Physics-based Sphere Packing for Lagrangian Mesh Morphing

2026-10-06

AI Summary

This study addresses the degradation of fixed-topology meshes under large deformations and the loss of node correspondence during remeshing by proposing the JamTet framework. This method generates volumetric meshes via a sphere-packing strategy that combines parallel octree-based packing with constrained Delaunay tetrahedralization, enabling inversion-free Lagrangian deformation while strictly preserving internal node identities. The framework integrates GPU acceleration with a JAX-based differentiable simulator, supporting both Neo-Hookean and mass-spring models. In soft robotic design tasks, JamTet improves swimming adaptability by 0.73–1.07, outperforming conventional voxelization methods by 32%–63%, thereby demonstrating its superiority in differentiable physical simulation.

Abstract

This paper studies tetrahedral meshes as the body representation for differentiable simulation and computational design. Fixed-connectivity meshes degrade under large morphs, while remeshing from scratch discards node correspondence. We present JamTet, a physics-based sphere-packing framework for volumetric meshing and morphing. We contribute (i) a GPU-parallel mesher combining octree-hierarchical packing with constrained Delaunay tetrahedralization, producing more uniform element volumes than TetGen and fTetWild; (ii) Lagrangian mesh morphing that preserves interior-node identities by re-equilibrating the same spheres within changing shapes and rebuilding the boundary and connectivity, remaining inversion-free where fixed-connectivity and TetSphere meshes invert; and (iii) a differentiable GPU simulator in JAX, with mass-spring edges and a volumetric Neo-Hookean term, integrated with mesh morphing in a design pipeline. In soft-robot morphology design experiments, interior-node gradients improve swimming fitness by 0.73-1.07 over a matched surface-only variant, while voxelized versions of the same designs yield 32-63% lower fitness. These results establish sphere packing as a practical volumetric mesh representation for gradient-based shape optimization. Code and media: under review.

Problem

• tetrahedral mesh morphing
• differentiable simulation
• sphere packing
• computational design
• mesh inversion

Innovation

• Sphere Packing
• Lagrangian Mesh Morphing
• Differentiable Simulation
• Tetrahedral Meshing
• Soft Robot Design