Per-particle stress tensor and contact force export in MPM simulation #8792

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Summary

Taichi's MPM implementation is excellent for simulating deformable materials, but currently lacks a convenient way to extract per-particle stress tensors and contact forces during simulation for downstream use (e.g., dataset generation, policy training).

What's missing

• Stress tensor readout: Stress is computed inside the P2G kernel but not stored as a persistent field. Extracting Cauchy stress or von Mises requires re-deriving from deformation gradient F in user code, which is fragile across different constitutive models.
• Contact force isolation: When soft bodies interact with rigid objects, there's no built-in way to separate contact reaction forces from internal elastic forces per particle or per surface vertex.

Use case

Generating labeled synthetic data for robotic manipulation of deformable objects. Per-step stress and contact force ground truth are needed for training manipulation policies and sim-to-real transfer.

Proposed API (sketch)

stress = mpm_model.get_stress(kind="cauchy")   # (n_particles, 3, 3)
von_mises = mpm_model.get_von_mises()          # (n_particles,)
contact_f = mpm_model.get_contact_forces()     # (n_surface, 3)

Potential benefits

• Enables large-scale synthetic data generation for contact-rich tasks without custom solver patches
• Opens up deformable manipulation benchmarking (grasp quality, damage prediction)
• Strengthens Taichi's position as an end-to-end simulation platform for robotics research

Happy to discuss or contribute if there's interest.