Computational optimization strategies for the simulation of random media and components

Computational optimization strategies for the simulation of random media and components

0.00 Avg rating0 Votes
Article ID: iaor20128216
Volume: 53
Issue: 3
Start Page Number: 903
End Page Number: 931
Publication Date: Dec 2012
Journal: Computational Optimization and Applications
Authors: ,
Keywords: heuristics, simulation
Abstract:

In this paper efficient computational strategies are presented to speed‐up the analysis of random media and components. In particular, a Hybrid Stochastic Optimization (HSO) tool, based on the synergy between various algorithms, i.e. Genetic Algorithms, Simulated Annealing as well as Tabu‐list is suggested to reconstruct a set of microstructures starting from probabilistic descriptors. The subsequent analysis (e.g. Finite Element analysis) can be performed to obtain the desired macroscopic quantity of interest and, providing a link between the micro‐ and the macro‐scale. Different computational speed‐up strategies are also presented. The proposed simulation approach is highly parallelizable, flexible and scalable. It can be adopted by other fields as well where an optimization analysis is required and a set of different solutions should be identified in order to perform computational experiments. Numerical examples demonstrate the applicability of the proposed strategies for realistic problems.

Reviews

Required fields are marked *. Your email address will not be published.