Supersonic Flow over SR-71 Blackbird CFD Simulation
Free
- The present CFD Project simulates supersonic airflow over SR-71 blackbird aircraft via ANSYS Fluent software.
- We modeled the geometry using ANSYS Design Modeler software and created the mesh using ANSYS Meshing software.
- The meshing is Polyhedra, and the number of cells is 1,744,624.
- the air property is selected as the ideal gas to model compressibility.
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Description
Supersonic Flow over SR-71 Blackbird Aircraft CFD Simulation, ANSYS Fluent Tutorial
Description
In this project, the supersonic airflow over SR-71 blackbird aircraft is simulated. Supersonic speed is the speed of an object that exceeds the speed of sound. The sound speed is estimated to be around 343 m/s in the dry air at a temperature of 20 C. In this simulation, the SR-71 aircraft experiences 446m/s speed, so the Mach number is 1.3. Plus, the angle of attack is assumed to be 2-degree.
The 3D geometry was imported and generated in Design Modeler software. An SR-71 blackbird aircraft geometry is imported and placed in an enclosure. In addition, an unstructured mesh grid was carried out using Ansys Meshing software, and overall, 1,744,624 elements were generated. Moreover, the tetrahedron mesh grid was converted to polyhedra in ANSYS Fluent software.
This CFD project is the 5th episode of the ANSYS Fluent General Training Course.
Methodology: Supersonic Flow over SR-71 Blackbird Aircraft
This simulation focuses on using a pressure-based solver and a Coupled pressure-velocity coupling algorithm along with the ideal-gas behavior of air density to model compressible flows instead of a having Density-based approach. Also, the simulation is independent of Time, so it has performed in steady state form.
Conclusion
In this project, the Mach number of the flow was assumed to be 1.3, and there was supersonic flow over the aircraft. Due to fluid compressibility, a density-based solver type should be hired. Instead, we came up with using a pressure-based solver type and coupled velocity-pressure coupling algorithm and ideal gas behavior of the density simultaneously.
Notice that the viscosity was a function of temperature, so we used the Sutherland model. As contours show, There is a shock wave around the aircraft’s nose and engines that causes an extreme velocity and pressure gradient. Therefore, the density experiences different values, and the compressibility assumption is of the essence. Furthermore, as expected, there is a direct correlation between pressure, density, and temperature.
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