Katalog Plus
Bibliothek der Frankfurt UAS
Bald neuer Katalog: sichern Sie sich schon vorab Ihre persönlichen Merklisten im Nutzerkonto: Anleitung.
Dieses Ergebnis aus BASE kann Gästen nicht angezeigt werden.  Login für vollen Zugriff.

On developing methods for predicting the laminar–turbulent transition in aerodynamic applications

Title: On developing methods for predicting the laminar–turbulent transition in aerodynamic applications
Authors: Boiko, A V; Demyanko, K V; Ivanov, A V; Kirilovskiy, S V; Mishenko, D A; Nechepurenko, Y M; Poplavskaya, T V
Source: Journal of Physics: Conference Series ; volume 1666, issue 1, page 012009 ; ISSN 1742-6588 1742-6596
Publisher Information: IOP Publishing
Publication Year: 2020
Description: Actual fundamental and computational problems of laminar–turbulent transition prediction in aerodynamic flows are discussed. The author’s approach based on the exp(N)-method is briefly described. The results of experimental studies aimed at clarifying the calibration of the exp(N)-method is highlighted. Particularly, one of the main problem is a limited experimental database for verification of different approaches for the transition prediction. To extend such a database, it is necessary to document in detail the flow parameters (velocity, free-stream turbulence level, etc.) and the model parameters (geometry, surface roughness, angle of attack, etc.) as well as to document in a statistically sound way the position of laminar-turbulent transition on the surface of experimental model. To this end we develop an experimental method of parametric measurements in different flow regimes of three-dimensional aerodynamic flows based on the thermal analysis of the surface.
Document Type: article in journal/newspaper
Language: unknown
DOI: 10.1088/1742-6596/1666/1/012009
DOI: 10.1088/1742-6596/1666/1/012009/pdf
Availability: https://doi.org/10.1088/1742-6596/1666/1/012009; https://iopscience.iop.org/article/10.1088/1742-6596/1666/1/012009/pdf; https://iopscience.iop.org/article/10.1088/1742-6596/1666/1/012009
Rights: http://creativecommons.org/licenses/by/3.0/ ; https://iopscience.iop.org/info/page/text-and-data-mining
Accession Number: edsbas.3C4B4933
Database: BASE