Search

Edge curling is a unique property of knitted fabrics which affects on fashion such as using upper and side curling in cloth design. The purpose of this research is to present a new method to simula...

Purpose Fabric-object friction force is a fundamental factor in cloth simulation. A large number of parameters influence the frictional properties of fabrics such as fabric structure, yarn structure, and inherent properties of component fibers. The purpose of this paper is to propose a novel technique for modeling fabric-object friction force in knitted fabric simulation based on the mass spring model. Design/methodology/approach In this technique, unlike other studies, distribution of friction coefficient over the fabric surface is not uniform and depends on the fabric structure. The main reason for considering non-uniform distribution is that in various segments of fabric, contact percent of fabric-object is different. Findings The proposed technique and common methods based on friction coefficient uniform distribution are used to simulate the frictional behavior of knitted fabrics. The results show that simulation error values for proposed technique and common methods are 2.7 and 9.4 percent as compared with the experimental result, respectively. Originality/value In the existing methods of the friction force modeling, the friction coefficient of fabric is assumed uniform. But this assumption is not correct because fabric does not have an isotropic structure. Thus in this study, the friction coefficient distribution is considered based on fabric structure to achieve more of realistic simulations.

In this paper, a mass spring system is developed to simulate the draping behavior of knitted fabric. A new type of mesh based on loop structure, which is called Loop mesh, is introduced. The effective properties on fabric drape are measured using the Fast system, and the experimental data are incorporated into the mass spring model to simulate the draping behavior of knitted fabrics. 3D shape of real drape behavior of fabric samples is achieved using depth camera. Then in order to reduce error value between simulated and real results, distances between mass points in the Loop mesh are optimized using the Imperialistic Competitive Algorithm (ICA). In order to investigate validity and accuracy of the Loop mesh, drape behavior of knitted fabrics falling over a square table are also simulated using common meshes. It can be found that the Loop mesh produced a closest drape shape to the real fabric drape than other mesh models. Finally, fabrics drape is simulated in other situations and compared with it...

Fabric simulation is result of combining various methods that have been dramatically evolved during the decade. However, there still exist some limitations. One of the limitations in fabric simulation is lack of using fabric properties such as material, weave structure, density and so on in mass spring modeling. In knitted fabrics, this issue is more important due to their different fabric structures. In this paper, a new mesh based on loop shape for simulating 1×1 rib fabric is proposed which is called Loop mesh. By using the Loop and common meshes, 3D model of drape behavior in 18 types of knitted fabric are simulated. Results of simulation are compared with 3D shape of actual drape behavior in fabric samples which are achieved by depth camera. Results show that the Loop mesh is able to predict the drape behavior of knitted fabric with error value of 5 percent as compared with the real result. It can be found that the Loop mesh produced a closest drape shape to the actual fabric drape than other mesh models.

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.

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.