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Proposal (Summary)

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Challenge: Hard to achieve both physical accuracy and visual fidelity in digital twins.
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Existing methods:
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Our idea:
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Work with;
Material-Aware Gaussian Crack Simulation

Isaac Sim–generated datasets meet an MLS‑MPM/CPIC cutting engine for physically grounded learning.

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Mesh → SDF Pipeline
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Colliders (Knife/Board)
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Elasticity/Plasticity
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MPM Kernels
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Rendering/Overlay
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CLI / Output
SDF Demos:
Demo video:
Learning to Cut: High‑Fidelity Simulation & Dataset for Robotic Cutting
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Describe Lava’s localization with wax.
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Use numeric animation for real data in Gen AI
Lava Localization Simulation Based on the Wax
TVCG Teaser Video:
Rendering results:
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Sphere to Bunny & Duck to Cow:
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D to Dragon:
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TVCG:
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Abstract :
A Differentiable Material Point Method Framework for Shape Morphing
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Abstract :
Rendering results:
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Sand particle example:
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Snow with Car:
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Primitive Rectangle (vs MPM):
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Snowflakes (Neo-Hookean):
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Mater’s Thesis: (Dissertation Defense: 11/17)
MPM-Based Angular Animation of Particles using Polar Decomposition Theory