“The key to pursuing excellence is to embrace an organic, long-term learning process, and not to live in a shell of static, safe mediocrity. Usually, growth comes at the expense of previous comfort or safety.”

AMR-based Scalable DSMC Flow Solver: SUGAR

Hypersonic flows exhibit large gradients of macroscopic flow parameters. To simulate them using the kinetic Direct Simulation Monte Carlo (DSMC) method, I developed an MPI-based solver, known as SUGAR (See Sawant et al.), which employed an adaptive mesh refinement (AMR) strategy and was demonstrated to have ideal strong scaling speed-up up to 4092 processors and 87% weak scaling efficiency for 8192 processors. Figure shows differences in the maximum level of AMR for a simple Mach 7 flow at a Knudsen number of 0.04.

© 2020 by Saurabh S. Sawant

Linear Instability of a 3-D Laminar Separation Bubble

SUGAR code was used to simulate complex shock-wave/boundary-layer interactions in the Mach 7, Re=52000/m flow of nitrogen over a double wedge using 60 billion computational particles, 4.5 billion collision cells, and 19200 MPI processors. A spanwise-periodic linear instability, synchronized with that in the separation zone, is identified for the first time, which exists in the internal structure of the separation and detached shock layers, and manifests itself as spanwise-periodic cats-eyes patterns in the amplitude functions of all linear flow perturbations. See my video presentation for details. This work is published in JFM.

Low-frequency Fluctuations in a 1-D Shock of Monatomic gases

All macroscopic quantities fluctuate about their mean value even at equilibrium due to molecular fluctuations. The frequency of these fluctuations is on the order of mean-collision time in the freestream. However, inside the shock layer, we have found that the dominant frequencies are two orders of magnitude lower. We showed that this is a consequence of the bimodal energy distribution function of particles' velocities and energies in the shock, using a simple predator-prey type two energy bin model. These bins correspond to low energy particles from the downstream subsonic region and high energy particles from the upstream hypersonic region. The figure on the right shows the dynamics of particles in a shock, where any fluctuations in particles of these bins spiral to critical values. Such molecular fluctuations may not be ignored while studying the receptivity of shocks to freestream disturbances. See video presentation for details. This work is published in Phys of Fluids as editor's pick.

© 2020 by Saurabh S. Sawant

Bimodal Non-Central Chi-Squared Energy Distributions inside Shocks

This work, published in TCFD, is an extension of the work described above. A bimodal energy distribution obtained from DSMC inside a shock is shown in the figure. In this work, these distribution functions are analytically derived and shown to be of the form known as non-central chi-squared distributions, well-known in statistics. We correlated the changes in the location of peak in the distribution function corresponding to high energy particles with the low-frequencies obtained from DSMC. Using this correlation, we can easily predict an average characteristic low-frequency of molecular fluctuations in a shock at any arbitrary conditions in a broad range of input parameters. Such an estimate can be used in the receptivity analysis of laminar to turbulent transition and by experimentalists for comparison.

© 2020 by Saurabh S. Sawant

Kinetic Modeling of AVCOAT- like Thermal Protection Materials

In this project, I demonstrated a multi-scale modeling approach to study the thermal response of an ablative heat shield used on a reentry spacecraft by accounting for its microstructure characteristics. We extended a unique stochastic approach to couple the DSMC-derived convective fluxes in the interior of the microstructure to conductive and radiative modes of heat transfer. See Sawant et al. and Harpale et al. for details.

Figure (a) shows the SEM image of the AVCOAT microstructure by Gladysz & Chawla, (b) shows the CAD model I created to study DSMC flows, (c) shows a schematic of the random-walk model.

© 2020 by Saurabh S. Sawant

Particle Lifting in a Shock Tube Experiment

I modified the FLASH flow solver to incorporate particles. Figure shows the numerical modeling of the shock tube experiment of Gosteev & Fedorov, where a dust particle is lifted in the boundary layer downstream of a shock moving to the right. The other part of this work, published in the Int. J. Multiph. Flow, was lead by my junior Ph.D. labmate, Akhil, who studied the interaction of lifted particles with the electrostatic discharge plasma.

© 2020 by Saurabh S. Sawant