Nouvelles techniques et outils pour les études de stabilité au glissement des barrages-poids incluant les effets de la rugosité des surfaces des fondations

Tarik Fethi Saichi

Ph.D. thesis (2024)

Access this document
Available
Open access to the full text in PolyPublie
Unspecified
Text Text • 55MB •

Abstract

«ABSTRACT: Over the past several decades, enhancing methods for assessing the stability of gravity dams has been a significant focus in civil engineering research. Dam-foundation interfaces are generally regarded as vulnerable zones where failure can occur due to various extreme forces, including ice thrust, floods, and earthquakes. This thesis introduces the advancements and work done to carry out a novel, thorough investigation into how the large-scale roughness of dam-foundation interfaces impacts their shear strength. Additionally, this work has led to the development of innovative tools and techniques for incorporating the effects of rock foundation roughness into stability analyses. To achieve this objective, Bathymetric and Light Detection and Ranging (LiDAR) surveys were conducted on existing rock foundation surfaces near operational dam sites. These surveys yielded realistic dam-rock interface geometries with varying degrees of roughness. The resulting rock profiles were then incorporated into nonlinear Finite Element (FE) models for stability analyses of gravity dams differing in size. The comprehensive analysis of the non-linear response at dam-rock interfaces considers parameters such as limit friction angles, sliding safety factors, dilation angles, apertures, dam displacements, and shear stresses. Notably, the research demonstrates that overall roughness along dam-rock interfaces significantly enhances their shear strength. Additionally, the presence of natural local shear keys at the dam-rock interface can substantially improve the sliding stability of gravity dams. However, this effect is sensitive to both dam size and rock mechanical properties. Interestingly, the impact of rock strength parameters becomes more pronounced when the rock foundation surface features prominent natural shear keys. This thesis introduces a progressive approach for evaluating the characteristics of large-scale roughness at dam-rock interfaces and integrating their effects into practical dam stability analyses. The approach involves a series of three steps, with each analysis increasing in complexity. Depending on the application, the approach starts with the simplest, and moves up as required to the most complex. The analyses in order are: (i) Gravity Method (GM); (ii) Finite Element Method (FEM) with simplified horizontal interface; and (iii) Detailed FEM with irregular interface geometry. In the first two steps, the rock foundation geometry is simplified, and apparent cohesion and friction angles are introduced into the models. These parameters are evaluated based on a proposed nonlinear shear strength criteria, along with an Interface Roughness Coefficient (IRC) that characterizes the roughness of the entire dam-rock joint. In this work, the IRC is numerically approximated using FE models. The progressive approach is exemplified through various typical dam-rock systems and rock profiles derived from the bathymetric and LiDAR surveys. The results demonstrate that the impact of rock foundation roughness on dam sliding stability can be effectively captured using apparent cohesion and friction angles. The simplified models, while conservative, are likely to find favor among practicing engineers due to their practical effectiveness.»

Program:
Génie civil
Academic/Research Directors :
Institution:
Polytechnique Montréal
OAI:
oai:publications.polymtl.ca:58353
ORCID
Date Deposited:
17 Jul 2024 13:49
Last Modified:
02 Oct 2026 23:57
Cite in APA 7:
Saichi, T. F. (2024). Nouvelles techniques et outils pour les études de stabilité au glissement des barrages-poids incluant les effets de la rugosité des surfaces des fondations [Ph.D. thesis, Polytechnique Montréal]. PolyPublie. https://lx-publications2.polymtl.ca/58353/

Statistics

Total downloads

Downloads per month in the last year

Origin of downloads

Repository Staff Only

View Item
View Item