Modelling the non-linear site response at the LSST down-hole accelerometer array in Lotung

Elia, Gaetano; Karofyllakis, Dimitrios; Guzel, Yusuf

doi:10.1016/j.soildyn.2017.08.007

Cited by 8 publications

(1 citation statement)

References 33 publications

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“…Located in the northeast of Taiwan, the Lotung large-scale seismic test (LSST) site was established in a seismically active region in 1985 to study seismic soil-structure-inter action (SSI) effects on nuclear power plants. In addition to the scaled structures constructed by the Electric Power Research Institute (EPRI) and the Taiwan Power Company [54], the ground was instrumented at the surface in several locations and at different depths, and the recorded data from this site have been the subject of many studies [42,[55][56][57][58][59]. Among these studies, Zeghal and Elgamal [12,16] have extensively studied 18 earth quake datasets recorded between 1985 and 1986 (see Table 1 in [12,16]; data are publicly available at http://soilquake.net/Downholearray/Lotung/ (accessed on 8 December 2022)) Out of these 18 events, the respective amplitude resolutions of the signals in several events (Events 5, 6, 8, 9, 10, 15, 17, and 18) are not appropriate for identification studies.…”

Section: Seismic Data From Lotung Sitementioning

confidence: 99%

Identification of Nonlinear Soil Properties from Downhole Array Data Using a Bayesian Model Updating Approach

Ghahari

Abazarsa

Ebrahimian

et al. 2022

Sensors

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An accurate seismic response simulation of civil structures requires accounting for the nonlinear soil response behavior. This, in turn, requires understanding the nonlinear material behavior of in situ soils under earthquake excitations. System identification methods applied to data recorded during earthquakes provide an opportunity to identify the nonlinear material properties of in situ soils. In this study, we use a Bayesian inference framework for nonlinear model updating to estimate the nonlinear soil properties from recorded downhole array data. For this purpose, a one-dimensional finite element model of the geotechnical site with nonlinear soil material constitutive model is updated to estimate the parameters of the soil model as well as the input excitations, including incident, bedrock, or within motions. The seismic inversion method is first verified by using several synthetic case studies. It is then validated by using measurements from a centrifuge test and with data recorded at the Lotung experimental site in Taiwan. The site inversion method is then applied to the Benicia–Martinez geotechnical array in California, using the seismic data recorded during the 2014 South Napa earthquake. The results show the promising application of the proposed seismic inversion approach using Bayesian model updating to identify the nonlinear material parameters of in situ soil by using recorded downhole array data.

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