Journal of Japan Society of Civil Engineers, Ser. C (Geosphere Engineering)
Online ISSN : 2185-6516
ISSN-L : 2185-6516
Paper (In Japanese)
PREDICTED PERFORMANCE OF ESTIMATED SEEPAGE ANALYSIS MODEL BY DATA ASSIMILATION BASED ON MEASUREMENT DATA OF SOIL COLUMN TEST
Shinichi ITOKazunari SAKORyosuke KITAMURAYoshiteru KANEMARUKazuo KANEMARUMitsunari KAWASHIMA
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2020 Volume 76 Issue 4 Pages 350-362

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Abstract

 This study aimed to estimate seepage analysis models combining measurement data of soil column test and data assimilation by the merging particle filter, and to discuss predicted performance of the estimated models. Concerning two types of materials with different particle sizes, the estimated models learning the measurement data of 30 days could predict soil moisture conditions after a few months later with enough accuracy. As a consequence, the data assimilation of seepage analysis model using merging particle filter was available to predict future soil moisture conditions.

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© 2020 by Japan Society of Civil Engineers
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