Topology optimization for particle flow problems using Eulerian-Eulerian model with a finite difference method

TL;DR

This paper introduces a topology optimization approach for particle flow devices using an Eulerian-Eulerian model with finite difference methods, aiming to improve particle resistance and flow efficiency.

Contribution

It develops a novel topology optimization framework incorporating automatic differentiation and validates it through numerical experiments on particle flow problems.

Findings

Serpentine flow fields enhance particle drag force variation.

Optimized flow fields reduce fluid power dissipation.

Reynolds and Stokes numbers influence flow field design.

Abstract

Particle flow processing is widely employed across various industrial applications and technologies. Due to the complex interactions between particles and fluids, designing effective devices for particle flow processing is challenging. In this study, we propose a topology optimization method to design flow fields that effectively enhance the resistance encountered by particles. Particle flow is simulated using an Eulerian-Eulerian model based on a finite difference method. Automatic differentiation is implemented to compute sensitivities using a checkpointing algorithm. We formulate the optimization problem as maximizing the variation of drag force on particles while reducing fluid power dissipation. Initially, we validate the finite difference flow solver through numerical examples of particle flow problems and confirm that the corresponding topology optimization produces a result comparable to the benchmark problem. Furthermore, we investigate the effects of Reynolds and Stokes numbers on the optimized flow field. The numerical results indicate that serpentine flow fields can effectively enhance the variation in particle drag force.