Investigation for probabilistic prediction of shear strength properties of clay-rich fault gouge in the Austrian Alps

• Published in: Engineering geology Vol. 94; no. 1; pp. 103 - 121
• Main Authors: Liu, Q., Button, E., Klima, K.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 16-10-2007; Elsevier
• Subjects: Applied sciences; Bayes's theorem; Buildings. Public works; Clay-rich fault gouge; Exact sciences and technology; Geotechnics; Shear strength properties; Significance test; Soil investigations. Testing; Soil mechanics. Rocks mechanics; Stepwise Discriminant Analysis; Austria; Europe; Significance test; Stepwise Discriminant Analysis; Shear strength properties; Bayes's theorem; Clay-rich fault gouge; Bayes estimation; Clay; Discriminant analysis; Rock mechanics; Probabilistic approach; Site analysis; Shear strength; Fault; Forecast model; Consolidation
• ISSN: 0013-7952; 1872-6917
• DOI: 10.1016/j.enggeo.2007.08.001

Geotechnical practice in the Austrian Alps determined that it is difficult to evaluate the shear strength properties of clay-rich fault gouge associated with thin shear zones because of a lack of undisturbed samples and the high normal stresses required for appropriate shear tests. The objective of this paper is to do a probabilistic prediction of the shear strength properties of clay-rich fault gouges through simple geotechnical parameters. The representative clay-rich fault gouge samples were selected from engineering projects. Their characteristics, i.e. water content and density, were simulated through high normal stress consolidation. Then they were sheared under different normal stress with low velocities. Shear test results show that there are four types of shear strength properties, which can be classified by geotechnical parameters. The significance of the parameters for the classification was tested. Using the Stepwise Discriminant Analysis, the best predictors were evaluated from basic soil classification parameters. The probabilistic prediction of shear strength properties was established by the combinations of the best predictors using Bayes's theorem. This makes the prediction of the shear strength properties of clay-rich fault gouge in the Austrian Alps easy and practical when sample availability is limited.