High dimensional model representation for flood fragility analysis of highway bridge. (15th April 2023)

• Record Type: Journal Article
• Authors: Anisha, A.; Sahu, Deepak Kumar; Sarkar, Pradip; Mangalathu, Sujith; Davis, Robin
• Is Part Of: Engineering structures. Volume 281(2023)
• Publication Date: 2023-04-15
• Subjects: Flood -- Bridge -- Metamodel -- HDMR -- RSM; 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.2023.115817
• Languages: English
• ISSNs: 0141-0296

Abstract

Abstract: Climate changes and global warming have increased the frequency and severity of rains, hence the vulnerability of structures due to floods. Bridges are the most affected components of the transportation infrastructure affected by floods. Analysis in a probabilistic framework is required for reliable performance assessments of bridges. However, the detailed performance assessment of bridges requires consideration of the uncertainties in geometry, material properties, and flood loading. The random structural responses due to flood loading can be obtained by stochastic analysis; conventionally, this is carried out using Monte Carlo Simulations (MCS). Due to the high computational cost required for MCS, non-statistical methods like High Dimensional Model Representation (HDMR) can be a feasible alternative to MCS. The present study is an application of the HDMR method to develop metamodels for the flood response of the highway bridge, considering the uncertainties. The structural responses due to flood at the sampling points of the HDMR are obtained by conducting finite element analysis. The HDMR could predict the random bridge responses due to flood loading fairly well compared to other popular response surface methods (like Central Composite Design, Box Behnken Design, and Full Factorial Design) with significantly fewer simulations. HDMR provides a flood response metamodel, as a function of the sensitive random parameters, with a substantial reduction in the computational effort. The efficiency of the HDMR method can be attributed to the ability of HDMR to model the nonlinear flood responses in terms of the statistical properties of random variables. The metamodels for the pier drifts developed are further utilized to generate flood fragility curves. The HDMR metamodels are found to simplify the fragility computations. Highlights: The present study is the first attempt to examine the efficiency of HDMR to express the random flood responses of bridge. These responses are used to develop metamodels which are further utilized to generate flood fragility curves. With much fewer simulations, the results of HDMR is found to match closely with that of the MCS method.