Application of an HMC Based Approximate Method for Combined Identification of Hydraulic Conductivity and Piping Region Interface

Michael C. Koch; Misato Osugi; Kazunori Fujisawa; Akira Murakami

doi:10.1007/978-3-030-64514-4_96

Application of an HMC Based Approximate Method for Combined Identification of Hydraulic Conductivity and Piping Region Interface

Michael C. Koch^*
, Misato Osugi
, Kazunori Fujisawa
, Akira Murakami

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › peer-review

Abstract

The detection of piping and the extent to which it progresses is important in the serviceability of natural dams and levees, where the soil is usually poorly consolidated and filters or drainage zones are absent. Practically, information of the spatial variation of hydraulic conductivity is also unavailable in the domain of interest. An approximate version of a Hamiltonian Monte Carlo (HMC) based method for combined probabilistic inversion is detailed. The inverse problem consists of Karhunen-Loève (KL) expansion parameters and solid-void interface parameters which are determined simultaneously. The interface parameter updates are carried out using a reversible proposal in a mesh moving framework. To maintain computational efficiency, the parameter update is enforced in an approximate sense, where the covariance matrix for the KL expansion is kept constant throughout the analysis. Synthetic data from a numerical experiment on a domain containing a predefined piping region, is used to validate the approximate method. A total of 30000 samples are generated using the HMC sampler. Results show that the Markov chains converge to the stationary distribution. A good match is also observed between the inferred mean interface, and the true interface and the true spatial distribution of hydraulic conductivity is obtained.

Original language	English
Title of host publication	Challenges and Innovations in Geomechanics
Subtitle of host publication	Proceedings of the 16th International Conference of IACMAG - Volume 1
Editors	Marco Barla, Alice Di Donna, Donatella Sterpi
Publisher	Springer Science+Business Media B.V.
Pages	886-894
Number of pages	9
ISBN (Electronic)	9783030645144
ISBN (Print)	9783030645137, 9783030645168
DOIs	https://doi.org/10.1007/978-3-030-64514-4_96
Publication status	Published - 2021
Externally published	Yes
Event	16th International Conference of the International Association for Computer Methods and Advances in Geomechanics, IACMAG 2021 - Turin, Italy Duration: 5 May 2021 → 8 May 2021

Publication series

Name	Lecture Notes in Civil Engineering
Volume	125
ISSN (Print)	2366-2557
ISSN (Electronic)	2366-2565

Conference

Conference	16th International Conference of the International Association for Computer Methods and Advances in Geomechanics, IACMAG 2021
Country/Territory	Italy
City	Turin
Period	5/05/21 → 8/05/21

Access to Document

10.1007/978-3-030-64514-4_96

Cite this

Koch, M. C., Osugi, M., Fujisawa, K., & Murakami, A. (2021). Application of an HMC Based Approximate Method for Combined Identification of Hydraulic Conductivity and Piping Region Interface. In M. Barla, A. Di Donna, & D. Sterpi (Eds.), Challenges and Innovations in Geomechanics: Proceedings of the 16th International Conference of IACMAG - Volume 1 (pp. 886-894). (Lecture Notes in Civil Engineering; Vol. 125). Springer Science+Business Media B.V.. https://doi.org/10.1007/978-3-030-64514-4_96

Koch, Michael C. ; Osugi, Misato ; Fujisawa, Kazunori et al. / Application of an HMC Based Approximate Method for Combined Identification of Hydraulic Conductivity and Piping Region Interface. Challenges and Innovations in Geomechanics: Proceedings of the 16th International Conference of IACMAG - Volume 1. editor / Marco Barla ; Alice Di Donna ; Donatella Sterpi. Springer Science+Business Media B.V., 2021. pp. 886-894 (Lecture Notes in Civil Engineering).

@inproceedings{87cec4e917ec49a8aff98420f929695c,

title = "Application of an HMC Based Approximate Method for Combined Identification of Hydraulic Conductivity and Piping Region Interface",

abstract = "The detection of piping and the extent to which it progresses is important in the serviceability of natural dams and levees, where the soil is usually poorly consolidated and filters or drainage zones are absent. Practically, information of the spatial variation of hydraulic conductivity is also unavailable in the domain of interest. An approximate version of a Hamiltonian Monte Carlo (HMC) based method for combined probabilistic inversion is detailed. The inverse problem consists of Karhunen-Lo{\`e}ve (KL) expansion parameters and solid-void interface parameters which are determined simultaneously. The interface parameter updates are carried out using a reversible proposal in a mesh moving framework. To maintain computational efficiency, the parameter update is enforced in an approximate sense, where the covariance matrix for the KL expansion is kept constant throughout the analysis. Synthetic data from a numerical experiment on a domain containing a predefined piping region, is used to validate the approximate method. A total of 30000 samples are generated using the HMC sampler. Results show that the Markov chains converge to the stationary distribution. A good match is also observed between the inferred mean interface, and the true interface and the true spatial distribution of hydraulic conductivity is obtained.",

keywords = "Hamiltonian Monte Carlo, Interface and hydraulic conductivity estimation",

author = "Koch, \{Michael C.\} and Misato Osugi and Kazunori Fujisawa and Akira Murakami",

note = "Publisher Copyright: {\textcopyright} 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 16th International Conference of the International Association for Computer Methods and Advances in Geomechanics, IACMAG 2021 ; Conference date: 05-05-2021 Through 08-05-2021",

year = "2021",

doi = "10.1007/978-3-030-64514-4\_96",

language = "English",

isbn = "9783030645137",

series = "Lecture Notes in Civil Engineering",

publisher = "Springer Science+Business Media B.V.",

pages = "886--894",

editor = "Marco Barla and \{Di Donna\}, Alice and Donatella Sterpi",

booktitle = "Challenges and Innovations in Geomechanics",

address = "Netherlands",

}

Koch, MC, Osugi, M, Fujisawa, K & Murakami, A 2021, Application of an HMC Based Approximate Method for Combined Identification of Hydraulic Conductivity and Piping Region Interface. in M Barla, A Di Donna & D Sterpi (eds), Challenges and Innovations in Geomechanics: Proceedings of the 16th International Conference of IACMAG - Volume 1. Lecture Notes in Civil Engineering, vol. 125, Springer Science+Business Media B.V., pp. 886-894, 16th International Conference of the International Association for Computer Methods and Advances in Geomechanics, IACMAG 2021, Turin, Italy, 5/05/21. https://doi.org/10.1007/978-3-030-64514-4_96

Application of an HMC Based Approximate Method for Combined Identification of Hydraulic Conductivity and Piping Region Interface. / Koch, Michael C.; Osugi, Misato; Fujisawa, Kazunori et al.
Challenges and Innovations in Geomechanics: Proceedings of the 16th International Conference of IACMAG - Volume 1. ed. / Marco Barla; Alice Di Donna; Donatella Sterpi. Springer Science+Business Media B.V., 2021. p. 886-894 (Lecture Notes in Civil Engineering; Vol. 125).

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › peer-review

TY - GEN

T1 - Application of an HMC Based Approximate Method for Combined Identification of Hydraulic Conductivity and Piping Region Interface

AU - Koch, Michael C.

AU - Osugi, Misato

AU - Fujisawa, Kazunori

AU - Murakami, Akira

PY - 2021

Y1 - 2021

N2 - The detection of piping and the extent to which it progresses is important in the serviceability of natural dams and levees, where the soil is usually poorly consolidated and filters or drainage zones are absent. Practically, information of the spatial variation of hydraulic conductivity is also unavailable in the domain of interest. An approximate version of a Hamiltonian Monte Carlo (HMC) based method for combined probabilistic inversion is detailed. The inverse problem consists of Karhunen-Loève (KL) expansion parameters and solid-void interface parameters which are determined simultaneously. The interface parameter updates are carried out using a reversible proposal in a mesh moving framework. To maintain computational efficiency, the parameter update is enforced in an approximate sense, where the covariance matrix for the KL expansion is kept constant throughout the analysis. Synthetic data from a numerical experiment on a domain containing a predefined piping region, is used to validate the approximate method. A total of 30000 samples are generated using the HMC sampler. Results show that the Markov chains converge to the stationary distribution. A good match is also observed between the inferred mean interface, and the true interface and the true spatial distribution of hydraulic conductivity is obtained.

AB - The detection of piping and the extent to which it progresses is important in the serviceability of natural dams and levees, where the soil is usually poorly consolidated and filters or drainage zones are absent. Practically, information of the spatial variation of hydraulic conductivity is also unavailable in the domain of interest. An approximate version of a Hamiltonian Monte Carlo (HMC) based method for combined probabilistic inversion is detailed. The inverse problem consists of Karhunen-Loève (KL) expansion parameters and solid-void interface parameters which are determined simultaneously. The interface parameter updates are carried out using a reversible proposal in a mesh moving framework. To maintain computational efficiency, the parameter update is enforced in an approximate sense, where the covariance matrix for the KL expansion is kept constant throughout the analysis. Synthetic data from a numerical experiment on a domain containing a predefined piping region, is used to validate the approximate method. A total of 30000 samples are generated using the HMC sampler. Results show that the Markov chains converge to the stationary distribution. A good match is also observed between the inferred mean interface, and the true interface and the true spatial distribution of hydraulic conductivity is obtained.

KW - Hamiltonian Monte Carlo

KW - Interface and hydraulic conductivity estimation

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U2 - 10.1007/978-3-030-64514-4_96

DO - 10.1007/978-3-030-64514-4_96

M3 - Conference Paper

AN - SCOPUS:85101575025

SN - 9783030645137

SN - 9783030645168

T3 - Lecture Notes in Civil Engineering

SP - 886

EP - 894

BT - Challenges and Innovations in Geomechanics

A2 - Barla, Marco

A2 - Di Donna, Alice

A2 - Sterpi, Donatella

PB - Springer Science+Business Media B.V.

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 -

Koch MC, Osugi M, Fujisawa K, Murakami A. Application of an HMC Based Approximate Method for Combined Identification of Hydraulic Conductivity and Piping Region Interface. In Barla M, Di Donna A, Sterpi D, editors, Challenges and Innovations in Geomechanics: Proceedings of the 16th International Conference of IACMAG - Volume 1. Springer Science+Business Media B.V. 2021. p. 886-894. (Lecture Notes in Civil Engineering). doi: 10.1007/978-3-030-64514-4_96

Application of an HMC Based Approximate Method for Combined Identification of Hydraulic Conductivity and Piping Region Interface

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