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Published February 11, 2023 | Accepted Version
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CHARMS: A Simple Framework for Adaptive Simulation

Abstract

Finite element solvers are a basic component of simulation applications; they are common in computer graphics, engineering, and medical simulations. Although adaptive solvers can be of great value in reducing the often high computational cost of simulations they are not employed broadly. Indeed, building adaptive solvers can be a daunting task especially for 3D finite elements. In this paper we are introducing a new approach to produce conforming, hierarchical, adaptive refinement methods (CHARMS). The basic principle of our approach is to refine basis functions, not elements. This removes a number of implementation headaches associated with other approaches and is a general technique independent of domain dimension (here 2D and 3D), element type (e.g., triangle, quad, tetrahedron, hexahedron), and basis function order (piece-wise linear, higher order B-splines, Loop subdivision, etc.). The (un-)refinement algorithms are simple and require little in terms of data structure support. We demonstrate the versatility of our new approach through 2D and 3D examples, including medical applications and thin-shell animations.

Additional Information

This work was supported in part by NSF (DMS-9874082, ACI-9721349, DMS-9872890, ACI-9982273), the DOE (W-7405-ENG-48/B341492), Intel, Alias|Wavefront, Pixar, Microsoft, the Packard Foundation, and the Hellman Fellowship 2001 (PK). Special thanks to Mathieu Desbrun, Steven Schkolne, Sylvain Jaume, Christopher Malek, Mika Nystroem, Patrick Mullen, Jeff Bolz, Mark Meyer, Ilja Friedel, Joe Kiniry, Andrei Khodakovsky, Nathan Litke, and Zoë Wood.

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Additional details

Created:
August 19, 2023
Modified:
January 15, 2024