Predictive Criteria for Electrospray-Assisted Droplet Dynamics in Aerodynamic Flow Fields

Ethan Kahn

公開日: 2025/9/15

Abstract

Electrospray technology enables external electric fields to steer charged droplets, with potential applications in fuel-air mixing and aerodynamic flow control. This study develops a computational framework that couples a steady OpenFOAM RANS solution of a NACA 1912 airfoil channel flow with a reduced-order Lagrangian particle model to examine droplet trajectories under viscous drag and electrostatic forces. Baseline uniform-flow tests confirmed that electrostatic deflection weakens as inertial effects grow with freestream velocity. In the non-uniform aerodynamic field, an opposing streamwise electric field increased residence times and produced local reversal in low-speed pockets. Building on these results, we derive a predictive criterion linking the minimum electric field for reversal to the local convective velocity and introduce a "control authority" map that highlights regions where modest fields achieve strong kinematic response. Together, these diagnostics provide a design-oriented basis for positioning electrodes and tuning field strength in aerodynamic environments. The framework thus establishes both a computationally efficient tool for parametric studies and predictive criteria for electrospray-assisted flow manipulation, laying groundwork for three-dimensional extensions and experimental validation.

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