Plasma-Based Flow Control at Hypersonic Speeds


A subtask of the Michigan/AFRL/Boeing Collaborative Center in Aeronautical Sciences (MAB-CCAS), this area of research addresses the following challenges:

  1. Assess performance required from plasma systems to achieve useful performance enhancement on a full scale hypersonic vehicle.
  2. Develop physically accurate simulation capabilities to predict performance of plasma flow control devices for hypersonic applications.

To address these challenges, Computational Fluid Dynamics (CFD) is used to solve the Navier-Stokes equations for full-scale 3D geometries at realistic hypersonic conditions.

Employing the Michigan Aerothermodynamic Navier-Stokes code (LeMANS) along with a phenomenological heat source model allows investigators to simulate flow around realistic geometries with various amounts of energy addition (Q).

Figure 1: Mach 14 blunt elliptic cone without energy deposition.

Figure 2: Mach 14 blunt elliptic cone with a total energy deposition of 1000 W.

The local energy deposition results in an increase in temperature, as seen in a visual comparison of Figures 1 and 2. This local increase in temperature also increases the pressure which could be used as an alternate option to mechanically driven control of the vehicle.

Figure 3: Pressure coefficient and Stanton number distributions along the top centerline of a Mach 14 blunt elliptic cone with various amounts of energy deposition.

Several simulations have been performed for various amounts of energy deposition, vehicle size, and freestream conditions. A correlation between the nondimensional total power and the vehicle's pitching moment is observed in Figure 4. In addition, efforts have indicated that the shape of the deposition does not dramatically affect the resultant pitching moment, whereas a vehicle surface temperature does decreases the effectiveness of the deposition as seen in Figure 5. The 'Radiative' surface means the surface is modeled as a non-conducting blackbody surface, where the local wall temperature is automatically set so that convective heat transfer from the gas is balanced by radiative
heat transfer from the surface.

Figure 4: Moment coefficient versus the nondimensional total power deposition.
Figure 5: Moment coefficient versus the total power deposition for various vehicle surface temperatures.


Current work in this area includes the addition of the Magnetohydrodynamic equations (MHD). This will provide an addition design tool allowing for the exploration of additional enhancement and control of the vehicle with magnetic and electric fields.  The two main challenges are efficiently computing solutions to the MHD equations for large 3D flowfields, and accurately computing the flow's electrical conductivity.

The electrical conductivity can be determined directly by solving Boltzmann's equation or can be approximated using any number of semi-analytical empircal models.  Unfortunately, these models can vary significantly, so a current area of research is effeciently solving Boltzmann's equation and using it directly.  One course of action is to use surrogate modeling to better represent this solution set as a function of a number of variables as represented below in Figure 6.  Here the electrical conductivity is being determined as function of the normalized electric field, percent ionization of the flow, and the molar fractions of the two species present (molecular nitrogen and oxygen).

Figure 6: The electrical conductivity of a gas a function of the normalized electric field (E/N), the ionization fraction (ne/N), and the species mole fractions for a gas mixture of nitrogen and oxygen.


This work is funded by MAB-CCAS and includes ongoing collaboration with colleagues at the Air Force Research Laboratory.