Efficient Unstructured Grid Adaptation Methods for Sonic Boom Prediction

Abstract

This paper examines the use of two grid adaptation methods to improve the accuracy of the near-to-mid field pressure signature prediction of supersonic aircraft computed using the USM3D unstructured grid flow solver. The first method (ADV) is an interactive adaptation process that uses grid movement rather than enrichment to more accurately resolve the expansion and compression waves. The second method (SSGRID) uses an a priori adaptation approach to stretch and shear the original unstructured grid to align the grid with the pressure waves and reduce the cell count required to achieve an accurate signature prediction at a given distance from the vehicle. Both methods initially create negative volume cells that are repaired in a module in the ADV code. While both approaches provide significant improvements in the near field signature (< 3 body lengths) relative to a baseline grid without increasing the number of grid points, only the SSGRID approach allows the details of the signature to be accurately computed at mid-field distances (3-10 body lengths) for direct use with mid-field-to-ground boom propagation codes. NomenclatureΔp/p = (local static pressure -free-stream static pressure)/free-stream static pressure H = vertical distance from body to boom measurement station L = reference length x = distance in the streamwise direction Xcone = distance in the streamwise direction relative to initial shock

Integration of Engine, Plume, and CFD Analyses in Conceptual Design of Low-Boom Supersonic Aircraft

“…More details about SSGRID can be found in [4]. In conclusion, the SSGRID approach was by far easier to use, provided more detail in the near field, and retained more of the detail into the mid-field than could be realized from the original VGRID grid.…”

“…Because the flow gradients are small in the stretch direction, the larger cell size allows these pressure waves to propagate to the mid-field with less dissipation than with the original grid. The grid stretching and shearing in SSGRID will generally produce some negative volume cells, so the grid is run through the ADV grid post-processing code [4] to repair these cells. The entire process is automated and typically takes less than a minute to create a grid for each new pair of a Mach number and an angle-of-attack.…”

“…However, the hybrid CFD method is more expensive both in labor hours and computational resources [11]. Recently, an a priori grid adaptation code (SSGRID) developed by Campbell [4] allows accurate predictions of mid-field (3 to 10 body lengths) pressure distributions with a reasonable grid size. Comparisons of USM3D predictions and the flight data show that USM3D predictions of dp/p using SSGRID are in very good agreement with flight data at 1.2, 2.6, 4.8, and 7.5 body lengths below the F-15QS.…”

“…Then a newly developed process for automated CFD analysis is T used for CFD plume and boom analyses of the conceptual geometry. The automated CFD process consists of the following steps: (i) start from a conceptual definition of a complete aircraft, (ii) convert the aircraft geometry to a watertight CFD geometry in VGRID [2] [3] (an unstructured grid generation code) format, (iii) generate sources for grid generation based on a few intuitive control parameters, (iv) use VGRID for unstructured grid generation, (v) use SSGRID [4] to shear and stretch the volume grid for improved boom predictions, and (vi) run USM3D [5] [6] (an unstructured flow solver) for CFD solutions, including engine simulation based on NPSS engine data. The CFD pressure distributions can be used by PCBOOM [7] for sonic boom predictions, and the CFD plume analysis results can be used to calibrate the low-fidelity code for plume shape prediction.…”

Integration of Off-Track Sonic Boom Analysis in Conceptual Design of Supersonic Aircraft

“…Computational fluid dynamics (CFD) techniques for accurate off-body pressure prediction have advanced rapidly in the last several years. [1][2][3] Relatively accurate off-body pressure distributions can now be obtained several body lengths below the aircraft, although the computational cost is substantially higher than for computing accurate surface pressures.…”