Options for the Implementations of Data Assimilation for Geotechnics

Conference Paper (2023)
Author(s)

Muhammad Mohsan (TU Delft - Reservoir Engineering)

Philip James Vardon (TU Delft - Geo-engineering)

Femke Vossepoel (TU Delft - Reservoir Engineering)

Research Group
Reservoir Engineering
Copyright
© 2023 M. Mohsan, P.J. Vardon, F.C. Vossepoel
DOI related publication
https://doi.org/10.1007/978-3-031-12851-6_31
More Info
expand_more
Publication Year
2023
Language
English
Copyright
© 2023 M. Mohsan, P.J. Vardon, F.C. Vossepoel
Research Group
Reservoir Engineering
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
Volume number
3
Pages (from-to)
255-262
ISBN (print)
9783031128509
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Data assimilation methods have been implemented on a slope stability problem, and the performance of different constitutive models and data assimilation schemes has been investigated. In the first part, a data assimilation scheme called the ensemble Kalman filter (EnKF) is implemented using a finite element model (FEM) and its performance with different constitutive models (the Mohr-Coulomb (MC) and Hardening Soil (HS) material models) is investigated to study their effect on the parameter and the factor of safety (FoS) estimation. Measurements of horizontal displacement are assimilated. The results from a synthetic example show that the HS model can generally be used to get reliable results for parameter and FoS estimation. However, using the MC model does not always output reliable parameter and FoS estimation. In the second part, the performance of different data assimilation schemes, i.e., the EnKF and ensemble smoother with multiple data assimilation (ESMDA), is studied with the preferred constitutive material model (the HS model). The results of a synthetic case show that the EnKF results in a narrower distribution for the FoS than the ESMDA method, while the latter results in FoS estimation which is closer to the ‘truth’.

Files

Mohsan_et_al.pdf
(pdf | 0.533 Mb)
- Embargo expired in 31-01-2023
License info not available