Probabilistic hurricane risk analysis of coastal bridges incorporating extreme wave statistics. (1st March 2019)

• Record Type: Journal Article
• Authors: Saeidpour, Arash; Chorzepa, Mi G.; Christian, Jason; Durham, Stephan
• Is Part Of: Engineering structures. Volume 182(2019)
• Page Start: 379
• Page End: 390
• Publication Date: 2019-03-01
• Subjects: Fragility -- Risk -- Bridge -- Wave spectrum -- Hurricane; Structural engineering -- Periodicals; Structural analysis (Engineering) -- Periodicals; Construction, Technique de la -- Périodiques; Génie parasismique -- Périodiques; Pression du vent -- Périodiques; Earthquake engineering; Structural engineering; Wind-pressure; Periodicals; 624.105
• DOI: 10.1016/j.engstruct.2018.11.069
• Languages: English
• ISSNs: 0141-0296

Abstract

Highlights: A hurricane risk assessment framework is introduced to identify vulnerable bridges. The maximum sustained wind speed is selected as the intensity measure. Uncertainties in both demand and capacity variables are considered. The proposed framework is highly effective in assessing risk of bridge failures. Abstract: Coastal bridges sustained severe damage during hurricanes Ike, Katrina, and Ivan. Reducing the impact of future hurricane events to coastal bridges requires conducting a comprehensive risk analysis. A comprehensive risk analysis of bridges enables owners to assign limited resources to the most critical bridges in the inventory through a risk-informed decision making process. This study presents a computationally efficient methodology for structural fragility analysis and risk assessment of simply supported coastal bridges vulnerable to hurricane hazard. Various sources of uncertainty associated with hurricane hazard and bridge response are identified, and thereby establishing probability distributions. The novelty of the proposed method includes the consideration of uncertainties in extreme wave heights and wave period by means of a wave spectral density distribution in the calculation of wave forces. The proposed hurricane risk analysis method was successfully applied to coastal bridges located in the state of Georgia (U.S.A). The application presents the derivation of probabilistic models of demand, capacity and hazard; and highlights the potential of the proposed framework for identification and ranking of the most vulnerable bridges.