Multiphysics simulation of corona discharge induced ionic wind

TL;DR

This paper introduces a comprehensive multiphysics numerical model to predict ionic wind device performance, accurately capturing charge injection and fluid dynamics, validated against experiments, and applied to optimize cooling device design.

Contribution

The work presents a novel coupled PDE-based simulation framework for ionic wind devices, integrating electrostatics, fluid flow, and heat transfer, with validation and practical design insights.

Findings

Simulation predictions closely match experimental data.

The model effectively estimates device performance and efficiency.

Design optimization insights for electrohydrodynamic cooling devices.

Abstract

Ionic wind devices or electrostatic fluid accelerators are becoming of increasing interest as tools for thermal management, in particular for semiconductor devices. In this work, we present a numerical model for predicting the performance of such devices, whose main benefit is the ability to accurately predict the amount of charge injected at the corona electrode. Our multiphysics numerical model consists of a highly nonlinear strongly coupled set of PDEs including the Navier-Stokes equations for fluid flow, Poisson's equation for electrostatic potential, charge continuity and heat transfer equations. To solve this system we employ a staggered solution algorithm that generalizes Gummel's algorithm for charge transport in semiconductors. Predictions of our simulations are validated by comparison with experimental measurements and are shown to closely match. Finally, our simulation tool is used to estimate the effectiveness of the design of an electrohydrodynamic cooling apparatus for power electronics applications.