Committee Chair
Belinskiy, Boris P.
Committee Member
Kong, Lingju; Cox, Christopher; Wang, Jin; Nichols, Roger
College
College of Engineering and Computer Science
Publisher
University of Tennessee at Chattanooga
Place of Publication
Chattanooga (Tenn.)
Abstract
We find an optimal mass of a structure described by a Sturm-Liouville (S-L) problem with a spectral parameter in the boundary conditions. While previous work on the subject focused on a somewhat simplified model, we consider a more general S-L problem. We use the calculus of variations approach to determine a set of critical points of a corresponding mass functional, yet these critical points - which we call \textit{predesigns} - do not necessarily themselves represent meaningful solutions. It is natural to expect a mass to be real and positive. To this end, we additionally introduce a set of solvability conditions on the S-L problem data, confirming that these critical points represent meaningful solutions we refer to as \textit{designs}. We further present the analytic continuation of these predesigns in regards to the spectral parameter as well as a discussion of the stability of these (pre)designs. We present a code that allows us to for the given data of the S-L problem check conditions of solvability, plot the design, and calculate the value of the functional that represents the optimal mass.
Acknowledgments
UTC Graduate School and Department of Mathematics
Degree
Ph. D.; A dissertation submitted to the faculty of the University of Tennessee at Chattanooga in partial fulfillment of the requirements of the degree of Doctor of Philosophy.
Date
12-2022
Subject
Calculus of variations; Differential equations
Document Type
Doctoral dissertations
DCMI Type
Text
Extent
xi, 71 leaves.
Language
English
Rights
http://rightsstatements.org/vocab/InC/1.0/
License
http://creativecommons.org/licenses/by/4.0/
Recommended Citation
Smith, Tanner, "Optimization for a Sturm--Liouville problem with the spectral parameter in the boundary condition" (2022). Masters Theses and Doctoral Dissertations.
https://scholar.utc.edu/theses/778
Department
Dept. of Computational Science