TY - GEN
T1 - Finite Element Analysis for Deep Mixing Column Considering Statistical Uncertainty
AU - Namikawa, T.
N1 - Funding Information:
Acknowledgements. The author acknowledges the support of the Japan Society for the Promotion of Science (JSPS KAKENHI Grant No. 18K04351).
Publisher Copyright:
© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - A probabilistic analysis framework in which the spatial variability and the statistical uncertainty are considered simultaneously is presented to evaluate an overall strength of a cement-treated soil column. In this framework, the statistical uncertainty is evaluated from sample data using a Bayesian inference. The inference about the statistical parameters is performed by a Markov chain Monte Carlo method. The drawn values of the parameters are adopted when making random fields of strength as realizations. Then, the finite element analysis is conducted for the generated realizations. The framework components are briefly described, and an example analysis is performed to illustrate the influence of the statistical uncertainty and the spatial variability on the evaluation of the overall strength.
AB - A probabilistic analysis framework in which the spatial variability and the statistical uncertainty are considered simultaneously is presented to evaluate an overall strength of a cement-treated soil column. In this framework, the statistical uncertainty is evaluated from sample data using a Bayesian inference. The inference about the statistical parameters is performed by a Markov chain Monte Carlo method. The drawn values of the parameters are adopted when making random fields of strength as realizations. Then, the finite element analysis is conducted for the generated realizations. The framework components are briefly described, and an example analysis is performed to illustrate the influence of the statistical uncertainty and the spatial variability on the evaluation of the overall strength.
KW - Cement-treated soil
KW - Finite element analysis
KW - Monte Carlo simulation
KW - Random field
KW - Statistical uncertainty
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U2 - 10.1007/978-3-030-64514-4_106
DO - 10.1007/978-3-030-64514-4_106
M3 - Conference contribution
AN - SCOPUS:85101573437
SN - 9783030645137
T3 - Lecture Notes in Civil Engineering
SP - 968
EP - 975
BT - Challenges and Innovations in Geomechanics - Proceedings of the 16th International Conference of IACMAG - Volume 1
A2 - Barla, Marco
A2 - Di Donna, Alice
A2 - Sterpi, Donatella
PB - Springer Science and Business Media Deutschland GmbH
T2 - 16th International Conference of the International Association for Computer Methods and Advances in Geomechanics, IACMAG 2021
Y2 - 5 May 2021 through 8 May 2021
ER -