Literature DB >> 34300893

Bounding the Multi-Scale Domain in Numerical Modelling and Meta-Heuristics Optimization: Application to Poroelastic Media with Damageable Cracks.

Albert Argilaga1, Efthymios Papachristos2.   

Abstract

It is very common for natural or synthetic materials to be characterized by a periodic or quasi-periodic micro-structure. This micro-structure, under the different loading conditions may play an important role on the apparent, macroscopic behaviour of the material. Although, fine, detailed information can be implemented at the micro-structure level, it still remains a challenging task to obtain experimental metrics at this scale. In this work, a constitutive law obtained by the asymptotic homogenization of a cracked, damageable, poroelastic medium is first evaluated for multi-scale use. For a given range of micro-scale parameters, due to the complex mechanical behaviour at micro-scale, such multi-scale approaches are needed to describe the (macro) material's behaviour. To overcome possible limitations regarding input data, meta-heuristics are used to calibrate the micro-scale parameters targeted on a synthetic failure envelope. Results show the validity of the approach to model micro-fractured materials such as coal or crystalline rocks.

Entities:  

Keywords:  FEM; Particle Swarm Optimization; asymptotic homogenization; constitutive law; in-simulatio; meta-heuristics; multi-scale; periodic micro-structure

Year:  2021        PMID: 34300893     DOI: 10.3390/ma14143974

Source DB:  PubMed          Journal:  Materials (Basel)        ISSN: 1996-1944            Impact factor:   3.623


  2 in total

1.  Calibration and Validation of a Linear-Elastic Numerical Model for Timber Step Joints Based on the Results of Experimental Investigations.

Authors:  Matthias Braun; Jan Pełczyński; Anna Al Sabouni-Zawadzka; Benjamin Kromoser
Journal:  Materials (Basel)       Date:  2022-02-22       Impact factor: 3.623

2.  Predicting the Non-Deterministic Response of a Micro-Scale Mechanical Model Using Generative Adversarial Networks.

Authors:  Albert Argilaga; Duanyang Zhuang
Journal:  Materials (Basel)       Date:  2022-01-26       Impact factor: 3.623

  2 in total

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