Quantifying uncertainties and correlations of engineering demand parameters of building structures for regional seismic loss assessment

Electrical substations are critical elements of a power grid, enabling the transmission and distribution of electric power from power generators to the end‐users. Experiences from previous earthquakes have shown that electrical substations can be damaged due to ground shaking, reducing their functionality and potentially preventing the generated electric power from reaching end‐users. To assess the seismic vulnerability of a substation, a modular quantitative assessment method is proposed. In this method, the relation between the functionality state of a substation and the damage state of its components was established through the connection matrix technique. A substation is viewed as a network system, whose topology is defined by the connections among various pieces of electrical equipment (i.e., the components), represented in the connection matrix. The maximum allowable power transmission capacity of the substation after an earthquake is adopted as the system functionality metric, which is jointly determined by the power input, transform, and output capacity of the substation. The seismic vulnerability of an electrical substation is quantified by probabilistically calculating its postearthquake functionality when exposed to various earthquake intensities using Monte Carlo sampling. Finally, the risk of substation functionality loss is quantified by integrating the seismic hazard curve with the seismic vulnerability model of the substation. Two realistic case studies on a distribution substation and a transmission substation, with the same equipment configuration but different power delivery paths, were performed using the proposed method. Furthermore, a sensitivity analysis regarding the equipment fragility parameters is conducted, providing a risk‐informed basis for improving the seismic performance of the substation system.

Section: Probabilistic Seismic Assessment Of Substation Vulnerabilitymentioning

confidence: 99%

Seismic risk analysis of electrical substations based on the network analysis method

Liang

Blagojević

Xie

et al. 2022

“…Therefore, the variance 𝜎 2 𝜓 and correlation coefficient 𝜌 𝜓 𝑖 𝜓 𝑗 of EDP residuals estimated using the elastic IDA curves are also valid for the structures that show nonlinear behaviors for evaluation purposes. More details of justification on the linear assumption are discussed in Kang et al 26 . It is noted that the linear assumption makes it possible to predict the generalized EDP residuals regardless of ground motion sets.…”

Section: Marginal and Joint Failure Probabilities Considering The Unc...mentioning

confidence: 99%

“…In addition, repeated nonlinear time history analyses inevitably require high computational costs and structural modeling efforts. To overcome this issue, Kang et al 26 proposed an "IM-invariant" method for estimating the EDP residuals of building structures based on the behavior in the elastic range. The effects of the EDP residual correlation on the regional seismic loss assessment were also demonstrated for various building types.…”

Section: Introductionmentioning

confidence: 99%

“…Although the regression models developed by Kang et al 24,26 facilitate the efficient evaluation of the EDP residuals, the accuracy and applicability remain challenges. The regression models can describe the overall trend of EDP residuals of buildings but show a limited level of accuracy for specific structures.…”

Section: Introductionmentioning

confidence: 99%

“…To train the DNN models, a new database is developed by performing time history analyses with many SDOF systems and MDOF models of building structures. The proposed frameworks are tested by comparing the prediction accuracy with the existing regression models in Kang et al 26 . Section 5 demonstrates the applicability and effectiveness of the frameworks in the community-level seismic assessment using a virtual city example.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Deep neural network‐based regional seismic loss assessment considering correlation between EDP residuals of building structures

Kang

Kim

Kwon

et al. 2022

Self Cite

Regional seismic loss assessment is essential for developing an emergency response plan in the event of an earthquake, which can reduce casualties and socioeconomic losses in an urban community. The uncertainties and correlations of structures’ engineering demand parameters (EDP) should be adequately considered to evaluate the community‐level seismic risk. Recently, the authors proposed an incremental dynamic analysis‐based method and regression‐based models to estimate the variances and correlations of residuals in EDP termed “EDP residuals.” The quantified uncertainties of the EDP residuals facilitate the accurate evaluation of the regional seismic performance. Still, the computational cost required in the estimation process makes its application a challenge. This study proposes two frameworks for regional seismic loss assessment based on deep neural networks (DNNs) to extend the applicability of EDP residual estimation and improve its accuracy. The first framework estimates the EDP residuals of buildings by combining the EDP residuals of various single‐degree‐of‐freedom (SDOF) systems through the modal combination rules. Three DNN models are constructed to predict the EDP residuals of SDOF systems. The second framework predicts the EDP residuals of buildings directly using two DNN models. The proposed frameworks are verified by numerical examples of regional seismic loss assessment, for which time history‐based “exact” solutions exist. The supporting source code, data, and trained models are available for download at https://github.com/TyongKim/EDP_residual.Highlights The importance of considering EDP residual correlation in seismic system reliability analysis is demonstrated. Two DNN‐based frameworks are developed to estimate EDP residuals of building structures. Modal combination rule is employed to utilize EDP residuals of SDOF systems representing structural modes. DNN models are constructed to predict EDP residuals of SDOF and MDOF systems. Accuracy and applicability of DNN‐based frameworks are successfully demonstrated by example of regional seismic loss assessment.

The role of risk measures in relating earthquake risks at building and portfolio levels

Bodenmann

Broccardo

Galanis

et al. 2023

The potentially large spatial footprint of earthquake disasters and the increased concentration of population and values in dense urban areas call for an explicit consideration of seismic risk at a regional, building portfolio level. The relation between the building‐level seismic risk and the portfolio‐level seismic risk is helpful if one wants to meet a specific regional seismic risk tolerance level by specifying seismic risk targets for individual buildings. We examine four types of common risk measures and point to the importance of subadditivity, a risk measure mathematical property, for deriving a conservative upper‐bound relation between the building‐specific and the building portfolio seismic risks. Subadditive risk measures, such as the Expected Shortfall, allow estimates of conservative upper bounds of the portfolio‐level seismic risk. In a case study, we show that nonsubadditive risk measures commonly used in earthquake engineering can lead to counter‐intuitive and nonconservative perceptions of the regional seismic risk, especially when one extrapolates from individual buildings to the entire building portfolio. We also illustrate the advantages of subadditive risk measures for regional seismic risk assessment.