Creep Modeling for Injection-Molded Long-Fiber Thermoplastics

Author:

Nguyen Ba Nghiep1,Kunc Vlastimil2,Bapanapalli Satish K.1

Affiliation:

1. Pacific Northwest National Laboratory, Richland, WA

2. Oak Ridge National Laboratory, Oak Ridge, TN

Abstract

This paper proposes a model to predict the creep response of injection-molded long-fiber thermoplastics (LFTs). The model accounts for elastic fibers embedded in a thermoplastic resin that exhibits the nonlinear viscoelastic behavior described by the Schapery’s model. It also accounts for fiber length and orientation distributions in the composite formed by the injection-molding process. Fiber length and orientation distributions were measured and used in the analysis that applies the Eshelby’s equivalent inclusion method, the Mori-Tanaka assumption (termed the Eshelby-Mori-Tanaka approach) and the fiber orientation averaging technique to compute the overall strain increment resulting from an overall constant applied stress during a given time increment. The creep model for LFTs has been implemented in the ABAQUS finite element code via user-subroutines and has been validated against the experimental creep data obtained for long-glass-fiber/polypropylene specimens. The effects of fiber orientation and length distributions on the composite creep response are determined and discussed.

Publisher

ASMEDC

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A review of Long fibre thermoplastic (LFT) composites;International Materials Reviews;2019-03-11

2. Prediction of failure properties of injection-molded short glass fiber-reinforced polyamide 6,6;Composites Part A: Applied Science and Manufacturing;2013-09

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3