A novel Doppler Monte Carlo code for modeling Photonic Doppler Velocimetry (PDV) spectrograms of ejecta from shock-loaded samples

When a shock wave emerges at a metal free surface presenting geometrical defects such as pits, scratches, or grooves, "ejected matter" (ejecta) can be emitted from these defects in the form of thin jets expanding ahead of the main surface and breaking up into small particles. This process is referred to as microjetting. Photonic Doppler Velocimetry (PDV) is often used to track the velocity of the cloud of ejecta, due to its ability to record multiple velocities simultaneously. In recent years, various attemps have been undertaken in order to retrieve more information from the PDV spectrograms, especially the particle size and velocity distributions, using different methods to treat the radiative transfer within the cloud of ejecta. In this work, a novel Doppler Monte Carlo (MC) code, written in Python, has been developed for modeling optical radiation propagation in inhomogeneous polydisperse scattering ejecta clouds. A detailed convergence study, including the initial number of photons and the maximum number of scattering events, has first been performed in order to assess the accuracy of our MC algorithm. Then the code has been applied to the simulation of typical PDV ejecta spectrogams using a diversity of input distributions for their sizes and velocities, so as to build a representative database. This database is used to highligth how the PDV spectrograms are qualitatively and quantitatively influenced by the physical parameters of the cloud of ejecta.