Abstract

Recent catastrophe events have shown how vulnerable communities are to disasters and how the recovery of the impacted communities are contingent on appropriate preparedness. Measurement and assessment of community disaster resilience are therefore become crucial for communities to support collective actions to reduce the associated potential social disruptions and significant economic losses; and to quickly recover from hazard events. Among the essential ingredients for evaluating disaster resilience of communities are models for the assessment of hazard performance and impacts for the built environment. While assessment of such models require both data-driven (i.e, based on data from past hazard events or experimental data) and synthetic modelling techniques, advanced probabilistic methods are also needed to systematically treat significant uncertainties associated with these impact models. This mini symposium will provide a platform to bring together researchers and practitioners aiming to provide insights on recent experiences and developments in hazard impact assessment modeling of structural and infrastructure systems. Contributions related to recent advancements in field data-collecting protocols, data-driven techniques, simulation approaches, probabilistic tools, machine-learning approaches and big analytics in context of hazard-impact modeling are welcome.