Head of Dept: Prof. Giulio Magli
Vice-Head of Dept: Prof. Gabriele Grillo
Department Manager: Dr.ssa Franca Di Censo

  About us…

  Today’s events 18 dicembre 2018

  • dec 18 tue 2018

    MOX Seminar
    Michele Botti, Advanced polyhedral discretization methods for poromechanical modelling,  12-18-2018, 14:00
    logo matematica
    MOX Numeth
    MOX Compgeo

    • MOX Seminar
    • Michele Botti
    • Université de Montpellier
    • Advanced polyhedral discretization methods for poromechanical modelling
    • Tuesday, 18 December 2018 at 14:00
    • Aula Seminari ‘Saleri’ VI Piano MOX-Dipartimento di Matematica, Politecnico di Milano – Edificio 14
    • Abstract
      During the talk, I will present analytical and numerical results for the (possibly nonlinear) coupled equations of poroelasticity describing the fluid flow in a deformable porous medium. We will focus on novel schemes based on a Hybrid High-Order discretization of the mechanics and a Symmetric Weighted Interior Penalty discontinuous Galerkin discretization of the flow. The method has several assets, including, in particular, the validity in two and three space dimensions, inf-sup stability, and the support of general polyhedral meshes, nonmatching interfaces, and arbitrary space approximation order. Our analysis delivers stability and error estimates that hold also when the constrained specific storage coefficient vanishes, and shows that the constants have only a mild dependence on the heterogeneity of the permeability coefficient. The performance of the method is extensively investigated on a complete panel of model problems using stress-strain laws corresponding to real materials. In the last part of the talk, we will consider the numerical solution of the poroelasticity problem with random physical coefficients in the context of uncertainty quantification. The uncertainty is modelled with a finite set of parameters with prescribed probability distribution. The approximation of the stochastic partial differential system is realized by non-intrusive techniques based on polynomial chaos decompositions. We will conclude by performing a sensitivity analysis to asses the propagation of the input uncertainty on the solutions considering application-oriented test cases.

    • Politecnico di Milano, Dipartimento di Matematica via Bonardi 9, 20133 Milano – Telefono: +39 02 2399 4505 – Fax: +39 02 2399 4568

Innovative Teaching


Mathematical Engineering
Educational Program

PhD School
Mathematical Models and Methods in Engineering

AIM Associazione degli Ingegneri Matematici
Associazione degli
Ingegneri Matematici