Uncertainties in the Estimate of Strong Ground Motion in the Surroundings of a Large Earthquake

Author(s):  
Giuliano F. Panza ◽  
Peter Suhadolc ◽  
Paolo Harabaglia
Author(s):  
Tsung-Jen Teng ◽  
Pei-Ting Chen ◽  
Ting-Wei Chang ◽  
Yuan-Sen Yang ◽  
Chien-Kuo Chiu ◽  
...  

This study presents strong ground motion simulation methods for the future fragility study of a power plant in Southern Taiwan. The modified stochastic method and empirical Green function method are utilized to synthesize the strong ground motions of specific events. A modified physical random function model of strong ground motions for specific sites and events is presented in this study with verification of sample level. Based on the special models of the source, path, and local site, the random variables of the physical random function of strong ground motions is obtained. The inverse Fourier transform is used to simulate strong ground motions. For the empirical Green function method, the observed site records from small earthquake events occurring around the source area of a large earthquake are collected to simulate the broadband strong ground motion from a large earthquake event. Finally, an application of proposed two simulated methods of this study for simulating the ground motion records of Nishi-Akashi Station at 1995 Kobe earthquake and 2006 Southern Taiwan PingDong earthquake are presented.


1998 ◽  
Vol 88 (2) ◽  
pp. 357-367 ◽  
Author(s):  
Katsuhiro Kamae ◽  
Kojiro Irikura ◽  
Arben Pitarka

Abstract A method for simulating strong ground motion for a large earthquake based on synthetic Green's function is presented. We use the synthetic motions of a small event as Green's functions instead of observed records of small events. Ground motions from small events are calculated using a hybrid scheme combining deterministic and stochastic approaches. The long-period motions from the small events are deterministically calculated using the 3D finite-difference method, whereas the high-frequency motions from them are stochastically simulated using Boore's method. The small-event motions are synthesized summing the long-period and short-period motions after passing them through a pair of matched filters to follow the omega-squared source model. We call the resultant time series “hybrid Green's functions” (HGF). Ground motions from a large earthquake are simulated by following the empirical Green's function (EGF) method. We demonstrate the effectiveness of the method at simulating ground motion from the 1995 Hyogo-ken Nanbu earthquake (Mw 6.9).


Author(s):  
Ken Hatayama ◽  
Haruki Nishi ◽  
Masahiko Hayashi ◽  
Koya Tokutake

Abstract Damage and influences to oil tanks caused by severe strong ground motion due to a large earthquake (Mw6.6) that occurred in the district of Iburi-tobu, Hokkaido, Japan on September 6, 2018 are reported in this paper. In the vicinity of the seismic source region, two large-scale crude-oil storage bases are located. The neighboring two bases had in total 86 large oil storage tanks with a capacity of 115,000 m3. The oil storage bases were hit by strong ground motion with peak ground accelerations of 590 to 1,570 cm/s2 and with peak ground velocities of 50 to 80 cm/s. Shell plates of a small bunker A tank with a capacity of 306 m3 suffered diamond buckling and elephant-foot buckling. No large oil storage tanks lost their function of oil storage despite of the severe strong ground motion. However, most of them splashed oil from the gap between the floating roof and the shell plate, and many of them had damage to their pontoons, gauge poles, guide poles, rolling ladders, liquid-level meters, and shoulders of foundation. One of the 115,000-m3-in-capacity tanks was equipped with a displacement gauge system to measure uplift of the bottom of the shell plate from the shoulder of tank foundation. The system recorded a maximum uplift of 4.4 cm. This is the world’s first record of uplift of a large tank caused by a natural earthquake.


2014 ◽  
Vol 119 (2) ◽  
pp. 1316-1336 ◽  
Author(s):  
Vahe Gabuchian ◽  
Ares J. Rosakis ◽  
Nadia Lapusta ◽  
David D. Oglesby

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