Mass spring parameters identification for knitted fabric simulation based on FAST testing and particle swarm optimization
Autor: | Pedram Payvandy, Vajiha Mozafary |
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Rok vydání: | 2016 |
Předmět: |
Mass spring
010407 polymers Materials science Polymers and Plastics General Chemical Engineering Mass spring model Mesh networking Particle swarm optimization 020207 software engineering 02 engineering and technology General Chemistry 01 natural sciences 0104 chemical sciences Computer graphics Taguchi methods 0202 electrical engineering electronic engineering information engineering Elasticity (economics) Algorithm Simulation based |
Zdroj: | Fibers and Polymers. 17:1715-1725 |
ISSN: | 1875-0052 1229-9197 |
DOI: | 10.1007/s12221-016-6567-8 |
Popis: | In computer graphics, Mass-Spring model is used to obtain fast and visual results in physical simulations. A disadvantage of the method is to obtain accurate result because of the difficulty to define parameters of a Mass-Spring Model. Different works and results have been carried out to define model parameters. In this field, researchers have used optimization technique based on meta-heuristic method or applied fabric properties such as FAST and Kawabata test to determine model parameters. So far no research has been done using combination of two mentioned methods to recover mass spring parameters. Therefore; the purpose of this paper is to determine parameters of mass spring model applying Particle Swarm Optimization techniques and FAST test. For this point, the effective properties on fabric drape including stretch, shear, and bending properties are measured using the Fast System. Then, in order to reduce error value between simulated and actual fabric behavior, parameters of the mass spring model such as super elasticity rate, mesh topology and natural length of spring are optimized by applying the Particle Swarm Optimization (PSO). The PSO parameters are specified by using Taguchi Design of Experiment. Finally, fabrics drape are simulated in other situations and compared with its actual result to validate the model parameters. Results show that the optimized model is able to predict the drape behavior of knitted fabric with error value of 2.9 percent as compared with the real result. |
Databáze: | OpenAIRE |
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