Proper Orthogonal Decomposition-based Model-Order Reduction for Smoothed Particle Hydrodynamics Simulation—Mass-Spring-Damper System

Model Order Reduction (MOR) based on Proper Orthogonal Decomposition (POD) and Smooth Particle Hydrodynamics (SPH) has proven effective in various applications. Most MOR methods utilizing POD are implemented within a pure Eulerian framework, while significantly less attention has been given to POD in a Lagrangian context. In this paper, we present the POD-MOR of SPH simulations applied to a mass-spring-damper system with two primary objectives: 1. To evaluate the performance of the data-driven POD-MOR approach. 2. To investigate potential methods for accel-erating POD-MOR computations. Although the mass-spring-damper system is linear, its SPH implementations are nonlinear, and POD-MOR does not automatically lead to faster computations. Our findings indicate that (1) the POD-MOR effectively reduces the degrees of freedom in the SPH simulations by capturing the essential modes, and (2) in various cases, the acceleration of POD-MOR can be achieved without compro-mising accuracy. We hope that our results will motivate further investigations into the design of POD-MOR algorithms for nonlinear Lagrangian systems.