Energy and Buildings最新文献

{"title":"Revealing the role of Fe particle size in soft magnetic geopolymer for enhancing energy conversion in airport pavement induction heating","authors":"Gonghui Gu ,&nbsp;Xinchi Xu ,&nbsp;Jinsheng Han ,&nbsp;Lin Wan-Wendner ,&nbsp;Zhiji Gao ,&nbsp;Rongze Fu ,&nbsp;Chuanqing Fu ,&nbsp;Tao Ma","doi":"10.1016/j.enbuild.2025.116182","DOIUrl":"10.1016/j.enbuild.2025.116182","url":null,"abstract":"<div><div>In this study, a soft magnetic geopolymer (SMG) co-modified with nanomagnetic fluid and spherical micron-sized Fe powders was developed for enhancing the energy conversion in airport pavement induction heating. The effects of Fe particle size on the microstructure, electromagnetic behavior, and mechanical performance of SMG were systematically investigated, with a focus on the size-dependent coupling mechanisms. Results show that Fe powder with a particle size no less than 150 μm provides pore-filling and skeletal reinforcement, leading to improved compressive strength and stable magnetic permeability. In contrast, finer particles significantly increase the specific surface area, which intensifies internal demagnetizing fields and magnetic flux pinning, thereby reducing saturation magnetization and coercivity. Simultaneously, excessive water demand caused by fine particles suppresses geopolymer gel formation, resulting in increased porosity and decreased mechanical strength. COMSOL simulations confirm the development of localized demagnetizing fields around smaller Fe particles. Indoor induction heating tests further reveal that the incorporation of SMG improved the energy conversion efficiency during induction heating by 19.4 % when the Fe powder particle size was not less than 150 μm, demonstrating its potential for energy-responsive, structure-integrated infrastructure.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"346 ","pages":"Article 116182"},"PeriodicalIF":6.6,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144685710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Silica aerogel composites with excellent thermal insulation for building applications","authors":"Song He ,&nbsp;Hongcheng Li ,&nbsp;Yuling Zhang ,&nbsp;Hongliang Sheng ,&nbsp;Yajun Huang","doi":"10.1016/j.enbuild.2025.116169","DOIUrl":"10.1016/j.enbuild.2025.116169","url":null,"abstract":"<div><div>In high altitude regions with low air pressure, the thermal insulation performance and thermal stability of building insulation materials are more demanding. Developing effective thermal insulation materials for buildings is crucial for achieving energy efficiency and reducing emissions. In this study, a modified glass fiber reinforced aerogel (GFRA) composite was successfully synthesized using inexpensive water glass as the raw material. Experimental results show that GFRA is significantly hydrophobic with water contact angle of 146° and low thermal conductivity of 0.018 W/(m·K). The complex network structure within the fiber mat and the high loading ratio of the aerogel contribute to the excellent thermal insulation properties of GFRA. Measurements indicate that 2.25 mm thick GFRA can maintain insulation temperature of 38.3 °C when exposed to 90 °C. Under simulated low pressure conditions in environmental chamber, with pressure of 0.06 MPa, the GFRA’s insulation temperature increased significantly, reaching 227.3 °C at approximately 400 °C. The thermogravimetric analysis confirmed the material’s excellent thermal stability, with maximum total mass loss limited to 7 % while maintaining significant hydrophobicity with water contact angle of 120.3°<!--> <!-->in high-temperature environments. GFRA’s properties demonstrate its exceptional thermal insulation capabilities, making it highly suitable for building applications.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"346 ","pages":"Article 116169"},"PeriodicalIF":6.6,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144685789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Domain-invariant representation learning for generalizable chiller model: a real-world case study","authors":"Jin Hong Kim ,&nbsp;Young Sub Kim ,&nbsp;Hyeong Gon Jo ,&nbsp;Jeeye Mun ,&nbsp;Cheol Soo Park","doi":"10.1016/j.enbuild.2025.116168","DOIUrl":"10.1016/j.enbuild.2025.116168","url":null,"abstract":"<div><div>Data-driven models have been widely adopted due to their ease of modeling and good prediction accuracy. However, they face a challenge in ensuring predictive performance on <em>unseen</em> datasets, especially when the training dataset is imbalanced. For this reason, Transfer learning (TL), that leverages source domain datasets, has attracted attention. However, TL is often limited by its <em>one-way</em> learning process, which transfers knowledge from a data-rich (<em>source</em>) domain to a data-scarce (<em>target</em>) domain. In this regard, this study proposes a Domain-Invariant Representation Learning (DIRL) modeling approach that extracts generalizable knowledge through a <em>bidirectional</em> learning framework. To realize it, the authors develop a DIRL chiller model using two real-life chillers’ datasets where hidden layers are shared within an artificial neural network (ANN). Relevant data were collected at the sampling time of one hour between April 2020 and December 2023.</div><div>For comparison, the following five simulation models of the two-chillers were cross-compared in terms of model accuracy and extrapolation ability: (1) an individual ANN model, (2) an ANN model developed by combined data from two chillers, (3) a transfer learning model developed by the other chiller data, (4) a transfer learning model developed by a physics-based model, and (5) a DIRL model. The predictive performance of all five models was satisfactory for the target chiller by achieving a mean average error (MAE) = 0.41–0.49 and a coefficient of the variation of the root mean square error (cvRMSE) = 7.0–8.3 % for the coefficient of performance (COP). In contrast, the combined-data ANN and DIRL presented superior predictive performance by achieving an MAE = 0.10–0.13 and a cvRMSE = 2.0–3.1 %. The DIRL model demonstrated best superior extrapolation ability with an MAE = 0.36 and a cvRMSE = 8.5 %. As a result, the DIRL model achieved improvements of 0.81 of MAE and 16.4 % of cvRMSE for chiller COP prediction, and 0.83 in MAE and 17.4 % in cvRMSE for extrapolation ability, compared to the individual ANN model. By leveraging bidirectional learning with combined datasets and a shared feature extractor, the DIRL chiller model can infer general chiller knowledge while maintaining a consistent predictive performance in terms of both accuracy and extrapolation ability.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"346 ","pages":"Article 116168"},"PeriodicalIF":6.6,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144685791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling for coupled thermal and humidity environments in spaces with impinging jet ventilation using zonal model theory","authors":"Peng Du ,&nbsp;Xiao Ye ,&nbsp;Wentao Xi ,&nbsp;Yanming Kang ,&nbsp;Ke Zhong","doi":"10.1016/j.enbuild.2025.116171","DOIUrl":"10.1016/j.enbuild.2025.116171","url":null,"abstract":"<div><div>Thermal stratification, due to the coupling of heat and moisture transfer, also results in humidity stratification. While many models address thermal stratification in impinging jet ventilation (IJV) systems, few consider its humidity distribution. This study develops a zonal model that simultaneously predicts vertical temperature and humidity profiles for IJV. The space is vertically divided into sub-zones, with mass and energy balance equations established for each. A critical parameter in the model is the inter-zonal mass flow rate (<em>m</em>), which governs the exchange of air between adjacent zones and thus determines the transport of heat and moisture. To quantify this parameter, CFD simulations are performed under various operating conditions, and a height-dependent function is derived for <em>m</em>. The model’s accuracy is validated by comparing the predicted temperature and humidity distributions with numerical results. The results show that the proposed model achieves a mean relative error of 6.95 % for temperature prediction and of 1.41 % for humidity prediction. Besides, the proposed model is compared with original zonal model considering only heat transfer. It reveals that the maximum temperature prediction discrepancy for the original model reaches up to 5.03 °C, whereas the proposed zonal model shows a discrepancy of only 1.99 °C. This underscores the importance of considering the coupling of air temperature and moisture in indoor environmental studies. The current model not only provides a more accurate description of temperature distributions for IJV but also enables the prediction of indoor humidity distribution—a capability that the original zonal model lacks.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"346 ","pages":"Article 116171"},"PeriodicalIF":6.6,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144679980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 fault diagnosis strategy for refrigerant leakage of the air conditioning system in high-efficiency internet data centers","authors":"Chuang Yang,&nbsp;Shikai Tan,&nbsp;Huanxin Chen","doi":"10.1016/j.enbuild.2025.116176","DOIUrl":"10.1016/j.enbuild.2025.116176","url":null,"abstract":"<div><div>Internet data centers (IDCs) are large energy consumers and the IDCs air conditioning system will inevitably experience refrigerant leakage due to long-term and non-stop operation, which increases the risk of computer services’ health and leads to unnecessary energy waste. Therefore, this paper presents a fault diagnosis strategy for refrigerant leakage of the IDCs air conditioning systems based on deep neural network (DNN). The <em>Gini</em> coefficient is utilized to choose important feature variables. Then a fault diagnosis model was developed based on the DNN. On-the-spot experiments of an IDCs air conditioning system are conducted to collect practical operational data to validate this strategy. Refrigerant charge under normal conditions and five various leakage levels are investigated. The offline data of IDCs air conditioning system are collected to train the DNN models, testing results show that the proposed DNN model has good classification performance and generalization ability. The accuracy, geometric mean accuracy (GMA), false alarm rate (FAR), missing alarm rate (MAR) reach to 99.99%, 99.92%, 0%, 0%, respectively. A small amount of online data was used to update the model, the classification performance of the model will be greatly improved, which shows that the proposed DNN model has great potential for online data classification. Accuracy increase by 26.62%, from 73.66% to 93.27%, FAR decrease from 32.82% to 0%.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"346 ","pages":"Article 116176"},"PeriodicalIF":6.6,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144711700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards energy flexible commercial buildings: Machine learning approaches, implementation aspects, and future research directions","authors":"M.M.A.L.N. Maheepala ,&nbsp;Hangxin Li ,&nbsp;Dilan Robert ,&nbsp;Lasantha Meegahapola ,&nbsp;Shengwei Wang","doi":"10.1016/j.enbuild.2025.116170","DOIUrl":"10.1016/j.enbuild.2025.116170","url":null,"abstract":"<div><div>Commercial buildings encounter considerable challenges in predicting and managing energy flexibility, arising from the complexity of their energy systems and the interdependencies among system components and building thermal mass. Nonetheless, the emergence of “smarter buildings” creates significant opportunities for applying machine learning (ML) techniques in energy flexibility. These methods provide significant benefits to commercial building owners, with multiple states integrating energy flexibility provisions for commercial buildings into their regulatory frameworks. This paper provides a systematic review of the role of commercial buildings in energy flexibility studies, with a particular emphasis on ML techniques used in the characterisation, optimisation, and forecasting of energy flexibility. Furthermore, it examines the direct monetary and non-direct monetary benefits and practical challenges associated with integrating flexibility concepts into commercial buildings, as well as the policy and regulatory frameworks that facilitate flexibility implementations. A comprehensive understanding of these aspects will be beneficial for developing robust frameworks that enhance the adaptive capacity of commercial buildings, thus enabling their seamless integration into dynamic energy markets while supporting grid stability and sustainability objectives.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"346 ","pages":"Article 116170"},"PeriodicalIF":6.6,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144685711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Approaching the single-family building to the zero residential building status by implementing photovoltaic panels and external wall-roof pergolas for different locations in the Western Serbia region","authors":"Aleksandar Nešović ,&nbsp;Aleksandar Radaković ,&nbsp;Dragan Cvetković ,&nbsp;Robert Kowalik ,&nbsp;Igor Saveljić","doi":"10.1016/j.enbuild.2025.116173","DOIUrl":"10.1016/j.enbuild.2025.116173","url":null,"abstract":"<div><div>With the legislative strengthening of the Energy Efficiency Directive in October 2023, Europe established a new green energy policy that mandates reducing total final energy consumption to 763 Mtoe by 2030. Given that the residential building sector currently accounts for approximately 25 % of this consumption, it is clear that promoting energy-efficient residential buildings will be significantly intensified in the near future.</div><div>Following current trends, this paper critically investigates the energy, ecological and economic aspects of active (photovoltaic panels) and passive (external wall-roof pergolas) solar systems to approach the single-family building to the zero residential building status in the Western Serbia region for the following two main reasons: (1) Serbia (the same applies to the Balkan Peninsula) represents critical link in the European energy transformations chain and (2) solar potential for a moderate continental climate is about 40% higher than the European average.</div><div>All three residential building models (building without solar systems – scenario S1, building with photovoltaic panels – scenario S2 and building with photovoltaic panels and external wall-roof pergolas – scenario S3) were created in the Google SketchUp software following the Serbian Rulebook on Energy Efficiency for New Buildings. All thermo-technical systems (home appliances, internal lighting, water heating, space heating – central heating system with pellet boiler and radiators, space cooling – individual air-conditioner units, photovoltaic panels and pergolas) and people occupancy are simulated using the EnergyPlus software.</div><div>Based on the conducted simulations and obtained results (for 10 different locations in the adopted region) the following main conclusions can be drawn: (1) the Western Serbia region is suitable for green (sustainable) architecture and energy-efficient residential buildings, (2) depending on the location parameters, pergolas can reduce the area of photovoltaic panels by 0.92–5.07 m² without endangering the zero-energy residential building status, (3) thermo-technical systems based on renewable energy sources for space heating and cooling positively contribute to the zero-emission residential building status (carbon footprint), but not always zero-cost residential building status and (4) zero residential building concept is not possible without responsible occupancy behavior.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"346 ","pages":"Article 116173"},"PeriodicalIF":6.6,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144679978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 novel interpolation method for high temporal-resolution electricity usages based on volatility quantification and pattern extraction","authors":"Yinao Zhou ,&nbsp;Ruoxi Geng ,&nbsp;Xuyuan Kang ,&nbsp;Huiming Xu ,&nbsp;Xiao Wang ,&nbsp;Rui Li ,&nbsp;Da Yan","doi":"10.1016/j.enbuild.2025.116174","DOIUrl":"10.1016/j.enbuild.2025.116174","url":null,"abstract":"<div><div>As the penetration rate of renewable energy in the power grid increases, it is essential to reduce energy consumption and carbon emissions associated with buildings. Interactions between a building’s microgrid and power grids have attracted significant research attention. However, most building energy data have been collected at 1-hour intervals, which mismatches the 15-min intervals used in current power grid control and demand responses. Variations in building electricity data at different temporal time-steps were observed in electricity load distribution, daily peak usage, and volatility values, and existing high-resolution interpolation methods failed to quantify these features. In this study, we developed a novel high temporal-resolution interpolation method for hourly building electricity usage data, using volatility quantification and pattern extraction. The proposed methodology includes two folds: analyzing daily fluctuation amplitudes and analyzing hourly fluctuation patterns. Validation results of the proposed method on high-resolution electricity data of 19 commercial complexes in North and Northeast China was conducted, and compared to a baseline zero-order interpolation model. The proposed method significantly decreased the median KS statistic from 0.0155 to 0.0048 for electricity load distribution, from 0.0712 to 0.0356 for daily electricity peak usage distribution, and from 0.6932 to 0.1726 for daily electricity VF value distribution. These results indicate that the proposed method accurately captures the critical features of high-resolution building electricity usage profiles and improved the quantification of electricity usage volatility and randomness. Additionally, the proposed method enhanced the precision of the analysis of operational energy costs and battery cycles, supporting the design and operation of the building microgrid systems.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"346 ","pages":"Article 116174"},"PeriodicalIF":6.6,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144714237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy performance optimization and economic analysis of SVG-insulated facades","authors":"Hao Zhou ,&nbsp;Jinqing Peng ,&nbsp;Wenhao Zhu ,&nbsp;Hongxing Yang","doi":"10.1016/j.enbuild.2025.116165","DOIUrl":"10.1016/j.enbuild.2025.116165","url":null,"abstract":"<div><div>Solar PV vacuum glazing (SVG) insulated façades enhance building fire safety and energy efficiency due to their high thermal resistance. While increasing the thermal resistance of SVG-insulated façades reduces building operational energy consumption, it may also limit heat dissipation, negatively impacting PV generation. To assess the overall energy performance of SVG-insulated facades, this study developed numerical models, which were validated using outdoor experimental data. Parametric optimization simulations were then conducted to maximize energy savings of SVG-insulated facades, focusing on three critical aspects: (i) vacuum glazing properties; (ii) PV module efficiency; and (iii) the air cavity thickness. The simulation results indicate that the optimized configuration reduces annual wall-related energy consumption by 50 %-59 % across five Chinese cities, compared to the non-optimized case. Notably, the wall-related energy consumption excludes contributions from transparent windows and internal heat sources. Furthermore, an economic analysis was performed to evaluate the profitability of SVG-insulated façades, revealing a payback period of 2.51–6.46 years and a return on investment (ROI) ranging from 189 % to 612 % over a 25-year lifespan. Consequently, this study underscores the great energy-saving potential and economic viability of SVG-insulated façades, supporting their implementation in engineering projects.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"346 ","pages":"Article 116165"},"PeriodicalIF":6.6,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144664705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the performance of portable gas-phase air cleaners and Implications for their use in buildings","authors":"Yiming Xiang ,&nbsp;Kanta Amada ,&nbsp;Asit Kumar Mishra ,&nbsp;Shin-ichi Tanabe ,&nbsp;Lei Fang ,&nbsp;Pawel Wargocki","doi":"10.1016/j.enbuild.2025.116152","DOIUrl":"10.1016/j.enbuild.2025.116152","url":null,"abstract":"<div><div>We examined the performance of two different brands of gas-phase air cleaners using Proton Transfer Reaction Time-of-Flight Mass Spectrometry (PTR-ToF-MS) measurements; both air cleaners used activated carbon filters. The measurements were made in a typical office with furnishing and two occupants. The air cleaners were examined under multiple airflow settings and with different numbers of active units. The distinct non-negligible 44 mass-to-charge ratio (<em>m</em>/<em>z</em>) signals for ions representing various organic compounds or their fragments were identified by PTR-ToF-MS. Operation of air cleaners consistently reduced the magnitude of twenty-two of them. We analysed the decay of the <em>m</em>/<em>z</em> signals to characterize the performance of air cleaners in terms of their pollutant removal effect. We observed that it was different for the different <em>m</em>/<em>z</em> signals, suggesting different removal efficiencies for various compounds or their fragments. Removal efficiency decreased with higher airflow rates through the air cleaners though the rate of clean air delivered by them was higher. Our results document that describing the performance of gas-phase air cleaners must include reporting of removal effects for different organic compounds along with the clean air delivery rate. Alternatively, target compounds can be identified and their removal efficiencies reported together with the air cleaning effect. The present work describes the methodological approach that can guide the revision of current practice and standards for evaluating the performance of gas-phase air cleaners. More studies using this methodological framework can lead towards greater adoption and use of gas-phase air cleaners in sustainable and healthy buildings.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"346 ","pages":"Article 116152"},"PeriodicalIF":6.6,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144664706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}