Polynomial Chaos Expansion |

UQ state-dependent framework for seismic fragility assessment of industrial components

Mon, 01 Sep 2025 00:00:00 +0000

Abstract

Recently, there has been increased interest in assessing the seismic fragility of industrial plants and process equipment. This is reflected in the growing number of studies, community-funded research projects and experimental campaigns on the matter. Nonetheless, the complexity of the problem and its inherent modelling, coupled with a general scarcity of available data on process equipment, has limited the development of risk assessment methods. In fact, these limitations have led to the creation of simplified and quick-to-run models. In this context, we propose an innovative framework for developing state-dependent fragility functions. This new methodology combines limited data with the power of metamodelling and statistical techniques, namely polynomial chaos expansions (PCE) and bootstrapping. Therefore, we validated the framework on a simplified and computationally efficient MDoF system endowed with Bouc–Wen hysteresis. Then, we tested it on a real nonstructural industrial process component. Specifically, we applied the state-dependent fragility framework to a critical vertical tank of a multicomponent full-scale 3D steel braced frame (BF). The seismic performance of the BF endowed with process components was captured by means of shake table campaign within the European SPIF project. Finally, we derived state-dependent fragility functions based on the combination of PCE and bootstrap at a greatly reduced computational cost.

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State-dependent seismic fragility functions for bolted flange joints on special-risk industrial substructures

Sun, 28 Jul 2024 00:00:00 +0000

Abstract

Seismic vulnerability assessment of industrial plants and process equipment has gained attention lately. However, the complexity of the problem and its modelling, combined with a general scarcity of available data on industrial systems, contributed to limiting or developing risk assessment methods based on extremely simplified models. On these premises, a new methodology that combines limited data from finite element (FE) models with cutting-edge machine learning techniques is developed to generate state-dependent fragility functions for critical components mounted on archetypical industrial substructure modules. Specifically, referring to the classical forward uncertainty quantification scheme, a physics-informed FE model, calibrated on the results of a comprehensive shake table test campaign of a real-scale industrial braced-frame (BF) steel substructure, is considered. Time histories of seismic event sequences generated by a site-based ground motion model compose the input provided to the FE model. The uncertainty is then propagated through Monte Carlo analysis on inexpensive-to-run polynomial chaos expansion (PCE) metamodels set for each starting damage level condition measure. As a result, empirical state-dependent fragilities are evaluated, assuming the lognormal distribution.

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State-dependent seismic fragility functions for vertical tanks installed on major hazard industrial substructure module

Mon, 01 Jul 2024 00:00:00 +0000

Abstract

Suggerimento

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