Prediction of compressibility effects using unstructured Euler analysis on vortex dominated flow fields

Tom A. Kinard, Dennis B. Finley, Steve L. Karman

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Two unstructured-grid Euler methods, one based on Cartesian grids and the other on tetrahedral grids, are applied to simulate vortex flows on two modular transonic vortex interaction wind-tunnel models. Both models have sharp-edged chined forebody and cropped-delta wing but different vertical tail arrangements: one has centerline tail and the other twin tail. The principal objective of the study is to assess the ability of the two Euler methods in predicting compressibility effects. The approach involves comparing computed forces, moments and surface pressures from the two methods with each other and with experimental data. In this paper, force and moment correlations are presented for symmetric and asymmetric flow conditions at 0.4 and 0.85 Mach numbers. In addition, surface pressure correlations are shown for the 20 angle-of-attack case. The results show that Euler methods can provide meaningful data to support preliminary design of fighter aircraft configurations whose aerodynamic characteristics are dominated by vortex flows in some parts of their flight envelope.

Original languageEnglish
Title of host publication14th Applied Aerodynamics Conference
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781563472121
DOIs
StatePublished - 1996
Externally publishedYes
Event14th Applied Aerodynamics Conference, 1996 - New Orleans, United States
Duration: Jun 17 1996Jun 20 1996

Publication series

Name14th Applied Aerodynamics Conference

Conference

Conference14th Applied Aerodynamics Conference, 1996
Country/TerritoryUnited States
CityNew Orleans
Period06/17/9606/20/96

Fingerprint

Dive into the research topics of 'Prediction of compressibility effects using unstructured Euler analysis on vortex dominated flow fields'. Together they form a unique fingerprint.

Cite this