A modified sub-assembly approach for hurricane induced wind-surge-wave vulnerability assessment of low-rise wood buildings in coastal communities

Abstract

The coastal low-rise buildings account for large amounts of property loss during hurricanes, which makes it essential to perform vulnerability assessments of buildings and communities to estimate the possible structural damage and economical loss. Fragility assessment and loss prediction are usually performed with the sub-assembly (SA) approach in the HAZUS-MH model. However, hydrodynamic forces caused by surge and waves are excluded, and damages from wind and flood are assumed independent of each other. In the present study, a modified sub-assembly (MSA) approach is proposed based on the SA approach for the hurricane-induced wind-surge-wave vulnerability assessments for buildings and communities considering the hurricane-induced wind-surge-wave loadings without the predefined assumption. The physics-based high-fidelity finite element models are established, and the structural performances are analyzed for three typical coastal residential wood buildings under individual wind or surge-wave loadings and combined wind-surge-wave loadings. Building type is found to be a key factor influencing the vulnerabilities of the buildings, and building elevation is an effective method to mitigate building damages from surge-wave loadings as well as hurricane-induced wind-surge-wave loadings. Profound influences of wind profile shifting under combined wind-surge-wave loading are observed on elevated buildings' vulnerabilities at some stillwater levels for different building types. The MSA approach outperforms the SA approach in the building vulnerability prediction at the hurricane-induced wind-surge-wave scenarios, especially for the elevated buildings. A smaller wind speed interval is recommended to help with the building vulnerability prediction accuracy of the MSA approach. The vulnerability assessment of a coastal community further validates the accuracy of the proposed MSA approach.