Seismic Fragility Analysis of Steel Liquid Storage Tanks Using Earthquake Ground Motions Recorded in Korea

Abstract

Liquid-containing storage tanks are important structures in industrial complexes. Because earthquake damages to liquid storage tanks can cause structural collapse, fires, and hazardous material leaks, there have been continuous efforts to mitigate earthquake damages using seismic fragility analysis. In this regard, this study focuses on the seismic responses and fragility of liquid storage tanks. First, the characteristics of earthquake ground motions are a critical factor influencing the seismic fragility of structures; thus, this study employs real earthquake records observed in the target area, southeastern Korea, with the earthquake characteristics estimated based on the ratio of peak ground acceleration to peak ground velocity. When a liquid storage tank oscillates during an earthquake, additional forces can impact the tank wall owing to hydrodynamic pressures. Therefore, this study presents a sophisticated finite element (FE) model that reflects the hydrodynamic effect of an oscillating liquid. Another advantage of such an FE model is that detailed structural responses of the entire wall shells can be estimated; this is not possible in simplified lumped mass or surrogate models. Lastly, probabilistic seismic demand models are derived for three critical limit states: elastic buckling, elephant’s foot buckling, and steel yielding. Using the real earthquake ground motion records, constructed FE model, and limit states, a seismic fragility analysis is performed for a typical anchored steel liquid storage tank in Korea. In addition, for comparison purposes, a ring-stiffened model is investigated to derive a seismic fragility curve. The results of the seismic fragility assessment show that elastic buckling is the most vulnerable damage state. In contrast, elephant’s foot buckling and steel yielding indicate relatively severe damage levels. Furthermore, it is observed that ring stiffeners decrease the elastic buckling damage, although there is no practical effect on elephant’s foot buckling and steel yielding in all ground motion intensities.

A hybrid deep belief network-based label distribution learning system for seismic damage estimation of liquid storage tanks

“…Although a lot of efforts have been made in the research on the seismic fragility of liquid storage tanks (D'Amico and Buratti, 2019;Lee et al, 2019;O'Rourke and So, 2000;Saha et al, 2016), existing studies are still limited by the imperfections of past databases. Thus, in this work, the enhancement of post-earthquake damage data is the core of the proposed methodology.…”

“…As mentioned by many studies (D'Amico and Buratti, 2019;Gabbianelli et al, 2022;Lee et al, 2019;Miladi and Razzaghi, 2019), anchoring technology can greatly improve the seismic performance of storage tanks. (Miladi and Razzaghi (2019) observed the damage state of 28 above-ground cylindrical tanks that experienced the 2006 Silakhor earthquake.…”

“…As one of the core tasks of in process safety and risk management, the seismic damage estimation of liquid storage tanks has received considerable attention in recent years (Antonioni et al, 2007;Zuluaga Mayorga et al, 2019). As mentioned by Marta et al (D'Amico and Buratti, 2019)., most of the related studies focus on simulating and analyzing the fluid-structure interaction system (Zhou and Zhao, 2021;Bakalis and Karamanos, 2021;Ozdemir et al, 2010) or assessing the seismic fragility of liquid storage tanks (D'Amico and Buratti, 2019;Lee et al, 2019;Salzano et al, 2003;Zuluaga Mayorga et al, 2019). Given the stochastic nature of accident evolution, probabilistic fragility is essential to understand the response behavior of liquid storage tanks under extreme circumstances (D'Amico and Buratti, 2019;Men et al, 2022c;Yang et al, 2020;Zuluaga Mayorga et al, 2019).…”

“…Given the stochastic nature of accident evolution, probabilistic fragility is essential to understand the response behavior of liquid storage tanks under extreme circumstances (D'Amico and Buratti, 2019;Men et al, 2022c;Yang et al, 2020;Zuluaga Mayorga et al, 2019). Research on fragility analysis is abundant and most probabilistic models were driven by the post-earthquake damage data (D'Amico and Buratti, 2019;Salzano et al, 2003;Vıĺchez et al, 2001;Alliance, 2001b;Alliance, 2001a) or the analytical and numerical approximations (Berahman and Behnamfar, 2009;Fabbrocino et al, 2005;Zuluaga Mayorga et al, 2019;Lee et al, 2019;Saha et al, 2016;Gabbianelli et al, 2022). An overview of representative studies for the seismic fragility of liquid storage tanks is shown in the Appendix.…”

Accelerated System-Level Seismic Risk Assessment of Bridge Transportation Networks through Artificial Neural Network-Based Surrogate Model

“…The target network lies on a dense fault in southeast South Korea, and a magnitude 5.4 earthquake occurred in 2017 [45]. South Korea is known to have a relatively low earthquake probability, but recent frequent earthquakes and aftershocks have increased the level of interest in seismic risk assessment [46]. Figure 3 shows the topology of the target bridge transportation network, which comprises 1440 nodes and 3490 links.…”