Results 181 to 190 of about 21,521 (207)
Some of the next articles are maybe not open access.

Two-dimensional airfoil shape optimization for airfoils at low speeds

AIAA Modeling and Simulation Technologies Conference, 2012
This paper presents a fast methodology for the design of two-dimensional low-speed airfoils. We propose a methodology in which the design process starts from an already known airfoil or from a new defined airfoil by imposing some basic geometrical characteristics, such as: the airfoil’s radius at the leading edge, the maximum height of the airfoil’s ...
Paul Silisteanu, Ruxandra Botez
openaire   +1 more source

Nonsinusoidal Path Optimization of a Flapping Airfoil

AIAA Journal, 2007
The path of a flapping airfoil undergoing a combined, nonsinusoidal pitching and plunging motion is optimized for maximum thrust and/or propulsive efficiency. The nonsinusoidal, periodic flapping motion is described using nonuniform rational B splines. A gradient based algorithm is then employed for the optimization of the nonuniform rational B-spline ...
TUNCER, İSMAİL HAKKI, Kaya, MUSTAFA
openaire   +2 more sources

Multi-objective Optimal Airfoil Design

2018
The aerodynamic design of airfoil should have optimal performance on a wide range of operating conditions. The requirements of airfoil design are often conflicting. Although there exists many studies on direct and inverse design of airfoil, less attention has been paid to simultaneous consideration of multiple conflicting objectives.
Jian-Qiao Sun   +3 more
openaire   +1 more source

Airfoil Topology Optimization using Teaching-Learning based Optimization

International Journal of Applied Metaheuristic Computing, 2015
This paper primarily deals with the optimization of airfoil topology using teaching-learning based optimization, a recently proposed heuristic technique, investigating performance in comparison to Genetic Algorithm and Particle Swarm Optimization. Airfoil parametrization and co-ordinate manipulations are accomplished using piecewise b-spline curves ...
Dushhyanth Rajaram   +2 more
openaire   +1 more source

Bézier–PARSEC parameterization for airfoil optimization

Canadian Aeronautics and Space Journal, 2009
A new parameterization method is developed for airfoils. The method combines the best characteristics of two previous polynomial methods: the Bezier parameterization and the PARSEC parameterization...
T. Rogalsky, R W Derksen
openaire   +1 more source

Multifidelity Optimization for High-Lift Airfoils

54th AIAA Aerospace Sciences Meeting, 2016
High-lift airfoil design is subjected to many constraints in terms of regulation and efficiency. It also involves complex flows that are still challenging to be estimated by Computational Fluid Dynamics. The time required to solve flow around a multielement airfoil makes it difficultly applicable to optimization.
Jean Demange, A Mark Savill, T. Kipouros
openaire   +1 more source

Deep neural network for airfoil optimization

AIAA SCITECH 2022 Forum, 2022
Wenhui Peng, Yao Zhang, Michel Desmarais
openaire   +1 more source

Optimization of airfoils for maximum lift

CASI/AIAA Subsonic Aero-and Hydro-Dynamics Meeting, 1969
The pressure distribution which provides the maximum lift without separation for a monoelement airfoil in an incompressible flow is determined using existing boundary-layer theory and the calculus of variations. The airfoil profiles corresponding to these pressure distributions are determined using second-order airfoil theory.
ROBERT H. LIEBECK, ALLEN I. ORMSBEE
openaire   +1 more source

Optimization of Multi-Element Airfoils

1981
Abstract : A review of techniques aimed at maximizing C1/Cd and C1 for multi- element airfoils showed the need for more exhaustive testing of possible configurations of flap deflection, slot geometry and airfoil angle of attack. For a typical 4-element airfoil, the number of possible configurations can easily be in the billions.
openaire   +1 more source

Learning-Guided Exploration in Airfoil Optimization

2013
A learning-based exploration approach is proposed to escape from the basins of attraction of converged-to optima, by selecting on what is termed the interestingness of a solution. This interestingness is based on the modeling error made by a surrogate model that is trained on all solutions encountered earlier during the search.
Edgar Reehuis   +3 more
openaire   +1 more source

Home - About - Disclaimer - Privacy