Modeling Plasma Plumes from Rapid Target Heating with Smoothed Particle Hydrodynamics and data-assimilation

Compressible Smoothed Particle Hydrodynamics (SPH) provides a mesh-free framework well-suited to model hydrodynamic flows that expand into vacuum. In this work, its predictive capability is quantified for the hydrodynamic evolution of plasma plumes generated when ~1015 electrons at 20 MeV heat thin targets to temperatures above 1 eV. The generation of plasma plumes during such heating processes can significantly impact various high-energy physics experiments, making accurate prediction of their behavior crucial for experimental design and analysis. Further the SPH formulation contains parameterized terms whose coefficients are optimized through Ensemble Kalman Filter Inversion on experimental data while tracking uncertainties. Time-resolved shadowgraph and interferometric imaging supply spatially resolved electron-density and temperature fields that benchmark the simulations, and are used in the data-assimilation approach. We explore the ability of the calibrated model to reproduce plume characteristics over multiple target materials during the characteristic time scale.