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Composites: Mechanics, Computations, Applications: An International Journal

Publication de 4  numéros par an

ISSN Imprimer: 2152-2057

ISSN En ligne: 2152-2073

The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) IF: 0.2 To calculate the five year Impact Factor, citations are counted in 2017 to the previous five years and divided by the source items published in the previous five years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) 5-Year IF: 0.3 The Eigenfactor score, developed by Jevin West and Carl Bergstrom at the University of Washington, is a rating of the total importance of a scientific journal. Journals are rated according to the number of incoming citations, with citations from highly ranked journals weighted to make a larger contribution to the eigenfactor than those from poorly ranked journals. Eigenfactor: 0.00004 The Journal Citation Indicator (JCI) is a single measurement of the field-normalized citation impact of journals in the Web of Science Core Collection across disciplines. The key words here are that the metric is normalized and cross-disciplinary. JCI: 0.08 SJR: 0.153 SNIP: 0.178 CiteScore™:: 1 H-Index: 12

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PERMEABILITY IDENTIFICATION FOR A FIBER-REINFORCED COMPOSITE BY INVERSE ANALYSIS

Volume 7, Numéro 1, 2016, pp. 81-93
DOI: 10.1615/CompMechComputApplIntJ.v7.i1.60
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RÉSUMÉ

The permeability of textile reinforcements is a crucial input to the simulation of a composite material process. In this paper, we present an accurate simulation approach for identifying fiber reinforcement permeability in the resin transfer moulding (RTM) process. The Gauss−Newton− Levenberg−Marquardt method was utilized to identify the permeabilities of fibrous reinforcement. Knowing the boundary conditions, the permeability can be deduced from pressure values at some given positions through the part. Starting from the initial estimate of permeability, the inverse method begins by solving the direct problem. The solution gives the pressure field everywhere in a composite sample. The calculated pressure field is then compared with an analytical pressure based on a criterion. The permeability is modified iteratively so as to minimize this criterion until the desired accuracy is achieved. A comparison between experimental and the computed parameters is used as convergence criteria in the iterative inverse technique, and good agreement is found.

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