REVIEW OF MODELING AND SIMULATION OF VOID FORMATION IN LIQUID COMPOSITE MOLDING

空隙(复合材料) 复合数 材料科学 转移模塑 汽车工业 复合材料 造型(装饰) 毛细管作用 互连性 压缩成型 压实 机械 机械工程 工程类 计算机科学 模具 物理 人工智能 航空航天工程
作者
Aouatif Saad,Adil Echchelh,Mohamed Hattabi,Mohammed El Ganaoui
出处
期刊:Composites: mechanics, computations, applications [Begell House]
卷期号:9 (1): 51-93 被引量:5
标识
DOI:10.1615/compmechcomputapplintj.v9.i1.50
摘要

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.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
lllllcc完成签到,获得积分10
1秒前
2秒前
刘晓冉完成签到,获得积分10
2秒前
大G发布了新的文献求助10
4秒前
4秒前
sone给sone的求助进行了留言
4秒前
zwj发布了新的文献求助10
5秒前
6秒前
6秒前
6秒前
一一完成签到,获得积分20
7秒前
爱因斯坦刘刘完成签到,获得积分10
8秒前
朵朵发布了新的文献求助10
9秒前
董董的发布了新的文献求助10
9秒前
12秒前
LYQ完成签到 ,获得积分10
12秒前
稳重安蕾发布了新的文献求助30
13秒前
13秒前
虚心小凝完成签到 ,获得积分10
13秒前
所所应助科研通管家采纳,获得10
14秒前
14秒前
顺利完成签到,获得积分20
14秒前
无花果应助科研通管家采纳,获得10
14秒前
上官若男应助科研通管家采纳,获得10
14秒前
SciGPT应助科研通管家采纳,获得10
14秒前
李爱国应助科研通管家采纳,获得10
14秒前
年过半摆应助科研通管家采纳,获得10
14秒前
年过半摆应助科研通管家采纳,获得10
14秒前
CipherSage应助科研通管家采纳,获得10
14秒前
完美世界应助科研通管家采纳,获得10
14秒前
张欢馨应助科研通管家采纳,获得30
14秒前
李爱国应助科研通管家采纳,获得10
15秒前
无极微光应助科研通管家采纳,获得20
15秒前
搜集达人应助科研通管家采纳,获得10
15秒前
15秒前
15秒前
15秒前
15秒前
15秒前
15秒前
高分求助中
Overcoming Stigma and Bias in Obesity Management 1200
Signals, Systems, and Signal Processing 610
Software that combines deep learning,3D reconstruction and CFD to analyze the state of carotid arteries from ultrasound imaging 500
Bounds for Statistical Estimation in Semiparametric Models 500
Forced degradation and stability indicating LC method for Letrozole: A stress testing guide 500
Ideology and Meaning-Making under the Putin Regime 450
Adhesion Science: Principles & Practice 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6493379
求助须知:如何正确求助?哪些是违规求助? 8290746
关于积分的说明 17691768
捐赠科研通 5585554
什么是DOI,文献DOI怎么找? 2915624
邀请新用户注册赠送积分活动 1892723
关于科研通互助平台的介绍 1751145