A first-order reliability approach to building portfolio loss estimation and mitigation prioritization.

摘要

The prediction of future losses from earthquake events and other natural hazards is of importance to community developers, insurance entities, political organizations and many others in hazard-prone regions. Often, this risk assessment is preferred at a regional level as many private and public entities are concerned with the impact of an earthquake on a suite of buildings, as opposed to that for a single site. Assessing risk at a regional level is more complicated than doing so for individual sites due to the correlation that exists between the performances of spatially distributed buildings within a single hazard. This spatial correlation has been shown to be vital for characterizing potential loss at a regional level; however, it is often neglected in existing loss estimation methodologies.;This dissertation proposes the use of the First-Order Reliability Method (FORM) to quantify probabilistic losses to a portfolio while incorporating the spatial correlation that exists between building performances. FORM is an approximate, analytical structural reliability technique that computes failure probability based on a linearization of a performance limit state. Unlike existing loss estimation tools that evaluate loss based on expected values or with the use of simulation, the proposed method evaluates the distribution of potential losses analytically and is also computationally efficient. In addition, sensitivity measures are computed using FORM to prioritize cost-effective retrofit strategies within a building portfolio.;This proposed method is applied to a selected San Francisco building inventory to estimate total structural and nonstructural repair cost in the form of loss exceedance curves. Sensitivity measures are used to prioritize building types that yield the most reduction in regional risk per dollar of retrofit.;In additional to quantifying losses, the proposed framework is extended to assess the seismic resilience for the San Francisco building portfolio. Sensitivity measures are computed relative to changes in system resilience for each dollar allocated to pre-disaster retrofit and to increasing post-disaster restoration efficiency.;Finally, the study also investigates the extension of the proposed FORM-based approach to assess the cumulative hazard-induced risk for regions subjected to multiple hazards. In this extended study, FORM is used to compute the distribution of loss for Charleston County, South Carolina, specific to potential earthquake and hurricane wind hazards.;The proposed approach provides an analytical and efficient tool for quantifying hazard risk at a regional level. By more effectively quantifying hazard-induced loss, resilience and sensitivities within a portfolio system, information is provided to improve hazard risk assessments and support more efficient risk management decision making.