Seismic vulnerability of above-ground storage tanks with unanchored support conditions for Na-tech risks based on Gaussian process regression

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Abstract

This paper aims to investigate the seismic vulnerability of an existing unanchored steel storage tank ideally installed in a refinery in Sicily (Italy), along the lines of performance-based earthquake engineering. Tank performance is estimated by means of component-level fragility curves for specific limit states. The assessment is based on a framework that relies on a three-dimensional finite element (3D FE) model and a low-fidelity demand model based on Gaussian process regression, which allows for cheaper simulations. Moreover, to approximate the system response corresponding to the random variation of both peak ground acceleration and liquid filling level, a second-order design of experiments method is adopted. Hence, a parametric investigation is conducted on a specific existing unanchored steel storage tank. The relevant 3D FE model is validated with an experimental campaign carried out on a shaking table test. Special attention is paid to the base uplift due to significant inelastic deformations that occur at the baseplate close to the welded baseplate-to-wall connection, offering extensive information on both capacity and demand. As a result, the tank performance is estimated by means of component-level fragility curves for the aforementioned limit state which are derived through Monte Carlo simulations. The flexibility of the proposed framework allows fragility curves to be derived considering both deterministic and random filling levels. The comparison of the seismic vulnerability of the tank obtained with probabilistic and deterministic mechanical models demonstrates the conservatism of the latter. The same trend is also exhibited in terms of risk assessment.

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Phan, H. N., Paolacci, F., Di Filippo, R., & Bursi, O. S. (2020). Seismic vulnerability of above-ground storage tanks with unanchored support conditions for Na-tech risks based on Gaussian process regression. Bulletin of Earthquake Engineering, 18(15), 6883–6906. https://doi.org/10.1007/s10518-020-00960-7

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