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Lecture

Computational Geomechanics

In course

CIVIL-423: Computational geomechanics

The goal of this course is to introduce the student to modern numerical methods for the solution of coupled & non-linear problems arising in geo-mechanics / geotechnical engineering. ...

Description

This lecture introduces the fundamentals of computational geomechanics, focusing on the analysis of geotechnical problems using numerical methods. Topics covered include assumptions in geomechanical modeling, poroelasticity, plasticity, and numerical techniques for solving complex geomechanical problems.

Instructor

Brice Tanguy Alphonse Lecampion

I am currently an assistant Professor and the head of the Geo-Energy Lab - Gaznat Chair on GeoEnergy at Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland. Prior to joining EPFL, I have worked for Schlumberger in research and development from 2006 until May 2015 - serving in a variety of roles ranging from project manager to principal scientist in both Europe and the United States. I received my PhD in mechanics from Ecole Polytechnique, France in 2002 and worked as a research scientist in the hydraulic fracturing research group of CSIRO division of Petroleum resources (Melbourne, Australia) from 2003 to 2006. During my time in Schlumberger R&D, I have worked on problems related to the integrity of deep wells, large scale monitoring of reservoir deformation and more specifically on the stimulation of oil and gas wells by hydraulic fracturing. My current research interests cover hydraulic fracture mechanics, mechanics of porous media and dense suspensions flow.

Official source

Related concepts (32)

Numerical integration

In analysis, numerical integration comprises a broad family of algorithms for calculating the numerical value of a definite integral, and by extension, the term is also sometimes used to describe the numerical solution of differential equations. This article focuses on calculation of definite integrals. The term numerical quadrature (often abbreviated to quadrature) is more or less a synonym for numerical integration, especially as applied to one-dimensional integrals.

Numerical analysis

Numerical analysis is the study of algorithms that use numerical approximation (as opposed to symbolic manipulations) for the problems of mathematical analysis (as distinguished from discrete mathematics). It is the study of numerical methods that attempt at finding approximate solutions of problems rather than the exact ones. Numerical analysis finds application in all fields of engineering and the physical sciences, and in the 21st century also the life and social sciences, medicine, business and even the arts.

Numerical methods for partial differential equations

Numerical methods for partial differential equations is the branch of numerical analysis that studies the numerical solution of partial differential equations (PDEs). In principle, specialized methods for hyperbolic, parabolic or elliptic partial differential equations exist. Finite difference method In this method, functions are represented by their values at certain grid points and derivatives are approximated through differences in these values.

Numerical methods for ordinary differential equations

Numerical methods for ordinary differential equations are methods used to find numerical approximations to the solutions of ordinary differential equations (ODEs). Their use is also known as "numerical integration", although this term can also refer to the computation of integrals. Many differential equations cannot be solved exactly. For practical purposes, however – such as in engineering – a numeric approximation to the solution is often sufficient. The algorithms studied here can be used to compute such an approximation.

Numerical stability

In the mathematical subfield of numerical analysis, numerical stability is a generally desirable property of numerical algorithms. The precise definition of stability depends on the context. One is numerical linear algebra and the other is algorithms for solving ordinary and partial differential equations by discrete approximation. In numerical linear algebra, the principal concern is instabilities caused by proximity to singularities of various kinds, such as very small or nearly colliding eigenvalues.

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