Three-dimensional aerodynamic shape optimization using genetic evolution and gradient search algorithms

Norman F. Foster; George S. Dulikravich; Jeff Bowles

Three-dimensional aerodynamic shape optimization using genetic evolution and gradient search algorithms

Norman F. Foster, George S. Dulikravich, Jeff Bowles

Applied Research Laboratory (ARL)

Research output: Contribution to conference › Paper › peer-review

1 Scopus citations

Abstract

This study introduces various gradient search methods as well as hybrid genetic techniques that achieve impressive convergence rates on constrained problems. These methods are applied to threedimensional shape optimization of ogive-shaped, starshaped, and spiked projectiles and lifting bodies in a hypersonic flow. Flow field analyses are performed using Newtonian flow theory and, in certain cases verified using a parabolized Navier-Stokes (PNS) flow analysis algorithm. Three-dimensional geometrical rendering is achieved using a variety of techniques including beta-splines from the computer graphics industry.

Original language	English (US)
State	Published - Jan 1 1996
Event	34th Aerospace Sciences Meeting and Exhibit, 1996 - Reno, United States Duration: Jan 15 1996 → Jan 18 1996

Other

Other	34th Aerospace Sciences Meeting and Exhibit, 1996
Country/Territory	United States
City	Reno
Period	1/15/96 → 1/18/96

All Science Journal Classification (ASJC) codes

Space and Planetary Science
Aerospace Engineering

Cite this

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title = "Three-dimensional aerodynamic shape optimization using genetic evolution and gradient search algorithms",

abstract = "This study introduces various gradient search methods as well as hybrid genetic techniques that achieve impressive convergence rates on constrained problems. These methods are applied to threedimensional shape optimization of ogive-shaped, starshaped, and spiked projectiles and lifting bodies in a hypersonic flow. Flow field analyses are performed using Newtonian flow theory and, in certain cases verified using a parabolized Navier-Stokes (PNS) flow analysis algorithm. Three-dimensional geometrical rendering is achieved using a variety of techniques including beta-splines from the computer graphics industry.",

author = "Foster, {Norman F.} and Dulikravich, {George S.} and Jeff Bowles",

year = "1996",

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TY - CONF

T1 - Three-dimensional aerodynamic shape optimization using genetic evolution and gradient search algorithms

AU - Foster, Norman F.

AU - Dulikravich, George S.

AU - Bowles, Jeff

PY - 1996/1/1

Y1 - 1996/1/1

N2 - This study introduces various gradient search methods as well as hybrid genetic techniques that achieve impressive convergence rates on constrained problems. These methods are applied to threedimensional shape optimization of ogive-shaped, starshaped, and spiked projectiles and lifting bodies in a hypersonic flow. Flow field analyses are performed using Newtonian flow theory and, in certain cases verified using a parabolized Navier-Stokes (PNS) flow analysis algorithm. Three-dimensional geometrical rendering is achieved using a variety of techniques including beta-splines from the computer graphics industry.

AB - This study introduces various gradient search methods as well as hybrid genetic techniques that achieve impressive convergence rates on constrained problems. These methods are applied to threedimensional shape optimization of ogive-shaped, starshaped, and spiked projectiles and lifting bodies in a hypersonic flow. Flow field analyses are performed using Newtonian flow theory and, in certain cases verified using a parabolized Navier-Stokes (PNS) flow analysis algorithm. Three-dimensional geometrical rendering is achieved using a variety of techniques including beta-splines from the computer graphics industry.

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M3 - Paper

T2 - 34th Aerospace Sciences Meeting and Exhibit, 1996

Y2 - 15 January 1996 through 18 January 1996

ER -

Three-dimensional aerodynamic shape optimization using genetic evolution and gradient search algorithms

Abstract

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All Science Journal Classification (ASJC) codes

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