Simultaneous identification of time and space variant dynamic soil properties during the 1995 Hyogoken-Nanbu earthquake

Mikami, Atsushi; Sawada, Tsutomu

doi:10.1016/j.soildyn.2004.07.003

Cited by 2 publications

(1 citation statement)

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“…In this study, the simulations were performed focusing on the variability of geotechnical parameters more than that of other quantities. Geotechnical data came from a collection of previous literatures, and lots of laboratory results were referred (Inoue et al 1970;Chigira 1982;Okuda et al 1984;Miyagi 2004;Mikami and Sawada 2005;Sassa et al 2005). From the analysis of these geotechnical parameters above referred, one of uncertain variables, c′, could be assumed to be β general distributions, ϕ′ and m to be log-normal and normally distributed, respectively, as shown below (Table 1); other parameters were assumed as fixed in this research for the simplicity of displacement modeling.…”

Section: Data Processingmentioning

confidence: 99%

Probabilistic modeling of seismically triggered landslides using Monte Carlo simulations

Wang

et al. 2008

Landslides

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The 2004 Chuetsu earthquakes of Niigata (Japan) triggered numerous landslides, and the most widespread types of landslides were highly disrupted, relatively shallow slides and soil (debris) flows. This paper presented a method to evaluate slope instability using Newmark displacement on a pixel-by-pixel basis in a given area. The proposed method was able to integrate Newmark displacement modeling and Monte Carlo simulations within geographical information systems. In the modeling, an empirical attenuation relationship was utilized to calculate Arias intensity over this study area, and the variability of geotechnical parameters was taken into account to calculate coseismic landslide displacement. Before deriving the displacement from related inputs, the Monte Carlo simulations ran 1,500 times and generated 1,500 displacement values for each grid cell, and then means and standard deviations of displacement were calculated and probabilistic distributions can be obtained. Finally, given 10 cm as a threshold value of displacement, estimated probabilities of displacement exceeding 10 cm were shown as a map of seismic landslide hazards. The resulting hazard map was classified into four categories from very low to high level.

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Section: Data Processingmentioning

confidence: 99%