Identification of Diffusion Properties of Polymer-Matrix Composite Materials with Complex Texture
Marianne Beringhier (),
Marco Gigliotti () and
Paolo Vannucci ()
Additional contact information
Marianne Beringhier: University of Poitiers
Marco Gigliotti: University of Poitiers
Paolo Vannucci: University of Versailles Saint Quentin
Journal of Optimization Theory and Applications, 2020, vol. 184, issue 1, No 10, 188-209
Abstract:
Abstract The paper deals with the identification of three-dimensional anisotropic diffusion properties of polymer-matrix composite materials with complex texture, based on the exploitation of short-time gravimetric tests. According to the Thermodynamics of Irreversible Processes, the diffusion behavior can be isotropic or orthotropic: for many materials, due to the complexity of the microscopic texture, the principal directions of orthotropy are not known a priori and enter the identification issue. After reviewing some identification methods (proper generalized decomposition) for isotropic and orthotropic material whose orthotropy directions are known, the paper proposes an experimental protocol and an identification algorithm for the full three-dimensional diffusion case, aiming at establishing the 3 coefficients of diffusion along the principal directions of orthotropy and the orientation of the orthotropic reference frame with respect to the sample frame. The identification of the physical properties is done through the minimization of a distance in the space of the physical parameters. The problem being non-convex, the numerical strategy used for the search of the global minimum is a particle swarm optimization, the code adaptive local evolution-particle swarm optimization with adaptive coefficients.
Keywords: Identification; Diffusion behavior; Optimization method; PGD; ALE-PSO; 80A23; 45Q05; 35R30; 80M50; 90C31; 46N10 (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s10957-019-01602-y Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:joptap:v:184:y:2020:i:1:d:10.1007_s10957-019-01602-y
Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10957/PS2
DOI: 10.1007/s10957-019-01602-y
Access Statistics for this article
Journal of Optimization Theory and Applications is currently edited by Franco Giannessi and David G. Hull
More articles in Journal of Optimization Theory and Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().