You are here

DESIGN OPTIMIZATION OF SOLID ROCKET MOTOR GRAINS FOR INTERNAL BALLISTIC PERFORMANCE

Download pdf | Full Screen View

Date Issued:
2006
Abstract/Description:
The work presented in this thesis deals with the application of optimization tools to the design of solid rocket motor grains per internal ballistic requirements. Research concentrated on the development of an optimization strategy capable of efficiently and consistently optimizing virtually an unlimited range of radial burning solid rocket motor grain geometries. Optimization tools were applied to the design process of solid rocket motor grains through an optimization framework developed to interface optimization tools with the solid rocket motor design system. This was done within a programming architecture common to the grain design system, AML. This commonality in conjunction with the object-oriented dependency-tracking features of this programming architecture were used to reduce the computational time of the design optimization process. The optimization strategy developed for optimizing solid rocket motor grain geometries was called the internal ballistic optimization strategy. This strategy consists of a three stage optimization process; approximation, global optimization, and highfidelity optimization, and optimization methodologies employed include DOE, genetic algorithms, and the BFGS first-order gradient-based algorithm. This strategy was successfully applied to the design of three solid rocket motor grains of varying complexity. The contributions of this work was the development and application of an optimization strategy to the design process of solid rocket motor grains per internal ballistic requirements.
Title: DESIGN OPTIMIZATION OF SOLID ROCKET MOTOR GRAINS FOR INTERNAL BALLISTIC PERFORMANCE.
24 views
10 downloads
Name(s): Hainline, Roger, Author
Nayfeh, Jamal, Committee Chair
University of Central Florida, Degree Grantor
Type of Resource: text
Date Issued: 2006
Publisher: University of Central Florida
Language(s): English
Abstract/Description: The work presented in this thesis deals with the application of optimization tools to the design of solid rocket motor grains per internal ballistic requirements. Research concentrated on the development of an optimization strategy capable of efficiently and consistently optimizing virtually an unlimited range of radial burning solid rocket motor grain geometries. Optimization tools were applied to the design process of solid rocket motor grains through an optimization framework developed to interface optimization tools with the solid rocket motor design system. This was done within a programming architecture common to the grain design system, AML. This commonality in conjunction with the object-oriented dependency-tracking features of this programming architecture were used to reduce the computational time of the design optimization process. The optimization strategy developed for optimizing solid rocket motor grain geometries was called the internal ballistic optimization strategy. This strategy consists of a three stage optimization process; approximation, global optimization, and highfidelity optimization, and optimization methodologies employed include DOE, genetic algorithms, and the BFGS first-order gradient-based algorithm. This strategy was successfully applied to the design of three solid rocket motor grains of varying complexity. The contributions of this work was the development and application of an optimization strategy to the design process of solid rocket motor grains per internal ballistic requirements.
Identifier: CFE0001236 (IID), ucf:46929 (fedora)
Note(s): 2006-08-01
M.S.
Engineering and Computer Science, Department of Mechanical, Materials, and Aerospace Engineering
Masters
This record was generated from author submitted information.
Subject(s): solid rocket motor
propellant
optimization
internal ballistic
approximation
internal ballistic optimization strategy
surface recession
BFGS
Persistent Link to This Record: http://purl.flvc.org/ucf/fd/CFE0001236
Restrictions on Access: public
Host Institution: UCF

In Collections