Identification of coupling parameters between shear strength behaviour of compacted soils and chemical's effects with an evolutionary-based data mining technique

Cuisinier, Olivier; Javadi, Akbar A.; Ahangar-Asr, Alireza; Masrouri, Farimah

Abstract

When subjected to a very high-pH, most of the soil minerals undergo physico-chemical transformation. This could induce strong modifications of the shear strength behaviour of the soil. This issue is of high interest in the framework of the design of deep nuclear wastes repositories, since the degradation of the concrete lining of deep galleries after thousands of years will generate an alkaline solute (pH > 12) that would circulate through the backfill, and alter its hydromechanical characteristics. A study was undertaken to assess the impact of high-pH fluid circulation on the shear strength behaviour of a backfill material. Because of the complexity of the existing constitutive theories, a new approach was used, based on evolutionary polynomial regression (EPR), for modelling of these processes. EPR is an evolutionary data mining technique that generates a transparent and structured representation of the behaviour of a system directly from data. An EPR model was developed and validated using results from a comprehensive set of triaxial tests. Through a sensitivity analysis, the EPR model permitted to identify the specific surface, and to a lesser extent the micropore void ratio, as coupling parameters between hydromechanical behaviour alteration during alkaline fluid circulation and a physical process.

Citation

Cuisinier, O., Javadi, A. A., Ahangar-Asr, A., & Masrouri, F. (2013). Identification of coupling parameters between shear strength behaviour of compacted soils and chemical's effects with an evolutionary-based data mining technique. Computers and Geotechnics, 48, 107-116. https://doi.org/10.1016/j.compgeo.2012.10.005

• Journal Article Type: Article
• Online Publication Date: Dec 12, 2012
• Publication Date: 2013-03
• Deposit Date: Aug 1, 2023
• Journal: Computers and Geotechnics
• Print ISSN: 0266-352X
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 48
• Pages: 107-116
• DOI: https://doi.org/10.1016/j.compgeo.2012.10.005