Search results

The purpose of this paper is to provide an efficient tool for simulating electrospinning process in virtual 3D space and optimizing experimental parameters. The fiber orientation from virtual or real electrospinning process can be easily measured using the image analysis technique. Using the semi-implicit Euler integration, the time integration can be more fast and stable, which enabled optimization of the electrospinning process. Also boundary conditions can be easily adopted during conjugate gradient matrix solving step.

To simulate the electrospinning process, the authors have adopted a particle-based modeling technique using the molecular dynamics theory, which is known to be suitable for modeling materials with nonlinear and nonhomogeneous behavior such as fibers or fabrics. Gravitational, tensional, and electrostatical forces and their Jacobians were carefully defined and chosen to maintain the stability of the governing equation. Preconditioned conjugate gradient method was used to solve the matrix iteratively with boundary conditions. The 2-D metaball fitting technique, which was applied in the previous research (Sul et al., 2009) on experimental nanofiber scanning electron microscopy images, was utilized with virtual nanofiber images. A staircase function and a new shading language were proposed to automatically calculate the orientation and radius distribution of the graphically simulated electrospun fiber structures. The automatic measurement procedure was verified via graphically designed virtual replica images. Also the orientation tendency acquired from the simulation was compared with that of experimental data.

Simulation result of fiber orientation showed linear relationship with the collecting drum speed. Use of particle-based method generated a simple system to simulate electrospinning process.

The semi-implicit Euler integration was applied to the electrospinning process and the final linear system was numerically stable to solve.

Examines the fifthteenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.

The purpose of this paper is to determine the possibility of implementing parallel processing feature of graphic processor unit (GPU) in garment drape simulation.

Velocity‐Verlet method based on explicit integration is used to drape triangular table cloth meshes. Both drape simulation and collision detection engines are converted to GPU version. Simulation speeds of simple linear algebra and actual free fall table cloth simulation are compared with those of the central processing unit (CPU) version.

There is apparent calculation speed increase when the parallel computation of GPU is implemented. But the current GPUs have several limits for general purpose computation, so the original CPU version algorithm should be split and modified to be used in GPU.

This paper implemented GPU parallel processing technique in both drape simulation and collision detection. Voxel‐based method is used to find possible collision pairs. Triangular meshes, which are more difficult to implement than quadrilateral ones in GPU programming, are successfully implemented.

Examines the fifteenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.

The designing and initial alignments of 2D garment patterns in 3D space are the key procedures in 3D apparel design. This paper presents a new methodology to prepare and edit initial pattern shape in 3D space by simulating virtual cloth scissoring.

In conventional apparel CAD tools, flat 2D patterns are drawn and sewn in 3D space. Thus, the final appearance of 3D garment cannot be easily predictable for non‐specialized personnel from the flat patterns. This paper adopts the real pattern designing method of “draping”, incorporating it into computer‐based designing so that the user can realistically cut, sew and add the cloth by only using a mouse. 2D and 3D meshes are edited simultaneously and thus a flattening process is not needed.

Several mesh‐based operations such as cutting, sewing, adding, and fixing are devised and have been successfully applied to virtual garment cutting.

Our new pattern drawing method has an advantage that designer can look and feel the garment appearance interactively during the design process. Virtual cutting is identical to the real pattern draping technique and is easy to adopt for designers.

With current computer hardware speed and through using the drape simulation technique, it was possible to drape and cut cloth in real‐time. In addition, both the 3D pattern and 2D flat pattern could be simultaneously acquired.

Pattern marking is the allocation of garment patterns on the cloth roll minimizing the fabric loss, and thus very important for the cost reduction in garment manufacturing industries. But automatic marking is very difficult because it is a non‐deterministic in polynomial time problem. Most previous pattern marking methods needed collision detection routine to lay out patterns without interfering each other, which was the bottle neck of nesting speed. In this study, rectilinear polygon approximation technique was used to reduce the overall calculation time because the garment patterns are usually in non‐convex shape that can effectively be approximated by rectangles. Additionally, we adapted stochastic simulated annealing to search the optimal pattern marking.

The purpose of this paper is to combine patterns from different garment sets and preview garment styles in 3D apparel design by giving sewing names to patterns and sewing edges.

A new rule for 3D garment sewing is made. Unlike conventional vertex number‐based method, patterns and their edges are given specific names. If two edges have a same edge name, they make a sewing line. Thus, patterns from different garments can be combined and draped with this method. Numbers of boundary mesh nodes were controlled using B‐Spline to combine sewing edges of different lengths.

It is found that by only assigning names to patterns and sewing edges, garment style can be previewed by substituting patterns.

Styles and details of garments can be previewed in 3D by mixing patterns of different garment sets like in 2D technical flat sketching. Even patterns with different edge lengths can be combined by controlling the pattern meshes using B‐Spline.

The purpose of this paper is to find automatic post‐processing scheme to give textures and motion data to three dimensional (3D) body scan data.

Semi‐implicit particle‐based method was applied to post‐processing of 3D body scan data. The template avatar mesh was draped onto the target scan data and the texture/motion data were transferred to regenerated body. Automatic body feature detection was used to correlate the template body with the target body.

Using semi‐implicit particle method, there are advantages in both computational stability and accuracy. The calculation is done in a few minutes and even data with many holes could be used.

There are several researches for body feature detection and scan body regeneration but this paper aims for fully automatic method which needs no human intervention. The semi‐implicit particle method, which is popularly used for cloth simulation, is applied to body data regeneration. The conventional 3D body scan data, which had no colors and motions can be given textures and motions with this approach. And even the face can be freely interchanged with the use of external face generation software.

The purpose of this paper is to illustrate the generation of basic garment pattern using three‐dimensional body measurement data.

A pre‐defined garment model is deformed using free‐form deformation method and the model is flattened to generate flat patterns.

The paper finds that individual basic garment patterns are automatically generated and verified to be well fit on human subjects.

The current approach is to focus on the generation of basic bodice patterns; however, other patterns can also be generated by this method by preparing more garment models.

This method can reduce the time required to design basic patterns as well as enhance their fitness.

The automatic generation of individually fitted garment pattern is one of the most important steps in future garment production process.

The purpose of this paper is to develop a new and simple methodology for fabric collision detection and response.

A 3D triangle‐to‐triangle collision problem was converted to simple 2D point‐in‐triangle problem using pre‐computed 4×4 transformation matrices. The object space was partitioned using voxels to find easily collision pair triangles. k‐DOP was used to find inter‐pattern collisions.

Complex 3D collision detection problem is solved by simple matrix operations. Voxel‐based space partitioning and k‐DOP‐based hierarchical methods are successfully applied to garment simulation.

This paper shows that the collision matrix method can cover from triangle‐to‐point to triangle‐to‐triangle collision with mathematical validity and can be simply implemented in garment simulation.