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Description
To protect space vehicles of the extreme heat loads during atmospheric entries, appropriate heat shields are necessary. For the higher entry speed class of missions, their design requires the characterization of the both the incident radiative heat flux and associated uncertainties, as well as the impact of radiative cooling in the flow field. An accurate prediction of these properties is also needed for ground testing, since radiation measurements offer a good accessibility to characterize flow fields.
Experimental measurements have shown that thermal and chemical non-equilibrium effects can be crucial for the correct prediction of radiative heat fluxes and interpretation of spectrometric measurements. Computational Fluid Dynamics (CFD) methods, which are typically used for these kind of flow field simulations, are based on Navier–Stokes equations. These equations are physically correct only in a certain range of gas and plasma flows. Strong thermal and chemical non-equilibrium effects found in the region surrounding a bow shock lead to locally high gradients in the flow field. In addition, the backshell protecting the payload from the recirculating flow is subject to rarefaction effects in the wake of the capsule, where continuum assumptions break down. These effects lead to increasing errors in Navier–Stokes-based CFD results and alternative modeling approaches become necessary. The Direct Simulation Monte Carlo (DSMC) method has proven to be an efficient method for calculating these types of flows. Using this well-established approach, it is possible to calculate detailed information about each flow species. Additionally, it is possible to calculate electronic excitation temperatures directly.
In this work, the open source plasma suite PICLas is bidirectionally coupled with a radiation solver. A line-by-line method is implemented to calculate radiative properties in the flow field, a photon Monte Carlo approach is used to calculate the radiative energy transfer. Models to overcome the downsides (computational costs, statistical fluctuations, memory requirements) of the used methods are implemented. Different test and application cases have been simulated and will be shown.
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