A Sequential Global Programming Approach for Two-scale Optimization of Homogenized Multiphysics Problems with Application to Biot Porous Media

TL;DR

This paper introduces a sequential global programming method for optimizing microstructures in homogenized multiphysics problems, demonstrated on Biot poroelastic media, enabling efficient multi-microstructure design with minimal computational effort.

Contribution

The paper develops a novel optimization framework combining a precomputed database with sequential global programming for microstructure design in homogenized multiphysics models.

Findings

Efficient handling of multiple microstructure types with low computational cost.

Stable and low number of state problems needed for optimization.

Successful numerical experiments demonstrating the approach's effectiveness.

Abstract

We present a new approach and an algorithm for optimizing the material configuration and behaviour of a fluid saturated porous medium in a two-scale setting. The state problem is governed by the Biot model describing the fluid-structure interaction in homogenized poroelastic structures. However, the approach is widely applicable to multiphysics problems involving several macroscopic fields where homogenization provides the relationship between the microconfigurations and the macroscopic mathematical model. The optimization variables describe the local microstructure design by virtue of the pore shape which determines the effective medium properties - the material coefficients - computed by the homogenization method. The main idea of the numerical optimization strategy consists in a) employing a precomputed database of the material coefficients associated to the geometric parameters and b) applying the sequential global programming (SGP) method for solving the problem of macroscopically optimized distribution of material coefficients. Although there are similarities with the free material optimization (FMO) approach, only effective material coefficients are considered admissible, for which a well-defined set of corresponding configurable microstructures exist. Due to the flexibility of the SGP approach, different types of microstructures with fully independent parametrizations can easily be handled. The efficiency of the concept is demonstrated by a series of numerical experiments. We show that the SGP method can handle simultaneously multiple types of microstructures with nontrivial parametrizations using a considerably low and stable number of state problems to be solved.