Prediction of Spatial Distribution for N-Values in Earth-Fill Embank Ments

Nishimura, Shinichi; Takayama, Yuta; Suzuki, Makoto; Murakami, Akira; Fujisawa, Kazunori

doi:10.2208/jscejge.67.252

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Cited by 2 publications

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“…From all the trend functions, the one with the smallest AIC is selected by using the minimizing Akaike information criterion estimation (MAICE). The MAICE is elaborated in detail by Nishimura, 29 and thus, will not be repeated here.…”

Section: Methodsmentioning

confidence: 99%

Data assimilation for surface wave method by ensemble Kalman filter with random field modeling

Ren

Nishimura

Shibata

et al. 2022

Num Anal Meth Geomechanics

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The ensemble Kalman filter (EnKF) was used to estimate the spatial distribution of the Young's modulus of a model of an earth‐fill dam by assimilating the travel time to the first arrival of the surface waves. By the ensemble data assimilation, the measured data from a geophysical exploration was applied to simultaneously estimate the geotechnical properties and evaluate the uncertainties. Swedish weight sounding (SWS) test results were employed as the prior information to generate the initial ensemble through the sequential Gaussian simulation (sGs). In the experiments of assimilation, it was shown that the reproducibility of the parameter field is enhanced by this initial ensemble generation method, and that the uncertainties of the identified parameters can be reduced by the assimilation.

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Section: Methodsmentioning

confidence: 99%