Construction and Building Materials最新文献

{"title":"Post-earthquake characterisation of building stones used in Hatay","authors":"Yunus Arca ,&nbsp;Kerem Kurnaz ,&nbsp;Medine Ispir ,&nbsp;Sinan Acikgoz ,&nbsp;Hazal Ozlem Ersan ,&nbsp;Pascal Lava ,&nbsp;Anil Ozdemir","doi":"10.1016/j.conbuildmat.2025.143529","DOIUrl":"10.1016/j.conbuildmat.2025.143529","url":null,"abstract":"<div><div>A significant part of the Hatay historical building stock is constructed of stone masonry and suffered extensive damage during the 2023 Kahramanmaraş earthquakes. Two years after the earthquakes, restoration and rebuilding continues. To aid these activities, this study establishes a reference dataset describing the chemical, physical, and mechanical properties of building stones used in the province. To determine these properties, stone samples were collected from 16 buildings and were first subjected to non-destructive mechanical tests (specifically, Ultrasonic Pulse Velocity and Schmidt hammer tests). Further characterisation was then conducted in the laboratory, where ground and cut samples were subjected to X-ray fluorescence (XRF) tests to determine stone types, and Impact Excitation of Vibration (IEV), flexural and compressive strength tests to determine mechanical properties. During the mechanical tests, stereo Digital Image Correlation (DIC) was used to extract detailed information on material response, considering the limited availability of samples. The results highlight the dominant use of limestone in the province, with compressive strengths varying from ∼3 to ∼100 MPa. Linear correlations are revealed between the mechanical parameters and a good agreement is observed between on-site and laboratory results. This paves the way for using simple non-destructive site measurements and correlation equations to quickly estimate stone properties for future restoration and reconstruction activities.</div></div>","PeriodicalId":288,"journal":{"name":"Construction and Building Materials","volume":"495 ","pages":"Article 143529"},"PeriodicalIF":8.0,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145048022","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":"SHAP-enhanced tree-based regression for predicting the compressive strength of high performance concrete","authors":"Ahmed Abdelghafour Ghrici ,&nbsp;Ali Benzaamia ,&nbsp;Freha Mezzoudj ,&nbsp;Chahreddine Medjahed ,&nbsp;Mohamed Ghrici","doi":"10.1016/j.conbuildmat.2025.143602","DOIUrl":"10.1016/j.conbuildmat.2025.143602","url":null,"abstract":"<div><div>Accurate prediction of concrete compressive strength (CS) is essential for designing sustainable mixtures incorporating supplementary cementitious materials (SCMs) such as fly ash (FA) and blast furnace slag (BFS). This study systematically evaluates five advanced tree-based regression algorithms—Decision Tree, Random Forest, Gradient Boosting, XGBoost, and CatBoost—using the well-established UCI concrete dataset. Hyperparameters were optimized with Optuna’s Bayesian search and validated through five-fold cross-validation. Model performance was assessed on an independent test set using R², RMSE, MAE, and a composite confidence index. Among the models, CatBoost achieved the best predictive accuracy (R² = 0.95; RMSE = 4.05 MPa; MAE = 2.57 MPa), outperforming previously reported methods such as Gradient Boosted Regression Trees, Gaussian Process Regression, and Random Forest. Error-based analysis confirmed its robustness across FA-only, BFS-only, and ternary blends, with variations consistent with known hydration behaviors. To enhance interpretability, SHapley Additive exPlanations (SHAP) were applied, identifying curing age and water-to-binder ratio as the most influential features. The results demonstrate that ensemble boosting methods combined with Bayesian optimization provide a reliable and interpretable framework for predicting the compressive strength of SCM-blended concrete, supporting data-driven mix design and sustainable construction practices.</div></div>","PeriodicalId":288,"journal":{"name":"Construction and Building Materials","volume":"495 ","pages":"Article 143602"},"PeriodicalIF":8.0,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental study and theoretical evaluation of an innovative prefabricated RCS interlocking tenon connection","authors":"Chenglong Wu ,&nbsp;Hao Li ,&nbsp;Ruizhe Sun ,&nbsp;Ben Mou ,&nbsp;Zhe Qu ,&nbsp;Xinpeng Wang ,&nbsp;Zhentao Liu","doi":"10.1016/j.conbuildmat.2025.143606","DOIUrl":"10.1016/j.conbuildmat.2025.143606","url":null,"abstract":"<div><div>To address the shortcomings of existing prefabricated RCS composite joints in connection detailing and the application of high-performance materials, a novel prefabricated reinforced concrete column-steel beam joints (PRCSJs) enhanced with ultra-high performance concrete (UHPC) and based on interlocking tenon connections is proposed. The seismic performance of three PRCSJ specimens was evaluated through low-cycle reciprocating loading tests, with axial compression ratio (<em>n</em>) and post-cast concrete type as experimental parameters. The results indicate that the failure mode of the PRCSJs was beam-end flexural failure. The PRCSJs exhibited full hysteresis curves, with average ductility coefficients and equivalent viscous damping coefficients ranging from 2.76 to 4.88 and 0.28–0.31, respectively. The load-bearing capacity and stiffness degradation were stable, demonstrating favorable seismic performance. Post-cast UHPC can effectively improve the bearing capacity of PRCSJs, enhance the overall deformation performance of PRCSJs, and reduce concrete cracking in the post-cast area. When the <em>n</em> is in the range of 0.15–0.3, increasing the <em>n</em> can effectively improve the initial stiffness, but it will notably reduce the ductility and stiffness degradation performance of PRCSJs. The established finite element model of PRCSJs demonstrates good adaptability and accuracy. The thicknesses of the flange connection plate and cover plate have a significant influence on the load-bearing capacity of PRCSJs, while the effects of other parameters can be considered negligible. PRCSJs were characterized as semi-rigid and partially strength-based joints under lateral drift conditions. The theoretical, experimental, and finite element values of the ultimate flexural capacity agree well, verifying the reliability of the ultimate flexural capacity calculation formula.</div></div>","PeriodicalId":288,"journal":{"name":"Construction and Building Materials","volume":"495 ","pages":"Article 143606"},"PeriodicalIF":8.0,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047999","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":"Development of phosphate mine waste-based geopolymer by mechanosynthesis","authors":"Ghizlane Moutaoukil ,&nbsp;Isabel Sobrados ,&nbsp;Jorge S. Dolado","doi":"10.1016/j.conbuildmat.2025.143573","DOIUrl":"10.1016/j.conbuildmat.2025.143573","url":null,"abstract":"<div><div>This study explores the valorization of phosphate mine by-product—an abundant aluminosilicate-rich waste—through the synthesis of geopolymers using the mechanosynthesis method. While mechanosynthesis has been applied in geopolymer research, this work is the first to employ it by using the phosphate mine waste as a precursor. The geopolymer samples produced by mechanosynthesis (GPMS) were compared with conventionally prepared geopolymer pastes (GPC) to assess their microstructural and mechanical properties. Geopolymer powders (PGP) were prepared by milling a solid blend of phosphate mine waste (YC) and alkaline activators. The YC/alkaline activator ratios were (1.5 and 2.5), Na₂SiO₃/NaOH mass ratios were (1.5, 2.5 and 3.5) and milling times of 10 and 20 min. The obtained GP-P, GP-C and GP-MS were characterized by X-ray diffraction (XRD), Magic-Angle Spinning Nuclear Magnetic Resonance Spectroscopy (²⁹Si and ²⁷Al MAS NMR), particle size distribution and compressive strengths. Milling the raw materials resulted in the development of new crystalline structures. Additionally, the mechanosynthesis process improved the reactivity of the YC, which was evidenced by the observed increase in compressive strength 45 % for mix1 and 26 % for mix2.</div></div>","PeriodicalId":288,"journal":{"name":"Construction and Building Materials","volume":"495 ","pages":"Article 143573"},"PeriodicalIF":8.0,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145048030","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":"Modelling and optimization of viscoelastic flow behaviour of thermoplastic resin modified asphalt binder in dynamic shear domain","authors":"Hakan Yurdakul,&nbsp;Ahmet Münir Özdemir","doi":"10.1016/j.conbuildmat.2025.143578","DOIUrl":"10.1016/j.conbuildmat.2025.143578","url":null,"abstract":"<div><div>In response to the increasing demand for high-temperature durability in asphalt pavements, the modification of asphalt binders using thermoplastic resin (TPR) additives has gained attention due to their aromatic structure, chemical compatibility, and ability to improve rutting resistance. This study investigates the viscoelastic flow behavior and performance optimization of TPR-modified asphalt (TPRMA) binders through a comprehensive experimental and numerical modeling framework. A petroleum-derived thermoplastic resin was incorporated into a 70/100 penetration grade asphalt binder at different ratios (1 %, 3 %, 5 %, 7 %). Rheological characterization was performed using Dynamic Shear Rheometer (DSR) tests under a wide range of temperatures and frequencies. Master curves of complex viscosity were constructed using time–temperature superposition and fitted with Cross and Carreau-Yasuda models. Both models showed excellent agreement with experimental data (R²&gt;0.99), with 5 % TPR yielding the highest zero-shear viscosity and lowest critical shear rate. In the second phase of the study, Response Surface Methodology (RSM) was employed to optimize the G*/sinδ parameter, a critical indicator of rutting resistance. RSM model was developed (R²=0.9922; p &lt; 0.0001), and numerical optimization identified 5.702 % TPR at 64 °C as the optimum formulation, producing a predicted G*/sinδ value of 5453.91 Pa. Post-analysis confirmed the statistical reliability of the prediction, with tight confidence and tolerance intervals enclosing the target response. Regression coefficient analysis further emphasized the dominant effects of temperature, TPR content, and their interactions. Overall, the findings highlight that moderate dosages of thermoplastic resin, particularly around 5 %, significantly enhance the high-temperature performance of asphalt binders.</div></div>","PeriodicalId":288,"journal":{"name":"Construction and Building Materials","volume":"495 ","pages":"Article 143578"},"PeriodicalIF":8.0,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145048032","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":"Building damage assessment based on an enhanced PSPNet network and UAV images","authors":"Shuai Kang,&nbsp;Menghao Jiao,&nbsp;Haitao Wan,&nbsp;Ye Yu,&nbsp;Junhong Yin,&nbsp;Tiejun Zhao","doi":"10.1016/j.conbuildmat.2025.143613","DOIUrl":"10.1016/j.conbuildmat.2025.143613","url":null,"abstract":"<div><div>Building damage assessment is critical for emergency response following natural disasters. Conventional methods, such as manual inspections, physics-based analytical methods, are limited by low computational efficiency, subjectivity, computational complexity and environmental conditions. Damage detection powered by image data and vision technologies overcomes the limitations of conventional methods, enabling more comprehensive and accurate structural damage assessment while demonstrating significant advantages in post-disaster structural damage assessment. In recent years, deep learning-based vision approaches have improved damage segmentation performance through multi-scale feature extraction, yet they remain challenged by noise interference and limited sensitivity to subtle damage features in complex post-disaster scenarios. Therefore, this study proposed an enhanced PSPNet (Pyramid Scene Parsing Network) architecture specifically tailored for post-disaster unmanned aerial vehicle images. First, the original Pyramid Pooling Module (PPM) was replaced with an Atrous Spatial Pyramid Pooling (ASPP) module, which leveraged multi-scale atrous convolutions to strengthen the capture of fine-grained spatial features associated with microscopic damage. Subsequently, a parallel fusion module integrating both PPM and ASPP was introduced to enable complementary extraction of global contextual information and localized multi-scale details, facilitating robust cross-scale feature representation. Experimental evaluations on a UAV-acquired post-disaster image RescueNet dataset demonstrated that the proposed optimal model achieved a Mean Intersection-over-Union (MIoU) of 90.6 %, showing a 5.2 % improvement over the original model while maintaining stable segmentation performance under adverse conditions. The experimental evaluations on the xBD dataset reveal that the improved model achieved a MIoU of 87.2 %, exhibiting a 4.4 % enhancement compared to the original model. The results highlight the effectiveness of the proposed global-local dual-path feature collaboration strategy in improving both the accuracy and robustness of automated post-disaster building damage assessment.</div></div>","PeriodicalId":288,"journal":{"name":"Construction and Building Materials","volume":"495 ","pages":"Article 143613"},"PeriodicalIF":8.0,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145048031","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":"Flexural behavior prediction of reinforced seawater sea sand concrete beams based on deep learning techniques","authors":"Bo Da ,&nbsp;Xianyou Chang ,&nbsp;Lilin Zhu ,&nbsp;Hao Huang ,&nbsp;Jiayang Ma ,&nbsp;Weili Song ,&nbsp;Da Chen","doi":"10.1016/j.conbuildmat.2025.143576","DOIUrl":"10.1016/j.conbuildmat.2025.143576","url":null,"abstract":"<div><div>To accurately assess the flexural behavior of reinforced seawater sea sand concrete beams (RSSSCB), the influence of input features was investigated using an experimental dataset with 163 ultimate bending moment (<em>M</em>_u) sets. For optimal model selection, deep learning algorithms (CNN, Transformer, LSTM) were compared with traditional machine learning methods (XGBoost, Random Forest) via comprehensive metrics: mean absolute error, root mean square error, and coefficient of determination. This integrated methodology enabled precise characterization of flexural behavior and quantitative interpretation of feature importance correlations. The results indicate that: The CNN exhibited superior predictive performance on both training and testing datasets compared to Transformer, LSTM, XGBoost, and Random Forest algorithms, increased by 9.2 % and 29.33 %, 13.1 % and 11.49 %, −2.1 % and 16.87 %, 0 % and 24.36 %, respectively. This finding indicates that the CNN model demonstrates a notable advantage in terms of prediction accuracy and generalization capability. Furthermore, relative to the empirical formulations in GB 50010–2010, JGJ 12–2006, and Da et al., the CNN model exhibited accuracy enhancements of 21 %, 25 %, and 19 %, respectively. Through the interpretation of the CNN model, it is found that the cross-sectional area of longitudinal reinforcement in the tension zone and height of concrete in the compression zone have a significant influence on its predictive performance. Additionally, a noteworthy positive correlation was observed between rectangular cross-section height and concrete height in the compression zone.</div></div>","PeriodicalId":288,"journal":{"name":"Construction and Building Materials","volume":"495 ","pages":"Article 143576"},"PeriodicalIF":8.0,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145048000","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":"Material design and structural optimization of sustainable high-performance pervious concrete for engineering application","authors":"Xunli Jiang ,&nbsp;Jian-Xin Lu ,&nbsp;Xudong Zhao ,&nbsp;Weichen Tian ,&nbsp;Tiejun Liu ,&nbsp;Zhen Leng ,&nbsp;Chi Sun Poon","doi":"10.1016/j.conbuildmat.2025.143591","DOIUrl":"10.1016/j.conbuildmat.2025.143591","url":null,"abstract":"<div><div>The recycling of waste glass has garnered attention in construction materials, yet its application remains limited due to the risk of alkali-silica reaction. This study presents a sustainable approach to the development of high-performance glass pervious concrete (HPGPC) for engineering applications, combining material innovation with structural optimization. In terms of material design, an ultra-high-strength mortar incorporating waste glass powder was developed to enhance aggregate bonding in HPGPC. Structurally, a robust ternary composite cover with steel reinforcement was introduced to integrate HPGPC, significantly improving the load-bearing capacity. Then, a life cycle assessment (LCA) was conducted to identify the optimal cover structure, followed by implementation in a pilot-scale demonstration. The results indicated that an HPGPC with a compressive strength exceeding 50 MPa and satisfactory permeability was developed when the content of waste glass aggregates reached 20 %. X-ray CT analysis revealed that controlling the amount of ultra-high-strength mortar effectively regulated the pore structure, increasing the number of interconnected pores, enlarging the throat EqDiameter and coordination number, and significantly reducing the quantity and size of isolated pores. Seepage simulation results confirmed that the permeability coefficient was closely correlated with these parameters, influenced by connected porosity, throat size, coordination number, and tortuosity. Additionally, the ternary composite structure with steel reinforcement significantly enhanced the mechanical performance of the HPGPC covers, meeting the Class F requirements according to the FACTA standard. The S-LCA and E-LCA analysis indicated that the HPGPC covers offered superior performance in terms of social sustainability, economic cost, energy consumption and GHG emissions. The excellent engineering performance was verified by on-site monitoring.</div></div>","PeriodicalId":288,"journal":{"name":"Construction and Building Materials","volume":"495 ","pages":"Article 143591"},"PeriodicalIF":8.0,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047997","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":"Chloride–sulfate coupled peridynamic model incorporating calcium leaching to simulate reaction–diffusion-damage in compressed concrete","authors":"Yujiao Liu ,&nbsp;Wanjin Li ,&nbsp;Jinwei Guan ,&nbsp;Xin Zhou ,&nbsp;Li Guo","doi":"10.1016/j.conbuildmat.2025.143506","DOIUrl":"10.1016/j.conbuildmat.2025.143506","url":null,"abstract":"<div><div>The durability of concrete infrastructure is compromised by the combined chloride–sulfate attacks in marine environments. Predicting concrete service life is challenging due to accelerated ion diffusion induced by cracks and complex multi-ion interactions. To characterize the competitive relationship between chloride and sulfate, a coupled chloride–sulfate peridynamic model is developed by taking into account sulfate-induced desorption of bound chlorides, electrostatic multi-ion interactions, and the effect of calcium leaching on the diffusion field. Specifically, to examine the effect of porosity and damage on the diffusion field, a newly defined diffusion coefficient is introduced, in which the relation between porosity and material damage is embedded. According to the experimental results, the enhanced reliability of the proposed model is validated through comparisons with four independent experimental datasets. The limitations of the traditional chloride–sulfate model in capturing crack-induced ion diffusion are overcome by the proposed model. The concrete service life can be extended from 63 years to 90 years under the high-protection scenario.</div></div>","PeriodicalId":288,"journal":{"name":"Construction and Building Materials","volume":"495 ","pages":"Article 143506"},"PeriodicalIF":8.0,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145048033","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":"Higher-order sorption scanning behavior and prediction models of gypsum-based inorganic mineral materials","authors":"Yue Xie ,&nbsp;Jingchao Xie ,&nbsp;Lu Bai ,&nbsp;Jingwen Wang ,&nbsp;Jiaping Liu","doi":"10.1016/j.conbuildmat.2025.143221","DOIUrl":"10.1016/j.conbuildmat.2025.143221","url":null,"abstract":"<div><div>Traditional isotherm sorption curves are insufficient to characterize the moisture exchange behavior observed in the hysteresis area. This study investigates three gypsum-based inorganic materials through isotherm boundary curve and high-order scanning curve experiments. Results indicated that all materials exhibited Type IV isotherm boundary curves with H3-type hysteresis loops, indicative of slit-shaped pores or aggregates of plate-like particles composed of mesopores and macropores. During the primary scanning curve tests, the materials demonstrated convergent sorption behavior and high reversibility in low-humidity ranges. Multi-cycle tests further revealed that the moisture content tended to stabilize after three humidity cycles, and the corresponding scanning curves displayed a hierarchical structure, where loops under broader humidity intervals encompassed those under narrower intervals. Comparative model analysis demonstrates that the Independent Domain Model tends to overestimate sorption capacity (−5 % to 43 %), whereas the Thermodynamic Model yields more accurate predictions (−10 % to 8 %). These findings enhance the understanding of absorption-desorption mechanisms in gypsum-based materials and offer theoretical guidance for their application in passive humidity regulation.</div></div>","PeriodicalId":288,"journal":{"name":"Construction and Building Materials","volume":"495 ","pages":"Article 143221"},"PeriodicalIF":8.0,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047569","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}