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International Journal for Multiscale Computational Engineering
Impact-faktor: 1.016 5-jähriger Impact-Faktor: 1.194 SJR: 0.554 SNIP: 0.82 CiteScore™: 2

ISSN Druckformat: 1543-1649
ISSN Online: 1940-4352

International Journal for Multiscale Computational Engineering

DOI: 10.1615/IntJMultCompEng.2020032669
pages 141-157


Giovanni Formica
Dipartimento di Architettura, University of Roma Tre, Rome, 00181, Italy
Franco Milicchio
Dipartimento di Ingegneria, University of Roma Tre, Rome, 00146, Italy
Walter Lacarbonara
Dipartimento di Ingegneria Strutturale e Geotecnica, Sapienza University of Rome, Rome, 00184, Italy


Optimization of the storage modulus and the hysteretic damping capacity of multilayer carbon nanotube (CNT) nanocomposites is carried out via a differential evolution algorithm coupled with a nonlinear finite element implementation of a 3D mesoscale theory of nanocomposites exhibiting CNT/polymer stick-slip behavior. Such constitutive theory describes the hysteresis due to the shear stick-slip between the carbon nanotubes and the long molecular chains of the hosting matrix wrapped around them. The storage modulus and the amount of energy dissipated through the CNT-matrix stick-slip depend on the nanocomposite microstructural parameters, such as the elastic mismatch, the nanofiller content, its distribution, and the CNT-matrix interfacial shear strength. The optimization problem seeks to determine the set of material parameters of a multilayer stacking sequence that can give rise to the largest storage modulus and damping capacity of the ensuing nanocomposite. The results confirm that the genetic-type multilayer nanocomposite damping optimization resorting on a sound mechanical model of the nonlinear hysteretic material response can be an effective and affordable design method.


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