WIT Press


HURRICANE VULNERABILITY OF COASTAL BRIDGES USING MULTIPLE ENVIRONMENTAL PARAMETERS



Price

Free (open access)

Paper DOI

10.2495/SAFE-V6-N1-10-18

Volume

Volume 6 (2016), Issue 1

Pages

8

Page Range

10 - 18

Author(s)

M.G. CHORZEPA, A. SAEIDPOUR, J.K. CHRISTIAN, & S.A. DURHAM

Abstract

Hurricanes and other severe storms have proven themselves to be one of the major threats to transportation assets throughout the world, particularly to bridges located along coastal areas. Bridges as key components of transportation networks have shown to be vulnerable to hurricane-induced wave and surge forces. A large number of bridges along the U.S. Gulf coast suffered severe damage from recent hurricanes. Current risk-assessment practices include the fragility analysis of bridges based on a single hazard intensity parameter such as peak ground acceleration. However, this study investigates the vulnerability of highway bridges against hurricanes for multiple hazard parameters, not including the risk of substructure failure due to scour and/or erosion. The proposed hurricane vulnerability assessment methodology is applied to bridges along the surge-prone coastal regions of the state of Georgia. The surge-prone region is identified by the USGS SLOSH maps, and vulnerable bridges are selected based on the available NBI database. Nonlinear bridge models have been developed to apply a time history of wave loading as a function of the wind speed and storm water depth. Different combinations of bridge geometric and material parameters are generated to develop meta-models which cover a wide range of bridge configurations and wave/surge loads. This study yields a fragility function which describes the probability of failure for vulnerable bridges in terms of two environmental parameters: wind speed and storm water depth. The findings of this study will ultimately be beneficial to policy makers prioritizing recovery efforts and allocation of essential resources.

Keywords

bridge, environmental parameters, fragility, Hurricane, metamodel, surge, SVM, vulnerability, wave