Comparison of equivalent linear and nonlinear methods in seismic analysis of liquefiable site response due to near-fault incident waves: a case study

Adampira, Mohammad; Alielahi, Hamid; Panji, Mehdi; Koohsari, Hamid

doi:10.1007/s12517-014-1399-6

Cited by 36 publications

(7 citation statements)

References 19 publications

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“…5); the conservative aptitude degree of these models is the object of different case studies and suggestions (e.g. in Adampira et al, 2015;Zidan, 2015). (ii) The seismic responses obtained by the meta-model process are affected by checked trainer errors (intrinsic errors); in contrast the maps developed by the metamodel solving are affected by non-checked errors (prediction errors), that nevertheless have values comparable with the aforementioned checked errors.…”

Section: Discussionmentioning

confidence: 99%

SiSeRHMap v1.0: a simulator for mapped seismic response using a hybrid model

Grelle

Bonito

Lampasi³

et al. 2016

Geosci. Model Dev.

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Abstract. The SiSeRHMap (simulator for mapped seismic response using a hybrid model) is a computerized methodology capable of elaborating prediction maps of seismic response in terms of acceleration spectra. It was realized on the basis of a hybrid model which combines different approaches and models in a new and non-conventional way. These approaches and models are organized in a code architecture composed of five interdependent modules. A GIS (geographic information system) cubic model (GCM), which is a layered computational structure based on the concept of lithodynamic units and zones, aims at reproducing a parameterized layered subsoil model. A meta-modelling process confers a hybrid nature to the methodology. In this process, the one-dimensional (1-D) linear equivalent analysis produces acceleration response spectra for a specified number of site profiles using one or more input motions. The shear wave velocity–thickness profiles, defined as trainers, are randomly selected in each zone. Subsequently, a numerical adaptive simulation model (Emul-spectra) is optimized on the above trainer acceleration response spectra by means of a dedicated evolutionary algorithm (EA) and the Levenberg–Marquardt algorithm (LMA) as the final optimizer. In the final step, the GCM maps executor module produces a serial map set of a stratigraphic seismic response at different periods, grid solving the calibrated Emul-spectra model. In addition, the spectra topographic amplification is also computed by means of a 3-D validated numerical prediction model. This model is built to match the results of the numerical simulations related to isolate reliefs using GIS morphometric data. In this way, different sets of seismic response maps are developed on which maps of design acceleration response spectra are also defined by means of an enveloping technique.

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Section: Discussionmentioning

confidence: 99%

SiSeRHMap v1.0: a simulator for mapped seismic response using a hybrid model

Grelle

Bonito

Lampasi³

et al. 2016

Geosci. Model Dev.

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“…During the Tarlay Earthquake, soil liquefaction had occurred in CR-1 (Mase et al, 2020b). In general, Chiang Rai subsoils (represented by CR-1) is dominated by saturated sandy soils with shallow ground water (Adampira et al, 2015).…”

Section: Figure 1 Location Of Site Investigations and Earthquake Epicentrementioning

confidence: 99%

The Use of Ground Motion Parameters to identify the Liquefaction during a Strong Earthquake in Northern Thailand

Mase

2021

MKTS

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This paper presents a ground response analysis to simulate the liquefaction phenomenon during the 2011 Tarlay Earthquake in northern Thailand. The site investigation data and geophysical measurements on 7 sites in northern Thailand were collected. The multi-springs element model was implemented in finite element ground response analysis. Several parameters, such as peak ground acceleration, peak ground velocity, amplification factor, excess pore pressure ratio, were observed. Furthermore, the correlation from the ground motion parameters was generated to estimate liquefaction potential, which was represented by excess pore pressure ratio. The result showed that the excess pore pressure ratio was relatively well correlated with several ground parameters, such as amplification factor, velocity-acceleration ratio, and factor of safety against liquefaction. The results could be also used for the engineering practice in predicting liquefaction potential in Northern Thailand.

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“…In Figure 4, the soil profile is divided into elements computed based on wave propagation theory and the minimum size for each was reported by Pender et al (2016) and Mase et al (2017) to be 0.5 m. The boundary conditions were limited on vertical direction of the soil column while there is no lateral direction at the bottom and this led to the adoption of elastic half-space assumption through the surface, Vs, of 760 m/s which was assigned at the bottom of the soil column. This assumption has also been applied in several studies, such as Adampira et al (2015) and Mase et al (2018) to conduct seismic ground response analysis in Assaluyeh (Iran) and Chiang Rai (Thailand) respectively. Moreover, a ground motion generated based on earthquake characteristics proposed by Mase et al (2019) was applied as the input motion as indicated in Figure 5.…”

Section: Research Frameworkmentioning

confidence: 99%

The Implementation of Ground Response Analysis to Quantify Liquefaction Potential Index (LPI) in Bengkulu City, Indonesia

Mase

Farid

Sugianto

et al. 2020

Journal of the Civil Engineering Forum

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Bengkulu City is one of the areas vulnerable to earthquakes in Indonesia and several studies have shown the city experienced a unique phenomenon called liquefaction during the Mw 8.6 Bengkulu-Mentawai Earthquake. This event has initiated a step by step intensive study on earthquake in the area but previous studies are generally limited by the use of site investigation data to empirically analyse liquefaction potential and those that used advance method such as the seismic wave propagation model are rare. This means the level of liquefaction damage in the study area is not totally understood, therefore, this research focused on implementing the ground response analysis to quantify the Liquefaction Potential Index (LPI) using several areas in Bengkulu City in order to determine their vulnerability. The process involved the collection of several site investigation data including boring log and shear wave velocity profile as well as a desk study to determine the geological condition of the observed sites. Moreover, a non-linear seismic ground response analysis was conducted to obtain maximum ground surface acceleration (amax) parameter which was further used to analyse the liquefaction potential in the study area. The results showed several sites have the potential to experience liquefaction during earthquakes. The method applied was considered successful and the results are expected to be implemented for city development. Furthermore, the framework is recommended for adoption in investigating the liquefaction in other areas.

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Comparison of equivalent linear and nonlinear methods in seismic analysis of liquefiable site response due to near-fault incident waves: a case study

Cited by 36 publications

References 19 publications

SiSeRHMap v1.0: a simulator for mapped seismic response using a hybrid model

SiSeRHMap v1.0: a simulator for mapped seismic response using a hybrid model

The Use of Ground Motion Parameters to identify the Liquefaction during a Strong Earthquake in Northern Thailand

The Implementation of Ground Response Analysis to Quantify Liquefaction Potential Index (LPI) in Bengkulu City, Indonesia

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