scholarly journals Enhanced data efficiency using deep neural networks and Gaussian processes for aerodynamic design optimization

2021 ◽  
Vol 111 ◽  
pp. 106522
Author(s):  
S. Ashwin Renganathan ◽  
Romit Maulik ◽  
Jai Ahuja
Keyword(s):  
Neural Networks ◽  
Design Optimization ◽  
Gaussian Processes ◽  
Deep Neural Networks ◽  
Aerodynamic Design ◽  
Aerodynamic Design Optimization ◽  
Data Efficiency

scholarly journals Numerical Investigation of an Optimized Rotor Head Fairing for the RACER Compound Helicopter in Cruise Flight

Aerospace ◽  
2021 ◽  
Vol 8 (3) ◽  
pp. 66
Author(s):  
Patrick Pölzlbauer ◽  
Andreas Kümmel ◽  
Damien Desvigne ◽  
Christian Breitsamter
Keyword(s):  
Drag Reduction ◽  
Design Optimization ◽  
Cost Effective ◽  
Aerodynamic Design ◽  
Ansys Fluent ◽  
Aerodynamic Design Optimization ◽  
Flow Phenomena ◽  
Compound Helicopter ◽  
Rotor Head ◽  
Cruise Flight

The present work is part of the Clean Sky 2 project Full-Fairing Rotor Head Aerodynamic Design Optimization (FURADO), which deals with the aerodynamic design optimization of a full-fairing rotor head for the Rapid And Cost-Effective Rotorcraft (RACER) compound helicopter. The rotor head is a major drag source and previous investigations have revealed that the application of rotor head fairings can be an effective drag reduction measure. As part of the full-fairing concept, a new blade-sleeve fairing was aerodynamically optimized for cruise flight. Within this publication, the newly developed blade-sleeve fairing is put to test on an isolated, five-bladed rotor head and compared to an already existing reference blade-sleeve fairing, which was developed at Airbus Helicopters. Numerical flow simulations are performed with ANSYS Fluent 2019 R2 considering a rotating rotor head with cyclic pitch movement. The aerodynamic forces of the isolated rotor head are analyzed to determine the performance benefit of the newly developed blade-sleeve fairing. A drag reduction of 4.7% and a lift increase of 20% are obtained in comparison to the Airbus Helicopters reference configuration. Furthermore, selected surface and flow field quantities are presented to give an overview on the occurring flow phenomena.

scholarly journals Double-stage Metamodel and Its Application in Aerodynamic Design Optimization

2011 ◽  
Vol 24 (5) ◽  
pp. 568-576 ◽  
Author(s):  
Dehu ZHANG ◽  
Zhenghong GAO ◽  
Likeng HUANG ◽  
Mingliang WANG
Keyword(s):  
Design Optimization ◽  
Aerodynamic Design ◽  
Aerodynamic Design Optimization

Practical considerations in aerodynamic design optimization

1995 ◽  
Author(s):  
W Jou ◽  
W Huffman ◽  
D Young ◽  
R Melvin ◽  
M Bieterman ◽  
...  
Keyword(s):  
Design Optimization ◽  
Aerodynamic Design ◽  
Aerodynamic Design Optimization

Aerodynamic Design Optimization of a Staggered Rotors Octocopter Based on Surrogate Model

2021 ◽  
Vol 34 (4) ◽  
Author(s):  
He Zhu ◽  
Hong Nie ◽  
Limao Zhang ◽  
Siqiang Deng ◽  
Xiaohui Wei
Keyword(s):  
Design Optimization ◽  
Surrogate Model ◽  
Aerodynamic Design ◽  
Aerodynamic Design Optimization

Adjoint-Based Methods in Aerodynamic Design-Optimization

1998 ◽  
pp. 91-112 ◽  
Author(s):  
Eugene M. Cliff ◽  
Matthias Heinkenschloss ◽  
Ajit R. Shenoy
Keyword(s):  
Design Optimization ◽  
Aerodynamic Design ◽  
Aerodynamic Design Optimization
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