Drape Simulation Estimation for Non-Linear Stiffness Model

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