Force-Dual Modes: Subspace Design from Stochastic Forces

TL;DR

This paper introduces a method to design simulation subspaces for reduced order modeling by leveraging force distributions and a statistical approach, improving simulation efficiency for complex scene interactions.

Contribution

It presents a novel force-based subspace construction framework using a linearized simulation and Gaussian modeling, generalizing existing modal and Green's function methods.

Findings

Framework constructs physically meaningful subspaces for diverse interactions.

Subspaces are optimal for specific force distributions and material properties.

Method generalizes traditional modal analysis and Green's function approaches.

Abstract

Designing subspaces for Reduced Order Modeling (ROM) is crucial for accelerating finite element simulations in graphics and engineering. Unfortunately, it's not always clear which subspace is optimal for arbitrary dynamic simulation. We propose to construct simulation subspaces from force distributions, allowing us to tailor such subspaces to common scene interactions involving constraint penalties, handles-based control, contact and musculoskeletal actuation. To achieve this we adopt a statistical perspective on Reduced Order Modelling, which allows us to push such user-designed force distributions through a linearized simulation to obtain a dual distribution on displacements. To construct our subspace, we then fit a low-rank Gaussian model to this displacement distribution, which we show generalizes Linear Modal Analysis subspaces for uncorrelated unit variance force distributions, as well as Green's Function subspaces for low rank force distributions. We show our framework allows for the construction of subspaces that are optimal both with respect to physical material properties, as well as arbitrary force distributions as observed in handle-based, contact, and musculoskeletal scene interactions.