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Article
Multifidelity Comparison of Supersonic Wave Drag Prediction Methods Using Axisymmetric Bodies †
Aerospace
  • Troy Abraham, Utah State University
  • David Lazzara, Boeing Research and Technology
  • Douglas Hunsaker, Utah State University
Document Type
Article
Publisher
MDPI AG
Publication Date
4-30-2024
Creative Commons License
Creative Commons Attribution 4.0
Disciplines
Abstract

Low-fidelity analytic and computational wave drag prediction methods assume linear aerodynamics and small perturbations to the flow. Hence, these methods are typically accurate for only very slender geometries. The present work assesses the accuracy of these methods relative to high-fidelity Euler, compressible computational-fluid-dynamics solutions for a set of axisymmetric geometries with varying radius-to-length ratios (R/L). Grid-resolution studies are included for all computational results to ensure grid-resolved results. Results show that the low-fidelity analytic and computational methods match the Euler CFD predictions to around a single drag count (~1.0 × 10–4) for geometries with R/L ≤ 0.05 and Mach numbers from 1.1 to 2.0. The difference in predicted wave drag rapidly increases, to over 30 drag counts in some cases, for geometries approaching R/L ≈ 0.1, indicating that the slender-body assumption of linear supersonic theory is violated for larger radius-to-length ratios. All three methods considered predict that the wave drag coefficient is nearly independent of Mach number for the geometries included in this study. Results of the study can be used to validate other numerical models and estimate the error in low-fidelity analytic and computational methods for predicting wave drag of axisymmetric geometries, depending on radius-to-length ratios.

Author ORCID Identifier

Troy Abraham https://orcid.org/0009-0002-9360-928X

Douglas Hunsaker https://orcid.org/0000-0001-8106-7466

Journal Article Version
Version of Record
Citation Information
Abraham, T.; Lazzara, D.; Hunsaker, D. Multifidelity Comparison of Supersonic Wave Drag Prediction Methods Using Axisymmetric Bodies. Aerospace 2024, 11, 359. https://doi.org/10.3390/aerospace11050359