergy.2026.127451","DOIUrl":"10.1016/j.apenergy.2026.127451","url":null,"abstract":"<div><div>Green hydrogen production through water electrolysis (WE) powered by renewable energy offers a promising pathway for decarbonization but faces challenges related to cost, variability, and stable off-grid operation. This study proposes an optimal design and operational strategy for an off-grid green hydrogen production system integrating photovoltaic (PV) generation, alkaline water electrolysis, proton exchange membrane water electrolysis (PEMWE), and battery energy storage systems (BESS). A dynamic simulation framework using one-minute PV irradiance data was developed to capture short-term renewable fluctuations and evaluate the interactions among the electrolyzers and BESS under real-time operation. The optimal system configuration was determined as 120 MW PV, 100 MW PEMWE, and 34.8 MWh BESS, achieving a Levelized Cost of Hydrogen (LCOH) of $10.77/kg under base conditions. Sensitivity analyses indicated that a 20% reduction in PV CAPEX reduced the LCOH to $9.81/kg, while doubling the BESS C-rate or halving the AWE minimum load range further decreased LCOH by 5–10%. These results demonstrate that integrating dynamic modeling with techno-economic evaluation enables a realistic and comprehensive assessment of off-grid hydrogen systems, providing practical guidance for the cost-effective and stable production of green hydrogen under renewable energy variability.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"409 ","pages":"Article 127451"},"PeriodicalIF":11.0,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076650","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":"Instantaneous urban facade PV potential assessment: An end-to-end deep learning framework for arbitrary planning horizons","authors":"Kechuan Dong ,&nbsp;Zhiling Guo ,&nbsp;Qing Yu ,&nbsp;Jian Xu ,&nbsp;Xuanyu Liu ,&nbsp;Jinyue Yan","doi":"10.1016/j.apenergy.2026.127357","DOIUrl":"10.1016/j.apenergy.2026.127357","url":null,"abstract":"<div><div>Traditional physics-based simulation approaches for urban facade photovoltaic potential assessment remain computationally intractable for metropolitan-scale deployment, requiring weeks to months of processing time that effectively paralyzes evidence-based urban energy policy development. This computational barrier has prevented the transition from theoretical renewable energy potential to operational decarbonization planning tools despite building facades representing the primary scalable pathway for distributed solar generation in space-constrained urban environments. To overcome this fundamental barrier, we introduce E2AY-Net, an end-to-end deep learning framework that transforms urban facade PV assessment from slow multi-stage simulation into instantaneous spatially-resolved energy yield generation. E2AY-Net integrates three specialized encoding pathways: convolutional neural networks capturing hierarchical urban morphological features across spatial scales from individual facades to city-scale configurations, Transformer architectures processing arbitrary-length meteorological sequences spanning hours to years with attention mechanisms preserving long-range temporal dependencies, and multilayer perceptrons accommodating diverse photovoltaic module specifications. Validated in the hyper-dense urban environment of Hong Kong, the framework achieves comprehensive annual assessment of the complete urban domain in 33.79 s with 678,955<span><math><mo>×</mo></math></span> computational acceleration, while maintaining engineering-grade accuracy with 5.56% mean relative error and 84.6% of building surfaces achieving predictions within 10% tolerance. The anytime capability enables flexible assessment across arbitrary planning horizons from short-term feasibility studies to comprehensive annual evaluations through processing variable-length meteorological sequences in single forward passes without architectural modification or pipeline re-execution. Strategic deployment analysis reveals that targeted installation on the highest-performing 25% of facades, concentrated within merely 9.2% of total available facade area, achieves 3200 GWh annual generation potential with 1500 kt CO₂ emission reduction capacity. This work establishes a practical breakthrough enabling the transition from computationally intractable urban energy assessment to real-time interactive planning tools, fundamentally transforming urban building envelopes into accessible distributed energy infrastructure for evidence-based decarbonization policy development across space-constrained metropolitan environments worldwide.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"409 ","pages":"Article 127357"},"PeriodicalIF":11.0,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076633","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":"Insights into the role of gasification media in gasification process: Principles, advantages, bottlenecks and prospects","authors":"Beibei Yan ,&nbsp;Rui Zhang ,&nbsp;Zhuang Yuan ,&nbsp;Zhi Wang ,&nbsp;Jian Li ,&nbsp;Shengquan Zhou ,&nbsp;Xiaochao Zhu ,&nbsp;Guanyi Chen","doi":"10.1016/j.apenergy.2026.127543","DOIUrl":"10.1016/j.apenergy.2026.127543","url":null,"abstract":"<div><div>Gasification technology is a sustainable energy generation technology that converts biomass into syngas products. At the same time, gasification media (GM) can change the core reaction principle of gasification reaction, resulting in different syngas compositions, yields and efficiencies. The appropriate selection of GM is an important way to improve the economy and performance of gasification technology. This review provides an overview of the GM currently used for gasification, which fall into two main categories: gas (air, O₂, steam, H₂, CO₂ and High-temperature flue gas (HTFG)) and solid (metal oxides and sulphates and natural ore, and industrial slag) GM with the monomers and complexes. Moreover, the principles, advantages, bottlenecks and application scenarios of various GM involved in the gasification reaction are described. In the further, potential proposals such as the application and precise control of multi GM, industrial preparation for full-scale and integration of gasification with other technologies, may be the development directions for GM. This work provides insights and references for the selection of GM to achieve efficient conversion of substrates into syngas during the gasification process.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"409 ","pages":"Article 127543"},"PeriodicalIF":11.0,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146170943","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":"Leveraging the capabilities of physics-informed neural networks for channel optimization in PEM fuel cells","authors":"Julian Nicolas Toussaint ,&nbsp;Sebastian Pieper ,&nbsp;Max Paul Mally ,&nbsp;Stefan Pischinger","doi":"10.1016/j.apenergy.2026.127478","DOIUrl":"10.1016/j.apenergy.2026.127478","url":null,"abstract":"<div><div>Physics-informed neural networks (PINNs) offer a promising alternative to computationally expensive CFD-based design studies of proton exchange membrane fuel cells (PEMFCs). However, their suitability for modeling realistic fuel cell channel flows and their ability to generalize across different geometric designs have not yet been systematically assessed. This work addresses this gap by developing a mesh-free PINN framework that embeds the governing transport equations of multicomponent channel flow, including oxygen consumption, directly into the learning process. Unlike conventional artificial neural networks (ANNs), the proposed PINN does not require labelled CFD training data. In this work, CFD data are used for benchmarking and validation, while the PINN training itself does not rely on CFD field solutions in the interior of the computational domain, and the PINN training itself is driven solely by the embedded governing equations without labelled CFD target fields. The model is evaluated with respect to two core research questions: (i) Can a PINN accurately reproduce the coupled flow and species transport fields in a PEMFC gas channel? and (ii) Can the learned physics be leveraged to predict performance for previously unseen channel widths? Results show that the PINN reproduces CFD reference fields with high accuracy and substantially outperforms ANNs in generalizing to channel widths not included in training. Moreover, the PINN-based design study achieves a computational time reduction of approximately 83.9% compared to full CFD simulations. These findings demonstrate that PINNs provide a data-efficient and computationally lightweight surrogate model suitable for accelerating iterative PEMFC channel design, here exemplarily demonstrated for variations in channel width.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"409 ","pages":"Article 127478"},"PeriodicalIF":11.0,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146171503","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":"Aggregator electricity price guarantees for households with flexibility potential utilizing thermal building inertia","authors":"Leo Semmelmann ,&nbsp;Steven O. Kimbrough ,&nbsp;Philipp Staudt","doi":"10.1016/j.apenergy.2026.127430","DOIUrl":"10.1016/j.apenergy.2026.127430","url":null,"abstract":"<div><div>This study introduces an approach to mitigate the reluctance of households to adopt dynamic electricity tariffs by proposing individual price contracts tailored to household characteristics. These contracts guarantee individual electricity rates to households with flexibility potential, such as thermal or electrical storage and the thermal mass of buildings, in exchange for granting aggregators operational control. The household-specific contracts are determined and evaluated through a three-step process, combining deterministic and stochastic modeling. First, an optimization problem for the operation of home energy management systems is formulated. The proposed model incorporates the thermal inertia of buildings as a flexibility potential, an aspect frequently overlooked in existing studies. Then, a Monte Carlo simulation of household parameter combinations is run, followed by a quantile regression prediction of household-level low-price guarantees. The simulations of 9404 household configurations in Germany demonstrate that aggregator-managed flexibility consistently lowered electricity costs by an average of 7.36% (2.5 ct/kWh) compared to static tariffs, with 78.4% of households achieving rates below the competitive retail benchmark. Aggregators also realized higher profitability on a per-household basis across all three analyzed years compared to scenarios without flexibility control. Our results demonstrate that building parameters, particularly thermal inertia, substantially influence the available flexibility potential and should be considered a key factor in the design of household-level guarantee contracts. The study contributes to understanding and quantifying uncertainty in dynamic tariffs for households, aiming to advance the utilization of household demand response potential in modern power markets.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"409 ","pages":"Article 127430"},"PeriodicalIF":11.0,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146171149","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":"Locational marginal emission rates calculation considering reserve requirements","authors":"Md Arifin Arif ,&nbsp;Fengyu Wang ,&nbsp;Di Shi ,&nbsp;Liang Sun","doi":"10.1016/j.apenergy.2026.127439","DOIUrl":"10.1016/j.apenergy.2026.127439","url":null,"abstract":"<div><div>As new policies are adopted to transition toward emission-free electricity, effective metrics are needed to accurately quantify emissions. Locational Marginal Emission Rates (LMERs) effectively capture the change in emissions associated with a change in demand. This paper introduces a computationally efficient LMER calculation algorithm that considers reserve requirements and network constraints in the economic dispatch model. Unlike locational marginal prices (LMPs), which can be directly derived from shadow prices expressed in $/MWh, calculating LMERs requires identifying marginal units that adjust their outputs in response to infinitesimal changes in system parameters. The LMER calculation algorithms also compute the incremental output changes of these marginal units and utilize these output changes, combined with the respective emission rates to compute LMERs accurately. However, the inclusion of reserve requirements, which are essential in modern electricity markets to address the uncertainties introduced by contingencies and significant intermittent generation, complicates identification of marginal units and calculation of their corresponding output changes in response to the locational demand changes. Thus calculating LMERs become increasingly complex. The proposed algorithm for the calculation of LMERs considering the reserve requirement systematically identifies marginal units and their corresponding output changes to calculate LMERs. This algorithm has been tested on both a four-bus system and a synthetic Texas Test System to show its efficiency and validate its accuracy. Furthermore, this algorithm is examined with different levels of reserve requirements and hence analyzes the impact of reserve requirements on marginal units and LMERs.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"409 ","pages":"Article 127439"},"PeriodicalIF":11.0,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076596","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":"Performance and feasibility assessment of a wave energy converter with underwater vehicle docking and charging","authors":"David Okushemiya ,&nbsp;Bryson Robertson ,&nbsp;Curtis J. Rusch","doi":"10.1016/j.apenergy.2026.127453","DOIUrl":"10.1016/j.apenergy.2026.127453","url":null,"abstract":"<div><div>Wave energy converters (WECs) offer a promising renewable solution to enable persistent unmanned underwater vehicle (UUV) missions by supporting at-sea docking and recharging. However, integrated WEC–UUV systems remain under-studied, with no broadly applicable frameworks for assessing their long-term effectiveness and viability. This study addresses these gaps by developing two complementary and generalizable frameworks: (i) one for evaluating long-term WEC power performance under realistic, time-varying sea conditions, and (ii) another for assessing UUV docking feasibility. The frameworks were demonstrated using the field-deployed TigerRAY WEC–UUV system with 2024 wave data from NDBC buoy station 42,036 on the U.S. Atlantic South Coast. Power performance results showed that TigerRAY could sustain persistent UUV operations although it could not always guarantee uninterrupted recharging, with the BlueROV2 and REMUS100 completing 368 and 109 missions, respectively, compared with 2927 and 627 missions possible under an unlimited power source. This suggests the need for supplemental battery buffering or hybrid energy sources, where each kilowatt-hour of energy buffer added approximately 1.67 missions for BlueROV2 and 0.5 for REMUS100. Docking feasibility probability for BlueROV2 remained 1 (i.e., 100 % feasible) across all operational sea states, decreasing slightly to 0.7 under extremes (<span><math><msub><mi>H</mi><mi>s</mi></msub><mo>=</mo><mn>5</mn></math></span> m), indicating that dock motions stayed within UUV motion limits, although actual docking success will ultimately depend on UUV control, sensing, and communication. These results demonstrate that WEC-UUV systems are technically viable, while the developed frameworks provide a generalizable foundation for performance assessment, design optimization, and system integration of future WEC–UUV technologies toward persistent autonomous ocean observation and intervention.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"409 ","pages":"Article 127453"},"PeriodicalIF":11.0,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076652","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":"Decarbonization pathways of Hard-to-Abate sectors through hydrogen blending solutions","authors":"S. Mazzoni,&nbsp;M. Vellini,&nbsp;M. Gambini","doi":"10.1016/j.apenergy.2026.127420","DOIUrl":"10.1016/j.apenergy.2026.127420","url":null,"abstract":"<div><div>Following up on European Regulatory plans towards carbon neutrality targets by exploiting cost-effective, reliable and easy-to-implement solutions based on hydrogen penetration in the Hard-to-Abate sectors are a challenge. Under this umbrella, the authors proposed a methodological approach to model the demand and supply of HTA sector needs (e.g. electricity, heat), integrated with proprietary databases of H2-specific production costs and related CO₂ emission factors, and of HTA sectors (e.g. refinery, paper production, glass &amp; steel manufacturing) specific consumptions (electricity, heat) and emissions per production unit. The authors presented an H2-CH4 blending model capable of assessing blended fuel CO₂ emission factors and OPEX through maps. The first map shows that achieving a specific decarbonization target, as an example, 20% in respect of the current configuration, requires up to 70% blending of blue H2 (80 kg CO₂/MWh emission factor) or only 50% blending of green H2 (near-zero CO₂ emissions). The second map incorporates LCOH and Carbon Tax to evaluate economic feasibility. In a case study with CH4 priced at 70 EUR/MWh and CO₂ Tax of 100 EUR/ton, green H2 remains costlier, while blue H2 blending leads to a slight OPEX reduction of 2 EUR/MWh, since Carbon Tax is applied. Thanks to these maps, a sensitivity analysis varying H2 blending fraction with CH4 has been performed for five HTA sectors, highlighting CO₂ emissions reduction potential, up to 70% in the sectors with larger heat demands, such as Oil&amp;Gas, and evaluating OPEX in respect to the reference scenario, showing that at the current CO₂ Tax of almost 100 EUR/ton and for the actual LCOH the decarbonisation economic viability would require the support of regulation and environmental policies implementation.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"409 ","pages":"Article 127420"},"PeriodicalIF":11.0,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076636","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":"An incentivized cooperative scheme for transmission expansion in a 100% renewable Europe","authors":"Alessio Santecchia ,&nbsp;Ivan Kantor ,&nbsp;Rafael Castro-Amoedo","doi":"10.1016/j.apenergy.2026.127415","DOIUrl":"10.1016/j.apenergy.2026.127415","url":null,"abstract":"<div><div>In the age of transformative European initiatives like the Green Deal, the electrification surge in mobility, heating, and services stands as a beacon towards carbon neutrality. This study illuminates the pivotal role of electrical grid interconnection in this monumental endeavor. Through a comparative analysis between isolated grids and an interconnected European system, we unveil the extraordinary potential of a collaborative grid: a 30 EUR/kWh (18%) reduction in electricity costs and a 12 gCO₂eq/MWh (24%) decrease in environmental impact. The equitable distribution of this economic advantage across European nations allows us to establish the price nations ought to pay for the security of supply (96 EUR/MWh for Belgium) or, alternatively, the rightful compensation for providing cost-effective renewable energy (75 EUR/MWh for Sweden). Overall, the collaborative grid ushers in remarkable cost savings of 130 billion EUR annually, amounting to 174 EUR per European citizen. Furthermore, uncertainty analysis, grounded in a comprehensive literature review, reinforces the robustness of our findings. The transition towards a 100% renewable, interconnected European electricity grid over the next two decades necessitates an investment of 7 trillion EUR. In annual terms, this represents a manageable 4.2% of the European GDP. The payoff, however, is colossal: an 85% reduction in the environmental footprint of the European economy, equating to 2000 Mt of annually avoided CO2 emissions–a significant stride towards combating global climate change.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"409 ","pages":"Article 127415"},"PeriodicalIF":11.0,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076634","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}