Bulletin of Earthquake Engineering最新文献

{"title":"Macromodeling and experimental investigation of RC frames infilled with clay bricks and autoclaved aerated concrete blocks under cyclic loading","authors":"Ahmed M. El-Kholy,&nbsp;Huda Sayed,&nbsp;Ibrahim M. Metwally,&nbsp;Ayman A. Shaheen","doi":"10.1007/s10518-025-02358-9","DOIUrl":"10.1007/s10518-025-02358-9","url":null,"abstract":"<div>\u0000 \u0000 <p>This study investigates the cyclic behavior of reinforced concrete (RC) frames infilled with autoclaved aerated concrete (AAC) blocks—a novel and environmentally friendly material—compared to traditional clay masonry infill commonly used in Egypt. In addition, the RC frames were reinforced with an advanced type of reinforcing steel designed to enhance seismic resistance. Three 2/3-scale RC frames were experimentally tested under cyclic lateral loading. Both infill types contributed approximately equally to increasing the lateral strength of the RC frame (around 60% improvement); however, the AAC infill significantly outperformed the brittle clay infill in terms of ductility enhancement. To characterize the response, trilinear and quadlinear backbone curves were developed for the clay and AAC infills, respectively. Alongside the experimental work, numerical macromodeling of the infill panel as multi-strut and single-strut macromodels using SeismoStruct and SAP2000, respectively, was conducted. Additionally, both concentrated and distributed plasticity approaches were employed to model the nonlinear behavior of the RC elements. A suitable constitutive steel model was used to numerically track the experimental hysteresis response of the steel reinforcement. The multi-strut macromodel demonstrated superior accuracy in capturing the hysteresis behavior of the infilled RC frames compared to the single-strut model. The strut width and its post-cracking degradation rate, the shear-to-axial stiffness ratio, and the strain in the infill at peak stress were key parameters influencing the accuracy of the complex multi-strut macromodel in distinguishing between the brittle behavior of clay infill and the ductile response of AAC infill.</p>\u0000 </div>","PeriodicalId":9364,"journal":{"name":"Bulletin of Earthquake Engineering","volume":"24 5","pages":"3173 - 3209"},"PeriodicalIF":4.1,"publicationDate":"2026-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10518-025-02358-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147863062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predictive models for the in-plane strength and drift capacity of unreinforced masonry walls with various types of failure modes using machine learning algorithms","authors":"Mohammad Amir Najafgholipour,&nbsp;Mahsa Zohrei","doi":"10.1007/s10518-026-02389-w","DOIUrl":"10.1007/s10518-026-02389-w","url":null,"abstract":"<div>\u0000 \u0000 <p>The unreinforced masonry (URM) walls serve as the primary load resisting elements in URM structures, supporting gravity loads from the floors and lateral loads during earthquakes. The in-plane lateral strength and drift capacity of URM walls are key parameters necessary in the seismic vulnerability assessment of existing URM buildings. Analytical and empirical expressions have been developed to estimate the ultimate in-plane strength and drift capacity of URM walls. However, based on test results and observations of damaged buildings in earthquakes, URM walls typically exhibit a hybrid failure mode. Therefore, there is a need for a more comprehensive predictive model that can accurately estimate the in-plane strength and drift capacity of URM walls regardless of the dominant failure mode. By developing advanced data analysis and artificial intelligence (AI) algorithms and applying them in structural engineering, this study investigates the effectiveness of these algorithms in predicting the in-plane behavior of URM walls. In this regard, a dataset of in-plane tests on 191 URM walls is compiled. Moreover, six well-known machine learning (ML) algorithms including Decision Tree, Random Forest, Gradient Boosting, Extreme Gradient Boosting, Light Gradient Boosting Machine, and Bagging Regressor are employed to predict the in-plane strength and drift capacity of the walls. The input variables considered in this study are the geometrical characteristics of the walls, boundary conditions, and the compressive strength of the masonry. According to the analysis results, despite the high level of uncertainties associated with masonry material, the machine learning algorithms could estimate the in-plane strength and drift capacity of the walls with an acceptable level of accuracy. Among the examined algorithms, Gradient Boosting showed the best performance in predicting both the ultimate strength and drift capacity of the walls. In addition, a finite element (FE) model for URM walls was developed and a parametric study was conducted. Comparing the in-plane strength of the walls obtained from the FE study and the proposed models demonstrates the acceptable accuracy of the developed machine learning-based predictive models.</p>\u0000 </div>","PeriodicalId":9364,"journal":{"name":"Bulletin of Earthquake Engineering","volume":"24 5","pages":"2661 - 2684"},"PeriodicalIF":4.1,"publicationDate":"2026-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147863138","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":"Finite element analysis of seismic energy dissipation and quantitative damage evaluation in reinforced concrete frame structures","authors":"Liang Luo,&nbsp;Yuxiang Yan,&nbsp;Lian Shao,&nbsp;Hui Lv,&nbsp;Chong Xiao","doi":"10.1007/s10518-026-02382-3","DOIUrl":"10.1007/s10518-026-02382-3","url":null,"abstract":"<div>\u0000 \u0000 <p>The damage of reinforced concrete frame structures during seismic events is frequently severe, potentially resulting in significant casualties and substantial economic losses. Therefore, the investigation of collapse mechanism and quantitative damage assessment for frame structures subjected to earthquakes is of great significance. Using Finite Element software, a three-dimensional solid finite element (FE) model of a 3-storey, 2-span reinforced concrete plane frame structure was established. Based on good verification with pseudo dynamic tests, a full-scale model of the 5- and 10-storey 3 × 3 span reinforced concrete space frame structure system was subsequently developed for seismic wave elastic-plastic time history analysis. The critical thresholds for “energy damage” and “stiffness damage” corresponding to the five states of “small earthquake elasticity”, “moderate earthquake elastic-plastic”, “large earthquake small plasticity”, “maximum earthquake large plasticity”, and “failure”. The results show that: (1) as the local seismic wave acceleration increases, the absolute displacement of floors, the displacement angle between floors and the total plastic energy dissipation value of the frame structure all increase, and the energy dissipation ratio of columns gradually increases while that of beams and slabs decreases; (2) under the influence of ultimate seismic wave, plastic hinges initially appear at the column end and then at the beam end in both frames. The failure mode is that the concrete is crushed when it reaches the axial compressive strength, and the reinforcement is pulled off when it reaches the ultimate strain; (3) the damage assessment method used can accurately and quantitatively evaluate the extent of seismic damage to concrete frame.</p>\u0000 </div>","PeriodicalId":9364,"journal":{"name":"Bulletin of Earthquake Engineering","volume":"24 5","pages":"3105 - 3137"},"PeriodicalIF":4.1,"publicationDate":"2026-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147863061","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":"Seismic performance of mid-rise moment-resisting RC frames with buckling-restrained braces under sequential earthquakes","authors":"İlhan Emre İnam,&nbsp;Ahmet Anıl Dindar","doi":"10.1007/s10518-026-02402-2","DOIUrl":"10.1007/s10518-026-02402-2","url":null,"abstract":"<div>\u0000 \u0000 <p>Effectiveness and feasibility of various seismic retrofitting strategies for reinforced concrete (RC) moment frames have been proposed and studied to date. Due to their stable hysteretic response and high energy dissipation capabilities, incorporating buckling-restrained braces (BRBs) into existing buildings is deemed one of the most efficient techniques. This paper investigates the seismic performance of mid-story moment-resisting RC frames with BRBs under the 2023 Kahramanmaras sequential earthquakes. For this purpose, 3 and 8-story RC frames with various BRB placements and stiffness ratios were studied in terms of distribution of inelastic deformations, inter-story drift demands, base shear-roof displacement response, and energy dissipation through static pushover and dynamic time history analyses. Further, introducing BRBs could significantly increase the lateral load capacity while reducing deformation demands but lead to increased story accelerations, emphasizing the trade-off between the demand on the structural and nonstructural components. Therefore, the horizontal acceleration demands are also examined with and without BRBs. Since successive earthquakes are shown to produce cumulative damage, and inter-story shear force, energy dissipation models emphasize the critical role of BRB placement and optimization. Energy-based design and engineering evaluations revealed that BRBs absorb more seismic energy at low stiffness ratios. Optimal BRB placements resulted in balanced deformation and energy absorption, especially in mid-rise models. This study underlines the necessity of BRB placement strategically and stiffness optimization to improve seismic performance while mitigating adverse effects like reduced ductility and excessive accelerations. These findings offer practical suggestions for enhancing the seismic engineering and design of RC structures retrofitted with BRB in earthquake-prone regions.</p>\u0000 </div>","PeriodicalId":9364,"journal":{"name":"Bulletin of Earthquake Engineering","volume":"24 5","pages":"3069 - 3103"},"PeriodicalIF":4.1,"publicationDate":"2026-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147863106","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":"Parametric study of masonry-infilled RC frames with openings: subassembly contributions to shear resistance and the role of vertical confinement","authors":"Davorin Penava,&nbsp;Lars Abrahamczyk,&nbsp;Shashikant Shambhu Sharma,&nbsp;Liborio Cavaleri,&nbsp;Amin Mohebkhah,&nbsp;Vasilis Sarhosis","doi":"10.1007/s10518-026-02376-1","DOIUrl":"10.1007/s10518-026-02376-1","url":null,"abstract":"<div>\u0000 \u0000 <p>The seismic performance of reinforced concrete (RC) frames with masonry infill walls is strongly affected by the presence of openings, which are unavoidable for architectural reasons. While previous research has often neglected or simplified the role of openings, this study presents a systematic parametric investigation of infilled RC subassemblies with both window- and door-type openings. The analysis explicitly considers opening size (A_o/A_i ratio), position (central vs. eccentric), and the presence of vertical confining elements (ties/serklaži). Using a calibrated micromodelling framework, the study quantifies component-wise shear resistance contributions of the RC frame, masonry infill, and confinement across different drift levels associated with EMS-98 damage grades. Results show that opening size and eccentricity substantially influence stiffness degradation and load transfer, with eccentric door openings imposing shear demands on the RC frame that often exceed the bare-frame design capacity. Vertical confinement proves effective at early damage stages (DG1–DG2), delaying infill degradation and enhancing out-of-plane stability, but its relative contribution remains below 20% and diminishes at higher drifts. Comparison with previous unconfined benchmarks highlights that vertical ties improve both shear resistance and safety against expulsion, establishing infills as integral parts of the seismic load-resisting system. Practical trends and interpolation ranges are proposed to inform design and to support future refinement of the contemporary building code provisions and guidelines.</p>\u0000 </div>","PeriodicalId":9364,"journal":{"name":"Bulletin of Earthquake Engineering","volume":"24 5","pages":"3005 - 3067"},"PeriodicalIF":4.1,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147863142","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":"Seismic performance evaluation of subway station structures with concrete-filled-steel-tube columns","authors":"Zilan Zhong,&nbsp;Qinglong Guo,&nbsp;Jiaxu Shen,&nbsp;Mi Zhao,&nbsp;Xiuli Du","doi":"10.1007/s10518-026-02381-4","DOIUrl":"10.1007/s10518-026-02381-4","url":null,"abstract":"<div>\u0000 \u0000 <p>To enhance the seismic performance of underground subway station structures, the concrete-filled-steel-tube (CFST) columns were adopted in the subway station structures instead of the conventional reinforced concrete (RC) columns in engineering practice. This study primarily compares the effects of CFST columns and RC columns on the seismic performance of subway station structures based on numerical simulations with explicit consideration of the nonlinear dynamic response of soil and structures. Initially, this study designs the CFST column section based on the RC column section using the equivalent bending stiffness method. Two numerical models of the CFST-column and RC-column subway station structures considering nonlinear soil-structure interaction (SSI) were established on the OpenSees finite element platform. A set of 21 ground motions were selected and back-calculated to derive the bedrock motions in a layered site, and subsequently used as the input motions for the SSI system. Moreover, a nonlinear static pushover analysis was performed on the SSI system to determine the damage states of the subway station structures with CFST- and RC-columns. Linear regression analysis was conducted to establish the seismic fragility curves of the subway station structures. The results show that the CFST column subway station structures exhibits an average 44% lower damage probability compared to the RC column subway station structures for a 2450-year return period region with peak ground acceleration of 0·63 g. This study quantifies the failure probability of the structure at different performance levels and presents a reference for performance-based seismic design of subway station structures.</p>\u0000 </div>","PeriodicalId":9364,"journal":{"name":"Bulletin of Earthquake Engineering","volume":"24 5","pages":"3357 - 3383"},"PeriodicalIF":4.1,"publicationDate":"2026-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147863134","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":"Development of magnitude estimation relations from P-wave onset parameters for earthquake early warning applications in Iran","authors":"Bita Niazpour,&nbsp;Zaher Hossein Shomali,&nbsp;Ali Moradi,&nbsp;Iman Soltani Mohammadi","doi":"10.1007/s10518-026-02380-5","DOIUrl":"10.1007/s10518-026-02380-5","url":null,"abstract":"<div>\u0000 \u0000 <p>Reliable magnitude estimation is essential for earthquake early warning systems. This study develops empirical magnitude estimation relations for Iran, based on frequency, amplitude, and energy characteristics of the P-wave onset using earthquakes waveforms recorded across the country. The P-wave parameters of characteristic period (τ_c), dominant period (τ_p^max), peak displacement (P_d), velocity, and acceleration, cumulative absolute velocity, integral of velocity squared, and integral of absolute velocity are calculated within initial P-wave windows of 1–8 s. Linear regression models are developed and tuned based on 80% of the dataset and then validated on the remaining 20%. The analysis of the P-wave time window effect shows that the conventional 3-second window is the shortest duration at which errors noticeably decrease and model performance improves, while for τ_c, the scatter reduces more from the 5-second window. The results indicate that magnitude estimation relations based on amplitude- and energy-related parameters generally provide more stable and accurate performance, with lower standard deviation and scatter, compared to those based on frequency parameters. Among all parameters, relations derived from P_d exhibit the smallest errors and scatter, whereas those based on τ_p^max (within the 3-second window) show the least magnitude underestimation for earthquakes larger than M 6.5. Finally, comparisons with global and regional models highlight both compatibilities and also significant differences, particularly for energy-based parameters, underlining the importance of regional calibration.</p>\u0000 </div>","PeriodicalId":9364,"journal":{"name":"Bulletin of Earthquake Engineering","volume":"24 4","pages":"1883 - 1904"},"PeriodicalIF":4.1,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147579588","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 hybrid SSA-CNN-SVM model for seismic-induced sand liquefaction discrimination","authors":"Ying Yuan,&nbsp;Yunming Su,&nbsp;Mingyu Zhao,&nbsp;Aihong Zhou,&nbsp;Lei Ren","doi":"10.1007/s10518-026-02375-2","DOIUrl":"10.1007/s10518-026-02375-2","url":null,"abstract":"<div>\u0000 \u0000 <p>Seismic-induced sand liquefaction represents a high-impact geohazard, rendering the discrimination and prediction of sand liquefaction states essential for geohazard mitigation research. For the rational discrimination of sand liquefaction states, this study proposes an SSA-CNN-SVM model that integrates Sparrow Search Algorithm (SSA)-optimized Convolutional Neural Networks (CNN) with Support Vector Machines (SVM) for liquefaction discrimination. This model initiates from raw sand liquefaction data, accomplishes layer-by-layer learning to extract liquefaction features and discriminate the states of liquefaction, and employs SVM in lieu of Softmax functions for liquefaction state classification. This study integrated raw sand liquefaction data from the Tangshan earthquake and datasets from two other journal articles, constructing a comprehensive sample set comprising 300 instances. The evaluation metrics—standard penetration test (SPT) blow count, mean particle size, coefficient of uniformity, groundwater table depth, effective overburden pressure, seismic intensity, and cyclic shear stress ratio—were input into the SSA-CNN-SVM model for prediction. The predictions were compared with those from SSA-SVM, SVM, CNN, and Backpropagation Neural Network (BPNN) models, validated against actual sand liquefaction data. The results indicate that the SSA-CNN-SVM model demonstrates superior performance in sand liquefaction discrimination, achieving an accuracy of 88.33%, a precision of 86.19%, a recall of 89.44%, and an F1-Score of 87.89%—all exceeding the corresponding metrics of the other comparative models. This validates the high precision of the proposed liquefaction discrimination model and provides a novel approach for practical applications.</p>\u0000 </div>","PeriodicalId":9364,"journal":{"name":"Bulletin of Earthquake Engineering","volume":"24 4","pages":"1971 - 1998"},"PeriodicalIF":4.1,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147579464","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":"Seismic analysis based on a new interval method with incomplete information","authors":"Shizhong Liang,&nbsp;Yuxiang Yang,&nbsp;Chen Li,&nbsp;Feng Wu","doi":"10.1007/s10518-026-02372-5","DOIUrl":"10.1007/s10518-026-02372-5","url":null,"abstract":"<div>\u0000 \u0000 <p>For seismic analysis in engineering structures, it is essential to consider the dynamic responses under seismic excitation, necessitating the description of seismic accelerations. The scarcity of seismic samples leads to incomplete uncertainty information, for which non-probabilistic methods provide a reasonable description. This study employs the minimum interval radius-based interval process (MRIP) based on the convex model to describe the time-variant uncertain seismic acceleration, subsequently conducting uncertainty analysis for seismic structures. However, the Monte Carlo simulation for uncertainty analysis requires extensive deterministic computations to ensure accuracy, exhibiting poor computational efficiency. To address this issue, this paper first improves the covariance matrix adaptation evolution strategy (CMA-ES) through the dynamic evolution sequence (DES), proposing DES-ES, whose efficiency is validated to be higher than that of CMA-ES. Furthermore, leveraging the dependency of the responses, a computational framework named DES-ES-SS is proposed. Numerical experiments demonstrate that DES-ES-SS improves computational efficiency while maintaining the accuracy of the interval uncertainty analysis of the seismic structures whether the seismic acceleration is stationary or non-stationary. Furthermore, the proposed method can be extended to other complex engineering systems with time-variant spatial uncertainties, including nuclear reactor safety assessment and spacecraft dynamics.</p>\u0000 </div>","PeriodicalId":9364,"journal":{"name":"Bulletin of Earthquake Engineering","volume":"24 4","pages":"2475 - 2493"},"PeriodicalIF":4.1,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147579463","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 review of ground motion correlation modelling for regional seismic risk analysis","authors":"Vitor A. Monteiro,&nbsp;Gerard J. O’Reilly","doi":"10.1007/s10518-026-02377-0","DOIUrl":"10.1007/s10518-026-02377-0","url":null,"abstract":"<div><p>Inter and intra-site correlation of ground-motion intensity measures (IMs) plays a critical role in seismic hazard and risk assessment. Ignoring such correlations can lead to significant misrepresentation of losses in regional-scale studies and misrepresentation of ground motion field simulations. Accurate correlation modelling is essential for scenario-based risk assessments, emergency preparedness planning, and understanding systematic infrastructure vulnerabilities in portfolio risk analyses. This study presents a detailed overview of intra-site (non-spatial) and inter-site (spatial) correlation models developed over the past two decades. It reviews over 45 models proposed in the literature, encompassing diverse methodologies applied to different regional databases and a variety of IM. The analyses reveal considerable variability among models, particularly in short-range spatial correlation and in how inter-IM correlations are treated. Despite this diversity, most models rely on simplifying assumptions such as stationarity and isotropy, which may not fully capture the complexities of real-world ground motion patterns. This work provides a valuable resource for researchers and practitioners by summarising the current state of correlation modelling and offering guidance on model selection based on database, regional context, and engineering application. It underscores the importance of informed model choice for improving the accuracy of hazard and risk assessments in spatially distributed systems.</p></div>","PeriodicalId":9364,"journal":{"name":"Bulletin of Earthquake Engineering","volume":"24 5","pages":"2497 - 2546"},"PeriodicalIF":4.1,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147863110","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}