PLEASE SCROLL DOWN FOR ARTICLE This article was downloaded by: [North Carolina State University] On: 31 October 2008 Access details: Access Details: [subscription number 778556984] Publisher Taylor & Francis Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK Journal of the Textile Institute Publication details, including instructions for authors and subscription information: http://www.informaworld.com/smpp/title~content=t778164490 Enhancing accuracy of drape simulation. Part II: Optimized drape simulation using industry-specific software Pradeep Pandurangan a ; Jeffrey Eischen a ; Narahari Kenkare b ; Traci A. M. Lamar b a College of Engineering, North Carolina State University, Box 7910, Raleigh, NC b College of Textiles, North Carolina State University, Box 8301, Raleigh, NC First Published:June2008 To cite this Article Pandurangan, Pradeep, Eischen, Jeffrey, Kenkare, Narahari and Lamar, Traci A. M.(2008)'Enhancing accuracy of drape simulation. Part II: Optimized drape simulation using industry-specific software',Journal of the Textile Institute,99:3,219 — 226 To link to this Article: DOI: 10.1080/00405000701489198 URL: http://dx.doi.org/10.1080/00405000701489198 Full terms and conditions of use: http://www.informaworld.com/terms-and-conditions-of-access.pdf This article may be used for research, teaching and private study purposes. Any substantial or systematic reproduction, re-distribution, re-selling, loan or sub-licensing, systematic supply or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material.
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PLEASE SCROLL DOWN FOR ARTICLE
This article was downloaded by: [North Carolina State University]On: 31 October 2008Access details: Access Details: [subscription number 778556984]Publisher Taylor & FrancisInforma Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House,37-41 Mortimer Street, London W1T 3JH, UK
Journal of the Textile InstitutePublication details, including instructions for authors and subscription information:http://www.informaworld.com/smpp/title~content=t778164490
Enhancing accuracy of drape simulation. Part II: Optimized drape simulationusing industry-specific softwarePradeep Pandurangan a; Jeffrey Eischen a; Narahari Kenkare b; Traci A. M. Lamar b
a College of Engineering, North Carolina State University, Box 7910, Raleigh, NC b College of Textiles, NorthCarolina State University, Box 8301, Raleigh, NC
First Published:June2008
To cite this Article Pandurangan, Pradeep, Eischen, Jeffrey, Kenkare, Narahari and Lamar, Traci A. M.(2008)'Enhancing accuracy ofdrape simulation. Part II: Optimized drape simulation using industry-specific software',Journal of the Textile Institute,99:3,219 — 226
To link to this Article: DOI: 10.1080/00405000701489198
URL: http://dx.doi.org/10.1080/00405000701489198
Full terms and conditions of use: http://www.informaworld.com/terms-and-conditions-of-access.pdf
This article may be used for research, teaching and private study purposes. Any substantial orsystematic reproduction, re-distribution, re-selling, loan or sub-licensing, systematic supply ordistribution in any form to anyone is expressly forbidden.
The publisher does not give any warranty express or implied or make any representation that the contentswill be complete or accurate or up to date. The accuracy of any instructions, formulae and drug dosesshould be independently verified with primary sources. The publisher shall not be liable for any loss,actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directlyor indirectly in connection with or arising out of the use of this material.
1College of Engineering, North Carolina State University, Box 7910, Raleigh, NC, 27695-79102College of Textiles, North Carolina State University, Box 8301, Raleigh, NC, 27695-8301
Abstract: Three-dimensional virtual representations of fabrics are done based on mass-spring model-ing, which represents cloth as a mesh of particles connected by springs. The spring constant valuesinput to the model correspond to the mechanical properties of the modeled fabric. For apparel, theserepresentations have been incorporated into commercial software packages for use in design and devel-opment of garments. However, fabric mechanical property values as derived using industry test methodscannot be input directly into the commercial software to produce simulations that accurately representa specific fabric. A systematic way of selecting input parameters to a particle model was developedby comparing the drape of circular fabric samples whose mechanical properties were measured by theKawabata evaluation system to simulations produced by the particle model using methods developed inPart I of this paper. Also, a relationship was developed between measured fabric mechanical propertiesand simulation input parameters and then tested on simulations of apparel samples.
Key words: Simulation, fabric drape, particle model, 3D body scanner, garment drape.
INTRODUCTION
Accurate three-dimensional (3D) virtual representation offabric drape is a very effective tool for the textile industryand would greatly facilitate many aspects of business pro-cesses. At present, drape simulation technologies lack accu-racy in their representation of the diverse variety of apparelfabrics due to very little understanding of how variations infabric mechanical properties affect drape simulations. Sim-ulations based on particle models represent cloth as a meshof particles connected by springs. The springs exert forceson the particles causing them to move, thus representingthe deformation of fabric. The spring constant values inputto the model represent properties such as bending, stretch-ing, and shear stiffness of the simulated fabric. In the last
Corresponding author:Traci A. M. LamarCollege of Textiles Box 8301North Carolina State UniversityRaleigh, NC 27695-8301Tel: 919-513 4196; Fax: 919-515 3733Email: [email protected]
decade, commercial software based on this approach hasbecome available to garment producers. Such 3D drapemodeling software is gaining attention in the textile indus-try as a tool for design, development, merchandising, andvisualization of apparel.
The most well-known industry provider of software fortwo-dimensional and 3D CAD/CAM fashion design isOptiTex (Isaacs, 2005). OptiTex’s commercially availablecloth simulation software package, ModulateTM, is basedon an interacting particle modeling approach recently de-veloped by Choi and Ko (2002). This formulation wasinspired by, and is an extension of, the pioneering work ofBreen et al. (1994). ModulateTM allows users to input me-chanical properties of a fabric and simulate its drape overa simulated human form. By varying the mechanical prop-erties input to the software, the appearance of differentfabrics can be simulated. Simulations done by the particlemodel approach used in ModulateTM do not produce accu-rate representations of particular fabrics when mechanicalproperty values derived using the Kawabata evaluation sys-tem (KES) (Kawabata, 1980) are input directly, leading toan ad hoc selection of input parameters to make the simu-lation look more like the drape of a particular fabric. There
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is a need to avoid this nonsystematic selection of inputparameters. This paper presents a simple way of relat-ing fabric mechanical properties measured by conventionaltesting systems like the KES to input parameters requiredfor the particle model to produce realistic simulations. Thisrelationship was developed by comparing the drape of cir-cular fabric samples of various fabrics whose mechanicalproperties were measured by the KES to matching particlemodel simulations produced by ModulateTM. Since drapeis a complex function of many unpredictable variables, asimple way of varying only a few parameters in simula-tions without compromising their resemblance to realityhas been developed. Figure 1 is a flowchart describing theprocess of developing the relationship. Steps 1, 2, and 3in the flowchart were discussed in Part I of this two partpaper. This paper elaborates on steps 4, 5, and 6.
GENERATION OF SIMULATIONS FOR CIRCULARFABRIC SAMPLES
Many drape quantifying parameters for fabrics encom-passing a wide spectrum of properties were obtained fromdrape testing of circular fabric samples. The drape coeffi-cient (BS 5058: 1973; British Standard Institution, 1974b),the number of folds (nodes), and fold dimensions producedby each fabric during the variability tests described in PartI gave a clear idea of how each fabric draped in reality. Thenext step was to simulate the drape of a circular sample ofeach of those fabrics.
The ModulateTM software was used for generatingsimulations. The circular fabric sample simulations inModulateTM were done using the same dimensions as thoseused for fabric variability testing, that is a 36-cm diameterfabric sample draped over an 18-cm diameter surface. The18-cm virtual platform to support the simulated fabric sam-ples for virtual draping was generated by the researchersand imported into the ModulateTM software.
Through experimentation, it was discovered that par-ticle model drape simulations, like real fabrics, are mostsensitive to changes in the bending stiffness parameter.Hence, the effect of varying the bending stiffness on drapeshapes was studied by holding all except one of the otherparameters constant. The weight input to the simulationswas the actual value measured in the KES experiments.Matching simulations were performed for each fabric ofthe 14 fabrics investigated (refer to Part I) using inputparameters shown in Table 1.
By varying only the bending stiffness while keepingmost parameters constant, the task of selecting simulationinput parameters for each fabric was simplified. Further-more, there was no drop in the degree of resemblance ofa simulation to the actual drape by using this approach. Itshould be emphasized that the bending stiffness value mea-sured in the KES experiments does not produce correctdrape shapes when input directly as the bend parameterin ModulateTM. In fact, the key discovery in this researchwas the relationship between the bending stiffness of cloth
Table 1 Input parameters to modulate simulations
Parameter Value
Bending stiffness Variable (dyne-cm)Stretching stiffness X = 1,500, Y = 1,000 g/cmShear stiffness 300 dyne-cmDamping 0.01 cm/sShrinkage X = 0, Y = 0Weight From KES (g/m2)Resolution 1.5 cmFriction coefficient 0.25Thickness 0.05 cm
measured by KES and an appropriate bending parameterfor the particle model simulation to produce realistic sim-ulations. Figure 2 shows snapshots of the simulation of thedrape of a circular fabric sample using ModulateTM.
CRITERIA FOR COMPARING DRAPE SIMULATIONSWITH 3D SCANS
Variability tests discussed in Part I showed that fabricsexhibit wide variation in drape shape during repeated trials.The significant outcome of the variability tests was thedetermination that there can be no single target drape shapefor a simulation in order to conclude it matches the drape ofa real fabric. Instead, if a simulation falls within a region ofacceptance it can be accepted as a good match to an actualtarget drape. Hence, based on results of the variabilitytests, criteria were developed for determining whether asimulation was a good match to the actual drape of a fabric.The criteria were as follows:� The drape coefficient of the simulation must be within
±10% of the mean value obtained from the variabilitytests.
� The number of nodes in the simulation must equal thenumber of nodes observed in at least one of the 12 trialsdone for each fabric.
� The dimensions of the nodes (d1, d2, d3) of the simulationmust be within ±20% of the mean value obtained fromthe variability tests.
To push the simulations toward the typical behavior foreach fabric, criteria established for matching simulationand actual fabric were chosen to be more stringent thanthe variability exhibited by the draped fabrics. Unlike thevalues for real fabric drapes, simulation drape values donot vary when a simulation is generated repeatedly. Also,in generating simulations, the average values were targetedfor each fabric. When a simulation of a particular fabricsatisfied the above criteria, it was classified as a good rep-resentation.
TRANSLATING KES MEASUREMENTS TOMODULATETM INPUT PARAMETERS
One simulation satisfying the criteria was generated foreach of the fabrics whose mechanical properties were tested
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Figure 3 Plot of input to ModulateTM simulations versus KES bending stiffness.
using the KES. The simulations were input with param-eters shown in Table 1. Figure 3 is a plot of the bendingstiffness of the fabrics measured from the KES against thebending stiffness input to ModulateTM simulations. Eachof the data points in the plot corresponds to the bendingstiffness input to produce the optimal matching simulationfor a particular fabric. The target simulation values werebased on averages of several readings for the fabrics, so thegoal was to best simulate the average behaviour. The pointswere fitted to a line. The significance of this plot is thatin order to realistically simulate a fabric using the particlemodel approach, the bending parameter to be input intothe simulation can be found easily from the graph oncethe KES bending value is obtained. Although other sim-ilar simulation codes may not use the identical translatedvalues, the method would be applied for obtaining suchvalues for another code. Other parameters to be input tothe simulation are as summarized in Table 1.
APPLICATION TO GARMENT SIMULATION
To be of practical use, the stiffness relationship developedthrough drape testing of circular fabric samples should beapplicable to simulating garments. This section presentsdetails of application of the developed relationship to sim-ulated garments. The testing was done using apparel thatwas expected to give the most variation in drape with vari-ation in mechanical properties. The approach in our re-search was to study the drape of circular fabric parts anddevelop a relationship from it. So, it was logical to apply therelationship to garments that drape from the body. Thereare a wide variety of garments of all sizes that can be madeto fit humans. Some garments cling to the body and exhibitvery little variation in appearance when made of differentfabrics. A garment designed such that it is a loose fit isan ideal case for drape testing because it will not cling to
the body (a mannequin in our work) when donned. Loosefitting skirts and dresses were chosen as the garments toexamine the applicability of the derived relationship.
The relationship was examined by scanning garmentsfitted to mannequins using the 3D scanner, running sim-ulations of garments of the same dimensions fitted to thescan of the mannequin used in the testing, and comparingthem based on the predetermined criteria. The process ofgenerating scans of garments was the same as in the case ofthe circular samples and required multiple scans, registra-tion and merging of the scans, and application of a surface.Scanning was accomplished using the 3D scanner and theprocessing was done using GeomagicTM.
The garment simulation input parameters were derivedfrom the previously obtained relationship between mea-sured bending stiffness and the optimal bend parametervalue used for simulation. Skirts and dresses of differentfabrics and dimensions were constructed and draped ontwo mannequins of different dimensions. The garmentswere conditioned in standard atmospheric conditions (BS1051: 1972; British Standard Institution, 1974a) before theexperimentation. The flowchart in Figure 4 shows the pro-cess of comparing garment simulations and scans.
MEASURES AND METRICS FOR COMPARISON OFGARMENT SIMULATION AND SCANS
Two factors were used in the comparison of garment scansand simulations:� The volume occupied by closing the top and bottom of
the garment, a measure analogous to drape coefficientused with circular fabric samples. Figure 5 shows a typ-ical draped skirt where this volume was computed viaGeomagicTM.
� The number of nodes obtained in the bottom section, ameasure that is analogous to the number of nodes for thecircular fabric samples.
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Enhancing accuracy of drape simulation. Part II: Optimized drape simulation
Figure 4 Flowchart of garment simulation evaluation process.
Figure 5 A scanned skirt closed at top and bottom forcomputation of volume.
Taking into account the range of variation that fabricsexhibit in their drape, criteria were established for clas-sifying a simulation as an acceptable representation of agarment. The criteria were defined as follows:
� The volume occupied by the simulated garment should bewithin ±15% of the volume occupied by the scan of thegarment.
� The number of nodes obtained in the simulated garmentshould be within ±2 of the number of nodes obtained inthe scan of the garment.
RESULTS OF TESTING ON GARMENTS
Three different garments (two skirts, one dress) were cre-ated and evaluated on two uniquely shaped mannequins.The garments were constructed with a minimal number ofseams to reduce their influence; other factors that could in-fluence drape such as closures and hemming were avoided.The garments were always constructed with the warp yarnparallel to the vertical direction. Details for one of the skirtsused in the experimentation are presented in Figure 6.
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Enhancing accuracy of drape simulation. Part II: Optimized drape simulation
Figure 9 Scan (always on left, lighter shade) and simulation of a skirt.
Table 2 Comparison of scan and simulation for skirt in Figure 9
Scan SimulationPercent difference
Target number Target Number of Volume between target andFabric of nodes volume (cm3) nodes obtained obtained (cm3) actual volumes
Lawn 7 65,064 6 65,008 0.09
Table 3 Input parameters for simulation inFigure 9 (obtained from previously derivedrelationship)
Parameter Value
Bending stiffness 3,000 dyne-cmStretching stiffness X = 1,500, Y = 1,000 g/cmShear stiffness 300 dyne-cmDamping 0.01 cm/sShrinkage X = 0, Y = 0Weight 95 g/m2
Resolution 1.5 cmFriction coefficient 0.25Thickness 0.05 cm
Figures 7 and 8 compare the scan and simulation of theskirt shown in Figure 6 constructed of different fabrics. Inall cases, the established criteria were satisfied.
Figure 9 shows different views of the scan and simu-lation of the skirt made from one fabric (Lawn). Table 2compares the scan and simulation of the skirt made of thesame fabric, in this case Lawn, shown in Figure 9, usingthe established criteria.
The bending stiffness of the Lawn fabric measured bythe KES is 69 dyne-cm and its weight per unit area is 95g/m2. From the plot in Figure 3, the bending stiffness tobe input into ModulateTM was obtained as 3,000 dyne-cm.Table 3 shows the input parameters used to simulate theskirt made of Lawn, shown in Figure 9.
CONCLUSIONS
Evaluation of the other two garments produced similarresults lending credence to the validity of the stiffnessrelationship. All the simulations done were classified asacceptable matches to the scans based on the developedcriteria. In most cases, the simulations fell well within thelimits defined by the criteria. Overall the resemblance ofthe simulations based on the developed relationship to theactual garment scans was quite good. Further researchwill seek to improve the accuracy of virtual representationwith the inclusion of other mechanical properties, garmentdesigns, and fabric varieties.
In simulating the drape of fabrics, it must be remem-bered that fabrics do not drape the same way each time.Hence, there is no precise target for a fabric or garmentsimulation to achieve. Fabric drape is dependent on a large
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number of variables such as fabric properties, shape of theobject over which it is draped, and environmental condi-tions. Each of these is in turn dependent on more vari-ables. It would be extremely difficult and an ineffective useof computational time to predict each of those preciselyin order to simulate fabric drape. The practical approachto simulating fabric drape is to minimize the number ofvariables in simulations without compromising the resem-blance of a simulation to reality. This is the approach thathas been followed in our research. Using bending stiffnessand weight as the only variables, keeping other variablesas constants, fabric drape simulations done by using theModulateTM software were shown to be very good repre-sentations of actual fabrics. In circumstances where KEStesting may be unavailable, a calculated bending stiffnessderived from bending length as obtained from cantilevertesting could be used.
This work also demonstrated the successful applicationof the 3D body scanner to evaluation of garment drape.We found that a 3D body scanner can be used successfullyto quantify drape parameters of entire draped garments bycapturing the image of the draped garments and process-ing the image in the GeomagicTM software. This capabil-ity allows for expanding investigation of drape behaviourbeyond study of circular samples to the complex, three-dimensional drape of garments supported by the humanform.
ACKNOWLEDGMENTS
The authors thank the National Textile Center for fund-ing the research, and OptiTex for providing the soft-ware used in this investigation. In addition, the au-thors thank Dr. David Bruner, Mr. Mike King, and Ms.Kim Munro of [TC]2.Special thanks to Sagi Shani andGadi Zadikoff of OptiTex R&D for their support of thiswork.
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