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A Hybrid Computational Fluid Dynamics Procedure for Sonic Boom Prediction

Authors: Kelly Laflin; Steven Klausmeyer; Mark Chaffin;

A Hybrid Computational Fluid Dynamics Procedure for Sonic Boom Prediction

Abstract

A hybrid computational fluid dynamics procedure for sonic boom predi ction is presented. The method begins with either Euler or Navier -Stokes unstructured mesh computations with mesh refinement adaptation performed to efficiently resolve the solution to a high degree of resolution in the extreme -near -field of the aircraft. Flow fi el d data is extracted from the unstructured mesh solution along a cylinder existing within the adapted region. This data is used as boundary conditions for an Euler structured mesh computation to resolve the pressure field several body lengths away from the aircraft. The method leverages advantages of both unstructured and structured meshes while avoiding many of their disadvantages. Near -field pressure measurements predicted using the method are compared to wind tunnel measured pressure data of two NASA shape sonic boom aircraft models. Comparisons to Shaped Sonic Boom Demonstrator flight test data are also presented. Results indicate that the method can confidently be used for sonic boom predictions.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Average
Top 10%
Average
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