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Seismic isolation structures have excellent seismic mitigation effects, but implementing isolation measures may increase the initial cost of the structure. This paper presents a method to calculate the seismic loss and assess the life-cycle cost of isolated structures, which is convenient for owners to make decisions. The life-cycle cost assessment model is divided into two parts: initial cost assessment and seismic loss assessment over life-cycle period. Among them, the assessment method of the isolation layer is proposed, including the cost assessment of isolation bearings and dampers. The assessment method of seismic loss considers direct loss, indirect loss, casualties and integrating casualties into a unified assessment system. Direct loss includes building loss, indirect loss includes rental loss, relocation loss, income loss, personal property loss and business inventory loss. The seismic loss model is associated with seismic damage probability, which is obtained through seismic vulnerability and seismic probability risk assessment. The 8-story base-isolated-reinforced concrete structure illustrates the feasibility of the life-cycle-cost assessment model. The example shows that the initial cost of the isolated structure exceeds that of the nonisolated structure, however, the rental loss, income loss, personal property loss and casualties are much lower than those of nonisolated structures. The income loss of the isolated structure is the maximum proportion in life-cycle cost, and the casualty loss is the minimum proportion in the seismic loss, due to its excellent seismic mitigation effects. [ABSTRACT FROM AUTHOR]

Jacket structures play an ever-increasing role in meeting the world's burgeoning energy demand by providing support structure for exploiting offshore wind energy and oil and gas resources. Many of these structures are past their design lifetimes, and thus may have suffered significant degradation, highlighting the importance of investigating their earthquake response in seismically active regions. This study investigates the seismic performance of a typical offshore jacket platform, denoted as baseline structure, as well as four versions with two longer (25% and 50% larger) and two shorter (25% and 50% smaller) natural vibration periods accounting for two levels of degradation and retrofit effects on structural performance. For each case, eleven ensembles of ground motions compatible with the site's seismic hazard are selected using the generalized conditional intensity measure methodology. The loading uncertainty is incorporated in the performance assessment procedure via probabilistic seismic demand analysis and the demand hazard is quantified. The results provide valuable information regarding reliability of these structures both at design stage and during service life, which can aid decision-making around rehabilitation of older platforms, the suitability of reusing obsolete platforms beyond service lifetime, and risk-based design of new platforms. [ABSTRACT FROM AUTHOR]

Catastrophe bonds (cat bond in short) are an alternative risk‐transfer instrument used to transfer peril‐specific financial risk from governments, financial institutions, or (re)insurers, to the capital market. Current approaches for cat bond pricing are calibrated on seismic mainshocks, and thus do not account for potential effects induced by earthquake sequences. This simplifying assumption implies that damage arises from mainshocks only, while aftershocks yield no damage. Postearthquake field surveys reveal that this assumption is inaccurate. For example, in the 2011 Christchurch Earthquake sequence and 2016–2017 Central Italy Earthquake sequence, aftershocks were responsible for higher economic losses when compared to those caused by mainshocks. This article proposes a time‐dependent aggregate loss model that takes into account seismicity clustering and damage accumulation effects in the computation of damage. The model is calibrated on the seismic events recorded during the recent 2016–2017 Central Italy Earthquake sequence. Furthermore, the effects of earthquake sequence on cat bond pricing is explored by implementing the proposed model on five Italian municipalities. The investigation showed that neglecting time‐dependency may lead to higher difference (up to 45%) in the cat bond price when compared to standard approaches. [ABSTRACT FROM AUTHOR]

Earthquake-induced damage to gas pipelines can have severe economic, social, and environmental consequences. To mitigate these risks, one effective way is to carefully design the route of gas pipelines, considering the seismic hazard of the region. This paper proposes a methodology that incorporates seismic risk assessment into the process of designing gas pipeline routes. Conventional gas pipeline design methods consider only minimum distances from faults and fail to account for seismic potential. The methodology is applied to three gas pipeline routing problems in the high seismic region of southern Iran. Seismic risk is evaluated using the HAZUS method, and routing is performed through a GIS-based approach. Results are compared with conventional approaches in terms of length, seismic risks, and damage costs, showing the proposed method's effectiveness in reducing immediate consequences like leaks and breaks in gas transportation. The proposed method reduces seismic damage by 3 to 68% for routing problems. [ABSTRACT FROM AUTHOR]

Earthquakes are major catastrophes that cause great life and economic losses to human society and environment. This paper reviews and synthesizes relevant studies, drawing from a systematic examination of 4229 articles from the Web of Science core collection (1982–2023). Employing the CiteSpace visualization and analysis tool, current research and emerging trends in seismic risk assessment are discussed and analyzed. This paper provides a holistic overview of principal contributions, knowledge sources, interdisciplinary characteristics, and principal research topics in this field. Additionally, we propose key technologies that are in urgent need of enhancement, including data availability, quantity and quality of data, interpretability of machine learning models, performance improvement of machine learning methods and application of foundation models, as well as real-time risk assessment techniques. These insights support both theoretical understanding and practical applications of seismic risk assessment and damage analysis.

Many structures service in complex environments where multiple environmental factors (MEFs) coexist, and the coupling effects of MEFs often aggravate structural damage, thus increasing the risk of structural collapse and economic loss under seismic excitation. For structural damage caused by coupling effects of MEFs, previous studies have been mostly focused on one-way coupling analysis, such as the effect of structural pre-corrosion on its fatigue damage, and less attention to the interaction coupling effect of MEFs, which make it difficult to quantitatively calculate the interactive coupling damage due to the existence of MEFs. The large error of using one-way coupling damage calculation method to estimate the residual mechanical performance of the structure will reduce the reliability of seismic risk assessment of the structures suffering interaction coupling of MEFs. To solve such problem, this paper proposes a damage calculation method for structures considering the effect of interaction coupling of MEFs by establishing a multivariable interaction model, in which a coefficient β(t) is introduced to characterize the time-varying mechanisms of the interaction coupling effect of MEFs (e.g., the acceleration of structural damage with service time). Then, the solution method for β(t) is proposed by using Bayesian inference. Finally, a framework for analyzing the time-varying seismic risk of engineering structures considering the evolution of damage caused by interaction coupling of MEFs is established in which the uncertainty of environmental factors is also involved. The presented analysis framework is illustrated using a towering structure in a coastal area, and the results emphasize that the interactive coupling effect of MEFs can significantly increase the risk of structural collapse and economic loss. [ABSTRACT FROM AUTHOR]

Abstract This study presents a probabilistic seismic risk model for the Beijing–Tianjin–Hebei region in China. The model comprises a township-level residential building exposure model, a vulnerability model derived from the Chinese building taxonomy, and a regional probabilistic seismic hazard model. The three components are integrated by a stochastic event-based method of the OpenQuake engine to assess the regional seismic risk in terms of average annual loss and exceedance probability curve at the city, province, and regional levels. The novelty and uniqueness of this study are that a probabilistic seismic risk model for the Beijing–Tianjin–Hebei region in China is developed by considering the impact of site conditions and epistemic uncertainty from the seismic hazard model.

Improved utilization of coal mine overburden material (CMOB)‐incorporated concrete in the construction sector can contribute to developing a more sustainable built environment if the results of proven research on the behavior of structures constructed of CMOB‐incorporated concrete are applied. Even though there have only been a few studies on CMOB‐incorporated concrete, no research has been done on how this type of concrete can be used in structures. In particular, researchers have not paid much attention to the fact that the strength properties of CMOB‐incorporated concrete tend to be very variable, even though this variability is needed for a wide range of structural applications (such as limit state design formulation, reliability‐based structural analysis, etc.). For the first time, this research provides quantitative estimates of the variability in compressive‐, flexural‐, and splitting tensile strengths of cured concrete using varying amounts of a CMOB sample as fine aggregate. Taking into account the suggested distribution model, the research also provides a reliability‐based seismic risk assessment of a standard CMOB‐incorporated framed building. The failure probability and dispersion in the drift demand were found to be the same for the frames modeled with CMOB and standard concrete (natural sand); the results demonstrate that CMOB samples can be safely used for earthquake‐resistant constructions. [ABSTRACT FROM AUTHOR]

Recent earthquakes have highlighted that aftershocks can considerably increase the structural demand and seismic risk of engineering structures. This study presents a probabilistic approach to assess the seismic risk of reinforced concrete (RC) frame structures subjected to mainshock‐aftershock sequences. In this approach, a predictive fragility method is used to evaluate the probabilities of structural damage under sequential excitations. The Bayes theorem is employed to generate posterior distributions of unknown model parameters. Then, a practical seismic hazard assessment method is used to conduct mainshock‐aftershock hazard analysis. The Copula technique is employed to develop a joint distribution model of the mainshock and aftershock intensity measures. Finally, the seismic risk is evaluated using the classical risk integration equation with the mainshock‐aftershock fragilities and hazard surfaces. Confidence bounds for fragilities and seismic risks are also obtained to account for the uncertainties of model parameters caused by aftershocks. The proposed approach is demonstrated by considering a seismic‐designed RC frame building. It can be concluded that aftershocks can significantly increase the seismic risk throughout the entire structural service life. The additional uncertainties caused by aftershocks result in wider confidence bounds for seismic risk. [ABSTRACT FROM AUTHOR]

Past major earthquakes have demonstrated that a significant proportion of existing residential buildings are vulnerable to seismic hazards, resulting in economic and social losses. The assessment of earthquake‐induced losses is crucial for devising strategies aimed at enhancing seismic resilience through mitigation plans and emergency response measures. This study intends to provide an analytical methodology for evaluating economic losses for existing residential concrete shear wall buildings in Eastern Canada seismic zones based on Canadian‐compatible seismic capacity parameters. A sampled data set related to residential buildings in Montreal was analyzed and statistical distributions were developed that represent the proportion of buildings in different seismic design code levels and number of stories. Vulnerability analyses were performed, which involved estimating buildings' response under seismic hazard inputs according to the 2020 National Building Code of Canada and conducting loss assessment for structural components, nonstructural displacement‐sensitive components, nonstructural acceleration‐sensitive components, and contents. The results of vulnerability analyses in terms of loss ratio curves showed that the seismic performance varies between mid‐rise and high‐rise concrete shear wall buildings with different seismic design code levels, and nonstructural displacement‐sensitive components exerted the most significant influence on overall economic losses among building components. In addition, a comparison was conducted between Canadian‐compatible economic loss ratio curves and those developed based on the standard seismic capacity parameters in the Hazus technical manual and differences in predicted loss ratios were discussed. The developed loss ratio curves can be integrated into regional scale loss assessment tools for rapid estimation of earthquake‐induced economic losses for concrete shear wall buildings as a function of seismic intensity. [ABSTRACT FROM AUTHOR]

This study presents a probabilistic seismic risk model for the Beijing–Tianjin–Hebei region in China. The model comprises a township-level residential building exposure model, a vulnerability model derived from the Chinese building taxonomy, and a regional probabilistic seismic hazard model. The three components are integrated by a stochastic event-based method of the OpenQuake engine to assess the regional seismic risk in terms of average annual loss and exceedance probability curve at the city, province, and regional levels. The novelty and uniqueness of this study are that a probabilistic seismic risk model for the Beijing–Tianjin–Hebei region in China is developed by considering the impact of site conditions and epistemic uncertainty from the seismic hazard model. [ABSTRACT FROM AUTHOR]

Accurately characterizing ground motions is crucial for estimating probabilistic seismic hazard and risk. The growing number of ground-motion models, and increased use of simulations in hazard and risk assessments, warrants a comparison between the different techniques available to predict ground motions. This research aims at investigating how the use of different ground-motion models can affect seismic hazard and risk estimates. For this purpose, a case study is considered with a circular seismic source zone and two line sources. A stochastic ground-motion model is used within a Monte Carlo analysis to create a benchmark hazard output. This approach allows the generation of many records, helping to capture details of the ground-motion median and variability, which a ground motion prediction equation may fail to properly model. A variety of ground-motion models are fitted to the simulated ground motion data, with fixed and magnitude-dependant standard deviations (sigmas) considered. These include classic ground motion prediction equations (with basic and more complex functional forms), and a model using an artificial neural network. Hazard is estimated from these models and then we extend the approach to a risk assessment for an inelastic single-degree-of-freedom-system. Only the artificial neural network produces accurate hazard results below an annual frequency of exceedance of 1 × 10–3 years−1. This has a direct impact on risk estimates—with ground motions from large, close-to-site events having more influence on results than expected. Finally, an alternative to ground-motion modelling is explored through an observational-based hazard assessment which uses recorded strong-motions to directly quantify hazard. [ABSTRACT FROM AUTHOR]

Abstract This study achieved the construction of earthquake disaster scenarios based on physics-based methods—from fault dynamic rupture to seismic wave propagation—and then population and economic loss estimations. The physics-based dynamic rupture and strong ground motion simulations can fully consider the three-dimensional complexity of physical parameters such as fault geometry, stress field, rock properties, and terrain. Quantitative analysis of multiple seismic disaster scenarios along the Qujiang Fault in western Yunnan Province in southwestern China based on different nucleation locations was achieved. The results indicate that the northwestern segment of the Qujiang Fault is expected to experience significantly higher levels of damage compared to the southeastern segment. Additionally, there are significant variations in human losses, even though the economic losses are similar across different scenarios. Dali Bai Autonomous Prefecture, Chuxiong Yi Autonomous Prefecture, Yuxi City, Honghe Hani and Yi Autonomous Prefecture, and Wenshan Zhuang and Miao Autonomous Prefecture were identified as at medium to high seismic risks, with Yuxi and Honghe being particularly vulnerable. Implementing targeted earthquake prevention measures in Yuxi and Honghe will significantly mitigate the potential risks posed by the Qujiang Fault. Notably, although the fault is within Yuxi, Honghe is likely to suffer the most severe damage. These findings emphasize the importance of considering rupture directivity and its influence on ground motion distribution when assessing seismic risk.

Recent seismic events and the damages related to them have highlighted the crucial role of urban planning in coping with the fragility and intrinsic vulnerability of cities. The paper presents a methodology for assessing seismic risk at an urban scale, expanding from a single-building investigation to an urban-scale analysis by adopting an empirical method for assessing the vulnerability of the urban fabric. Data collection and analysis have been conducted through the Geographic Information System (GIS). The methodology has been applied to the Italian city of Castelfranco Emilia, in the Emilia-Romagna region, where the current regional urban planning law is guiding municipalities towards the development of strategies mostly oriented toward the retrofit of the existing building stock and the overall regeneration of the urbanized territory, in accordance with the target of no net land take by 2050. The novelty of the method stands in the transposition of approaches born in the civil engineering and protection domains to the urban planning sphere, stressing the importance of developing urban planning instruments which are well-integrated with vulnerability assessments and, therefore, able to successfully incorporate risk considerations in the decision making. [ABSTRACT FROM AUTHOR]

Identifying seismic risk factors and determining necessary resources are critical for effective post-earthquake mitigation planning. This usually involves field assessments, data collection, and disaster scenario simulations. After an earthquake, the focus is on providing medical services and although hospitals are vital in saving lives, they may become overwhelmed with injured patients. As a result, it is essential to establish post-disaster strategies to ensure continued access to medical services. This study introduces a framework that analyses an earthquake's temporal effect on a hospital network's emergency response capabilities under various casualty transfer strategies. The framework initially evaluates the seismic vulnerability of buildings to estimate the medical demand and subsequently assesses the resilience of the hospital network based on patients waiting times for ambulance arrivals and treatment in the emergency departments of the hospitals. The model determines the optimal allocation of emergency department capacity across the hospital network and evaluates each hospital's performance. The framework is implemented in Bayrakli, a metropolitan district in Izmir, Turkey, which has a unique building inventory dataset. The study demonstrated how various casualty transfer decisions can expedite the transportation process, providing valuable insights for creating effective emergency management and mitigation strategies in areas that are prone to earthquakes. [ABSTRACT FROM AUTHOR]

This study achieved the construction of earthquake disaster scenarios based on physics-based methods—from fault dynamic rupture to seismic wave propagation—and then population and economic loss estimations. The physics-based dynamic rupture and strong ground motion simulations can fully consider the three-dimensional complexity of physical parameters such as fault geometry, stress field, rock properties, and terrain. Quantitative analysis of multiple seismic disaster scenarios along the Qujiang Fault in western Yunnan Province in southwestern China based on different nucleation locations was achieved. The results indicate that the northwestern segment of the Qujiang Fault is expected to experience significantly higher levels of damage compared to the southeastern segment. Additionally, there are significant variations in human losses, even though the economic losses are similar across different scenarios. Dali Bai Autonomous Prefecture, Chuxiong Yi Autonomous Prefecture, Yuxi City, Honghe Hani and Yi Autonomous Prefecture, and Wenshan Zhuang and Miao Autonomous Prefecture were identified as at medium to high seismic risks, with Yuxi and Honghe being particularly vulnerable. Implementing targeted earthquake prevention measures in Yuxi and Honghe will significantly mitigate the potential risks posed by the Qujiang Fault. Notably, although the fault is within Yuxi, Honghe is likely to suffer the most severe damage. These findings emphasize the importance of considering rupture directivity and its influence on ground motion distribution when assessing seismic risk. [ABSTRACT FROM AUTHOR]

Recent earthquakes clarified that existing a soft/weak-story in a building could completely invert the failure mechanisms of the structure. Several studies were implemented to evaluate the potential risk subjected to the buildings under the earthquake hazard. However, these researchers discarded the effect of soft/weak-story on the demand parameters of their models. This paper presents a rapid demand estimation framework for generic buildings considering the effect of soft/weak-story. In this regard, the simplified model developed according to the HAZUS approach is rectified to apply the effect of soft/weak-story on the structural behavior of the generic buildings. Artificial neural networks are implemented to remove the required time-consuming nonlinear response history analyses from the post-earthquake actions. This research utilized a suite of 111 earthquake records, originally developed by the SAC project. These motions are uniformly scaled from 0:1g to 1:5g to obtain a generalized dataset with different intensities. Bayesian optimization algorithm is conducted to achieve a prediction model with optimized hyperparameters. Results clarify that the proposed method is reliable and computationally cost-effective in predicting the demand parameters of generic buildings. This framework can be used in the body of a risk assessment platform to facilitate the emergency response to the earthquake hazard. [ABSTRACT FROM AUTHOR]

• A simple and easy-to-understand seismic risk assessment method for cultural artifacts was proposed. • The Law of Large Numbers was applied to achieve the seismic risk assessment. • Three types of common porcelain vases were taken as case studies for seismic risk assessment. • A comparison was conducted between the developed method and an existing method. Earthquakes can cause significant damage to cultural artifacts, which often hold significant historical or cultural value. Seismic risk assessments can contribute to a more targeted approach by museum staff to the preventive conservation of cultural artifacts. The primary objective of this research is to suggest a new approach for assessing the seismic risk of cultural artifacts. This innovative method is founded on the Law of Large Numbers and aims to provide a more user-friendly way of evaluating the likelihood of potential seismic threat to cultural artifacts. The proposed method takes into account the statistical distribution of seismic ground motion and the seismic response characteristics of artifacts, and its accuracy and practicality are demonstrated by case studies. Compared with existing methods, the proposed method has the advantages of theoretical simplicity, low computational effort, and easier to be understood and mastered by museum staff. Furthermore, the impact of sample size on the assessment results was investigated. The findings demonstrate that the proposed method represents a valuable tool for cultural heritage risk decision-makers to evaluate the seismic risk of artifacts. By using this method, they can more effectively assess the potential damage caused by seismic effects and design suitable mitigation measures accordingly. [Display omitted] [ABSTRACT FROM AUTHOR]

Copyright of Journal of Harbin Institute of Technology. Social Sciences Edition / Haerbin Gongye Daxue Xuebao. Shehui Kexue Ban is the property of Harbin Institute of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Efficient regional seismic risk assessment including ground motion prediction and damage risk estimation is needed for emergency response planning. However, a conventional regional assessment suffers from low data‐ and time‐ efficiency as it generally involves a large number of locations and infrastructure systems that have specific soil conditions, and geometric, material, and structural properties, requiring access to large data and massive individual calculations with complicated procedures. To achieve efficient regional seismic risk assessment, this work presents a deep generative learning framework to construct input–output surrogate models of regional seismic risk by learning the underlying complex relation between earthquake source parameters and regional seismic risk involving many locations and structures from data. The learned deep surrogate models directly output the ground motion intensity map and the risk map of a region given earthquake source parameters, circumventing massive individual calculations and data access to individual locations and structures. The presented framework is validated on the bridge network risk assessment using simulated scenario earthquakes of the San Francisco Bay Area. We observe that the obtained deep surrogate models perform well without the need of data access to locations and structures and are time‐efficient. We also discuss the applicability and limitations of the presented framework. [ABSTRACT FROM AUTHOR]

The nation's transportation systems are complex and are some of the highest valued and largest public assets in the United States. As a result of repeated natural hazards and their significant impact on transportation functionality and the socioeconomic health of communities, transportation resilience has gained increasing attention in recent years. Previous studies on transportation resilience have heavily emphasized network functionality during and/or following a scenario hazard event by implicitly assuming that sufficient knowledge of structural capacity and environmental/service conditions is available at the time of an extreme event. However, such assumptions often fail to consider uncertainties that arise when an extreme hazard event occurs in the future. Thus, it is essential to quantify and reduce uncertainties to better prepare for extreme events and accurately assess transportation resilience. To this end, this paper proposes a dynamic Bayesian network-based resilience assessment model for a large-scale roadway network that can explicitly quantify uncertainties in all phases of the assessment and investigate the role of inspection and monitoring programs in uncertainty reduction. Specifically, the significance of data reliability is investigated through a sensitivity analysis, where various sets of data having different reliabilities are used in updating system resilience. To evaluate the effectiveness of the model, a benchmark problem involving a highway network in South Carolina, USA is utilized, showcasing the systematic quantification and reduction of uncertainties in the proposed model. The benchmark problem result shows that incorporating monitoring and inspection data on important variables could improve the accuracy of predicting the seismic resilience of the network. It also suggests the need to consider equipment reliability when designing monitoring and inspection programs. With the recent development of a wide range of monitoring and inspection techniques, including nondestructive testing, health monitoring equipment, satellite imagery, LiDAR, etc., these findings can be useful in assisting transportation managers in identifying necessary equipment reliability levels and prioritizing inspection and monitoring efforts. [ABSTRACT FROM AUTHOR]

Regional seismic risk assessment is necessary for designing effective seismic risk mitigation measures. In general, such risk assessment studies consist of three components: hazard, vulnerability, and exposure modelling. This paper lays the foundations for regional seismic risk assessment of the residential building stock in Serbia and addresses each of the three seismic risk assessment components, either by reviewing the existing or proposing novel models. First, a review of seismic hazard models and seismic design codes used in Serbia in the past 70 years was presented. Next, an overview of Serbia's population metrics and historical development of Serbian's residential building stock was presented to provide the context for the exposure model. Furthermore, the paper proposed a novel building classification for Serbia's residential building stock, which is based on the existing building taxonomies, but it has been adapted to account for the local building characteristics. Building damage patterns reported in past earthquakes in Serbia and neighbouring countries were reviewed as a basis for damage classification pertaining to building typologies included in the proposed classification. Finally, the results of a preliminary vulnerability model were presented in the form of expert-based fragility functions derived for buildings typical of Serbia's residential building stock. [ABSTRACT FROM AUTHOR]

Natural disasters pose a negative impact not only on human lives but also on infrastructures such as healthcare systems, supply chains, logistics, manufacturing, and service industries. The frequency of such calamities has grown over time, which not only poses a threat to human survival and the living environment but is also detrimental to the economic growth and sustainable development of society. Earthquakes cause the most destruction compared to other natural disasters, especially in developing countries where the conventional reactive approach to dealing with disasters gives less chance for the appropriate utilization of already limited resources. Additionally, mismanagement of the resources and the lack of a unified action plan hinder the purpose of helping the grieving population. Considering the foregoing, this study presents a methodology for identifying hotspots and helping prioritize pre- and post-disaster management action by conducting a thorough seismic risk assessment while taking into consideration the case of a developing country as its focus. This methodology allows for rapid risk assessment against any given scenario by providing quantitative estimates of the repercussions such as physical damage to the buildings, casualties including injuries, economic losses, displaced households, debris, shelter requirements, and hospital functionality. In short, it could help prioritize actions with greater impacts and serve as a foundation for the formulation of policies and plans intended to increase the resilience of a resource-constrained community. Thus, the findings can be utilized by government agencies, emergency management organizations, non-government organizations, and aiding countries as a decision support tool. [ABSTRACT FROM AUTHOR]

Considering the development of urban transportation systems and the importance of highway bridges in a city's resilience against earthquakes, it is critical to pay special attention to the seismic risk evaluation of highway bridges. The most significant issue to consider is the assessment of possible direct and indirect damages imposed on bridges before an earthquake. After this, the best practices for bridge rehabilitation can be adopted to minimize the induced damage. In this paper, we assessed the seismic risks associated with all 713 highway bridges in Tehran province (the capital of Iran). These bridges were initially divided into six categories according to their structural system and construction year and were also classified by whether or not seismic design was included. Among the 84,000 earthquakes recommended by the researchers' ten-thousand-year catalog, a set of 50 ground motion records was selected in the course of a probabilistic approach via the Optimization-based Probabilistic Scenarios (OPS) algorithm in an attempt to obtain the least amount of error compared to the original catalog in the final hazard curve in different regions of Tehran province. Afterward, the seismic fragility curves were plotted in four damage states of slight, moderate, extensive, and complete for the six bridge structural systems of simple, steel, concrete slab box, concrete slab–steel box, concrete slab, and steel girder–concrete slab. The results of the fragility curves extracted from the decision tree analysis were validated with those developed from incremental dynamic analysis (IDA) for a bridge case study modeled in the OpenSEES software V2.5.0. Later, using logical relationships, seismic risk curves were drawn for each structural system. The results show that, in general, the average seismic damage of bridges over ten years old is 0.88 times the average damage of bridges less than ten years old. The highest level of vulnerability is associated with the simple bridge system with a median vulnerability of 0.44. Moreover, the lowest level of vulnerability is related to the steel girder–concrete slab bridge system with a median vulnerability of 0.98, showing an increase of approximately 2.2 times in the median vulnerability. In addition, based on the sensitivity analysis results, the indirect and total risk levels increase almost exponentially with increasing the reconstruction index. [ABSTRACT FROM AUTHOR]

A seismic fragility curve is a visual representation that illustrates the likelihood of a structure surpassing a particular damage or performance limit state caused by an earthquake with a specific intensity or ground motion level. This curve is typically generated using probabilistic seismic hazard analysis and structural reliability analysis methods. It is based on statistical models that rely on past earthquake data and simulations of future earthquake scenarios to predict the structure or system's behavior under seismic forces. In this study, the seismic performance of 30 stories of 95 m height dual system reinforced concrete buildings located in Erbil is evaluated by analyzing three distinct ground motions. A non-linear platform is used to simulate and analyze data, followed by the generation of seismic inter-story drift fragility curves using Incremental Dynamic Analysis. The buildings' seismic structural performance is assessed based on five different performance levels, including operational phase, immediate occupancy, damage control, life safety, and collapse prevention (CP). Each level is associated with different levels of damage and corresponding degrees of functionality and safety. The fragility curves show that the building has a 50% chance of achieving or exceeding the (CP) level with highly intense ground vibrations with peak ground acceleration = 1.6 g. In addition, these curves can be beneficial in creating future local design codes and provide significant support in evaluating the seismic performance of existing buildings. [ABSTRACT FROM AUTHOR]

While earthquakes can have a devastating impact on the economic growth and social welfare of earthquake prone regions, probabilistic seismic risk assessment can be employed to assess and mitigate such risks from future destructive events. In a previous study (Sianko et al. in Bull Earthq Eng 18:2523–2555, 2020), a probabilistic seismic hazard analysis (PSHA) tool based on the Monte-Carlo approach, was developed to predict the seismic hazard for high seismicity areas. In this study, a seismic risk assessment framework is developed incorporating the previously developed PSHA tool, with vulnerability functions based on various damage criteria, exposures and casualty models. Epistemic uncertainty is addressed using logic trees and distribution functions. The developed seismic risk assessment framework can estimate human and economic losses for particular return periods using an event-based stochastic procedure. The framework is applied to a case study area, the city of Adapazari in Turkey. Seismic risk assessment is carried out for different return periods to identify the most vulnerable areas of the city. The verification of the developed seismic risk framework is performed by comparing the predicted seismic losses to those observed during the 1999 Kocaeli earthquake that severely affected the city of Adapazari. The results of the study indicate that while overall predictions for extensive and complete damage states demonstrate strong correlation with the observed data, accurate risk predictions at the district level are not achievable without microzonation studies. [ABSTRACT FROM AUTHOR]

Risk-based catastrophe bonds require the estimation of losses from the convolution of hazard, exposure and vulnerability models. These models are affected by different uncertainties that arise from the definition of their input parameters. In this paper, we propose a stochastic approach to treat the uncertainty in the asset location and attributes of the exposure model. The proposed method uses the Monte Carlo sampling approach to generate a stochastic exposure database, where each asset location is generated randomly within the geometric bound of the administration, while the asset attributes (i.e. construction type and material, number of storey, building activity type and number of dwelling) are sampled from distributions built from census data. Finally, a sensitivity analysis is performed to investigate the influence of the spatial resolution of the exposure model on the average annual losses (AAL) and catastrophe bond prices. To this end, we implement four exposure models, with spatial resolution at the asset, municipality and province levels, on a study region comprising ten provinces in southern Italy. Compared to the proposed model, the exposure model where assets are relocated and aggregated at the geometric centroid of the municipality underestimates AAL by 8 % , while a higher difference (up to 20 % ) is observed for the exposure model where assets are relocated and aggregated at the geometric centroid of the province. We also consider an exposure model whose asset locations are extracted from publicly available building footprints. Yet, this latter model was incomplete for some provinces resulting in underestimation of AAL up to 90 % . Differences in catastrophe bond prices obtained from the four exposure models are less evident, with the exposure model built based on the building footprints showing a difference up to 9.5 % . [ABSTRACT FROM AUTHOR]

Copyright of Engineering Mechanics / Gongcheng Lixue is the property of Engineering Mechanics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A methodology is proposed to enable state‐of‐the‐art record selection using ground motion components in all three principal loading directions. Relying on the well‐established Conditional Spectrum approach, its fundamental concepts are extended to ensure hazard consistency when the vertical ground motion component is considered along with the horizontal ones. To this end, different record selection techniques are employed, spanning sets of ground motion records with and without vertical motions, as well as with and without vertical ground motion hazard consistency. To demonstrate the effect that each record set can potentially have on a structure, an unanchored liquid storage tank is adopted as a case study, because of the vertical uplift motion it can exhibit, even under the application of horizontal loading only. A reduced‐order structural model is employed to generate the numerical output via multi‐stripe analysis, thus enabling the evaluation of the pertinent record selection approaches. Focusing on uplift and compressive meridional stress, response ratios and response hazard curves are extracted. It is shown that although the vertical ground motion component only mildly affects uplift, its effect on compressive meridional stress, on average, amplifies the response by a factor of 1.8 for moderate intensities and 2.8 for higher ones. Accounting for hazard consistency in the vertical component appears to be important for the case at hand, as it reveals notable discrepancies in the mean annual frequency of exceedance for the response parameters examined. [ABSTRACT FROM AUTHOR]

An investigation has been done to update key input parameters in the recent seismic-risk-screening tools developed by the National Research Council Canada for the six seismic categories. In this study, the seismic categorization system in the recent seismic-risk-screening tools of the National Research Council Canada is extended to include Canadian buildings abroad by including threshold peak ground acceleration values, a more global set of modified Mercalli intensity, peak ground acceleration, and spectral response acceleration and peak ground acceleration relationships. The relationships among spectral response acceleration, peak ground acceleration, and peak ground velocity values have been derived using least-squares regression analyses to obtain the threshold values of both peak values associated with various modified Mercalli intensity values for each seismic category. Based on the updated relationships, the seismic categorization system is applied to 679 locations in Canada and 226 locations outside Canada. [ABSTRACT FROM AUTHOR]

A prominent challenge in performance-based earthquake engineering is to select a suitable set of ground motions records with which to perform probabilistic seismic assessment of structures. The most common approach for engineering purposes is to employ actual recordings of worldwide events, given that large earthquakes do not occur frequently hence regional recordings of such events are usually not widely available. To address this not that uncommon issue, regionally simulated ground motions using a stochastic finite-fault method have been proposed as an alternative to real records. This study aims to explore the use of simulated records through a stochastic finite-fault method in probabilistic seismic assessment frameworks for reinforced concrete bridges, when compared to using real records. Direct seismic losses for a case-study existing bridge and a bridge portfolio are estimated and compared, as the reference risk metric. Finally, the similarities between seismic demands, obtained using both real and simulated record sets, are quantified and discussed via statistical hypothesis testing, resulting fragility curves and expected annual losses. The results show how simulated records can be a promising alternative to real records, becoming particularly useful in the absence of available recorded ground motions with specific seismogenic features. [ABSTRACT FROM AUTHOR]

A probabilistic seismic risk assessment is conducted in this study to quantify Annualized Earthquake Loss (AEL) of Tehran, the capital of Iran. To do so, a comprehensive review of three main components of risk assessment including the seismic hazard analysis, exposure model and vulnerability functions is performed. The classical seismic hazard analysis is carried out based on the most recent earthquake catalog by considering the available uncertainties. A high-quality building exposure model based on recent census data with geographic resolution of census blocks is also compiled. According to available information, buildings are classified into 19 groups by considering their construction material, quality and height. The results show that sum of AEL in Tehran is about 10,488 million USD, which is equivalent to 0.16% of exposed economic value. The spatial distribution of AEL indicated that value of AEL in the eastern districts is higher; however, the relative seismic risk in term of AELR in the southern districts of the city is much higher. In addition, a disaggregation analysis per building typology is performed to identify the contribution of different building taxonomies in AEL. The results show that the masonry and low-quality steel and concrete structures with poor designing specifications have the highest contribution in AEL. The finding from this study can be used by local authorities, government and insurance sector in order to develop effective risk mitigation plans and a robust insurance scheme for Tehran, Iran. [ABSTRACT FROM AUTHOR]

In the last years, many research efforts have been focusing on the development of fragility and risk models of different building classes and structural typologies for large-scale seismic risk applications. Although the role of masonry infills is well recognised, less attention has been paid to the quantification of the variability surrounding their mechanical properties and how this might affect the collapse fragility curves and loss estimates. This study investigates and quantifies, in a thorough manner, the impact of the variability in the characteristics of masonry infill on the expected annual losses (EALs) of existing infilled reinforced concrete frames of different configurations. To do so, a fully integrated portfolio, representative of buildings designed according to the Italian codes in force between 1970 and 1980, is used as case-study. Infill-related variability is accounted for by means of a macro-level distinction of five common infill types, defined in terms of stiffness and shear strength. Moreover, building-to-building variability is also included through different geometrical configurations. Multiple-stripe analyses are carried out and fragility curves are developed for buildings with different heights, in-plan layouts and structural typologies. Finally, EALs are computed and analysed in a statistical fashion in order to quantify, in a simplified manner, the uncertainty induced by the variability of the masonry infill properties, as a function of the number of storeys and masonry infill typology. [ABSTRACT FROM AUTHOR]

A seismic fragility curve is a visual representation that illustrates the likelihood of a structure surpassing a particular damage or performance limit state caused by an earthquake with a specific intensity or ground motion level. This curve is typically generated using probabilistic seismic hazard analysis and structural reliability analysis methods. It is based on statistical models that rely on past earthquake data and simulations of future earthquake scenarios to predict the structure or system’s behavior under seismic forces. In this study, the seismic performance of 30 stories of 95 m height dual system reinforced concrete buildings located in Erbil is evaluated by analyzing three distinct ground motions. A non-linear platform is used to simulate and analyze data, followed by the generation of seismic inter-story drift fragility curves using Incremental Dynamic Analysis. The buildings’ seismic structural performance is assessed based on five different performance levels, including operational phase, immediate occupancy, damage control, life safety, and collapse prevention (CP). Each level is associated with different levels of damage and corresponding degrees of functionality and safety. The fragility curves show that the building has a 50% chance of achieving or exceeding the (CP) level with highly intense ground vibrations with peak ground acceleration = 1.6 g. In addition, these curves can be beneficial in creating future local design codes and provide significant support in evaluating the seismic performance of existing buildings.

Robust performance‐based earthquake assessment should consider the effects of both aleatory and epistemic uncertainty on seismic response parameters. While the effects of modelling uncertainty on specific engineering demand parameters and collapse fragility curves have been widely investigated to date on bare frame structural typologies, little attention has been paid to the impact of masonry infill properties variability on the uncertainty estimation in existing infilled RC frames. Previous studies available in the literature are mainly related to seismically designed RC buildings and the suggestions provided in international guidelines cannot be reasonably adopted for poorly detailed RC existing frames. As regards the uncertainty in existing RC frames, the role of masonry infills was often neglected or their interaction with the surrounding frames was not rigorously accounted for in the uncertainty estimation. With such limitations in mind, the aim of this study is to provide more realistic modelling uncertainty quantities to be adopted in seismic assessment of existing infilled RC frames, including, in a thorough manner, the impact of the variability of the masonry infill typologies and the occurrence of RC frame shear failure. Both the aleatory and epistemic uncertainties are estimated, in terms of the overall dispersion on specific engineering demand parameters and collapse fragility curves. Finally, the impact of such uncertainties on seismic risk estimates, quantified through expected annual losses, is also thoroughly investigated. The inclusion of additional random variables, not considered so far, in the uncertainty estimation framework, led to importantly higher modelling uncertainty quantities than those currently available from previous studies. [ABSTRACT FROM AUTHOR]

The estimation of building seismic risk and loss utilising response history analysis is challenging, especially because the final objective is the seismic loss estimation for building stock. In this paper, this challenge is addressed by developing a simplified nonlinear structural model, which is capable of simulating the seismic response of predominantly plan‐symmetrical reinforced concrete frame buildings subjected to ground motions in both horizontal directions. The simplified structural model is plugged into the direct seismic risk and loss estimation methodology. Its capabilities are then demonstrated by estimating the seismic risk and losses for a four‐storey office building and a five‐storey school building. For the analysed buildings, it is shown that the frequency of collapse, the expected annual loss and the frequency of exceedance of a given loss can be simulated with the same level of accuracy as in the case of the conventional structural model, but with greater numerical robustness and computational efficiency. Research is needed to better define the limitations of the introduced simplified model and extend the capabilities of simplified nonlinear models to more complex structural systems of plan‐asymmetrical buildings. [ABSTRACT FROM AUTHOR]

Past earthquake evidence has shown the high vulnerability of Italian school buildings, given by the extensive damage observed to structural and non-structural elements. Such vulnerability demonstrates the need to undertake a seismic risk assessment and reduction strategies for critical facilities and allocation of national funds for retrofit interventions to those regions where seismic risk is higher. To do so, Expected Annual Losses (EAL) are evermore considered one of the main seismic risk metrics, which can, however, be largely affected by the epistemic uncertainty that typically characterizes the material and geometrical properties of existing buildings, particularly masonry-infilled reinforced concrete (RC) ones. This paper investigates the implications of accounting for a thorough identification of sources and characterization of uncertainty in seismic loss estimates on the risk assessment of a typical Italian masonry-infilled RC school building. The variability in masonry infill properties and modeling assumptions, as well as the subsequent epistemic uncertainty, are explicitly considered in the loss estimation of the RC school building. Specifically, the impact on the expected annual loss ratio is quantified in terms of both structural and non-structural components, depending on the engineering demand parameter to which they are sensitive. The results show that, when considering the uncertainty related to the variability in masonry infills, higher loss ratios of up to 30% are obtained with respect to the available literature estimates. [ABSTRACT FROM AUTHOR]

Our modern society is becoming increasingly reliant on transportation networks, as well as the interdependent infrastructures and technologies that interact with them. The increasing complexity and interconnectedness of infrastructure networks make them susceptible to impact not only directly from external shocks but also indirectly from the failure of dependent infrastructures. This research study was conducted in Padang city, one of the most disaster-prone areas in Indonesia. Based on the literature review, it is no doubt that research study on seismic risk assessment is insufficient and outdated. In fact, a study about the interdependency between Critical Infrastructures (CIs) is yet to be done in this region. In this study, there are two approaches used for data gathering which is by surveying existing CIs using Google Earth and by an online questionnaire survey via Google Form. Based on the qualitative survey, a functionality rating method is done to obtain the level of outage/loss functionality which is an indicator for the damage occurred to the structure and infrastructure. Following that, a seismic risk analysis was conducted to assess the interdependency between investigated CIs and facilities. Respondents' judgement from the questionnaire were used to identify the base criticality of each critical infrastructure. Based on the qualitative survey, the level of loss in functionality for the substation and the telecommunication tower is rated as "High", but the loss in functionality for the water supply system is rated as "Moderate". Moreover, the findings used from the respondents' judgements were used to establish the initial level of criticality for each vital infrastructure. According to the findings, hospitals, power substations, and communication towers all have a criticality level of "5-Vital", while police stations and fire stations both have a "3-medium" criticality rating. Eventually, the results of this assessment of interdependence are displayed in a criticality map, which shows how the interdependency relationship affects the initial criticality of a certain upstream infrastructure. Understanding the potential consequences of infrastructure failure, especially in regard to dependent infrastructures, can help emergency response teams formulate more targeted strategies for managing risks. As a consequence of this, the resilience of the wider community is improved, which contributes toward the implementation of Sustainable Development Goal (SDG) 11: Sustainable cities and communities particularly in reducing disasters and people in vulnerable situation. [ABSTRACT FROM AUTHOR]

Bridge infrastructures are critical nodes in a transportation network. In earthquake-prone areas, seismic performance assessment of infrastructure is essential to identify, retrofit, reconstruct, or, if necessary, demolish the infrastructure systems based on optimal decision-making processes. As one of the crucial components of the transportation network, any bridge failure would impede the post-earthquake rescue operation. Not only the failure of such high-risk critical components during an extreme event can lead to significant direct damages, but it also affects the transportation road network. The consequences of these secondary effects can easily lead to congestion and long queues if the performance of the transportation system before or after an event was not analyzed. These indirect losses can be more prominent compared to the actual damage to bridges. This paper brings about seismic performance assessment for the Cyprus transportation network from which the decision-making platform can be modeled and implemented. This study employs a seismic hazard analysis based on generated USGS ShakeMap scenarios for the risk assessment of the transportation network. Furthermore, identification of the resiliency and vulnerability of the transportation road network is carried out by utilizing the graph theory concept at the network level. Moreover, link performance measures, i.e., traffic modeling of the study region is simulated in a dynamic traffic assignment (DTA) simulation environment. Finally, for earthquake loss analysis of the bridges, the HAZUS loss estimation tool is used. The results of our investigations for three different earthquake scenarios have shown that seismic retrofitting of bridges is a cost-effective measure to reduce the structural and operational losses in the region. [ABSTRACT FROM AUTHOR]

While in poorly-detailed masonry-infilled reinforced concrete (RC) buildings the significance of masonry infills is acknowledged, less attention has been paid to the variability surrounding their mechanical properties and its potential impact on fragility and, consequently, vulnerability models to be used in seismic risk estimation. This study addresses this gap by proposing updated fragility and vulnerability models of existing poorly-detailed masonry infilled and pilotis RC frames that consider the variability in building layout and infill properties. A large building portfolio, representative of those designed according to Italian codes between 1970 and 1980, is selected as case study, incorporating building-to-building variability through various geometrical configurations. Updated modelling uncertainty parameters, specifically derived for existing infilled RC frames, are used, including the variability surrounding the properties of different infill typologies and the occurrence of RC frame shear failure. The portfolio was analysed through multiple-stripe analyses, followed by the development of upgraded fragility models for buildings with different heights and geometrical configurations. Finally, the corresponding vulnerability models were derived using damage-to-loss models calibrated with post-earthquake observation damage data from the 2009 L'Aquila earthquake. The updated fragility and vulnerability curves can be used for more refined seismic risk estimates of large building portfolios, that account for building-to-building and infill-to-infill variability, revised modelling uncertainty estimates and a more robust intensity measure (AvgSa). [ABSTRACT FROM AUTHOR]

The nation’s transportation systems are complex and are some of the highest valued and largest public assets in the United States. As a result of repeated natural hazards and their significant impact on transportation functionality and the socioeconomic health of communities, transportation resilience has gained increasing attention in recent years. Previous studies on transportation resilience have heavily emphasized network functionality during and/or following a scenario hazard event by implicitly assuming that sufficient knowledge of structural capacity and environmental/service conditions is available at the time of an extreme event. However, such assumptions often fail to consider uncertainties that arise when an extreme hazard event occurs in the future. Thus, it is essential to quantify and reduce uncertainties to better prepare for extreme events and accurately assess transportation resilience. To this end, this paper proposes a dynamic Bayesian network-based resilience assessment model for a large-scale roadway network that can explicitly quantify uncertainties in all phases of the assessment and investigate the role of inspection and monitoring programs in uncertainty reduction. Specifically, the significance of data reliability is investigated through a sensitivity analysis, where various sets of data having different reliabilities are used in updating system resilience. To evaluate the effectiveness of the model, a benchmark problem involving a highway network in South Carolina, USA is utilized, showcasing the systematic quantification and reduction of uncertainties in the proposed model. The benchmark problem result shows that incorporating monitoring and inspection data on important variables could improve the accuracy of predicting the seismic resilience of the network. It also suggests the need to consider equipment reliability when designing monitoring and inspection programs. With the recent development of a wide range of monitoring and inspection techniques, including nondestructive testing, health monitoring equipment, satellite imagery, LiDAR, etc., these findings can be useful in assisting transportation managers in identifying necessary equipment reliability levels and prioritizing inspection and monitoring efforts.

Catastrophe models are important tools to provide proper assessment and financial management of earthquake-related emergencies, which still create the largest protection gap across all perils. Earthquake catastrophe models include three main components, namely: (1) the earthquake hazard model, (2) the exposure model and, (3) the vulnerability model. Simulating spatially distributed ground-motion fields within either deterministic or probabilistic seismic hazard assessments poses a major challenge when site-related financial protection products are required. In this framework, we develop ad hoc correlation models for different Italian regions (specifically northern, central and southern Italy) and thereafter we perform both deterministic scenario-based and probabilistic event-based hazard and risk assessments in order to advance the understanding of spatial correlations within the catastrophe modelling process. We employ the OpenQuake engine for our calculations. This is an open-source tool suitable for accounting for the spatial correlation of earthquake ground-motion residuals. Our outcomes, albeit preliminary, demonstrate the importance of considering not only the spatial correlation of ground motions, but also its associated uncertainty in risk analyses. Although loss exceedance probability curves for the return periods of interest for the (re)insurance industry show similar trends, both hazard and risk footprints in terms of average annual losses feature less noisy and more realistic patterns if spatial correlation is taken into account. Such results will have implications for (re)insurance companies evaluating the risk to high-value civil engineering infrastructures. [ABSTRACT FROM AUTHOR]