Framework For Seismic Risk Assessment Research Articles

Rapid assessment of substation earthquake risk based on minimal cut sets

Electrical substation systems have been severely damaged in previous earthquakes. It is important to realize the rapid seismic risk assessment of substation systems before an earthquake occurs. This paper proposes a rapid seismic risk assessment framework based on seismic hazards and a functional network model. According to the structural connectivity of the substation, the series and parallel connections of equipment were clarified. Considering the power load capacity of equipment and the power transmission requirements of systems, a dual-functional network model combining structure and electricity was built. On the premise of ensuring earthquake risk probability information, the hierarchical simulation of the fault tree model was carried out. Also, the minimum cut set algorithm was used to rapidly evaluate the seismic risk of the substation system. Aiming at reducing the risk of substation function failure, two risk reduction strategies of seismic retrofitting and additional redundant equipment were put forward. After the seismic analysis of a typical 220 kV substation, key equipment of the substation and the optimal risk reduction strategies were obtained.

Implications of 5G rollout on post-earthquake functionality of regional telecommunication infrastructure

Telecommunication infrastructure (TI) is becoming increasingly vital in modern society, where information exchange is needed in almost all aspects of the built environment, business operations, and people's daily lives. The ongoing 5G rollout will lead to a paradigm shift in regional TI deployment landscape, with increased seismic hazard exposure particularly due to the densely deployed small cells. As TI is known to be vulnerable to seismic hazard impacts yet necessary for post-earthquake emergency response, this study carries out a pioneering effort in quantifying the post-earthquake TI failures and functionality to better support risk mitigation decision-making. We propose a novel seismic risk assessment framework for regional 5G TI, by holistically integrating regional seismic hazard analysis, infrastructure seismic exposure data, electric power infrastructure seismic fragility modeling and network connectivity analysis, as well as wireless TI functionality modeling. The proposed framework is evaluated based on a hypothetical regional infrastructure testbed located in Memphis, Tennessee, subjected to several earthquake scenarios. From a reference heterogeneous 5G TI deployment scenario, the results indicate that significant performance degradation of 5G TI is expected especially after major earthquake events. Enabled by the proposed framework, we further compared the efficacy of several risk mitigation strategies and pertinent implications are provided.

Probabilistic seismic risk assessment framework: case study Adapazari, Turkey

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.

An Ontology-Based Holistic and Probabilistic Framework for Seismic Risk Assessment of Buildings

To avoid over-reliance on the identification of building damage states post-earthquake in the seismic risk assessment process, an ontology-based holistic and probabilistic framework is proposed here for seismic risk prediction of buildings with various purposes and different damage states. Based on vulnerability analysis, the seismic risk probabilities of buildings are first obtained by considering the on-site seismic hazard. Taking economic losses and casualties as assessment indicators, a system for seismic risk assessment of buildings, OntoBSRA (Ontology for Building Seismic Risk Assessment), is then developed by combining ontology and semantic web rule language. A case study is carried out to demonstrate the application of the proposed framework and further validate the semantic web rules. The results show that the proposed framework can provide a holistic knowledge base that allows risk assessors or asset managers to predict the consequences of earthquakes effectively, thereby improving efficiency in decision-making.

A novel framework for seismic risk assessment of structures

AbstractSeismic risk assessment of new and existing structures has a long history, which is based on the development of specific methods for seismic hazard and vulnerability analyses. Performance‐based earthquake engineering is the natural evolution and integration of all these aspects that is nowadays implemented in several precodes. However, some critical aspects are not yet completely clarified. As a matter of fact, the vulnerability analysis suffers the so‐called record‐to‐record variability, which is usually controlled through different parameters used as seismic intensity measures (IMs), whose significance is still under discussion. Moreover, this variability represents an additional source of uncertainty, which is added to the dispersion derived from the ground motion prediction equation (GMPE), leading to an overconservatism. For these reasons, the present paper aims to propose a novel framework for the seismic risk assessment of structures, which is found on the idea to control the response variability in evaluating seismic hazard curves without taking into account the randomness (ε) of the GMPE, which instead is transferred to fragility curves. These latter are built by using groups of accelerograms, whose median and 84% fractile spectra fit well, for different return periods, the uniform hazard spectra for ε= 0 and 1, respectively. For this purpose, a new search algorithm for selecting natural records is formulated. The proposed method offers considerable advantages as it is no longer necessary to refer to a specific IM, and allows to select pairs of spectrum‐compatible natural records, which is enable to solve the problem of the seismic assessment of three‐dimensional structures. The procedure is then applied to assess seismic risk of a typical reinforced concrete frame, whose results demonstrate the robustness of the method and the practical independence from the record set used.

Commuter welfare-based probabilistic seismic risk assessment of regional road networks

This study integrates welfare, a measure of the impact of road network disruption on individual commuters’ well-being, with a probabilistic seismic risk assessment framework in a computationally tractable way. Welfare is a network performance measure that reflects the differential impacts of changes in commute time on various groups. For a case study of the San Francisco Bay Area, welfare loss is computed by augmenting an origin–destination matrix with publicly available information about commuters’ income levels, residences, and workplaces. While commuters from all income groups have similar risk of drivers’ delay due to road network disruption, commuters with low incomes have a substantially higher risk of welfare loss than those with high incomes. A comparison of bridge retrofit policies shows that disaggregation of welfare loss by income group is necessary to examine whether such policies reduce risk equitably. While a retrofit policy determined using drivers’ delay reduces the expected drivers’ delay, it increases the disparity in the per-capita welfare loss of commuters with low and high incomes relative to the network’s baseline state. In contrast, a retrofit policy that prioritizes low-income commuters reduces the difference in welfare loss of commuters with low and high incomes compared to the baseline network state.

Machine Learning-Based Fast Seismic Risk Assessment of Building Structures

ABSTRACT A machine learning-based fast seismic risk assessment framework is proposed to ease the computational burden in estimating the potential earthquake-induced loss of a building during its intended life. Both the hazard parameters of sites and structural parameters of buildings were incorporated as inputs. The continuous risk values and discrete risk levels were used as outputs for the regression and classification tasks of supervised learning, respectively. A proof-of-concept study of steel frames proved the feasibility of the proposed approach. Artificial neural networks achieved the lowest root mean square error of 0.0051 for regression and the highest accuracy of 96.8% for classification.

Earthquake risk and damage assessment for airport transportation system

Taking airport transportation system as the main research object, this paper studies the potential danger and direct economic loss of earthquake. Based on the structural response and damage characteristics of airport transportation system under earthquake action, the framework and theoretical model of HAZUS disaster assessment and direct economic loss developed by FMEA are introduced. This paper focuses on the application of vulnerability curve and capacity curve in airport transportation system risk assessment and economic loss assessment. Taking an airport terminal suffering from a magnitude 8 earthquake as an example, the potential damage degree, probability and direct economic loss of the earthquake are quantitatively calculated, and the property loss is given, thus explaining the importance of the seismic risk assessment framework and method to the safety assessment of China.

Life-cycle cost-based risk assessment of aging bridge networks

Road infrastructures and bridge networks are becoming increasingly complex systems due to the development of technology in transportation engineering and the continual growth of urban communities. Infrastructure disservice due to seismic events may lead to unacceptable discomfort for commuters. Moreover, network downtime results into economic losses for the affected community, to be quantified in monetary terms by user costs. Seismically vulnerable bridges are also affected by aging and deterioration processes that can reduce the bridge structural performance over time. This paper presents a comprehensive life-cycle cost-based probabilistic framework for seismic risk assessment of spatially distributed aging bridge networks. The seismic risk measure is formulated in terms of annual exceedance rate of a target threshold of user costs. The methodology is applied to a road system in Lombardy region, Italy, reproducing network connectivity and daily travel demands among four major cities and smaller neighbouring municipalities. Despite the area of interest is characterized by low seismicity, the results allow to quantify the impact of aging and deterioration in exacerbating the network seismic risk, highlighting the need for a life-cycle-informed approach to optimal management of infrastructure systems.

A Bayesian Inference driven computational framework for seismic risk assessment using large-scale nonlinear finite element analyses

Nuclear engineers are increasingly relying on large-scale simulations particularly for seismic risk assessment. Experimentally validated simulation models are used to consider the effects of uncertainties and evaluate fragilities by conducting multiple nonlinear analyses. However, such an approach becomes computationally prohibitive and care is needed to achieve desired degree of accuracy with a reasonable amount of computational effort. In this paper, a statistical framework is presented to minimize the total computational effort needed in conducting large-scale simulations for seismic risk assessment. The salient features of the framework are: (i) use of Bayesian inference to allow consideration of data from diverse sources like experiments, field data, existing or simplified approaches, and data from large-scale simulations, and (ii) embedment of Bayesian methods within an iterative process to plan and allocate adequate computing resources such that the desired accuracy is achieved using minimum possible simulations. The applicability and efficiency of the proposed framework is illustrated using the example of a box-shaped reinforced concrete shear wall.

Seismic Risk of Infrastructure Systems with Treatment of and Sensitivity to Epistemic Uncertainty

Modern society’s very existence is tied to the proper and reliable functioning of its Critical Infrastructure (CI) systems. In the seismic risk assessment of an infrastructure, taking into account all the relevant uncertainties affecting the problem is crucial. While both aleatory and epistemic uncertainties affect the estimate of seismic risk to an infrastructure and should be considered, the focus herein is on the latter. After providing an up-to-date literature review about the treatment of and sensitivity to epistemic uncertainty, this paper presents a comprehensive framework for seismic risk assessment of interdependent spatially distributed infrastructure systems that accounts for both aleatory and epistemic uncertainties and provides confidence in the estimate, as well as sensitivity of uncertainty in the output to the components of epistemic uncertainty in the input. The logic tree approach is used for the treatment of epistemic uncertainty and for the sensitivity analysis, whose results are presented through tornado diagrams. Sensitivity is also evaluated by elaborating the logic tree results through weighted ANOVA. The formulation is general and can be applied to risk assessment problems involving not only infrastructural but also structural systems. The presented methodology was implemented into an open-source software, OOFIMS, and applied to a synthetic city composed of buildings and a gas network and subjected to seismic hazard. The gas system’s performance is assessed through a flow-based analysis. The seismic hazard, the vulnerability assessment and the evaluation of the gas system’s operational state are addressed with a simulation-based approach. The presence of two systems (buildings and gas network) proves the capability to handle system interdependencies and highlights that uncertainty in models/parameters related to one system can affect uncertainty in the output related to dependent systems.

Quantifying the seismic risk for electric power distribution systems

Electric power distribution systems are generally more prone to disruption from natural hazards than transmission systems due to their often less redundant circuit structures. However, seismic risk analysis for distribution systems is rare compared to the rich body of literature focussing on transmission systems. This paper proposes a seismic risk assessment framework for electric power distribution systems considering both the network topology and the functional vulnerability of distribution substations. Implicit Z-bus method is applied to solve distribution system power flow and evaluate system serviceability. Monte Carlo simulation is applied to obtain probabilities of the scale of unserved loads resulting from disconnection and abnormal voltage condition. The seismic risk is jointly quantified using multiple risk metrics, and importance measures are used to determine criticality of substation components for prioritisation of seismic retrofit. The seismic risk assessment framework is applied to the CIGRE medium voltage distribution test network and two ground motion intensity scenarios – one for peak ground acceleration values based on a scenario earthquake and the other for uniformly distributed peak ground acceleration across the network. The framework allows the quantification of different network topologies and substation configurations. This enables network owners and operators to evaluate the seismic vulnerability of their substation configuration and network topology, identify potential bottlenecks of the systems and thus inform effective planning and risk-reduction investments.

Risk assessment for a long-span cable-stayed bridge subjected to multiple support excitations

Current probabilistic seismic risk assessment framework does not fully address the impact of the spatial variability of ground motions on long bridges. However, recent studies have highlighted that long-span bridges are more vulnerable to damage due to spatial varying ground motions. To achieve this increased vulnerability, this research presents a reliable risk assessment tool for long-span bridges subjected to spatial varying ground motions. The proposed method includes the following tasks: (i) the simulation of spatially variable ground motions, (ii) creation of numerical bridge model, (iii) generation of probabilistic seismic demand models, (iv) development of component and system fragility curves, (v) estimation of annual exceedance of damage through site-compatible hazard curves, and (vi) computation of repair time. As an illustration, a cable-stayed bridge is selected to highlight the effect of spatial variability of ground motions on the seismic risk and repair time of individual bridge components and bridge system in comparison to uniform excitations. Additionally, a sensitivity analysis is performed to examine the effect of spatial variability parameters and hazard curve-related parameters on the seismic risk of the bridge.

A comprehensive framework for seismic risk assessment of urban water transmission networks

Earthquakes are natural disasters which human beings cannot control, causing significant damage to the economy and society as a whole. In particular, earthquakes affect not only buildings but also lifeline structures such as water distribution, electric power, transportation, and telecommunication networks. The interruption of these networks is critical because it can directly damage the facilities and, at the same time, cause long-term loss of the overall system for society. In recent years, there has been increasing interest in the uncertainties of ground motion, deterioration of pipelines, and interdependency of lifelines. Therefore, it is essential to predict the damage through possible earthquake scenarios and accounting for factors affecting lifeline structures. This study proposes a comprehensive framework to quantify the impact of earthquakes on the connectivity of urban water transmissions. The framework proposes the following steps to predict damage from earthquakes: (1) estimate the ground motion considering the spatial correlation, (2) propose a modified failure probability of buried pipelines considering deterioration, and (3) evaluate the seismic fragility curves of network components and the interdependency among water treatment plants, pumping plants, and substations. For numerical simulations, an actual water network system in South Korea was constructed using graph theory, and the magnitudes and locations of the epicenters were determined based on historical earthquake data. Finally, the reliability performance indicators (e.g., connectivity loss and serviceability ratio) were measured when earthquakes of various magnitudes occurred in the urban area. This framework will enable the prediction of damage from earthquakes and enhance decision making to minimize the extent of damage.

Effects of various uncertainties on seismic risk of steel frame equipped with steel panel wall

Probabilistic risk analysis is an effective tool for risk-informed decision-making related to the building facilities. All sources of the uncertainties should be considered in seismic risk assessment framework. Not only the levels of these uncertainties but also the effects on the performance of the buildings should be clearly identified. This paper aims to assess the impacts of the potential uncertainties on the seismic risk of steel frame equipped with steel panel wall (SPWF). Firstly, the performance limits of the SPWF structures are determined according to cyclic test results of two SPWF specimens. Then a validated numerical model of a 12-story SPWF building is modeled and used to perform the nonlinear time-history analysis, and the record-to-record uncertainty is identified by a set of ground motions derived from SAC project. Furthermore, comparisons are made on fragility curves for the building with or without considering the combining uncertainties in structural system, in defining performance limits and modeling technology. Finally, the annual probability and probability in 50 years for each performance limit is calculated and compared. The impacts of such uncertainties on seismic risk of SPWF building are quantified for risk-informed evaluation of the SPWF buildings.

A Probabilistic Framework for Seismic Risk Assessment of Electric Power Systems

Uncertainty quantification in seismic risk assessment of spatially distributed infrastructure systems such as electric power systems poses two main challenges: (i) seismic hazard modeling that considers both the spatial variation in intensity for each hazard event as well as the probability of occurrence of the event, and (ii) system performance formulation that captures the probabilistic nature of component vulnerability and accessibility. This paper introduces a framework for seismic risk assessment of electric power systems that takes into account these challenges. Seismic hazard is modeled using a probabilistically weighted deterministic hazard scenarios approach in which a suite of earthquake scenarios with their corresponding annual probabilities of occurrence is considered. System performance is modeled using a probabilistic topological-based approach that considers component accessibility and vulnerability. The framework is demonstrated using a notional electric power system assumed to be located in Charleston, South Carolina, and New York City, New York. The framework can be used for pre-disaster preparation, mitigation, and post-disaster response planning.

NEES integrated seismic risk assessment framework (NISRAF)

The paper presents an integrated and extensible framework for assessment of the impact of earthquakes on civil infrastructure systems, particularly buildings and bridges. The framework, referred to as NEES Integrated Seismic Risk Assessment Framework (NISRAF), is developed with a focus on improving the reliability of earthquake assessment results. The components are structural fragility assessment using measured data and hybrid simulation, hazard characterization by free-field site response analysis, and integrated impact assessment. The hazard and fragility components are refined by employing nonlinear site response tools and model updating techniques, respectively. Several of these NISRAF components are tailored to achieve seamless integration and to arrive at an operational system. The novelty of the developed framework is primarily the integration of the various components of earthquake impact assessment, which have not been deployed in such an application before. The framework has been built and demonstrated via applications to a test bed in California. Earthquake impact assessment results using the generated hazard map and fragility curves correlate well with field reports, indicating the efficacy of the approach.

Bridge Functionality Relationships for Improved Seismic Risk Assessment of Transportation Networks

Relationships between bridge damage and the resulting loss of functionality of the bridge are critical to assessing the impact of an earthquake event on the performance of the transportation network. This study addresses this data need by use of a Web-based survey of central and southeastern U.S. Department of Transportation bridge inspectors and officials. Results of the 28 responses are analyzed and offer a link between various types of bridge component damage and the expected level of allowable traffic carrying capacity due to closure decisions and repair procedures. This data is utilized to assess the probability of meeting various damage states, expressed in terms of restoration of functionality, and subsequently facilitate the refinement of component limit-state capacities for analytical fragility curve development. The bridge functionality relationships and methodology outlined serve as the basis for refinement of critical tools in the seismic risk assessment framework and improved assessment of transportation network performance.