地震损伤模型

框架-核心筒体系在现代高层建筑中的广泛应用确实是个事实，但强震作用下非线性响应机制仍然存在许多没有解决的难题。尤其随建筑高度不断增长，结构动力放大效应与损伤累积过程的空间非均匀性变得越来越明显。导致传统抗震设计方法难以准确捕捉真实极限状态的是这种情况。近年的震害表明现有规范对框架-核心筒协同工作的简化假定可能严重低估关键构件损伤风险。长周期地震动下尤为突出的是此类问题。因此建立考虑非平稳激励特性的精细化分析模型变得很重要。系统揭示结构从弹性阶段至完全失效的性能演化规律成为提升抗震安全性的核心课题。本研究将聚焦动力荷载下该体系的极限性能，致力填补理论空白，那些分析工作的事情很必要。

随着我国基础设施建设的快速发展，桥梁安全与健康已成为交通运输领域亟需关注的重点问题。传统桥梁监测手段存在数据获取滞后、评估效率较低等局限，难以满足现代桥梁运行管理的实际需求。近年来，智能传感技术的兴起为桥梁实时监测与健康评估提供了新的解决方案。文中聚焦智能传感器在桥梁结构监测中的应用，通过布置多类型传感器，实现对桥梁关键参数的连续、实时采集，包括荷载响应、应变、振动、位移及温度等。基于采集的数据，运用智能分析方法，对桥梁运行状态进行动态评估，及时发现结构潜在损伤与异常。研究结果表明，智能传感系统具备数据采集全面、传输高效、响应迅速等优势，可大幅提升桥梁健康评估的准确性和及时性，为桥梁安全运行和维护决策提供科学依据。该研究对于推动桥梁智能化管理、延长结构服役寿命及保障交通安全具有重要意义。

为分析装配整体式钢筋混凝土梁柱中节点的抗震性能，开展了考虑不同节点装配形式的钢筋混凝土梁柱中节点的有限元分析。首先采用Abaqus 有限元分析软件建立了2种不同装配形式的梁柱中节点模型，随后对比了节点形式对塑性损伤、滞回性能和耗能能力的影响。结果表明：装配整体式梁柱中节点符合“强柱弱梁”思想，结构设计合理。型钢中节点的极限承载和极限变形明显优于原型中节点，节点内置型钢明显提高了节点的抗震性能。

钢筋混凝土结构在长期使用过程中容易受到环境、荷载及施工质量等多种因素的影响，导致耐久性下降。针对这一问题，提出了钢筋混凝土结构的耐久性评估方法，并结合具体案例，采用非破坏性检测技术评估结构的损伤程度。通过对不同加固技术的综合比较，如碳纤维加固、钢板加固等，提出了合理的加固方案。加固后，结构的承载力和耐久性得到了显著提高，有效延长了使用寿命。研究表明，通过科学评估和加固手段，可以有效提升钢筋混凝土结构的安全性与经济性。

钢筋混凝土框架结构在地震作用下的行为，旨在提升此类结构的抗震性能。首先分析了影响钢筋混凝土框架结构抗震性能的关键因素，包括材料特性、结构设计及施工质量等。通过对比不同地震条件下该类结构的行为特征，识别出其潜在的薄弱环节，并提出相应的改进措施。合理的结构设计与高质量的施工是提高钢筋混凝土框架结构抗震能力的重要保障。采用先进的数值模拟技术可以有效预测结构在地震中的响应，为优化设计方案提供科学依据。本研究对于增强建筑结构的抗震性能具有重要参考价值。

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李宗超,陈学良,吴清,李铁飞,李昌珑 中国地震局地球物理研究所 北京 100081, 中国 lizongchaoigo@163.com Abstract: On February 4, 2018, a Ms6.5 occurred in Hualien County in Taiwan Province. The source depth was 10 km. This earthquake killed 17 people and injured 285 people. The earthquake also caused huge property losses. Most of the casualties of the earthquake were caused by the collapse and damage of the buildings. The near field strong ground motion was the direct reason which caused the collapse of the building. The collapse of the buildings was greatly related to the amplitude and frequency of circulation of ground motion. The seismic response of system accumulated damage under cyclic load depends not only on the maximum amplitude of motion but also on the duration of motion. Many researchers suggest that the effective number of ground motion cycles is more reflective of seismic damage than the duration. The destructive ability of seismic ground motion depends on the amplitude of the movement and the number of cycles. In the geotechnical earthquake engineering, the number of motion cycles is the most important. Many researchers believe that the number of motion cycles is also an important factor in structural seismic design and damage assessment. Because the strength, stiffness and energy dissipation of the structure decreases with the increase of the load cycle, the amplitude itself is not sufficient to evaluate the seismic performance of the structure. In this paper, the spatial distribution characteristics of the damage index of Hualian earthquake is analyzed, and the correlation between the damage index and seismic intensity is analyzed. Keywords—damage Index, Hualian eartrhquake, characteristics analysis, seismic intensity 摘要:2018 年 2 月 4 日,台湾省花莲县附近海域(北 纬 24.2 度,东经 121.72 度)发生 6.5 级地震,震 源深度 10 千米,地震造成 17 人遇难,285 人受伤, 地震也造成了巨大的财产损失。本次地震的绝大部 分伤亡是由于建筑物倒塌破损造成的,而近场强地 震动是造成建筑物倒塌的直接原因,建筑物倒塌与 地震动的振幅和循环次数相关性极大。系统在循环 荷载下累积损伤的地震响应不仅取决于运动的最 大振幅,还取决于运动的持续时间。许多研究人员 提出,有效的地面运动周期数比持续时间更能反映 地震破坏能力。地震地面运动的破坏能力取决于运 动的振幅和循环次数。在岩土地震工程中,运动循 环次数是最重要的。许多研究人员认为,运动循环 次数也是结构抗震设计和损伤评估方面的一个重 要因素。由于结构的强度、刚度和耗能能力随着荷 载循环次数的增加而降低,因此振幅本身不足以评 估结构的抗震性能。本文将着重分析研究了花莲地 震的损伤指数的空间分布特征,并结合实际的灾害 烈度分布特征,分析了震害指数与地震烈度的相关 性。 关键词:损伤指数,花莲地震,特征分析,地震强 度

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The large degradation of the mechanical performance of hollow reinforced concrete (RC) bridge piers subjected to multi-dimensional earthquakes has not been thoroughly assessed. This paper aims to improve the existing seismic damage model to assess the seismic properties of tall, hollow RC piers subjected to pseudo-static, biaxial loading. Cyclic bilateral loading tests on fourteen 1/14-scale pier specimens with different slenderness ratios, axial load ratios, and transverse reinforcement ratios were carried out to investigate the damage propagation and the cumulative dissipated energy with displacement loads. By considering the influence of energy dissipation on structural damage, a new damage model (M-Usami model) was developed to assess the damage characteristics of hollow RC piers. The results present four consecutive damage stages during the loading process: (a) cracking on concrete surface, (b) yielding of longitudinal reinforcements; (c) spalling of concrete, and (d) collapsing of pier after the concrete crushed and the longitudinal bars ruptured due to the flexural failure. The damage level caused by the seismic waves can be reduced by designing specimens with a good seismic energy dissipation capacity. The theoretical damage index values calculated by the M-Usami model agreed well with the experimental observations. The developed M-Usami model can provide insights into the approaches to assessing the seismic damage of hollow RC piers subjected to bilateral seismic excitations.

AbstractA macroscopic global seismic damage model is proposed for reinforced concrete structures by considering the dynamic modal contributions. Modal damage is defined using the concepts of dynami...

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Strong earthquake disasters can cause noticeable damage correlations among regional buildings with similar mechanical properties, termed structure‐to‐structure seismic damage correlation, which has a pronounced impact on the regional seismic risk assessment and therefore needs to be properly quantified. This study first introduces a time‐domain analytical and equivalent frequency‐domain analysis based on random vibration theory for calculating structure‐to‐structure seismic damage correlation coefficients. Subsequently, by employing the spatially consistent white noise excitation and the spatially varying white noise excitation with the Luco–Wong coherence function, the structural filtering effect and the ground motion spatial correlation effect are progressively incorporated, and an analytical interstructural damage correlation model incorporating structural dynamic properties and spatial distance is derived. Comparations with Monte Carlo simulations and existing empirical models demonstrate that the proposed analytical model possesses a clear physical basis and high reliability. Finally, a case study was conducted on a district having 29,461 buildings in Shanghai, China to illustrate the influence of interstructural damage correlation on the regional seismic risk. Results show that disregarding the interstructural seismic damage correlation can lead to underestimation of overall loss uncertainty.

The research on the application of machine learning (ML) methods in the field of earthquake engineering shows a continuous and rapid progress in the last two decades. ML methods and models belonging to the category of supervised, unsupervised and semi-supervised learning are applied for the assessment of seismic vulnerability of structures and estimation of the expected level of seismic damage. These models lead to the classification of seismic damage into predefined classes through the extraction of patterns from data collected from various sources. However, the lack of detailed knowledge can affect their performance and ultimately reduce their reliability, as well as the generalizability that should characterize them. Towards this direction, the present paper attempts to compare and evaluate for the first time the ability of an extensive number of ML methods in the correct classification of R/C buildings at the first stage pre-and post-seismic inspection considering three seismic damage categories. A database consisting of 5850 training samples is used for this evaluation. This database is generated by solving 90 R/C buildings for 65 actual seismic excitations applying nonlinear time history analyses. For each one of the training samples the maximum interstory drift ratio is calculated as a damage index. In addition, a major contribution of this paper is the presentation and extensive documentation of the procedures required for the preprocessing of the data. Finally, an auto hyperparameter tuning method for the winning al-gorithm is proposed, so that the hyperparameters are automatically optimized utilizing Bayesian Optimization. The most significant conclusion extracted is that the studied ML algorithms extract very different classification results. In addition, the Support Vector Machine - Gaussian Kernel algorithm extracted the most accurate results of all the studied ML algorithms.

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Abstract The present study was aimed at assessing more accurately the seismic vulnerability and performance of highway bridges in an earthquake-damaged area. Based on mathematical statistics (data collection) and a probability model, (i) survey data for 2134 bridges in 22 highway sections (47 sub-sections) affected by the Wenchuan earthquake on May 12, 2008 were obtained and analysed, (ii) Gaussian and exponential regression models were developed, (iii) the empirical seismic-damage vulnerability function, plane, surface and curve model of the 22 highway sections with sample number and failure ratio were established, and (iv) a regression parameter matrix was constructed considering the empirical seismic-damage data. Using the method of probability exceedance, the bridge vulnerability curve models considering the seismic-damage exceedance probability of each section were analysed, and a parameter matrix model (mean seismic-damage index) was proposed to evaluate and predict the seismic vulnerability of regional bridges. Based on creating the actual seismic-damage sample database, vulnerability point-cloud models of the 22 highway bridges were constructed, and the vulnerability probability matrix, function, curve and point-cloud model of each highway section can be used to evaluate and estimate the vulnerability of regional bridges in the future.

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This study introduces a multiple-input convolutional neural network (MI-CNN) model for the seismic damage assessment of regional buildings. First, ground motion sequences together with building attribute data are adopted as inputs of the proposed MI-CNN model. Second, the prediction accuracy of MI-CNN model is discussed comprehensively for different scenarios. The overall prediction accuracy is 79.7%, and the prediction accuracies for all scenarios are above 77%, indicating a good prediction performance of the proposed method. The computation efficiency of the proposed method is 340 times faster than that of the nonlinear multi-degree-of-freedom shear model using time history analysis. Third, a case study is conducted for reinforced concrete (RC) frame buildings in Shenzhen city, and two seismic scenarios (i.e., M6.5 and M7.5) are studied for the area. The simulation results of the area indicate a good agreement between the MI-CNN model and the benchmark model. The outcomes of this study are expected to provide a useful reference for timely emergency response and disaster relief after earthquakes.

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Earthquakes cause significant damage to bridges, which have a very strategic location in transportation services. The destruction of a bridge will seriously hinder emergency rescue. Rapid assessment of bridge seismic damage can help relevant departments to make judgments quickly after earthquakes and save rescue time. This paper proposed a rapid assessment method for bridge seismic damage based on the random forest algorithm (RF) and artificial neural networks (ANN). This method evaluated the relative importance of each uncertain influencing factor of the seismic damage to the girder bridges and arch bridges, respectively. The input variables of the ANN model were the factors with higher importance value, and the output variables were damage states. The data of the Wenchuan earthquake were used as a testing set and a training set, and the data of the Tangshan earthquake were used as a validation set. The bridges under serious and complete damage states are not accessible after earthquakes and should be overhauled and reinforced before earthquakes. The results demonstrate that the proposed approach has good performance for assessing the damage states of the two bridges. It is robust enough to extend and improve emergency decisions, to save time for rescue work, and to help with bridge construction.

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This study evaluates the seismic fragility and code compliance of reinforced concrete buildings in Turkey following the 6 February 2023 Kahramanmaraş earthquake. Sixty representative buildings were modeled in SAP2000, consisting of thirty structures designed according to TEC-1975 and thirty according to TEC-1998. These models were subjected to three-dimensional nonlinear time history analyses using ground motions scaled to match the seismic characteristics of the earthquake. Structural performance was assessed by comparing calculated displacement demands with capacity thresholds defined by modern code provisions. The results show that buildings designed under TEC-1998 generally performed better than those constructed according to TEC-1975, particularly in terms of deformation capacity and collapse resistance. Fragility curves and exceedance probabilities were developed to quantify damage likelihoods across different performance levels. When compared with post-earthquake field observations, the analytical models produced lower collapse rates, which may suggest the presence of widespread code noncompliance in the actual building stock. These findings highlight the critical importance of ensuring adherence to seismic design regulations to improve the resilience of existing structures.

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The effect of an intensity measure’s (IM’s) sufficiency property on the probabilistic assessment of reinforced concrete (RC) structures due to floor-to-floor structural pounding conditions is examined. In the first part of this investigation, efficiency and sufficiency properties of 23 scalar IMs are verified. Then, the magnitude Mw and the distance Rrup are examined as elements in a vector with an efficient scalar IM to evaluate whether they have any significant effect on the structural response. Subsequently, probabilistic seismic demand models (PSDMs) are developed using linear regression analyses based on a scalar IM and a vector-valued IM. Fragility curves are developed based on these PSDMs, and the influence of Mw and Rrup on the evaluation of the minimum required separation gap distance dg,min due to the pounding effect is examined. More than two hundred nonlinear time history analyses are performed based on the Cloud Analysis method. Seismic displacement demands that control of the global state of the structure, as well as the probability of structural pounding, are examined. The results of this research indicate that once Mw or Rrup is increased, fragility curves are shifted to greater values of IM, and the probability of the exceedance of a certain performance level is reduced. Also, the predictive power of Rrup seems to be greater than the one of Mw. On the other hand, it is revealed that Mw and Rrup induce variabilities in the demand solutions for adequate separation gap distance between the adjacent structures. Therefore, variation in Mw or Rrup may lead, in some cases, to unacceptable evaluations of the pounding effect in the capacity levels of structures.

ABSTRACT This study investigates the hazard fragility analysis of soft soil-pile foundation bridge in coastal and seismically active regions with particular focus on joint impacts of water waves and earthquake accelerations. The research begins with a comprehensive characterization of soft soils found in coastal environments, followed by an assessment on their bearing capacity under both static and dynamic loads. Joint fragility analytical and numerical models are developed to evaluate the performance of the bridge components and systems during seismic events with incorporating the influence of water waves on soil stability. The resuls show that water waves contribute to the collision risk, and their impact can be up to 1.34 times greater than the seismic forces at the same joint width especially in soft soil areas. The combined impact of these forces highlights the importance of designing expansion joints to adequately mitigate the risks posed by both phenomena, which ensuring the structural resilience of bridges in dynamic environments. In addition, the results demonstrate that the joint fragility curves in the bridge system all exhibit damage probabilities that exceed the single-element damage probabilities, and that the single-element damage probabilities cannot be used as a benchmark for bridge systems under actual operating conditions.

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The vulnerability of coastal buildings to tsunami events has garnered increasing attention in the last decades due to the severe impacts of recent disasters. Numerous challenges have been addressed to develop valuable methodologies to estimate the probability of damage to structures and infrastructures and to formulate effective strategies to mitigate potential damages and losses. However, a comprehensive predictive framework for constructing damage probability models applicable across different structural types and tsunami scenarios, while also accounting for the potential impact of previous earthquake damage, is still missing. In the present study, a double-stage approach for investigating the vulnerability of masonry buildings under sequential earthquake-tsunami events is proposed and discussed. Monte Carlo simulations are performed, analyzing the response of different building classes, characterized by different numbers of storeys. The random generation of the involved and basic parameters characterizing structures and loads have been followed by time-history dynamic analyses for seismic actions and push-over analyses for tsunami loading. The results provide valuable insights for refining multi-risk evaluations, highlighting the impact of earthquake-induced damage on tsunami vulnerability compared with studies that neglect seismic effects. In the paper, the influence of previous random seismic action on tsunami loading vulnerability was obtained and translated into a new type of fragility curve for the earthquake-tsunami interaction. Meanwhile, the important effect of building height on tsunami vulnerability is stressed along with the influence of vertical loads and seismic intensity, expressed in terms of Peak Ground Acceleration (PGA). Comparative analyses were conducted to assess the effectiveness of the proposed methodology for constructing analytical fragility curves, evidencing the reliability of the proposed approach.

Performance‐based earthquake engineering (PBEE) is essential for ensuring engineering safety. Conducting seismic fragility analysis within this framework is imperative. Existing methods for seismic fragility analysis often rely heavily on double loop reanalysis and empirical data fitting, leading to challenges in obtaining high‐precision results with a limited number of representative structural analysis instances. In this context, a new methodology for seismic fragility based on a full‐probabilistic cloud analysis is proposed via the decoupled multi‐probability density evolution method (M‐PDEM). In the proposed method, the assumption of a log‐normal distribution is not required. According to the random event description of the principle of preservation of probability, the transient probability density functions (PDFs) of intensity measure (IM) and engineering demand parameter (EDP), as key response quantities of the seismic‐structural system, are governed by one‐dimensional Li‐Chen equations, where the physics‐driven forces are determined by representative analysis data of the stochastic dynamic system. By generating ground motions based on representative points of basic random variables and performing structural dynamic analysis, the decoupled M‐PDEM is employed to solve the one‐dimensional Li‐Chen equations. This yields the joint PDF of IM and EDP, as well as the conditional PDF of EDP given IM, resulting in seismic fragility analysis outcomes. The numerical implementation procedure is elaborated in detail, and validation is performed using a six‐story nonlinear reinforced concrete (RC) frame subjected to non‐stationary stochastic ground motions. Comparative analysis against Monte Carlo simulation (MCS) and traditional cloud analysis based on least squares regression (LSR) reveals that the proposed method achieves higher computational precision at comparable structural analysis costs. By directly solving the physics‐driven Li‐Chen equations, the method provides the full‐probabilistic joint information of IM and EDP required for cloud analysis, surpassing the accuracy achieved by traditional methods based on statistical moment fitting and empirical distribution assumptions.

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Fragility plays a pivotal role in performance‐based earthquake engineering, which represents the seismic performance of structural systems. To comprehensively understand the structural performance under seismic events, it is necessary to consider uncertainties in the structural model, i.e., epistemic uncertainties. However, considering such uncertainties is challenging due to computational complexity, leading most fragility analyses only to consider the chaotic behavior of ground motions on structural responses, i.e., aleatoric uncertainties. To address this challenge, this study proposes an adaptive algorithm that intertwines with the conventional fragility analysis procedures to consider both aleatoric and epistemic uncertainties. The algorithm introduces Gaussian process‐based metamodels to efficiently consider epistemic uncertainties with a small number of time history analyses. Steel moment‐resisting frame structures and a reinforced concrete building are used to demonstrate the improved efficiency and wide applicability of the proposed method. In each case, the proposed method yields fragility curves consistent with reference solutions but with substantially lower computational effort. Comprehensive discussions are provided regarding ground motion sets, structural types, and definitions of limit‐states to demonstrate the robustness of the proposed approach.

Colombia is in a high seismicity area where the Nazca and South American plate converge. Past earthquakes in 1985 and 1999 caused considerable economic and human losses to the country. As part of a seismic risk mitigation strategy, the National Geological Service commissioned a nationwide seismic risk model in 2022, which required developing seismic fragility functions representative of the country building stock. This article presents the seismic fragility results for conventional and thin reinforced concrete (RC) wall buildings. Conventional RC walls are those fulfilling ACI 318 provisions, and thin RC wall buildings (TRCWBs) are those reinforced with a single layer of a welded wire mesh with limited ductility. Leveraging a database of 259 structural drawings and models, 91 building archetypes were created in OpenSeesPy using a modeling approach that approximates non-planar walls with the MVLEM-2D. These underwent nonlinear dynamic analyses with over 3000 hazard-consistent ground motions, recording inter-story drifts, floor accelerations, and element forces. The results were used to calculate seismic fragility functions that served as input for the application of the FEMA P-695 methodology. The findings of this study provide fragility parameters for buildings between 4 and 30 stories constructed in low, intermediate, and high seismic hazard in Colombia, which are suitable for development of seismic risk scenarios. In addition, results also suggest that the Colombian code provisions for TRCWB require adjustments.

This article evaluates how different reinforced concrete (RC) building systems in Türkiye behaved during the extreme 2023 Kahramanmaraş earthquakes. The analysis relies on a comprehensive field survey covering 242 RC buildings across various heavily affected locations. Most surveyed buildings were low- and mid-rise RC moment frames and frame-wall (hybrid) systems, with RC wall construction being less commonly observed. Both RC frame and hybrid buildings exhibited several common deficiencies, resulting in significant structural and non-structural damage due to high drift demands. The performance of RC wall construction varied, with some buildings sustaining severe damage while others remained largely unaffected. An analysis of structural plans revealed that RC wall buildings with adequate wall amounts demonstrated exceptional performance, while those with inadequate amounts of walls experienced severe damage. In addition, fragility analyses using simplified models based on surveyed buildings reinforced these findings. The analyses suggested that RC frame and hybrid systems were insufficient in ensuring life safety during the earthquakes. Conversely, properly designed RC wall buildings are expected to perform well. This alignment between field observations and fragility analyses underscores the reliability of the study’s findings and emphasizes the effectiveness of RC wall construction in mitigating seismic risks and protecting life and property.

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Human perception in high‐rise buildings during far‐field long‐period earthquake ground motions often induces psychological discomfort, including fear and anxiety. A comprehensive understanding on human perception of seismic events is vital for city planning and emergency management, facilitating effective evacuation plans and minimizing stampede risks. This study addresses a gap by employing the seismic fragility analysis method to delineate how human perception in high‐rise buildings is affected during far‐field long‐period ground motions. The methodology involves several key steps. First, the far‐field long‐period earthquake ground motion was identified by detecting the later‐arriving surface waves, and a series of records were selected from the next generation attenuation (NGA) West‐2 ground motion database of the Pacific Earthquake Engineering Research center. Then, a high‐rise building in Shanghai, China was modeled using ETABS 20. Through the linear‐elastic time history analysis, the structural seismic response at each floor was computed. Furthermore, human perception thresholds to vibration were introduced to assess the degree of human perception at each floor, illustrating the difference of human perception to seismic tremor at different floors. Finally, a novel earthquake intensity measure (IM), namely average response spectrum intensity (ARSI) within the vibration period ranging from 0.1 s to 10 s was introduced to generate seismic fragility curves for human perception. According to the investigation, it was found that the corner frequency and the associated energy ratio are useful indicators to identify the far‐field long‐period earthquake ground motions. The ARSI is an effective parameter to assess human perception to seismic tremor compared to the spectral acceleration at a given fundamental period. The generated seismic fragility analysis can provide a complete and thorough understanding on the probability of people that should be evacuated under different earthquake intensity levels. The probability of human perception at different floors varies along the building height, demonstrating the difficulty to make crowd evacuation plan in practice. This insight is vital for understanding and mitigating seismic concerns in high‐rise buildings, particularly in low‐to‐moderate seismicity regions.

Lightweight steel structures are commonly used in industrial facilities due to their low weight, high strength, and excellent performance. The design of these structures for cold regions not only has to consider the effects of earthquakes but also the negative impact of snow loads. Industrial structures often have long spans, and the effects of uneven snow loads cannot be underestimated. However, relatively few studies have focused on the performance of lightweight steel structures under the influence of combined earthquake and non-uniform snow loads. Therefore, this study assessed the seismic fragility of a typical single-span, double-sloped lightweight steel factory under combined earthquake and non-uniform snow loads using incremental dynamic analysis. Non-uniform snow loads, as compared to uniform snow loads, substantially increase the structural displacement responses, thereby increasing the structural failure risk. The improved structural design developed in this study effectively decreases the impact of adverse loading scenarios and enhances the multi-hazard resilience of the structure. Accordingly, these results can serve as an important theoretical guide for enhancing the safety of lightweight steel structures subjected to multiple hazards in cold regions.

This study establishes a multi‐hazard probabilistic assessment framework for assessing the integrity of monopile offshore wind turbines (OWT) under the stochastic coupled effect of wind, wave and earthquake loading. The procedure deals with the entire operational range of inflow wind speed (i.e., 3–25 m/s), for which the probability of failure under multi‐hazard excitations is found to be non‐negligible. Numerical analysis is performed by implementing nonlinear finite‐element models of the OWT developed in OpenSees. The dynamic response of the OWT system under wind‐ and wave‐load combinations is individually validated against those obtained from the aero‐hydro‐servo‐elastic simulator OpenFAST. Following the Latin‐hypercube approach, a cloud‐based assessment procedure is then performed with an ensemble of 300 earthquake ground motions, from which the multi‐hazard performance of the OWT regarding the serviceability limit state (SLS) and the ultimate limit state (ULS) can be evaluated. The epistemic uncertainty associated with various loads, structural properties, and soil conditions is also accounted for. Based on this probabilistic assessment framework, the sensitivity of the resulting OWT fragility surfaces to different statistical regression methods and wind—ground motion intensity measure pairs (IM‐pairs) is further scrutinised. Regression methods are comparatively evaluated. The efficiency, practicality, proficiency and sufficiency of various IM‐pairs are examined for the purpose of assessing operating OWT multi‐hazard fragility functions. The optimum IM‐pair is then employed in a trained Gaussian Process Regression (GPR) scheme for cloud data regression to assess the multi‐hazard fragility of the system. The derived multi‐hazard fragility function shows that the contribution of seismic forces in structural demand for a design‐level earthquake is comparable to those caused by operational‐level wind and wave loads.

ABSTRACT The RINTC (2015–2017) project was a three-year research program aimed at assessing the seismic reliability of code-conforming structures in Italy. It dealt with five structural typologies of residential and industrial buildings: reinforced concrete, masonry, precast reinforced concrete, steel, and base isolated reinforced concrete. To reach its goals, several tens of structures featuring the same configuration were designed at different sites, characterized by different seismic hazard and considering two soil site conditions. The failure risk (i.e. the failure rate) of the buildings was evaluated by means of non-linear dynamic analysis of three-dimensional numerical models. The study herein presented parametrized the vulnerability models of the considered structures; in other words, it provides the seismic fragility curves for code-conforming Italian buildings analyzed in the RINTC project. Lognormal fragilities refer to global collapse failure and usability preventing damage, which are the performances considered in the project, and are derived via state-of-the-art methods, including consideration of the uncertainty in the estimation of their parameters. The curves are made available to be possibly used for further risk analyses and enable a discussion of the fragility fitting issues as a function on the site’s hazard.

The role of non‐structural elements (NSEs) in the seismic performance of buildings has been highlighted in past years. Research studies following state‐of‐the‐art methodologies generally find that when the structural collapse is not of significant concern, NSEs tend to dominate the repair costs and financial investment required in a building. This paper examines field observations from interviews and data collected from commercial buildings via structural health monitoring (SHM) following the 2018 Osaka earthquake in Japan. It suggests that fragility functions used in current methodologies for estimating NSE damage may not be entirely representative of the in‐situ reality and possibly underestimate actual damage. Additionally, interviews with building owners/managers indicate that the alarm and financial impact of NSEs was not as critical as anticipated, with much of the observed NSE damage not of serious concern and tolerable in many cases. This article provides discussion and insight into possible causes for these differences before discussing how current methodologies can benefit from these observations. It is believed that many of the fragility functions currently used to estimate NSE damage may not be representative because of differences in installation conditions and loading protocols used in experimental testing, possible interaction with other elements, variability in the quality of workmanship during installation and possible wear, tear and degradation during service. On the other hand, it is seen how SHM data recorded during seismic events may provide valuable data for an alternative means to develop fragility functions. Furthermore, it is seen that when building recovery states (RSs) other than the implicitly assumed ‘full recovery’ state used in guidelines like FEMA P‐58 are explored, the role of NSEs in direct monetary losses significantly reduces. This coincides with the field observations in Japan regarding the impact of NSEs and supports the recent developments in functional recovery on what building owners and occupants are prepared to tolerate post‐earthquake. It indicates that when discussing the relative importance of different building performance groups, it is vital that the expected RS is also stated, as for most decision‐makers following major events, functionality rather than full recovery remains the primary goal; hence, repairs and proactive measures should bear this in mind for more effective use of resources.

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The frequency content and time duration of earthquakes are as effective as the peak ground acceleration on structural damage. Therefore, using rapid seismic vulnerability assessment methods that consider the earthquake acceleration time history is noticeable. Kermanshah is a historical city that is generally affected by far-field earthquakes. Therefore, it is necessary to consider the effect of the low-frequency shocks in evaluating the vulnerability of buildings in this city. Herein, a historic school in Kermanshah is assumed as a case study and two well-known damage index formulas are used for determining the damage index spectra of this structure, considered as a single degree of freedom system. Then, the effective parameters of the damage index, including ductility, relative degradation of stiffness, and dissipated energy are determined from a nonlinear analysis of the structure under the effect of the most probable earthquake acceleration records. Finally, the damage index spectra can be used for rapid seismic vulnerability assessment of masonry buildings on similar sites with various fundamental periods for large-scale assessments. The result shows that the building tends to collapse at a peak ground acceleration of 0.15 g. Furthermore, results confirm the seismic resistance reduction effect of flexible floors.

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This study proposes a framework to evaluate probabilistic seismic risk of buildings in regions exposed to both crustal and subduction earthquakes. Ground motions from subduction earthquakes are typically longer in duration, causing higher damage to structure due to increased inelastic demand as compared to ground motions from crustal earthquakes having the same peak intensity. The increased vulnerability to structural damage from subduction earthquake ground motions needs to be accounted for in seismic loss assessment studies. This study investigates the same for India. The north and northeast of India are exposed to both crustal and continental subduction seismic sources, and Peninsular India is exposed to crustal seismic sources. Nonlinear analytical models are developed for a set of modern Indian code-compliant reinforced concrete special moment frame buildings located at 20 different sites in India. Incremental dynamic analysis (IDA) of building models using spectrally equivalent ground motions from crustal and subduction earthquakes is used for developing tectonic-region-type-specific (crustal and subduction) building vulnerability functions. The cumulative damage index is used as the engineering demand parameter to capture the increased inelastic demand from subduction earthquakes on buildings. For seismic risk assessment, the total seismic hazard at a site is separated into its contribution from crustal and subduction sources and combined with respective building vulnerability functions. The seismic risk of buildings is quantified by average annual loss ratio (AALR) through event-based probabilistic seismic risk analysis. For buildings located in high seismic zones of India, this study finds that AALR can be up to 40% higher on average as compared to studies not accounting for increased building vulnerability from subduction earthquakes.

Abstract The Lightweight Steel Framing (LSF) system has been proposed as an economical system that is earthquake resistant. Due to the lightness of LSF structures, the seismic performance of middle-rise buildings has been improved. Nowadays, various numerical-analytical methods have been proposed for seismic assessment of conventional structures. Using scientific and statistical standards, this article provides two new methods for calculating the damage index of LSF structures. Once this index is determined, a correct understanding of structural behavior is obtained and the retrofitting criteria are drawn. The modified relationship method is based on Papadopoulos relationship which is modified using modification factors of seismic geotechnics. From another viewpoint, non-linear static analysis was used to calculate the criteria of this relationship. To detect the limit of the first failure and destruction of the entire structure, the formation of plastic hinges in columns is considered. Material properties were defined according to the performed experimental studies. To give a qualitative simple and functional damage index, the functional method was given in the form of a qualitative method with statistical analysis and collection of different views. Using this method is very simple and meantime offers suitable accuracy. With a numerical study on three LSF models there were made clear that the difference of the new method and the amended method of Papadopoulos is approximately 5%. This shows that the given qualitative method is suitable to be used in broad terms. Since the damage index of light steel structure for Model 1 and Model 3 are between 0.4 and 0.8, it is necessary to rehabilitate these structures using the modified method and the proposed qualitative damage index.

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In this paper, the parameters optimization of a tuned mass damper (TMD) is presented to enhance the seismic performance of a six-story steel structure based on the ductility damage index. Herein, the six-story frame is modeled nonlinearly in the OpenSees software by a concentrated plasticity model. Finally, the most suitable algorithm is selected among several optimization algorithms based on the convergence rate and the objective function's values. In this process, the water cycle algorithm has shown the best results. Therefore, the optimal parameters of the TMD are calculated by this algorithm in such a way that the ductility damage index is minimized in the six-story structure under earthquake loads. For this purpose, the nonlinear dynamic analysis of the structure is performed under earthquakes loads using the OpenSees software. Also, the optimum parameters of the TMD are computed to minimize the ductility damage index under the earthquake loads by linking the OpenSees and Matlab software. The results show that the optimum parameters of the TMD system obtained by the water cycle algorithm could appropriately decrease the ductility damage index. It can simultaneously increase the structure's seismic performance to reduce the displacement, stories damage, and drift ratio.

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A vertical irregularity setback in reinforced concrete (RC) building affects its performance and response especially subjected to earthquake ground motions. It is necessary to understand how the seismic damage is established due to setbacks and avoid damage concentration on the irregularity section. The objective of this study is to propose a formula to estimate the damage distribution along the height of the setback building from a geometric measure of the degree of irregularity. First, previous experimental tests for two types of setback buildings, a towered and a stepped setback frames, were analyzed to verify the accuracy of the frame analysis. The results of the frame analysis considerably matched the experimental test results. Furthermore, to study the relationship between the degree of setback and the distribution of damage, a parametric study was conducted using 35 reinforced concrete setback frames, consisting of models with stepped setback type and towered setback type with different degrees of setback. The inelastic dynamic analyses of all the frames under three earthquake ground motions were conducted. The irregularity indices proposed in literature were adopted to express the degree of setback and the structural damage was expressed by the Park–Ang damage index. Using nonlinear regression analysis, formulas to estimate damage index ratio between two main structure parts (tower and base) from setback indices were proposed. Finally, the proposed formula was applied to the experimental test results to confirm its validity.

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Abstract In the analysis of damage to a structure after the occurrence of a destructive event, it is impossible to estimate the exact amount of damage to any part of the structure. Therefore, it is necessary to introduce failure indicators to assess the amount of damage to structural elements. For this purpose, in this study, the damage caused to the coupled-steel plate shear wall (C-SPSW) system under earthquake load was investigated. In this paper, three damage index of park and Ang, ductility and drift using numerical methods upon multi-story C-SPSW systems are investigated. Following the validation of the numerical simulation through a comparison of the experimental results and numerical predictions, a parametric study was performed to evaluate the damage indexes. Comparative results of the hysteresis curves obtained from the finite element analysis with the experimental curves indicated that the finite element model offered a good prediction of the hysteresis behavior of C-SPSW. In the parametric study, Thirty prototype multi-story C-SPSW systems with different the height of the structures were designed, modeled, and using nonlinear seismic analysis. The results show that the use of cumulative damage indices, which is a combination of several different failure parameters, it predicts the vulnerability of structures more realistically.

An effective, convenient and reliable intelligent seismic evaluation system for buildings in Malaysia has been developed in this study by using Back-Propagation Artificial Neural Network (ANN) algorithm. A total of forty one buildings with 164 sets of input data spreading throughout Peninsular and East Malaysia were chosen and analyzed using IDARC-2D finite element software under seismic loading at peak ground accelerations of 0.05g, 0.10g, 0.15g and 0.20g respectively. Non-linear dynamic analysis was performed in order to obtain the damage index of each building. The ANN algorithm comprising 15 hidden neurons with 1 hidden layer outperformed other combinations in predicting the damage index of buildings with accuracy statistical value of 93% in testing phase as well as 75% in validation stage. From the results, the ANN system is suitable to be used for predicting the seismic behaviour of their buildings at any given time.

Steel fiber reinforced concrete (SFRC) structures have been widely adopted and attracted great research attention due to their excellent performance in resisting tension and flexure bending. However, the existing analytical and numerical analyses of SFRC structures rely mainly on the experimental data of material tests, thereby being suitable for a case‐by‐case basis. This is due to the lack of a general and reliable constitutive material model for SFRC, which analytically considers the fiber‐dependent parameters such as fiber geometry, fiber stiffness, and interface properties of fibers and concrete matrix. This study presents an approach to modify the concrete plastic damage model to represent the SFRC material constitutive relations for simulating the structural behavior of SFRC. In this approach, the general procedure to integrate the bridging effect of fibers through the pull‐out mechanism into the constitutive relation of SFRC was proposed. The comparison between the numerical and experimental results was conducted to verify the reliability of the proposed model. The results demonstrated the proposed model could well represent the material performance of SFRC and the numerical simulations could capture reasonably the effect of the volume fraction, geometry, and properties of fibers on the structural response of SFRC.

In the literature, fatigue-loaded reinforced concrete (RC) beams have been the subject of several experimental investigations; however, few numerical studies have specifically examined this behavior. The primary goal of this study is to create and validate a comprehensive nonlinear finite element (FE) modeling framework that combines an existing concrete damage model with specialized modelling techniques (e.g., material modelling, structural modelling, mesh configuration) to forecast the behaviour of reinforced concrete beams under monotonic fatigue loads and track the failure progress. This was accomplished by implementing suitable constitutive and structural models pertaining to concrete and reinforcing steel using VecTor2 finite element software. The Lü concrete damage model, which accounts for the accumulated damage in the concrete at each loading cycle, was taken from the literature to enhance the numerical findings. A number of published experimental tests conducted under monotonic fatigue loading were used to assess the accuracy of the suggested numerical model. The obtained numerical results demonstrated that the FE model may be used to simulate the monotonic fatigue behaviour of various RC beam types. The monotonic fatigue results were significantly improved by applying the Lü concrete damage model. Additionally, the FE model was implemented into practice to offer valuable information on failure mechanisms, fracture patterns, and strain profiles at different loading cycles.

Abstract This paper presents a simple lumped damage model to analyse reinforced concrete beams under impact loads. The proposed model is based on the thermodynamics of irreversible processes. In this framework, key concepts of fracture and damage mechanics are applied on plastic hinges. Since the inelastic phenomena are modelled by two internal variables, named damage and plastic rotation, the plastic hinges are now called inelastic hinges. Therefore, the proposed finite element is an assemblage of an elastic beam with two inelastic hinges at its edges. Experimental results are used to propose the evolution laws of the internal variables. The proposed model is applied to other experiments and the obtained results show its accuracy. Finally, if an extensive experimental campaign could be carried out, a practical engineering criterion can be elaborated in terms of the damage variable (concrete cracking), which may be useful as a decision-making criteria for retrofit worthiness.

Abstract We present a method of simulating the cohesive fracture behavior of reinforced concrete. The proposed method achieved a satisfactory correspondence with the experimental results. An outstanding feature of the proposed method is its ability to reproduce the three-dimensional (3D) geometry and distribution of arbitrary cracks and the plastic deformation of reinforcing-bars by using the finite element method (FEM) and a damage model based on the concrete’s fracture mechanics, which were considered in the modeling of cohesive-crack behavior in concrete. Our study began with the formulation of a nonlinear computational model for each constituent in the reinforced concrete. Four-point bending tests for reinforced concrete (RC) beams with different shear reinforcements were used to verify and validate the effectiveness of the proposed method. The analysis results of an RC beam without shear reinforcements indicate that the crack propagation behavior simulated with the proposed method had little dependency on the mesh size. Finally, a comparison between the numerical and experimental results revealed that the proposed method enables the simulation of RC beam failure patterns with satisfactory accuracy and without changing the material parameters.

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This article presents a vision‐aided framework to achieve three‐dimensional (3D) concrete damage quantification and finite element (FE) model geometric updating for reinforced concrete structures. The framework can process images and point clouds to extract damage information and update it in an FE model. First, a mask region convolutional neural network was used to realize highly precise damage detection and segmentation based on images. Second, a 3D point cloud was adopted in conjunction with the processed images for 3D damage qualification. The model‐updating method enables an FE model to delete concrete elements to update the variations in volume caused by structural damage. This framework supports interaction with mainstream FE software for further analysis. To demonstrate the efficiency of the proposed framework, it was used in an experiment on a reinforced‐concrete shear wall.

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Abstract Structures subjected to cyclic loads show alternative tension–compression stress states; in such a case, even if certain damage (fracture) is reached during the tension cycle, the computational model of the structure should maintain its capacity to withstand subsequent compression based only on the contact effect in the damaged area (opening, closing and reopening of cracks). In order to control this behavior, a phenomenological constitutive model able to consider the contact as a structural limitation is required. From the constitutive point of view, geomaterials have different damage thresholds for tension and compression and, from the structural point of view, it must be ensured that the material damaged in tension still resist compression. In this case, it is accepted that cracks behave as a contact surface at the structural level. To meet the above mentioned phenomenology, a modification of the damage model differentiated in tension and compression proposed by Faria et al. [Faria R, Oliver J, Cervera M. A strain-based plastic viscous-damage model for massive concrete structures. Int J Solids Struct 1998; 35:1533–58] is performed in this paper, considering independent strength thresholds in each of these processes, controlled with two independent discontinuity threshold functions. Also, in this work an elasto-plastic constitutive model is used to represent the behaviour of the steel bars.

Seismic damage assessment of reinforced concrete (RC) structures is a vital issue for post-earthquake evaluation. Conventional onsite inspection depends greatly on subjective judgments and engineering experiences of human inspectors, and the efficiency is limited to large-scale urban areas. This study proposes a computer-vision and machine-learning-based seismic damage assessment framework for RC structures. A refined Park-Ang model is built to express the coupled effects of structural ductility and energy dissipation, which reflects the nonlinear seismic damage accumulation and generates a synthetical seismic damage indicator within 0~1 using hysteretic curve data. A deep neural network is established to regress the damage indicator using damage-related and design-related parameters as inputs. The results show that the correlation coefficients between the predicted and actual seismic damage index exceed 0.98, and the predicted seismic damage index is unbiased and stable without overfitting. Furthermore, the effectiveness, robustness, and generalization ability of the proposed method are verified.

Abstract This work presents a numerical method for damage analysis of reinforced concrete beams using the higher-order beam theory based on Carrera unified formulation. The component-wise approach is employed to model the concrete and steel reinforcing bars as two independent one-dimensional finite elements. A modified Mazars damage model with tensile and compressive damage propagation laws is utilized for concrete, and an elastic-perfectly plastic law is used for steel rebars. To address the instability and mesh dependence caused by the strain-softening behavior of concrete, a fracture energy regularization technique based on the crack band model is developed, especially for the higher-order beam theory. The proposed method is validated by comparing its numerical results with three experimental benchmark results. The comparison indicates that the method accurately predicts the damage distribution of concrete and the flexural behavior of RC beams under quasi-static loading conditions while remaining computationally efficient.

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Abstract Predicting the residual behaviour of buildings in the damaged state is essential for quantitative performance assessment of post-earthquake damaged structures, which facilitates post-earthquake reconstruction. Quantification of the damage level and distribution in post-earthquake damaged structures is challenging but necessary for predicting their residual behaviour. The objective of this study was to develop a new damage distribution model for accurately predicting the residual behaviour of an earthquake-damaged reinforced concrete (RC) column. The damage relationship along the column height in the plastic hinge zone between the reference concrete and the RC column was established via fitting to experimental data. According to this relationship and the plane section assumption, the damage distribution in the plastic hinge zone was derived analytically. The damage levels of materials at different locations in the plastic hinge zone can be evaluated. The proposed damage distribution model was used to predict the residual behaviour of an earthquake-damaged RC column, and the revised ASCE-41 model was used for comparison. The verification and analyses indicated that the residual behaviour of the damaged RC column can be predicted more accurately with the proposed damage distribution model than with the ASCE-41 model. The proposed model enables accurate prediction for the residual behaviour of damaged RC columns and provide reference for reconstruction decisions.

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A multi-scale micromechanical model is proposed to predict the damage degree of hybrid fiber-reinforced concrete under or after high temperatures. The thermal degradation of hybrid fiber-reinforced concrete is generally composed of the damage of the cement paste caused by thermal decomposition and thermal incompatibility, the deterioration of aggregates and fibers, and the interfacial damage between aggregates and the matrix. In this multi-scale model, four levels of hybrid fiber-reinforced concrete structures are considered when the thermal damage degree is derived; namely, the equivalent calcium silicate hydrate (C–S–H) product level, the cement paste level, the concrete level, and the hybrid fiber-reinforced concrete level. At the cement paste level, thermal decompositions of C–S–H product and calcium hydroxide are taken into account. In addition, a dimensionless parameter of the crack density is introduced to represent the thermal cracking of the matrix. At the concrete level, the interfacial damage of aggregates is simulated by a spring–interface model, in which the interfacial parameters are assumed to be functions of temperature. Moreover, at the cement paste level and the hybrid fiber-reinforced concrete level, a sub-stepping homogenization method is proposed to determine the effective properties. Comparisons between previously published experimental data and predictions and discussions illustrate the feasibility of the proposed multi-scale model in predicting thermal damage of concrete and hybrid fiber-reinforced concrete.

Rapid and accurate post‐earthquake damage evaluation of regional reinforced concrete (RC) bridges is a key issue for assessing the seismic resilience of cities and communities. Especially, RC bridges are susceptible to the aggressive environment, which can induce time‐dependent aging effects such as corrosion, and thus, it should be considered in the assessment. This paper presents an approach for regional seismic performance assessment of RC bridges in a life‐cycle context based on machine‐learning techniques. The life‐cycle seismic demand and capacity of the bridges are, firstly, obtained by the elaborated numerical model, which includes the deterioration induced by the aging corrosion effect. Then, the tagging‐based damage state (green, yellow, or red) is easily obtained by comparing the pairs of demand and capacity through machine learning. Four hundred and eighty bridge models are generated to develop the machine‐learning models and the performance of the machine learning models is evaluated. Results show that the extreme gradient boosting (XGBoost) model has the best performance, which has an accuracy of 81% in predicting the damage states. The proposed approach is demonstrated with a single bridge example and bridges in a sample region. It is shown that the machine learning model can accurately predict the post‐earthquake damage states of the single bridge, and it can also rapidly assess the damage states of the bridges in the sample region. Approximately 30% bridges in the sample region will experience damage states shift after 100 years, which highlights the importance of considering the aging effects on the post‐earthquake damage assessment of bridges.

Abstract n order to study the constitutive model of hybrid fiber concrete (HFRC) and the law of damage evolution, the damage constitutive model of -PP and PVA-PP mixed fiber with steel is studied by means of statistical method and energy method. The damage variable correction coefficient is introduced to optimize the statistics based method. The energy method is used to deduce the constitutive model of material damage based on the SIR model and the formula and to discuss the physical meaning of the parameters. At the same time, the accuracy of the model is verified by a single axial compression test. The results show that the stress strain curve obtained by the statistical method is in good agreement with the test results when the strain is relatively small. When the strain is large, the result is deviant from the test result. The calculation result is more accurate after the damage deformation correction coefficient is introduced. The calculation of the energy method based on the SIR model is simple, the result is high and the strain is still high. The residual stress of the specimen can be reacted. The two methods can be used to calculate the compression damage constitutive model of hybrid fiber reinforced concrete, and it can be applied in engineering.

Abstract In this paper, a rational analysis procedure is presented to model the typical cyclic behavior of reinforced concrete (RC) shear wall structures. A recently developed multi-dimensional softened damage-plasticity damage model, where the compression-softening effect of reinforced concrete is considered, is adopted to describe the concrete material behaviors. The steel material behaviors follow a modified Menegotto-Pinto model that including strain hardening, Bauschinger effect and tension stiffening. The multi-layer shell element, which is capable of simulating the coupled in-plane/out-of-plane bending as well as in-plane direct shear and the coupled bending-shear behavior of RC shear walls, is used for the finite element modeling of the structures. To overcome the convergence issues in the analysis procedure, the quasi-Newton method is adopted to solve the nonlinear finite equations and the iterative secant stiffness with plasticity offset for cyclic loading is introduced. Finally, several numerical simulations of RC shear walls with different failure modes are given, illustrating that the developed numerical model can accurately predict the cyclic behavior of RC shear wall structures.