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Tom Zickuhr

Researcher at Langley Research Center

Publications -  10
Citations -  875

Tom Zickuhr is an academic researcher from Langley Research Center. The author has contributed to research in topics: Drag & Computational fluid dynamics. The author has an hindex of 8, co-authored 10 publications receiving 803 citations.

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Proceedings ArticleDOI

Summary of the Fourth AIAA CFD Drag Prediction Workshop

TL;DR: The workshop is focused on the prediction of both absolute and differential drag levels for wing-body and wing-alone configuarations that are representative of transonic transport aircraft.
Journal ArticleDOI

Abridged Summary of the Third AIAA Computational Fluid Dynamics Drag Prediction Workshop

TL;DR: AIAA Drag Prediction Workshop (DPW-III) as discussed by the authors focused on the prediction of both absolute and differential drag levels for wing-body and wing-alone configurations that are representative of transonic transport aircraft.
Proceedings ArticleDOI

Summary of Data from the First AIAA CFD Drag Prediction Workshop

TL;DR: The AIAA CFD Drag Prediction Workshop as discussed by the authors was designed specifically to assess the state-of-the-art of computational fluid dynamics methods for force and moment prediction, and the results showed that well validated Reynolds-Averaged Navier-Stokes CFD methods are sufficiently accurate to make design decisions based on predicted drag.
Journal ArticleDOI

Grid Quality and Resolution Issues from the Drag Prediction Workshop Series

TL;DR: In this paper, the effect of grid resolution and grid quality on aerodynamic drag prediction has been examined in detail and recommendations for improvements in mesh generation technology which have the potential to impact the state-of-the-art of aerodynamic prediction are given.
Proceedings ArticleDOI

Summary of the Third AIAA CFD Drag Prediction Workshop

TL;DR: In this paper, the predicted absolute and differential drag levels for wing-body and wing-alone configurations of transonic transport aircraft were predicted using the Reynolds-Averaged Navier-Stokes computational fluid Dynamics Methods.