Title page for ETD etd-82597-124631


Type of Document Dissertation
Author Balabanov, Vladimir Olegovich
Author's Email Address balabanv@apollo.aoe.vt.edu
URN etd-82597-124631
Title Development of Approximations for HSCT Wing Bending Material Weight using Response Surface Methodology
Degree PhD
Department Aerospace and Ocean Engineering
Advisory Committee
Advisor Name Title
Haftka, Raphael T. Committee Chair
Grossman, Bernard M. Committee Member
Hughes, Owen F. Committee Member
Kapania, Rakesh K. Committee Member
Mason, William H. Committee Member
Watson, Layne T. Committee Member
Keywords
  • Structural optimization
  • Optimization
  • Finite element analysis
  • Finite element optimization
  • Design
  • Response Surface
  • Design of experiments
  • Multidisciplinary optimization
  • Parallel computing
Date of Defense 1997-05-09
Availability unrestricted
Abstract
A procedure for generating a customized weight

function for wing bending material weight of a High Speed Civil Transport

(HSCT) is described. The weight function

is based on HSCT configuration parameters. A response

surface methodology is used to fit a quadratic polynomial to data gathered

from a large number of structural optimizations.

To reduce the time of performing a large number of structural optimizations,

coarse-grained parallelization with a master-slave processor

assignment on an Intel Paragon computer is used.

The results of the structural optimization are noisy.

Noise reduction in the structural optimization results is discussed.

It is shown that the response surface filters out this noise.

A statistical design of experiments technique is used

to minimize the number of required structural optimizations and to maintain

accuracy. Simple analysis techniques

are used to find regions of the design space where reasonable HSCT designs

could occur, thus customizing the weight function to the design requirements of

the HSCT,

while the response surface itself is created employing detailed analysis

methods.

Analysis of variance is used to

reduce the number of polynomial terms in the response surface model function.

Linear and constant corrections based on a small number of high fidelity

results

are employed to improve the accuracy of the

response surface model.

Configuration optimization of the HSCT employing a customized weight function

is compared to the configuration optimization of the HSCT with

a general weight function.

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