• Journal of Fashion Business
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• v.15 no.3
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• pp.97-111
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• 2011

This study aims to apply 3D virtual fabric parameters - as obtained from previous research experiments - to 3D virtual clothing simulation in comparing its similarity with actual clothing as worn, with a view to verifying the objectivity and validity of the 3D virtual fabric simulation method devised by the drape image analysis method. In addition, the result is intended to be used as the basic data for new 3D virtual clothing simulation methods. As the results, 3D virtual fabric parameters designed to simulate 3D drape to be similar to actual fabrics were found to be Bending Strength, Buckling Point, Density, Particle Distance, and Shear. They were also found to be important measurements when evaluating visual similarity between drape shadow images and number of nodes. 3D virtual fabric simulation method devised by the drape image analysis method was appropriate in extracting 3D fabric parameters with the reflection of actual fabrics' physical and dynamic characteristics, in connection with 3D virtual fabric simulation. 3D virtual fabric parameters with the reflection of actual fabrics' physical and dynamic characteristics using the proposed 3D virtual fabric simulation method are accumulated and provided as a standard, this will facilitate the introduction 3D virtual fabric simulation technology.

• Journal of the Korean Society of Clothing and Textiles
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• v.45 no.6
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• pp.978-985
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• 2021

This study aims to propose a prediction model for the drape coefficient using artificial neural networks and to analyze the nonlinear relationship between the drape properties and physical properties of fabrics. The study validates the significance of each factor affecting the fabric drape through multiple linear regression analysis with a sample size of 573. The analysis constructs a model with an adjusted R² of 77.6%. Seven main factors affect the drape coefficient: Grammage, extruded length values for warp and weft (m_warp, m_weft), coefficients of quadratic terms in the tensile-force quadratic graph in the warp, weft, and bias directions (c_warp, c_weft, c_bias), and force required for 1% tension in the warp direction (f_warp). Finally, an artificial neural network was created using seven selected factors. The performance was examined by increasing the number of hidden neurons, and the most suitable number of hidden neurons was found to be 8. The mean squared error was .052, and the correlation coefficient was .863, confirming a satisfactory model. The developed artificial neural network model can be used for engineering and high-quality clothing design. It is expected to provide essential data for clothing appearance, such as the fabric drape.

• Proceedings of the Korean Fiber Society Conference
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• 2001.04a
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• pp.257-260
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• 2001

• Journal of the Korean Society of Clothing and Textiles
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• v.19 no.4
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• pp.684-695
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• 1995

The purpose of this study was to investigate the influence of the mechanical properties on drapability in the peach skin-like finished fabrics. For this study, the samples used were 50 kinds of peach skin-like finished fabrics. The mechanical properties such as tensile, shearing, bending, compressional, surface characteristic values, thickness and weight were measured with a KES-F system and drupe coefficient by drape tester. The relationship between the characteristic values and drape coefficicients of the peach skin-like finished fabrics results were obtained. 1. Peach skin-like finished fabric had $\pm$2o range of shearing, bending, compression, surface. properties, thickness and weight as compared with Japanese women's thin fabrics. The characteristic mixing values were better with the values of WC/T, W/T, etc. as compared with that of japanese women's thin fabrics. Accordingly, the peach skin-like finished fabrics had a little volume, excellent hanging and drapability as compared with japanese women's thin fabrics. 2. The drape coefficient of peach skin-like finished fabric had a high level of correlation between 2HB, G, WC, MIU, WT, MMD, 2HG, RT, W, B etc. of the mechanical properties. The blocked properties that contributed to the drape coefficient of peach skin-like finished fabrics were in the order of the bending> tensile> thickness> weight properties. This drape coefficients(DC) were found by measuring the mechanical properties according to the obtained regress on equate on. DC=99.0179+17.9023 log G -17.0543 log 2HG5+17.2104 log 2HG+35.7685 log 2HB+ 4.6082 log B-30.5906 log T+4.2308 log W 3. The contribution to the drape coefficient of the characteristic mixing values of peach skin-like finished fabric was in the order of > 2HB/W> 2HB/B> B/W The drape coefficients were found by measuring the characteristic mixing values according to the obtained regression equation. 4. The drape coefficients of peach skin-like finished fabrics were influenced by the differences between the bending of warp direction, bending of weft direction, shearing etc which in turn determine the level of hanging. The regression equation was as follows; 5. The drape coefficients of peach skin.like finished fabrics had a highly positive correlation with the node index. It has an negative correlation with number of nodes.

• Fashion & Textile Research Journal
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• v.23 no.5
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• pp.645-654
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• 2021

This study aimed to visually compare the implementation of digital virtual fabrics for stretch fabrics mainly used in clothing that closely touch the body, using CLO. A digital fabric was used in CLO after measuring the weight, thickness, bending, and tensile force of five adhering clothing fabrics using a CLO fabric kit. The visual similarity of draftability was compared by measuring the area of the bending angle and the shape of the wrinkles of the real and digital fabric. A comparison of the bending angles showed that Fabric A was -0.75° and Fabric D was -2.5°, showing slightly lower drape properties than the real fabric. Meanwhile, Fabric B was 2.75°, Fabric C was 2.13°, and Fabric E was 1.375°, showing slightly higher drape properties in the vertical direction than the real fabric. Comparing the widths of the drape shapes, Fabric A was 0.77%, Fabric B was 1.27%, Fabric C was 0.06%, and Fabric E was 1.48%, which showed a slight difference. Fabric D showed a difference of 3.17% and was implemented where the digital fabric spread a little wider. As a result, the stretch fabric was visually expressed similarly to the real fabric as a whole in CLO. For 3D virtual clothing technology to be used widely in the close clothing industry in the future, more research on real clothing is needed.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2004.11a
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• pp.40-40
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• 2004

• Proceedings of the Korean Fiber Society Conference
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• 1998.10a
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• pp.290-294
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• 1998

Colour tone, lustre, surface roughness of fabrics are very important factors in pursue of the beauty of external appearance, namely aesthetic appearance, and the dynamic functionality of fabric used to clothe the human body. Drape is one of many factors that influence the aesthetic appearance of fabric and has an outstanding effect on the formal beauty of fabric. For this reason, the measurement and understanding of drape is required to specify the performance of fabric used in clothing. (omitted)

• Fibers and Polymers
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• v.4 no.4
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• pp.169-175
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• 2003

A simulation system for versatile garment drape has been developed. Using this system, the shape of a garment can be simulated in consideration of fabric physical properties as well as the interaction between fabrics and other objects. Each fabric piece in a garment is modeled using a geometrically constrained particle system and its behavior is calculated from an implicit numerical integration algorithm in a relatively short time. The system consists of three modules including a preprocessor for the preparation of fabric patterns and external objects, a postprocessor for the results of three-dimensional visualization, and a drape simulation engine. It can be used for the design process of textile goods, garments, furniture, or upholsteries.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.401-405
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• 2006

A uniform velocity field of crust can be obtained by cumulative multi-year GPS data. Then the shortening and sliding of drape zones between Chinese Continent Blocks can be researched through the velocity field and dynamics meaning is also analyzed. A model of movement and strain is created to extract displacing and rotating information of blocks in this paper. On the basis of it, the shortening vectors and sliding states of drape zones between blocks can be obtained by the model of level center of gravity moving velocity vectors between neighboring blocks. Some result show as follows. India plate jostles greatly toward north, so a complicated movement situation is formed for 14 sub-blocks. And self-deformations of inner tectosomes can be greatly reflected according to the characteristics of drape zones between tectosomes. The extrusion deformation exists between Himalaya and Qiangtang blocks. Its contraction ratio is about 20.1 $mm.a^{-1}$. However, it only is $mm.a^{-1}$ between Tarim and Zhungar. The deformation characteristics and contraction ratio of other drape zones are obviously different with the former. The movement characteristics of contraction, shear, dislocation, etc. are showed in these zones. The average contraction ratio is about 5.0 $mm.a^{-1}$. The whole trend in the west continent has a big movement toward north, and in the east continent has a small movement toward south or southeast. The strain of west continent is far bigger than that of east, and the strain of southwest is bigger than that of the southeast. It is whole showed that India plate jostles toward north-east and the south-north zone has cutting and absorbing phenomena. The total characteristics and present-day trends of deformation of inland drape zones are basically described by the sinistrorse dislocation in south-north zone and Arjin fracture, the sinistrorse shear between south china and north china, etc.

• Journal of the Korea Computer Graphics Society
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• v.29 no.3
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• pp.117-125
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• 2023

In the development of clothing design through virtual simulation, it is essential to minimize the differences between the virtual and the real world as much as possible. The most critical task to enhance the similarity between virtual and real garments is to find simulation parameters that can closely emulate the physical properties of the actual fabric in use. The simulation parameter optimization process requires manual tuning by experts, demanding high expertise and a significant amount of time. Especially, considerable time is consumed in repeatedly running simulations to check the results of applying the tuned simulation parameters. Recently, to tackle this issue, artificial neural network learning models have been proposed that swiftly estimate the results of drape test simulations, which are predominantly used for parameter tuning. In these earlier studies, relatively simple linear stiffness models were used, and instead of estimating the entirety of the drape mesh, they estimated only a portion of the mesh and interpolated the rest. However, there is still a scarcity of research on non-linear stiffness models, which are commonly used in actual garment design. In this paper, we propose a learning model for estimating the results of drape simulations for non-linear stiffness models. Our learning model estimates the full high-resolution mesh model of drape. To validate the performance of the proposed method, experiments were conducted using three different drape test methods, demonstrating high accuracy in estimation.