David Lallemant

Framework for Incorporating Probabilistic Building Performance in the Assessment of Community Seismic Resilience

AbstractA framework is presented for incorporating probabilistic building performance limit states in the assessment of community resilience to earthquakes. The limit states are defined on the basis of their implications to postearthquake functionality and recovery. They include damage triggering inspection, occupiable damage with loss of functionality, unoccupiable damage, irreparable damage, and collapse. Fragility curves are developed linking earthquake ground motion intensity to the probability of exceedance for each of the limit states. A characteristic recovery path is defined for each limit state on the basis of discrete functioning states, the time spent within each state, and the level of functionality associated with each state. A building recovery function is computed accounting for the uncertainty in the occurrence of each recovery path and its associated limit state. The outcome is a probabilistic assessment of recovery of functionality at the building level for a given ground motion intensit...

A Beta Distribution Model for Characterizing Earthquake Damage State Distribution

This study investigates methods for modeling the distribution of post-earthquake damage among categorical damage states. Specifically, it is demonstrated that the beta distribution is a good model for characterizing the complete probability distribution of damage states conditioned on ground-motion intensity. Based on extensive post-earthquake damage surveys following the 2010 earthquake in Haiti, the paper proposes the method-of-moments and maximum likelihood estimate-based formulations to fit a beta distribution model to grouped categorical damage data. The beta distribution model is further compared with one based on the binomial distribution, often used to estimate damage state distribution. The study demonstrates that the beta distribution results in little bias and variance in predictions of damage and loss. This model can be the basis for developing damage probability matrices, fragility curves, post-disaster damage estimations, risk assessments, and more.