2007
DOI: 10.1088/0965-0393/15/2/006
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Identification of viscoplastic parameters of phenomenological constitutive equations for polymers by deterministic and evolutionary approach

Abstract: This study is concerned with the viscoplastic behaviour of polymers. A modified viscoplastic Bodner–Partom model was extended to include successively the post-yield (strain softening and strain hardening) and the pre-yield behaviour. In order to identify material parameters of the constitutive law, an analytical scheme and a numerical method based on evolutionary algorithms were developed. The capacity of the proposed viscoplastic approach is investigated for a representative glassy polymer (polycarbonate). Th… Show more

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Cited by 46 publications
(32 citation statements)
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“…A similar algorithm has been successfully applied in [18] for evaluation of Bodner-Partom model parameters for metals. The same universal methodology has been implemented to identification of the model parameters for polymers [13], textile fabric "Panama" and solid propellants [20]. Results presented in the next section reveal that it is also valid for investigated special granular structures.…”
Section: Modelling and Parameters Identificationmentioning
confidence: 97%
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“…A similar algorithm has been successfully applied in [18] for evaluation of Bodner-Partom model parameters for metals. The same universal methodology has been implemented to identification of the model parameters for polymers [13], textile fabric "Panama" and solid propellants [20]. Results presented in the next section reveal that it is also valid for investigated special granular structures.…”
Section: Modelling and Parameters Identificationmentioning
confidence: 97%
“…Since these nonlinear equations contain a lot of parameters, all ambiguity in identification result must be removed by a robust identification scheme. Considered in this paper analytical methodology of parameters identification is presented in details in [13]. A simplified schematic algorithm is presented in this section.…”
Section: Modelling and Parameters Identificationmentioning
confidence: 99%
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