Reliability assessment of structural dynamic systems subject to earthquake-induced tsunamis

Abstract

Recent earthquake-induced tsunamis occurred in Padang, 2004 and Tohoku, 2011 brought huge losses of lives and properties. To date, it is neither practical nor possible to accurately predict such hazard and construct perfectly effective countermeasures against them. Therefore, it is of our great interest to quantify the structural risk caused by earthquake-induced tsunamis. Despite continuous advancement in numerical simulation of tsunami and wave-structure interaction, it still remains a computationally challenging task to evaluate the reliability of structural dynamic system, especially when uncertainties related to the system and its modelling are taken into account. The failure of the structure in a tsunami-wavestructural system (the complement of reliability) is defined as any response quantities of the system exceeding specified thresholds during the time when the structure is subjected to dynamic wave impact due to earthquake-induced tsunamis. In this study, attempts have been made from two perspectives. Firstly, the focus is concentrated on the physical numerical simulation of the tsunami wave-structure interaction. The uncertainty arises from both the stochastic process of earthquake source generation and the structural parameters. Therefore, the tsunami generation, propagation and runup, are carried out, prior to the modelling of the wave-structure interaction. The stochastic earthquake source model is proposed to generate tsunami profile which propagates to shorelines. The numerical analysis of the interaction is performed through LS-DYNA on a high-performance computing system. Secondly, various approaches based on a novel integration of the Subset Simulation algorithm and two metamodels, i.e. modified moving least squares (MLS) response surface approach (Taflanidis & Cheung 2012), as well as Gaussian processes (GP), are proposed to evaluate the reliability of the dynamic system. The metamodels are used to replace the computationally expensive physical numerical simulations. The proposed algorithms follow a logical sequence. First of all, we proposed adaptive SSMLS/SSGP (Chapter 4) in order to assess the reliability of the complex system more accurately. For problems which involve high dimensional variables, the

Efficient methodology and algorithms for resilience analysis of critical infrastructure systems subjected to natural hazards

“…To overcome this problem, advanced stochastic sampling methodologies (for example, the Subset Simulation) can be integrated with the surrogate model. Z. Shao [62] proposed…”