358
Views
2
CrossRef citations to date
0
Altmetric
Original Articles

Identifying the parameters of a hydro-mechanical model for internal erosion occurring in granular soils by using an enhanced backtracking search algorithm

, , , &
Pages 2325-2344 | Received 25 Mar 2020, Accepted 02 Apr 2020, Published online: 27 Apr 2020
 

Abstract

Due to the complexity of the hydro-mechanical behaviour of soils subjected to internal erosion, a high number of parameters are usually required for the erosion models and the constitutive models. This aspect makes it difficult to determine by trial-error their relevant values from laboratory tests. To address this issue, an efficient optimisation-based procedure for identifying the parameters of a recently developed hydro-mechanical model for internal erosion using an enhanced backtracking search algorithm (so-called MBSA-LS) has been proposed. The MBSA-LS incorporates two points: (1) modifying the mutation of the original Backtracking Search Algorithm (BSA) and (2) incorporating an efficient differential evolution (DE) as a local search to improve the optimisation performance. A mono-objective framework with six different criteria has been proposed to identify the parameters related to the interlocking effect and the erosion process. The proposed procedure was successfully applied to identify the parameters from the erosion tests of Hong Kong-Completely Decomposed Granite mixture (HK-CDG). All results demonstrated that coupling the MBSA-LS and the hydro-mechanical erosion model could efficiently solve the issue of parameter identification accounting for both the mechanical behaviour and internal erosion.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The financial supports provided by a GRF project (Grant No. 15209119) from Research Grants Council (RGC) of Hong Kong and the National Institute for Industrial Environment and Risks of France (INERIS) are gratefully acknowledged.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 229.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.