Predicting thickness impregnation in a VaRTM resin flow simulation using machine learning-Reference-Cited by-同舟云学术

Predicting thickness impregnation in a VaRTM resin flow simulation using machine learning

Published:2021-07 Issue: Volume:5 Page:100158
ISSN:2666-6820
Container-title:Composites Part C: Open Access
language:en
Short-container-title:Composites Part C: Open Access

Author:

Matsuzaki Ryosuke,Morikawa Masato,Oikawa Yuya,Ushiyama Kengo

Funder

New Energy and Industrial Technology Development Organization

Publisher

Elsevier BV

Subject

Mechanical Engineering,Mechanics of Materials,Ceramics and Composites

Reference31 articles.

1. Use of resin transfer molding simulation to predict flow, saturation, and compaction in the VARTM process;Correia;J Fluids Eng,2004

2. Effect of convection coefficient and thickness on optimal cure cycles for the manufacturing of wind turbine components using VARTM;Struzziero;Compos Part A Appl Sci Manuf,2019

3. Advanced VARTM System for Aircraft Structures Materials Technologies;Kamae,2009

4. A-VARTM technology application for Japan's new regional jet aircraft;Shinoda;Fuel,2007

5. Research in the application of the VaRTM technique to the fabrication of primary aircraft composite structures;Takeda;Mitsubishi Heavy Ind Tech Rev,2005

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