Reaction-Diffusion Based Deformable Object Simulation

This paper presents a new methodology to simulate soft object deformation by drawing an analogy between reaction-diffusion and elastic deformation. The potential energy stored in an elastic body as a result of a deformation caused by an external force is propagated among mass points by the principle of reaction-diffusion. An improved reaction-diffusion model is developed to propagate the energy generated by the external force. A three-layer cellular neural network is established to solve the reaction-diffusion model for real-time simulation of soft object deformation. A material flux based method is presented to derive internal forces from the potential energy distribution established by the reaction-diffusion model. The proposed methodology not only accommodates isotropic, anisotropic and inhomogeneous deformations by simple modification of diffusion coefficients, but it also accepts large-range deformations.

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