Systematic quantification of modeling uncertainties in tank–foundation coupled systems

Abstract

Traditionally, uncertainty quantification in the context of liquid storage tanks has primarily focused on ground motion record-to-record variability, along with partial consideration of material randomness. This paper presents a comprehensive framework for addressing “modeling uncertainty” in the seismic analysis of rectangular tanks, including the influence of foundation interactions. The framework encompasses uncertainties inherent in both general finite element and mathematical modeling techniques, as well as uncertainty in modeling parameters (e.g., hydrodynamic mass and concrete constitutive model). This is achieved through the implementation of an efficient design of experiments. By employing an innovative intensifying artificial acceleration, over 26,000 transient simulations are conducted, spanning the full spectrum of structural behavior from linear to nonlinear regimes. Through a series of uncertainty quantification and sensitivity analyses, this study assesses bias and dispersion arising from diverse model assumptions. Furthermore, fragility analysis and machine learning post-processing techniques are employed to extract latent insights from the generated data. The outcomes underscore that numerical and mathematical modeling uncertainties can bear comparable significance to ground motion record-to-record variability. The adoption of distinct modeling strategies introduces biases in fragility curves, particularly within higher damage states. Consequently, it is advised to account for modeling randomness directly (via simulation) or approximately (leveraging the insights from this study) in any uncertainty quantification related to storage tanks.