Volume 4 Issue 1 (2025): In Progress

The occurrence of disasters is increasing in frequency and magnitude in Australia as a result of climate change. According to projections, disasters related to climate change and also other types of disasters are expected to impose an increasing burden on Australian communities and will increasingly challenge the capabilities of governments and other agencies to manage the post-disaster response and recovery. This paper explores whether Australian post-disaster recovery practices can be augmented to support and empower those impacted by catastrophic disasters. The research used a case study methodology to explore examples of major recent disasters in Australia and suggests how disaster recovery can be augmented by extending existing practices and/or utilising alternative practices. Recovery practices were identified from the literature and the selected case studies, and were analysed for importance, effectiveness and future potential improvements. Community engagement has been identified as a key factor in assessing the appropriate disaster recovery decisions and actions. The research on the disaster context and practices coupled with a review of the current scholarly discourse has been used to propose an indicative community recovery support matrix as a way of assisting governments and agencies involved in disaster recovery to develop strategies in the initial stage of supporting impacted communities.

This study introduces a multivariate demand model for Engineering Demand Parameters (EDPs) in Performance Based Seismic Design (PBSD), utilizing Gaussian copulas to characterize the dependence structure of the demand vector. The effectiveness of this approach is assessed by comparing EDPs generated using Gaussian copulas against those assumed under a joint lognormal distribution. This validation study is further carried forward to values of economic loss for the four special steel moment frames obtained via the three sets of EDPs. The Performance Assessment Calculation Tool (PACT) developed by the Federal Emergency Management Agency (FEMA) P-58 (2015) is used for loss estimation. Results indicate that using copulas to represent the dependence structure of EDPs better captures the characteristics of the population of EDPs rather than assuming a joint lognormal distribution. Distributions of economic loss generated using copulas match the loss generated from the true observations of EDPs better than loss generated assuming a joint lognormal distribution. The sample size of the selected and scaled ground motions required for the generation of realizations of building response via nonlinear dynamic analysis is also investigated, which proves to yield more accurate values of response but, at the expense of using a larger number of initial observations.