Inertial Effects of a Shock Accelerated Particle on the Time-Dependent Drag Coefficient

Despite a long history of theory and experimentation of shock-particle interaction, elucidating the time-dependent drag coefficients for single and multi-particle systems accelerated by shocked flow remains an open challenge. Numerical simulations are uniquely positioned as a relatively inexpensive alternative to experimentation to explore the parameter space of shock accelerated particle flows; supplying critically needed data to time-dependent drag models. We utilize the flexibility of a sharp-interface immersed boundary method (SI-IBM) to extract a high-fidelity approximation to the time-dependent drag coefficient of a spherical particle accelerated by a shock. Critically, the SI-IBM resolves the particle acceleration and interaction with its developing wake. We examine how variations of Reynolds number and density ratio affect the time-dependent drag coefficient for this Lagrangian particle. Finally, leveraging high-fidelity simulation data, we provide a physics-informed machine learning correction to a previous phenomenological model.