Draped Fabric Research Articles

Modeling of the draping textile on a curved surface

sThis paper presents algorithm for draping 2D textile fabric on curved surface. Using computer analyze to predicting strength and stiffness of textile reinforced composite details allows to achieve better characteristics of received parts. Part of this task is stacking initial cloth on the surface. Modeling of draped fabrics on surface produced by representation initial cloth by pin-jointed net model, which are describes position of each thread. This algorithm also provides to analyses angles between each pair of threads in considered object. It is used to find areas with critical tension, or places of formation of folds of fabrics. In this paper threads of fabrics are inextensibility.

Generating three-dimensional drape model based on projection and mesh deformation

In order to generate the three-dimensional (3D) mesh of draped fabric based on a two-dimensional (2D) fabric projection, the 3D point cloud of draped fabric was scanned via a self-built 3D scanning device followed by triangulation. The 3D boundary of fabric drape model and the two-dimensional contour of the projection of the fabric drape model were extracted respectively. Two neural networks were constructed to bridge the 2D fabric drape projection and the 3D boundary of draped fabric. With the trained neural networks, the 3D boundary of draped fabric could be inferred by merely referring a 2D projection of draped fabric. Six reference triangular meshes with different triangle density were generated. Driven by two mesh deformation methods, Laplacian deformation and Poisson deformation, the reference mesh was deformed into 3D mesh similar to scanned fabric drape models (meshes). The result shows that the generated models have a high agreement with the scanned meshes. In addition, the Laplacian deformation outperforms Poisson deformation in generating 3D fabric drape models.

Predicting the bending rigidity and shearing stiffness of fabric based on three-dimensional drape model

In this paper, the problem of inferring fabric mechanical properties based on three-dimensional (3D) fabric drape model and fabric weight was studied. Firstly, the three-dimensional point cloud of draped fabric was scanned via a self-built three-dimensional scanning device followed with triangulation. Then the local linear embedding (LLE) algorithm was used to resample the three-dimensional draped models (triangular meshes). Besides, all meshes resampled with the same uniform discrete points have the same triangular topology (vertex number and triangle index). Thirdly, the distribution function of curvature (DFC) of resampled 3 D mesh was extracted. At last, four neural networks with the combination of fabric weight and DFC as input were constructed to predict the bending rigidity and shearing stiffness separately. The result shows that the correlation coefficient between true warp bending rigidity and predicted result could reach 0.925. The correlation coefficient between true warp shearing stiffness and the predicted result is 0.7953. The correlation coefficient between true weft bending rigidity and the predicted result is 0.857. The correlation coefficient between true weft shearing stiffness and the predicted result is 0.605.

Draping woven sheets

Motivated by the manufacture of carbon fibre components, this paper considers the smooth draping of loosely woven fabric over rigid obstacles, both smooth and nonsmooth. The draped fabric is modelled as the continuum limit of a Chebyshev net of two families of short rigid rods that are freely pivoted at their joints. This approach results in a system of nonlinear hyperbolic partial differential equations whose characteristics are the fibres in the fabric. The analysis of this system gives useful information about the drapability of obstacles of many shapes and also poses interesting theoretical questions concerning well-posedness, smoothness and computability of the solutions. doi:10.1017/S144618112000019X

DRAPING WOVEN SHEETS

AbstractMotivated by the manufacture of carbon fibre components, this paper considers the smooth draping of loosely woven fabric over rigid obstacles, both smooth and nonsmooth. The draped fabric is modelled as the continuum limit of a Chebyshev net of two families of short rigid rods that are freely pivoted at their joints. This approach results in a system of nonlinear hyperbolic partial differential equations whose characteristics are the fibres in the fabric. The analysis of this system gives useful information about the drapability of obstacles of many shapes and also poses interesting theoretical questions concerning well-posedness, smoothness and computability of the solutions.

Filling the binary images of draped fabric with pix2pix convolutional neural network

To fill the binary image of draped fabric into a comparable grayscale image with detailed shade information, the three-dimensional point cloud of draped fabric was obtained with a self-built three-dimensional scanning device. The three-dimensional point cloud of drape fabric is encapsulated into a triangular mesh, and the binary and grayscale images of draped fabric were rendered in virtual environments separately. A pix2pix convolutional neural network with the binary image of draped fabric as input and the grayscale image of draped fabric as output was constructed and trained. The relationship between the binary image and the grayscale image was established. The results show that the trained pix2pix neural network can fill unknown binary top view images of draped fabric to grayscale images. The average pixel cosine similarity between filling results and ground truth could reach 0.97.

Automated detection of yarn orientation in 3D-draped carbon fiber fabrics and preforms from eddy current data

Abstract Ensuring the correct fiber orientation in draped textiles and 3D preforms is one of the current challenges in the production of carbon-fiber reinforced plastics (CFRP), especially in resin transfer molding (RTM). Small deviations in fiber angle during preforming have a considerable effect on the mechanical properties of the final composite. Therefore, this paper presents an automated method for determining local yarn orientation in three-dimensionally draped, multi-layered fabrics. The draped fabric is scanned with a robot-guided high-frequency eddy current sensor to obtain an image of the sample's local conductivity and permittivity. From this image, the fiber orientation not only of the upper, but also of the lower, optically non-visible layers can be analyzed. A 2D Fast Fourier Transform is applied to local segments of the eddy current image to determine the local yarn orientation. Guidelines for processing the eddy current data, including phase rotation, filtering and evaluation segment size, are derived. For an intuitive visualization and analysis of the determined yarn orientation, reference yarn paths are reconstructed from the determined yarn angles. The developed process can be applied to quality inspection, process development and the validation of forming simulation results.

Can you see what you feel? Color and folding properties affect visual-tactile material discrimination of fabrics.

Humans can often estimate tactile properties of objects from vision alone. For example, during online shopping, we can often infer material properties of clothing from images and judge how the material would feel against our skin. What visual information is important for tactile perception? Previous studies in material perception have focused on measuring surface appearance, such as gloss and roughness, and using verbal reports of material attributes and categories. However, in real life, predicting tactile properties of an object might not require accurate verbal descriptions of its surface attributes or categories. In this paper, we use tactile perception as ground truth to measure visual material perception. Using fabrics as our stimuli, we measure how observers match what they see (photographs of fabric samples) with what they feel (physical fabric samples). The data shows that color has a significant main effect in that removing color significantly reduces accuracy, especially when the images contain 3-D folds. We also find that images of draped fabrics, which revealed 3-D shape information, achieved better matching accuracy than images with flattened fabrics. The data shows a strong interaction between color and folding conditions on matching accuracy, suggesting that, in 3-D folding conditions, the visual system takes advantage of chromatic gradients to infer tactile properties but not in flattened conditions. Together, using a visual-tactile matching task, we show that humans use folding and color information in matching the visual and tactile properties of fabrics.

Unidirectional Fabric Drape Testing Method

In most cases, fabrics such as curtains, skirts, suit pants and so on are draped under their own gravity parallel to fabric plane while the gravity is perpendicular to fabric plane in traditional drape testing method. As a result, it does not conform to actual situation and the test data is not convincing enough. To overcome this problem, this paper presents a novel method which simulates the real mechanical conditions and ensures the gravity is parallel to the fabric plane. This method applied a low-cost Kinect Sensor device to capture the 3-dimensional (3D) drape profile, thus we obtained the drape degree parameters and aesthetic parameters by 3D reconstruction and image processing and analysis techniques. The experiment was conducted on our self-devised drape-testing instrument by choosing different kinds of weave structure fabrics as our testing samples and the results were compared with those of traditional method and subjective evaluation. Through regression and correlation analysis we found that this novel testing method was significantly correlated with the traditional and subjective evaluation method. We achieved a new, non-contact 3D measurement method for drape testing, namely unidirectional fabric drape testing method. This method is more suitable for evaluating drape behavior because it is more in line with actual mechanical conditions of draped fabrics and has a well consistency with the requirements of visual and aesthetic style of fabrics.

A mesoscopic model for coupled drape-infusion simulation of biaxial Non-Crimp Fabric

Modelling fabric draping can be performed using simplified mapping or more detailed finite element methods that allow greater accuracy and features such as tooling, blankholders and friction to be included. The materials laws, however, invariably treat the fabric as a homogenized continuum in which stretch, shear and bending stiffness are calibrated against coupon fabric tests. Certain fabrics such as stitched Non-Crimp Fabrics (NCFs) are particularly difficult to characterize using this macro approach since important deformation mechanisms occur at the tow and stitch (meso) level. Consequently, a meso-scale modelling methodology for drape of NCF is presented that allows individual tow and stitch deformations and their interaction. The approach uses deliberately coarse modelling so that structural scale problems may be tackled. A further aim is subsequent coupling of results to a meso-scale resin infusion simulation of the draped fabric. Experimental testing at the tow and fabric levels provides necessary fabric deformation and permeability data to calibrate the models. One aim of the work is to develop a methodology for coupled drape and infusion simulation at the meso-scale. It is recognized some aspects still require improvement; never-the-less the studies presented and a final validation study for draping of a hemisphere and coupled infusion simulation have provided encouraging results compared to test measurements.

Shadow Moiré aided 3-D reconstruction of fabric drape

The existing standard test method assesses draped fabrics two-dimensionally. In this study, a novel method is introduced to analyze and quantify fabric drapes in 3-D by using shadow moire method. Six different woven fabrics with dissimilar drape behaviors have been analyzed. A drape index has been mathematically derived from the moire patterns employing the shadow moire topography technique. The results have been compared with the standard drape coefficient. The 3-D profile of fabrics has been graphically formed and displayed applying the moire fringes’ data.

An investigation of the assessment of fabric drape using three-dimensional body scanning

This investigation explores how information on air gaps obtained from three-dimensional (3D) body scanning can be used to evaluate the drape of fabrics. Three-dimensional images of draped fabrics differing in physical and mechanical properties were acquired through 3D body scanning and the air gap distances and distribution between the outside edge of a cylinder and the fabric determined. Results demonstrate an inverse relationship between the overall average air gap distance and the amount of fabric drape. Findings were also compared to drape data obtained from the traditional cantilever and drapemeter methods. Not only does the 3D body scanning approach provide a measure of the degree of fabric drape but can also provide a more complete description of drape compared to traditional methods, as information about a fabric's draped appearance along the entire length of the fabric can also be obtained.

Modeling and Identifying the Parameters of a Fabric Drape Model

This paper presents a draped fabric model and identification methods for obtaining unknown parameters of the model. In the first part of this paper, we present a summary of previous works that have contributed to scientific advances in this topic. We then detail the mathematical model developed to simulate the dynamic behavior of a draped fabric. The second part is entirely devoted to identifying the parameters of this model, and its principal objective is to show that it is possible to obtain these parameters by means of tests that are currently used in the textile field. Finally, we present several simulations of a draped fabric, taking into account the model and the parameters obtained in practice.

Experimental studies and analysis of the draping of woven fabrics

This study investigates and compares the draping and forming of four types of woven fabrics, namely a loose plain weave (basket weave), a tight plain weave, a satin and a twill weave. The fabrics were draped over a hat mould consisting of a hemispherical dome surrounded by a flat base. The draping of each fabric was examined in terms of wrinkle formation, boundary profile of the draped fabric, distribution of fibre orientation and local shear angles. A theoretical analysis of the experimental results involved the calculation of the distributions of the fibre volume fraction and mechanical properties, in terms of components of the reduced stiffness matrix, from the experimental data of local shear angles.

The Shape of Nodes in Three-Dimensional Drape of Fabrics

The circular fabric specimen drapes three-dimens ionaliy into several pleats or nodes . The significance of the number and shape of nodes relates to some aesthetic criteria. This paper discusses theoretically and experimentally that the shape factor of the nodes depends upon the ratio of the specimen diameter to the diameter of a circle equal in area to the figure enclosed by the draped fabric hem .It has been ascertained by the subjective evaluation that the difference between the theoretical and experimental values of shape factor represents the uniformity of the distribution of nodes and the aesthetic appearance of draped fabrics.