Definition of Mass Spring Parameters for Knitted Fabric Simulation Using the Imperialist Competitive Algorithm

Author:

Mozafary Vajiha1,Payvandy Pedram1

Affiliation:

1. Iran, Yazd, University of Yazd, , Department of Textile Engineering

Abstract

The 3D simulation of fabrics is an interesting issue in many fields, such as computer engineering, textile engineering, cloth design and so on. Several methods have been presented for fabric simulation. The mass spring model, a typical physically-based method, is one of the methods for fabric simulation which is widely considered by researchers due to rapid simulation and being more consistent with reality. The aim of this paper is the optimization of mass spring parameters in the simulation of the drape behaviour of knitted fabric using the Imperialist Competitive Algorithm. First a mass spring model is proposed to simulate the drape behavior of knitted fabric. Then in order to reduce the error value between the simulated and actual result (reducing the simulation error value), parameters of the mass spring model such as the stiffness coefficient, damping coefficient, elongation rate, topology and natural length of the spring are optimized using the Imperialist Competitive Algorithm (ICA). The ICA parameters are specified using the Taguchi Design of Experiment. Finally fabrics drape shapes are simulated in other situations and compared with their actual results to validate the model parameters. Results show that the optimized model is able to predict the drape behavior of knitted fabric with an error value of 2.4 percent.

Publisher

Index Copernicus

Subject

Industrial and Manufacturing Engineering,General Environmental Science,Materials Science (miscellaneous),Business and International Management

Cited by 5 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

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