Journal of building engineering最新文献

{"title":"Quantifying the shiftable potential of peak loads under rooftop photovoltaics and rural household load matching: Decomposition and uncertainty characterization","authors":"Ding Gao ,&nbsp;Xingli Ding ,&nbsp;Ningrui Liu ,&nbsp;Xudong Yang","doi":"10.1016/j.jobe.2026.116171","DOIUrl":"10.1016/j.jobe.2026.116171","url":null,"abstract":"<div><div>The development of microgrid systems centered on rooftop photovoltaics (PV) is a key pathway for promoting clean energy transitions. Accurate characterization of electricity load profiles is essential for mitigating the mismatch between PV generation and electricity demand. Existing studies have largely focused on typical load pattern characterization but have not sufficiently explored the features of peak load behavior embedded in high-resolution, minute-level load data and their potential for shiftable load matching with PV. To address this gap, this study proposes a shiftable load matching potential assessment framework that integrates backward uncertainty modeling with forward scenario simulation. This framework was applied to real-world rural-load datasets. A peak load event identification algorithm based on power jump differentials is introduced, and a multi-parameter uncertainty modeling approach for peak load events is developed using a “load decomposition–reconstruction” strategy. Subsequently, assuming that loads can be optimally shifted within the maximum allowable time window, a Monte Carlo simulation based on Latin Hypercube Sampling was employed in conjunction with multiple PV output scenarios to systematically evaluate the matching potential of the shiftable loads (<em>MP</em>_<em>SL</em>). The results show that the proposed peak load detection method effectively isolates the peak load events from the base load, reducing the daily coefficient of variation by an average of 47.2%. These peak events exhibited multimodal distributions, and have short-duration and high-frequency characteristics. Although enhancing the load shiftability increases <em>MP</em>_<em>SL</em>, the potential declines rapidly once the time-cost coefficient exceeds 0.4, reflecting a clear benefit–cost trade-off. Furthermore, <em>MP</em>_<em>SL</em> increases rapidly with PV capacity, but shows diminishing marginal gains that eventually stabilize. The proposed framework provides theoretical support for evaluating the potential of flexible energy resources in rural areas.</div></div>","PeriodicalId":15064,"journal":{"name":"Journal of building engineering","volume":"125 ","pages":"Article 116171"},"PeriodicalIF":7.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147850884","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":"Daylight-linked lighting control sensing: Real-time prediction of daylight illuminance distribution using non-intrusive image","authors":"Zulin Zhuang ,&nbsp;Lin Lin ,&nbsp;Yan Lin ,&nbsp;Yu Bian","doi":"10.1016/j.jobe.2026.116166","DOIUrl":"10.1016/j.jobe.2026.116166","url":null,"abstract":"<div><div>An important issue for the effective operation of a daylight-linked control (DLC) lighting system is the accurate prediction of indoor daylight illuminance in real time, and this process of acquiring signal data is known as control sensing. Unlike existing control schemes that use distributed photo-sensors or images monitoring interior pixels, this study proposed a multimodal deep learning framework that can predict indoor workplane illuminance distributions in real time using non-intrusive images with temporal and spatial features. This approach achieves accurate predictions without being affected by space occupancy by extracting features only from the daylight source, the side-lit window areas. A field experiment was conducted in a test room in Guangzhou, China, where 17,344 samples were collected for model training and validation. The model was evaluated through 10-fold leave-one-day-out cross-validation and a completely unseen test day. The selected model achieved R² values above 0.85 on the unseen test day, with 90.8% of predictions falling within ±50 lx of measured values, demonstrating sufficient accuracy for DLCs applications.</div></div>","PeriodicalId":15064,"journal":{"name":"Journal of building engineering","volume":"125 ","pages":"Article 116166"},"PeriodicalIF":7.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147851425","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":"Continual learning-enhanced data-driven modeling: A method for improving building load prediction model performance","authors":"Zhe Tian ,&nbsp;Mingwei Song ,&nbsp;Yakai Lu ,&nbsp;Wenjie Song ,&nbsp;Jide Niu","doi":"10.1016/j.jobe.2026.116116","DOIUrl":"10.1016/j.jobe.2026.116116","url":null,"abstract":"<div><div>Accurate building load forecasting is pivotal for optimizing energy systems, yet it remains challenging due to complex and variable load patterns under real-world operating conditions, especially for regional building complexes. Conventional single-task learning models often fail to capture this variability, while previous multi-model approaches require manual or simplistic task partitioning, limiting their practicality. To overcome these limitations, this study proposes a novel, fully data-driven continual learning framework that integrates an error-based task partitioning strategy with the Elastic Weight Consolidation (EWC) algorithm. This method autonomously identifies distinct load patterns from prediction errors and incrementally learns them within a unified model, effectively mitigating catastrophic forgetting. Validated on a real-world case study of a regional cooling system serving mixed building types, our approach significantly enhances forecasting accuracy. With the optimized parameter settings, it reduces the mean absolute percentage error (MAPE) from 16.45% to 10.36%, successfully minimizing the number of high-error predictions. The proposed method provides a robust, scalable, and practical solution for improving load forecasting performance in complex building energy management applications without incurring the overhead of managing multiple models.</div></div>","PeriodicalId":15064,"journal":{"name":"Journal of building engineering","volume":"125 ","pages":"Article 116116"},"PeriodicalIF":7.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147851428","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":"Physicochemical, mechanical, and microstructural properties of ground granulated blast-furnace slag-steel slag-carbide slag ternary binders under carbonation curing","authors":"Wene Ma ,&nbsp;Liyuan Tong ,&nbsp;Tiantian Zhang ,&nbsp;Shuwen Zheng ,&nbsp;Hao Wu","doi":"10.1016/j.jobe.2026.116151","DOIUrl":"10.1016/j.jobe.2026.116151","url":null,"abstract":"<div><div>The accumulation of industrial solid wastes such as ground granulated blast-furnace slag (GGBS), steel slag (SS), and carbide slag (CS) poses serious environmental challenges but also provides potential resources for sustainable construction. In this study, ternary GGBS-SS-CS composite cementitious materials were prepared, and their physicochemical properties, mechanical performance, stress-strain-resistivity behavior, carbonation depth, and microstructural evolution under carbonation curing were systematically investigated through orthogonal experiments and microscopic analyses. Unlike previous studies limited to single-waste carbonation systems, this work demonstrates the distinctive synergy of the GGBS-SS-CS ternary blend. CS provides Ca(OH)₂ for activating GGBS and SS, while GGBS and SS supply reactive SiO₂ and Al₂O₃ that consume excess Ca(OH)₂ and facilitate CaCO₃ formation. This complementary chemistry creates a balanced hydration-carbonation environment that single systems cannot achieve. Results showed that both carbonation time and mix ratio significantly affected mechanical properties. The optimal ratios were identified as (GGBS + SS):CS = 2:3 (GGBS:SS = 2:1), providing a balanced alkaline environment and sufficient reactive components for effective hydration-carbonation synergy. A carbonation curing duration of 4-6 days is recommended. At this mix ratio, compressive and flexural strengths increased by 125.85% and 315.70%, respectively, compared with ordinary curing after 6 days. Resistivity and pH monitoring confirmed ion consumption and CaCO₃ formation during carbonation, while stress-strain-resistivity curves revealed characteristic electrical responses to densification, cracking, and failure. Carbonation depth analysis further verified progressive CO₂ penetration, reaching 15.73 mm at the optimal ratio. XRD and SEM results demonstrated that CaCO₃ and C-(A)-S-H were the dominant products under carbonation curing. The dense microstructure formed by CaCO₃ filling and C-(A)-S-H binding explained the superior mechanical performance. Overall, this study highlights the potential of carbonation curing to enhance the mechanical performance and microstructural densification of GGBS-SS-CS ternary binders, while simultaneously contributing to CO₂ utilization and sustainable development in construction materials.</div></div>","PeriodicalId":15064,"journal":{"name":"Journal of building engineering","volume":"125 ","pages":"Article 116151"},"PeriodicalIF":7.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147851473","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":"Machine learning-based method to maximize allowable axial load for green remodeling or vertical extension of existing reinforced concrete moment frame buildings","authors":"Heejin Hwang ,&nbsp;Kihak Lee ,&nbsp;Jiuk Shin","doi":"10.1016/j.jobe.2026.116096","DOIUrl":"10.1016/j.jobe.2026.116096","url":null,"abstract":"<div><div>Green remodeling or vertical extension of existing reinforced concrete (RC) building structures is one of green building strategies to reduce the carbon emissions rather than constructing new buildings. The amplified gravity loads from the remodeling measures can lead to the seismic vulnerability of existing building frames. This paper proposes a machine-learning (ML) based method that rapidly estimates allowable axial loads on the building frames using brief information and establishes stiffness- and ductility-based retrofit schemes to maximize the allowable loads. To accomplish this goal, a sequential approach with three learning models (identification model of failure modes, and prediction models of seismic performance for as-built and mass-amplified conditions) was adopted as follows: (1) predicting seismic performance for as-built conditions, (2) estimating additional axial loading by varying the structural masses within the target performance, and (3) maximizing additional axial loading by varying the retrofit-related variables. Through the ML-based method, the retrofit schemes maximizing the allowable axial loads on the existing RC frames were derived for various combinations of stiffness and confinement ranges. The increase in the allowable axial loads by increasing column stiffness was limited within the low level of confinement, while the allowable axial load was continuously increased by additional stiffness withing the high level of confinement. Therefore, combined retrofit schemes ensuring adequate ductility capacities were needed to maximize the axial-load carrying capacity on the existing RC building frames.</div></div>","PeriodicalId":15064,"journal":{"name":"Journal of building engineering","volume":"125 ","pages":"Article 116096"},"PeriodicalIF":7.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147736241","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":"Membrane-based quasi-isothermal humidifier: Performance characteristics and energy–exergy analysis for HVAC applications","authors":"Seong-Yong Cheon ,&nbsp;Hye-Jin Cho ,&nbsp;Jae-Weon Jeong","doi":"10.1016/j.jobe.2026.116139","DOIUrl":"10.1016/j.jobe.2026.116139","url":null,"abstract":"<div><div>Maintaining appropriate indoor humidity during winter is critical for occupant health and comfort. However, conventional heating, ventilation, and air-conditioning (HVAC) humidifiers, such as steam injection, ultrasonic atomization, and direct evaporative systems, often involve either high-grade heat consumption, aerosol carryover concerns, or additional reheating requirements. In this study, a membrane-based quasi-isothermal humidifier (QIMH) was investigated as an alternative humidification approach for HVAC applications. A two-dimensional steady-state heat- and mass-transfer model for a cross-flow hollow-fiber membrane module was developed and validated against laboratory-scale experimental data. Parametric simulations were then conducted by varying inlet water temperature and the air and water flow rates to identify the operating region satisfying the study-defined quasi-isothermal criterion of |ΔT_a| ≤ 0.5 °C. The results showed that quasi-isothermal operation is achieved when the inlet water temperature is maintained close to the inlet air temperature and the water flow rate is sufficiently high to supply latent heat without causing appreciable sensible heating or cooling of the air. Under these conditions, the membrane humidifier delivered humidification with near-theoretical thermal efficiency while avoiding the downstream reheating penalty associated with evaporative humidification. An HVAC-oriented exergy comparison under identical outlet-air conditions further showed that the membrane humidifier achieved the highest average exergy efficiency (10.2%), followed by evaporative humidification with reheat (8.9%) and steam injection (5.4%). These results demonstrate the thermodynamic potential of membrane-based quasi-isothermal humidification using low-grade heat in winter HVAC applications.</div></div>","PeriodicalId":15064,"journal":{"name":"Journal of building engineering","volume":"125 ","pages":"Article 116139"},"PeriodicalIF":7.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147736330","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":"Preparation and experimental investigation of thermal and mechanical properties of sandwiched aerogel-PCM (APCM) tiles","authors":"B. Pitchia Krishnan ,&nbsp;S. Suresh ,&nbsp;Neha Hebalkar ,&nbsp;R. Seeni Thangaraj Pandian ,&nbsp;Seepana Praveenkumar","doi":"10.1016/j.jobe.2026.116174","DOIUrl":"10.1016/j.jobe.2026.116174","url":null,"abstract":"<div><div>This study aims to synthesis eutectic shape stabilized phase change material to achieve desired phase transition temperature and high latent heat for thermal energy storage in building applications. Further, the present work involves developing the innovative combination of aerogel and phase change material-incorporated tile (APCM Tile) to obtain indoor thermal comfort. Differential scanning calorimetry analysis shows that the latent heat and phase transition temperature of eutectic shape stabilized phase change material are 194.8 J/g and 35 °C for heating and 183.4 J/g and 34 °C for cooling respectively. Indoor experiments are conducted for analyzing and comparing the thermal performance of APCM tiles with cement tiles by varying four different heat inputs such as 40W, 50W, 60W, and 70W of the infrared lamp used as a heat source to achieve the real-time building surface temperature range from 30 to 50 °C. The thermal performance of tiles are analyzed through thermal metrics such as surface temperature difference of tile, decrement factor, time lag, and thermal performance index. The experimentation results revealed that the APCM tile shows higher surface temperature difference and time lag and lower decrement factor than cement tile and APCM tile demonstrates acceptable thermal performance index of 73.3, 91.92, 115.3 and 123.9 for the heat inputs of 40W, 50W, 60W, and 70W respectively. The compressive strength, flexural strength and water absorption rate of the APCM tiles are found to be 70 MPa, 30 MPa and 13.3%. Overall, this research contributes to sustainable building solutions by providing insights into the effectiveness of phase change material technology for a more energy-efficient future.</div></div>","PeriodicalId":15064,"journal":{"name":"Journal of building engineering","volume":"125 ","pages":"Article 116174"},"PeriodicalIF":7.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147850872","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":"Quantifying the earthquake-related carbon emissions of steel moment-resisting framed buildings and their sensitivity to modeling and design decisions","authors":"Shiva Baddipalli,&nbsp;Nicholas Leavitt,&nbsp;Mohsen Zaker Esteghamati","doi":"10.1016/j.jobe.2026.116190","DOIUrl":"10.1016/j.jobe.2026.116190","url":null,"abstract":"<div><div>The construction sector is a major contributor to global carbon emissions, motivating quantifying and minimizing the environmental impacts of buildings over their life cycle. While whole-building life cycle assessment (LCA) is increasingly applied to evaluate embodied carbon, most existing studies do not account for earthquake-induced damage and post-event repair activities. This study quantifies the earthquake-related global warming potential (GWP) for 60 modern steel framed buildings with varying geometries and designs. Additionally, the influence of two methodologies on the estimated GWP was compared: (a) the detailed repair description LCA approach using environmental consequence functions, and (b) the simplified repair cost ratio (RCR) approach using three different seismic loss methodologies based on FEMA P-58, HAZUS, and story loss function. The results show that earthquake-related GWP contributes 20%-72% of total embodied GWP across different estimation methods. Additionally, although non-structural components account for only 15% of the initial embodied GWP, they produce nearly 10 times more earthquake-related GWP than structural elements, with gypsum wall assemblies and façade systems alone exceeding the combined earthquake-related emissions of all structural components by 3 to 6 times. Furthermore, simplified repair cost ratio approaches can substantially overestimate earthquake-related GWP for multi-story buildings, with the HAZUS-based method yielding estimates up to 20 times higher than the repair description approach for 19-story buildings, while the story loss function method provides the closest agreement. Lastly, a sensitivity analysis demonstrates the importance of key design decisions on the trade-offs between seismic performance and environmental impact. A Spearman correlation analysis indicates that conventional seismic design parameters strongly reduce expected annual loss (|<em>ρ</em>| = 0.55–0.87) but have negligible influence on earthquake-related GWP (|<em>ρ</em>| &lt; 0.31).</div></div>","PeriodicalId":15064,"journal":{"name":"Journal of building engineering","volume":"125 ","pages":"Article 116190"},"PeriodicalIF":7.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147850871","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":"Lightweight large language models for intent recognition and action invocation in building energy management","authors":"Deli Liu,&nbsp;Xiaoping Zhou,&nbsp;Yu Li","doi":"10.1016/j.jobe.2026.116170","DOIUrl":"10.1016/j.jobe.2026.116170","url":null,"abstract":"<div><div>Advancements in artificial intelligence have transformed intelligent building management by enabling natural language-driven control over complex operations. Large-parameter large language models (LLMs) demonstrate strong capability in interpreting free-form user instructions and routing them to diverse building functions. However, their high computational cost and latency make them impractical for edge or real-time deployment. In contrast, small-parameter LLMs offer higher efficiency but often lack the robustness required for conditional reasoning and multi-task invocation. This study develops a task planner based on a fine-tuned small-parameter LLM and formalizes its reasoning process as a Probabilistic Constraint Satisfaction Problem (PCSP). The PCSP extends the classical CSP framework into a probabilistic domain to enable robust intent recognition and action invocation under linguistic and sensor uncertainty. By integrating dual-branch encoding, a differentiable comparator, consistency regularization, and twin sampling, the planner generates interpretable, low-latency execution plans for conditional and multi-step tasks. Trained on a synthetic dataset and validated against manually annotated real-world commands, the planner achieves 0.90 intent F1, 0.88 gate accuracy, and 0.89 action accuracy, approaching GPT-4o few-shot results (0.94, 0.93, 0.92) with only 67 million parameters and 4.75 ms inference latency. The findings show that a fine-tuned small-parameter LLM, when structured through PCSP reasoning, can achieve high accuracy, interpretability, and computational efficiency for natural-language-driven building operations. This work demonstrates that fine-tuned small-parameter LLMs can rival large-parameter LLMs, enabling scalable, privacy-preserving building intelligence.</div></div>","PeriodicalId":15064,"journal":{"name":"Journal of building engineering","volume":"125 ","pages":"Article 116170"},"PeriodicalIF":7.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147850874","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":"Cement electrolytes with interconnected microporous structures for cement solid state batteries","authors":"Ziyu Liu ,&nbsp;Shihui Liu ,&nbsp;Kang Du ,&nbsp;Yanhai Liu ,&nbsp;Beatrice Magombana ,&nbsp;Yinghao Liu ,&nbsp;Richard Mu ,&nbsp;Lin Li","doi":"10.1016/j.jobe.2026.116178","DOIUrl":"10.1016/j.jobe.2026.116178","url":null,"abstract":"<div><div>Cement solid-state batteries have attracted significant attention in recent years due to their potential for structural energy storage integration. However, traditional cement-based electrolytes suffer from low porosity and poorly interconnected pore structures, which limit its ion-transport pathways and severely affect electrochemical performance.</div><div>In this paper, porous cement electrolytes with three-dimensional interconnected microporous structures were prepared by a facile foaming strategy, and their microstructures and electrochemical properties were systematically evaluated by cyclic voltammetry, electrochemical impedance spectroscopy and scanning electron microscopy. Cement solid-state batteries were constructed by combining nickel-iron electrodes and tested for galvanostatic charge-discharge. The results showed that the three-dimensional connected pore structure provides abundant and continuous migration channels for ions, which significantly improves the electrochemical performance of the cement-based electrolytes, and their ionic conductivity reaches 2.091 mS/cm, which was better than that of the cement-based electrolytes reported in the literature so far. The cement-based solid-state batteries constructed based on this electrolyte exhibited excellent energy output capability with an average energy density of 13.01 Wh/m² and good cycling stability. This study provided practical structural design ideas for realizing the high performance of cement-based energy storage materials and offers opportunities for further optimization and future development.</div></div>","PeriodicalId":15064,"journal":{"name":"Journal of building engineering","volume":"125 ","pages":"Article 116178"},"PeriodicalIF":7.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147850885","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}