“Neural-assisted Homogenization of Yarn-level Cloth” – ACM SIGGRAPH HISTORY ARCHIVES

“Neural-assisted Homogenization of Yarn-level Cloth”

  • ©

Conference:


Type(s):


Title:

    Neural-assisted Homogenization of Yarn-level Cloth

Presenter(s)/Author(s):



Abstract:


    We introduce a neural-assisted homogenization method for yarn-level cloth. Our approach incorporates a warm-start strategy to enhance the efficiency of the homogenization process. We then use tailored loss functions in constitutive models, ensuring stability for large time-step simulations (up to 1/30 second) while boosting accuracy.

References:


    [1]
    David Baraff and Andrew Witkin. 1998. Large Steps in Cloth Simulation. In Proceedings of SIGGRAPH 98(Computer Graphics Proceedings, Annual Conference Series), Eugene Fiume (Ed.). ACM, 43?54.

    [2]
    Mikl?s Bergou, Max Wardetzky, Stephen Robinson, Basile Audoly, and Eitan Grinspun. 2008. Discrete Elastic Rods. In ACM SIGGRAPH 2008 Papers (Los Angeles, California) (SIGGRAPH ?08). Article 63, 12 pages.

    [3]
    Bernd Bickel, Moritz B?cher, Miguel A. Otaduy, Wojciech Matusik, Hanspeter Pfister, and Markus Gross. 2009. Capture and Modeling of Non-linear Heterogeneous Soft Tissue. ACM Trans. Graph. (SIGGRAPH) 28, 3, Article 89 (July 2009), 9 pages.

    [4]
    Sofien Bouaziz, Sebastian Martin, Tiantian Liu, Ladislav Kavan, and Mark Pauly. 2014. Projective Dynamics: Fusing Constraint Projections for Fast Simulation. ACM Trans. Graph. (SIGGRAPH) 33, 4, Article 154 (July 2014), 11 pages.

    [5]
    Robert Bridson, Ronald Fedkiw, and John Anderson. 2002. Robust Treatment of Collisions, Contact and Friction for Cloth Animation. ACM Trans. Graph. (SIGGRAPH) 21, 3 (July 2002), 594?603.

    [6]
    Juan J Casafranca, Gabriel Cirio, Alejandro Rodr?guez, Eder Miguel, and Miguel A Otaduy. 2020. Mixing Yarns and Triangles in Cloth Simulation. In Computer Graphics Forum, Vol. 39. Wiley Online Library, 101?110.

    [7]
    Antoine Chan-Lock, Jes?s P?rez, and Miguel A Otaduy. 2022. High-Order Elasticity Interpolants for Microstructure Simulation. In Computer Graphics Forum, Vol. 41. Wiley Online Library, 63?74.

    [8]
    Gabriel Cirio, Jorge Lopez-Moreno, David Miraut, and Miguel A. Otaduy. 2014. Yarn-Level Simulation of Woven Cloth. ACM Trans. Graph. (SIGGRAPH Asia) 33, 6, Article 207 (Nov. 2014), 11 pages.

    [9]
    Gabriel Cirio, Jorge Lopez-Moreno, and Miguel A Otaduy. 2016. Yarn-Level Cloth Simulation with Sliding Persistent Contacts. IEEE transactions on visualization and computer graphics 23, 2 (2016), 1152?1162.

    [10]
    G Colasante and PD Gosling. 2016. Including Shear in a Neural Network Constitutive Model for Architectural Textiles. Procedia Engineering 155 (2016), 103?112.

    [11]
    Glenn W Ellis, Chengwan Yao, and Rongda Zhao. 1992. Neural Network Modeling of the Mechanical Behavior of Sand. In Engineering Mechanics. ASCE, 421?424.

    [12]
    Wenshan Fan, Bin Wang, Jean-Claude Paul, and Jiaguang Sun. 2011. A Hierarchical Grid Based Framework for Fast Collision Detection. In Computer Graphics Forum, Vol. 30. Wiley Online Library, 1451?1459.

    [13]
    Yun Fei, Christopher Batty, Eitan Grinspun, and Changxi Zheng. 2018. A Multi-Scale Model for Simulating Liquid-Fabric Interactions. ACM Trans. Graph. 37, 4 (2018), 1?16.

    [14]
    Xudong Feng, Wenchao Huang, Weiwei Xu, and Huamin Wang. 2022. Learning-Based Bending Stiffness Parameter Estimation by a Drape Tester. ACM Trans. Graph. 41, 6 (2022), 1?16.

    [15]
    Minjun Gao, Junhui Meng, Nuo Ma, Moning Li, and Li Liu. 2022. Artificial Neural Network?Based Constitutive Relation Modelling for the Laminated Fabric Used in Stratospheric Airship. Composites and Advanced Materials 31 (2022), 26349833211073146.

    [16]
    Marc G. D. Geers, Varvara G. Kouznetsova, and W. A. M. Brekelmans. 2010. Multi-Scale Computational Homogenization: Trends and Challenges. J. Comput. Appl. Math. 234, 7 (2010), 2175?2182.

    [17]
    Jamshid Ghaboussi, J. H. Garrett Jr, and Xiping Wu. 1991. Knowledge-Based Modeling of Material Behavior with Neural Networks. Journal of Engineering Mechanics 117, 1 (1991), 132?153.

    [18]
    Eitan Grinspun, Yotam Gingold, Jason Reisman, and Denis Zorin. 2006. Computing Discrete Shape Operators on General Meshes. In Computer Graphics Forum, Vol. 25. Wiley Online Library, 547?556.

    [19]
    Jos?Miranda Guedes and Noboru Kikuchi. 1990. Preprocessing and Postprocessing for Materials Based on the Homogenization Method with Adaptive Finite Element Methods. Computer Methods in Applied Mechanics and Engineering 83, 2 (1990), 143?198.

    [20]
    Kurt Hornik, Maxwell Stinchcombe, and Halbert White. 1989. Multilayer Feedforward Networks are Universal Approximators. Neural Networks 2, 5 (1989), 359?366.

    [21]
    Daniel Z Huang, Kailai Xu, Charbel Farhat, and Eric Darve. 2019. Predictive Modeling with Learned Constitutive Laws from Indirect Observations. arXiv preprint arXiv:1905.12530 (2019).

    [22]
    Jonathan M. Kaldor, Doug L. James, and Steve Marschner. 2008. Simulating Knitted Cloth at the Yarn Level. ACM Trans. Graph. (SIGGRAPH) 27, 3, Article 65 (Aug. 2008), 9 pages.

    [23]
    Jonathan M. Kaldor, Doug L. James, and Steve Marschner. 2010. Efficient Yarn-Based Cloth with Adaptive Contact Linearization. ACM Trans. Graph. (SIGGRAPH) 29, 4, Article 105 (July 2010), 10 pages.

    [24]
    Theodore Kim. 2020. A Finite Element Formulation of Baraff-Witkin Cloth. In Computer Graphics Forum, Vol. 39. Wiley Online Library, 171?179.

    [25]
    Theodore Kim, Fernando De Goes, and Hayley Iben. 2019. Anisotropic Elasticity for Inversion-Safety and Element Rehabilitation. ACM Trans. Graph. 38, 4 (2019), 1?15.

    [26]
    BA Le, Julien Yvonnet, and Q-C He. 2015. Computational Homogenization of Nonlinear Elastic Materials Using Neural Networks. Internat. J. Numer. Methods Engrg. 104, 12 (2015), 1061?1084.

    [27]
    Marek Lefik and Bernhard A Schrefler. 2003. Artificial Neural Network as an Incremental Non-linear Constitutive Model for a Finite Element Code. Computer Methods in Applied Mechanics and Engineering 192, 28-30 (2003), 3265?3283.

    [28]
    Xuan Li, Yu Fang, Lei Lan, Huamin Wang, Yin Yang, Minchen Li, and Chenfanfu Jiang. 2023b. Subspace-Preconditioned GPU Projective Dynamics with Contact for Cloth Simulation. In SIGGRAPH Asia 2023 Conference Papers. Article 1, 12 pages.

    [29]
    Yue Li, Stelian Coros, and Bernhard Thomaszewski. 2023a. Neural Metamaterial Networks for Nonlinear Material Design. ACM Trans. Graph. 42, 6, Article 186 (dec 2023), 13 pages.

    [30]
    Hernan J Logarzo, German Capuano, and Julian J Rimoli. 2021. Smart Constitutive Laws: Inelastic Homogenization Through Machine Learning. Computer Methods in Applied Mechanics and Engineering 373 (2021), 113482.

    [31]
    Miles Macklin, Matthias M?ller, and Nuttapong Chentanez. 2016. XPBD: Position-Based Simulation of Compliant Constrained Dynamics. In Proceedings of the 9th International Conference on Motion in Games. 49?54.

    [32]
    Karel Matou?, Marc GD Geers, Varvara G Kouznetsova, and Andrew Gillman. 2017. A Review of Predictive Nonlinear Theories for Multiscale Modeling of Heterogeneous Materials. J. Comput. Phys. 330 (2017), 192?220.

    [33]
    Eder Miguel, David Miraut, and Miguel A. Otaduy. 2016. Modeling and Estimation of Energy-Based Hyperelastic Objects. Comput. Graph. Forum (Eurographics) 35, 2 (May 2016), 385?396.

    [34]
    Eder Miguel, Rasmus Tamstorf, Derek Bradley, Sara C. Schvartzman, Bernhard Thomaszewski, Bernd Bickel, Wojciech Matusik, Steve Marschner, and Miguel A. Otaduy. 2013. Modeling and Estimation of Internal Friction in Cloth. ACM Trans. Graph. (SIGGRAPH Asia) 32, 6, Article 212 (Nov. 2013), 10 pages.

    [35]
    Zahra Montazeri, Chang Xiao, Yun Fei, Changxi Zheng, and Shuang Zhao. 2021. Mechanics-Aware Modeling of Cloth Appearance. IEEE Transactions on Visualization and Computer Graphics 27, 1 (2021), 137?150. https://doi.org/10.1109/TVCG.2019.2937301

    [36]
    Matthias M?ller, Bruno Heidelberger, Marcus Hennix, and John Ratcliff. 2007. Position Based Dynamics. Journal of Visual Communication and Image Representation 18, 2 (2007), 109?118.

    [37]
    Rahul Narain, Armin Samii, and James F. O?Brien. 2012. Adaptive Anisotropic Remeshing for Cloth Simulation. ACM Trans. Graph. (SIGGRAPH Asia) 31, 6, Article 152 (Nov. 2012), 10 pages.

    [38]
    Matthew Overby, George E Brown, Jie Li, and Rahul Narain. 2017. ADMM supseteq projective dynamics: Fast simulation of hyperelastic models with dynamic constraints. IEEE transactions on visualization and computer graphics 23, 10 (2017), 2222?2234.

    [39]
    Jos? M Pizana, Alejandro Rodr?guez, Gabriel Cirio, and Miguel A Otaduy. 2020. A Bending Model for Nodal Discretizations of Yarn-Level Cloth. In Computer Graphics Forum, Vol. 39. Wiley Online Library, 181?189.

    [40]
    Rosa Mar?a S?nchez-Banderas and Miguel A Otaduy. 2017. Dissipation Potentials for Yarn-Level Cloth. In Spanish Computer Graphics Conference (CEIG). 11?18.

    [41]
    Rosa Maria S?nchez-Banderas and Miguel A Otaduy. 2018. Strain Rate Dissipation for Elastic Deformations. In Computer Graphics Forum, Vol. 37. Wiley Online Library, 161?170.

    [42]
    Rosa M S?nchez-Banderas, Alejandro Rodr?guez, H?ctor Barreiro, and Miguel A Otaduy. 2020. Robust Eulerian-on-Lagrangian Rods. ACM Trans. Graph. 39, 4 (2020), 59?1.

    [43]
    Yuelin Shen, K Chandrashekhara, WF Breig, and LR Oliver. 2005. Finite Element Analysis of V-Ribbed Belts Using Neural Network Based Hyperelastic Material Model. International Journal of Non-Linear Mechanics 40, 6 (2005), 875?890.

    [44]
    Georg Sperl, Rahul Narain, and Chris Wojtan. 2020. Homogenized Yarn-Level Cloth. ACM Trans. Graph. (SIGGRAPH) 39, 4, Article 48 (July 2020), 16 pages.

    [45]
    J. Teran, S. Blemker, V. Ng Thow Hing, and R. Fedkiw. 2003. Finite Volume Methods for the Simulation of Skeletal Muscle. In Proceedings of SCA. 68?74.

    [46]
    Huamin Wang, James F. O?Brien, and Ravi Ramamoorthi. 2011. Data-Driven Elastic Models for Cloth: Modeling and Measurement. ACM Trans. Graph. (SIGGRAPH) 30, 4, Article 71 (July 2011), 9 pages.

    [47]
    Hanchen Wang, Yuanqi Du Tianfan Fu, Wenhao Gao, Kexin Huang, Ziming Liu, Payal Chandak, Shengchao Liu, Peter Van Katwyk, Andreea Deac, Anima Anandkumar, Karianne Bergen, Carla P. Gomes, Shirley Ho, Pushmeet Kohli, Joan Lasenby, Jure Leskovec, Tie-Yan Liu, Arjun Manrai, Debora Marks, Bharath Ramsundar, Le Song, Jimeng Sun, Jian Tang, Petar Veli?kovi?, Max Welling, Linfeng Zhang, Connor W. Coley, Yoshua Bengio, and Marinka Zitnik. 2023. Scientific Discovery in the Age of Artificial Intelligence. Nature 620 (2023), 47?60.

    [48]
    Huamin Wang and Yin Yang. 2016. Descent Methods for Elastic Body Simulation on the GPU. ACM Trans. Graph. (SIGGRAPH Asia) 35, 6, Article 212 (Nov. 2016), 10 pages.

    [49]
    Jia-Ji Wang, Chen Wang, Jian-Sheng Fan, and YL Mo. 2022. A Deep Learning Framework for Constitutive Modeling Based on Temporal Convolutional Network. J. Comput. Phys. 449 (2022), 110784.

    [50]
    Haomiao Wu and Theodore Kim. 2023. An Eigenanalysis of Angle-Based Deformation Energies. Proceedings of the ACM on Computer Graphics and Interactive Techniques 6, 3 (2023), 1?19.

    [51]
    Kailai Xu, Daniel Z Huang, and Eric Darve. 2021. Learning Constitutive Relations using Symmetric Positive Definite Neural Networks. J. Comput. Phys. 428 (2021), 110072.

    [52]
    Shan Yang, Junbang Liang, and Ming C. Lin. 2017. Learning-Based Cloth Material Recovery from Video. In IEEE International Conference on Computer Vision.

    [53]
    Zhan Zhang, Christopher Brandt, Jean Jouve, Yue Wang, Tian Chen, Mark Pauly, and Julian Panetta. 2023. Computational Design of Flexible Planar Microstructures. ACM Trans. Graph. 42, 6, Article 185 (dec 2023), 16 pages. https://doi.org/10.1145/3618396


ACM Digital Library Publication:



Overview Page:



Submit a story:

If you would like to submit a story about this presentation, please contact us: historyarchives@siggraph.org