Title page for ETD etd-32298-85910


Type of Document Master's Thesis
Author Hanuska, Alexander Robert Jr.
Author's Email Address ahanuska@vt.edu
URN etd-32298-85910
Title Thermal Characterization of Complex Aerospace Structures
Degree Master of Science
Department Mechanical Engineering
Advisory Committee
Advisor Name Title
Scott, Elaine P. Committee Chair
Diller, Thomas E. Committee Member
Vick, Brian L. Committee Member
Keywords
  • Parameter Estimation
  • Aerospace Structures
  • Genetic Algorithm
Date of Defense 1998-04-16
Availability unrestricted
Abstract
Predicting the performance of complex structures exposed to harsh

thermal environments is a crucial issue in many of today's aerospace

and space designs. To predict the thermal stresses a structure might

be exposed to, the thermal properties of the independent materials

used in the design of the structure need to be known. Therefore, a

noninvasive estimation procedure involving Genetic Algorithms was

developed to determine the various thermal properties needed to

adequately model the Outer Wing Subcomponent (OWS), a structure located at the trailing edge of the High Speed Civil Transport's (HSCT) wing tip.

Due to the nature of the nonlinear least-squares estimation method

used in this study, both theoretical and experimental temperature

histories were required. Several one-dimensional and two-dimensional finite element models of

the OWS were developed to compute the transient theoretical

temperature histories. The experimental data were obtained from

optimized experiments that were run at various surrounding

temperature settings to investigate the temperature dependence of the

estimated properties. An experimental optimization was performed to

provide the most accurate estimates and reduce the confidence

intervals.

The simultaneous estimation of eight thermal properties, including the

volumetric heat capacities and out-of-plane thermal conductivities of

the facesheets, the honeycomb, the skins, and the torque tubes, was

successfully completed with the one-dimensional model and the results used to

evaluate the remaining in-plane thermal conductivities of the

facesheets, the honeycomb, the skins, and the torque tubes with the

two-dimensional model. Although experimental optimization did not eliminate all

correlation between the parameters, the minimization procedure based

on the Genetic Algorithm performed extremely well, despite the high

degree of correlation and low sensitivity of many of the parameters.

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