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Abstract
This study presents the development of probabilistic models to assess the structural performance of a typical aboveground storage tank (AST) subjected to storm surge and wave loads. First, a finite element model is developed and validated against experimental results to determine hydrodynamic loads on the AST. This finite element model is then employed to derive a regression model of the hydrodynamic loads across ranges of surge and wave parameters using an Artificial Neural Network. This regression model is used as a surrogate of the finite element model to facilitate the investigation of the structural behavior of the case study AST. Finally, the buckling behavior of the AST and the stability of the tank to dislocation (uplift, overturning, or siding) are assessed for various AST modeling parameters and load conditions in order to develop fragility models. Two distinct fragility models are derived, one for dislocation and one for buckling. Key insights on the influence of surge and wave loads are obtained from these models. Results indicate that wave loads and hydrodynamic effects are significant, and neglecting them could underestimate the probability of dislocation or buckling of the AST by up to 30%. Overall, this paper proposes a rigorous yet efficient methodology for the fragility modeling of ASTs during storm events and opens the path for future investigations of the performance of ASTs with a range of design details and exposure conditions.References
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