Friedrich Ulrich, Christian Stemmer

DOI Number XXX-YYY-ZZZ

Conference Number HiSST-2022-379

This study investigates a re-entry scenario of an Apollo-like space capsule with Direct Numerical Simulations (DNS). The simulation includes the chemical equilibrium gas model. Cross-flow-like vortices are
induced through random distributed roughness patches on the capsule surface. Two different machinelearning methods are used to predict the maximum vorticity magnitude downstream of a random roughness patch. A large DNS database is formed for training and testing of the neural networks. In order to
understand the influence of the vorticity magnitude on the transition process, local one-dimensional inviscid (LODI) relations are used to describe perturbations at the inflow. The disturbance evolution in the
streamwise direction is analysed with a two dimensional Fourier transformation in time and space. The
vorticity magnitudes of the cross-flow-like vortices and the wall-normal vortex-core positions influence
the transition location.

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In Categories: 1.Events, High-Speed Aerodynamics and Aerothermodynamics, HiSST 2022
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