Prediction of wipp data using a relaxed-wake potential flow method

Julia A. Cole, Devin Barcelos, Travis Krebs, Michael Melville, Götz Bramesfeld

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


In this study, experimental results of the Workshop for Integrated Propulsion Prediction are compared with the authors’ initial and revised predictions using a relaxed-wake potential flow method. Digitized anonymous Navier-Stokes CFD predictions submitted by other groups are also provided for comparison. The potential flow method consists of higher-order distributed vorticity elements that are used to model both the propeller and wing surfaces and wakes. Viscous effects are taken into account through profile drag estimation using tabulated airfoil data and an empirical nacelle model. Inherent shortcomings of the method for this application lie primarily in the implicit assumption of a 2-D lift-curve slope of 2π per radian and an overly simplistic stall model for the wing. Regardless, predictions of wing lift and drag of the propeller-wing system found using this method are similar in accuracy to the CFD submissions in the pre-stall region. Four suggestions are made for ways to improve predictions: more extensive propeller performance data for validation, quantification of wind-tunnel freestream turbulence levels and model surface roughness, careful attention to detail with respect to the test model geometry, and more information on uncertainty with respect to the book-keeping process for separating drag from thrust in force measurements.

Original languageEnglish (US)
Title of host publicationAIAA AVIATION 2020 FORUM
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
Number of pages13
ISBN (Print)9781624105982
StatePublished - 2020
EventAIAA AVIATION 2020 FORUM - Virtual, Online
Duration: Jun 15 2020Jun 19 2020

Publication series



CityVirtual, Online

All Science Journal Classification (ASJC) codes

  • Nuclear Energy and Engineering
  • Aerospace Engineering
  • Energy Engineering and Power Technology


Dive into the research topics of 'Prediction of wipp data using a relaxed-wake potential flow method'. Together they form a unique fingerprint.

Cite this