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Go Green: General Regularized Green’s Functions for Elasticity

Published:24 July 2022Publication History

ABSTRACT

The fundamental solutions (Green’s functions) of linear elasticity for an infinite and isotropic media are ubiquitous in interactive graphics applications that cannot afford the computational costs of volumetric meshing and finite-element simulation. For instance, the recent work of de Goes and James [2017] leveraged these Green’s functions to formulate sculpting tools capturing in real-time broad and physically-plausible deformations more intuitively and realistically than traditional editing brushes. In this paper, we extend this family of Green’s functions by exploiting the anisotropic behavior of general linear elastic materials, where the relationship between stress and strain in the material depends on its orientation. While this more general framework prevents the existence of analytical expressions for its fundamental solutions, we show that a finite sum of spherical harmonics can be used to decompose a Green’s function, which can be further factorized into directional, radial, and material-dependent terms. From such a decoupling, we show how to numerically derive sculpting brushes to generate anisotropic deformation and finely control their falloff profiles in real-time.

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  1. Josephine Ainley, Sandra Durkin, Rafael Embid, Priya Boindala, and Ricardo Cortez. 2008. The method of images for regularized Stokeslets. J. Comput. Phys. 227, 9 (2008), 4600–4616.Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Alexis Angelidis, Geoff Wyvill, and Marie-Paule Cani. 2004. Sweepers: swept user-defined tools for modeling by deformation. In Proceedings of Shape Modeling Applications. 63–73.Google ScholarGoogle Scholar
  3. David M. Barnett. 1972. The precise evaluation of derivatives of the anisotropic elastic Green’s functions. Physica Status Solidi (b) 49, 2 (1972), 741–748.Google ScholarGoogle ScholarCross RefCross Ref
  4. Boost. 2021. Boost C++ Libraries. http://www.boost.org/.Google ScholarGoogle Scholar
  5. John Burkardt. 2020. Quadrature Rules for the Unit Sphere. https://people.sc.fsu.edu/~jburkardt/cpp_src/sphere_lebedev_rule/sphere_lebedev_rule.htmlGoogle ScholarGoogle Scholar
  6. Ricardo Cortez, Lisa Fauci, and Alexei Medovikov. 2005. The method of regularized Stokeslets in three dimensions: analysis, validation, and application to helical swimming. Physics of Fluids 17, 3 (2005), 031504.Google ScholarGoogle ScholarCross RefCross Ref
  7. Fernando de Goes and Doug L James. 2017. Regularized Kelvinlets: sculpting brushes based on fundamental solutions of elasticity. ACM Trans. Graph. 36, 4 (2017), 1–11.Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Fernando de Goes and Doug L James. 2018. Dynamic Kelvinlets: secondary motions based on fundamental solutions of elastodynamics. ACM Trans. Graph. 37, 4 (2018), 1–10.Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Fernando de Goes and Doug L. James. 2019. Sharp Kelvinlets: Elastic Deformations with Cusps and Localized Falloffs. In Digital Production Symposium. Article 2.Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Brian Gough. 2009. GNU Scientific Library Reference Manual(third ed.). Network Theory Ltd.Google ScholarGoogle Scholar
  11. Loukas Grafakos. 2008. Classical fourier analysis(second ed.). Springer.Google ScholarGoogle Scholar
  12. Robin Green. 2003. Spherical harmonic lighting: The gritty details. In Archives of the game developers conference, Vol. 56. 4.Google ScholarGoogle Scholar
  13. Doug L James, Jernej Barbič, and Dinesh K Pai. 2006. Precomputed acoustic transfer: output-sensitive, accurate sound generation for geometrically complex vibration sources. ACM Trans. Graph. 25, 3 (2006), 987–995.Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Doug L James and Dinesh K Pai. 1999. Artdefo: accurate real time deformable objects. In Proceedings of the Conference on Computer Graphics and Interactive Techniques. 65–72.Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Doug L James and Dinesh K Pai. 2003. Multiresolution Green’s function methods for interactive simulation of large-scale elastostatic objects. ACM Trans. Graph. 22, 1 (2003), 47–82.Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Lily Kharevych, Patrick Mullen, Houman Owhadi, and Mathieu Desbrun. 2009. Numerical coarsening of inhomogeneous elastic materials. ACM Trans. Graph. 28, 3 (2009), 1–8.Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Yaron Lipman, David Levin, and Daniel Cohen-Or. 2008. Green coordinates. ACM Trans. Graph. 27, 3 (2008), 1–10.Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Toshio Mura and N Kinoshita. 1972. The precise evaluation of derivatives of the anisotropic elastic Green’s functions. Physica Status Solidi (b) 49, 2 (1972), 741–748.Google ScholarGoogle ScholarCross RefCross Ref
  19. Roger G. Newton. 2002. Scattering Theory of Waves and Particles. Springer-Verlag.Google ScholarGoogle Scholar
  20. Rohan Sawhney and Keenan Crane. 2020. Monte Carlo geometry processing: A grid-free approach to PDE-based methods on volumetric domains. ACM Trans. Graph. 39, 4 (2020).Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Camille Schreck, Christian Hafner, and Chris Wojtan. 2019. Fundamental solutions for water wave animation. ACM Trans. Graph. 38, 4 (2019), 1–14.Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Wolfram Research, Inc.2021. Mathematica (version 13.0.0). https://www.wolfram.com/mathematicaGoogle ScholarGoogle Scholar
  23. Longtao Xie, Chuanzeng Zhang, Jan Sladek, and Vladimir Sladek. 2016. Unified analytical expressions of the three-dimensional fundamental solutions and their derivatives for linear elastic anisotropic materials. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 472, 2186 (2016), 20150272.Google ScholarGoogle ScholarCross RefCross Ref

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  • Published in

    cover image ACM Conferences
    SIGGRAPH '22: ACM SIGGRAPH 2022 Conference Proceedings
    July 2022
    553 pages
    ISBN:9781450393379
    DOI:10.1145/3528233

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    • Published: 24 July 2022

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