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Composites: Mechanics, Computations, Applications: An International Journal

Publicou 4 edições por ano

ISSN Imprimir: 2152-2057

ISSN On-line: 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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REVIEW OF MODELING AND SIMULATION OF VOID FORMATION IN LIQUID COMPOSITE MOLDING

Volume 9, Edição 1, 2018, pp. 51-93
DOI: 10.1615/CompMechComputApplIntJ.v9.i1.50
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RESUMO

Liquid composite molding (LCM) processes are being used in manufacturing near-net-shape, geometrically complex composite parts. One of the current obstacles to a larger scale application of these processes is the formation of defects such as voids during resin injection. To reach aeronautic requirements or short injection cycles in the automotive industry, entrapped air in the final part before curing has to remain as low as possible. Air entrapment will depend on the fibrous structure and on the injection parameters, or more precisely on the fluid pressure and the flow front orientation with respect to the fibrous direction. A key parameter for production of structural composite parts is air entrapment, since high void content could lead to mechanical softening, early failure, or part rejection. The quantitative simulation of the void formation is important for proper design and selection of material and processing parameters to minimize such voids in the composite materials. Despite several advancements in voidage predictions via modeling and simulations, the void formation mechanisms in RTM and similar processes are still not fully understood. In this study, a review of current approaches to modeling and simulation of void formation and unsaturated flow in the liquid composite molding process is presented. We examine modeling efforts considering all the mechanisms involved such as void formation and transport, bubble compression, and gas dissolution. In particular, the capillary number is identified as a key parameter for void formation and transport. The influence of voids on the global resin flow is also investigated and a state-of-the-art is presented.

CITADO POR
  1. Seong Dong, Kim Shino, Lee Doojin, Yi Jin, Kim Sang, Kim Seong, Prediction of Defect Formation during Resin Impregnation Process through a Multi-Layered Fiber Preform in Resin Transfer Molding by a Proposed Analytical Model, Materials, 11, 10, 2018. Crossref

  2. Di Fratta Claudio, Sun Yixun, Causse Philippe, Trochu François, A Dimensionless Characteristic Number for Process Selection and Mold Design in Composites Manufacturing: Part I—Theory, Journal of Composites Science, 4, 1, 2020. Crossref

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