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Title:

Turbulence Model Extension for Vortex Dominated Flows and Optimization with Experimental Data

Document type:
Konferenzbeitrag
Author(s):
Moioli, M.; Breitsamter, C.; Sørensen, K.
Abstract:
This document provides information and instructions for preparing a Full Paper to be included in the Proceedings of 14th WCCM – ECCOMAS CONGRESS 2020. © 2021, Univelt Inc., All rights reserved.
Keywords:
Artificial Neural Network; Data-Driven Models; Delta Wing; Modeling; Optimization; RANS; Turbulence; Vortex Dominated Flows
Dewey Decimal Classification:
620 Ingenieurwissenschaften
Book / Congress title:
14th WCCM-ECCOMAS Congress
Publisher:
CIMNE
Date of publication:
01.01.2021
Year:
2021
Covered by:
Scopus
Language:
en
Fulltext / DOI:
doi:10.23967/wccm-eccomas.2020.349
WWW:
https://www.scipedia.com/public/Moioli_et_al_2021a
Notes:
Funding text 1 The funding of parts of these investigations within the LUFO VI-1 project DIGIfly-I (Digital Flight of Air Vehicles - Adaptive turbulence model with neural network conditioning applied to wing flows featuring leading edge vortex systems, FKZ: 20X1909I) by the German Federal Ministry for Economic Affairs and Energy (BMWi) is gratefully acknowledged. Furthermore, the authors thank Airbus Defence and Space for the fruitful cooperation and the German Aerospace Center (DLR) for provid...     »
TUM Institution:
Lehrstuhl für Aerodynamik und Strömungsmechanik
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