Optimal distribution of the relaxation behavior of linear viscoelastic materials by the particle swarm optimization method applied to the problem of a twisting shaft

Saito, Yuta Steven

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https://hdl.handle.net/2142/101597 Copy

Description

Title

Optimal distribution of the relaxation behavior of linear viscoelastic materials by the particle swarm optimization method applied to the problem of a twisting shaft

Author(s)

Saito, Yuta Steven

Issue Date

2018-07-17

Director of Research (if dissertation) or Advisor (if thesis)

Hilton, Harry H.

Department of Study

Aerospace Engineering

Discipline

Aerospace Engineering

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(s)

Optimization methods, viscoelastic materials, functionally graded materials

Abstract

With rise of new manufacturing techniques such as additive manufacturing, there has been an increase in attention in designing components with distributed material properties. Utilizing the benefits of compliant mechanics, a strategic distribution of the relaxation behavior of linear viscoelastic materials was proposed. The motivation of this research is to outline a mathematical/computational framework for the material distribution optimization problem of a linear viscoelastic material. The distribution of the relaxation behavior (coefficients of the Prony series expansion) across the system was obtained to achieve a target performance of the dynamic system by the particle swarm optimization (PSO) method. The (PSO) method was applied to a simple fixed shaft to demonstrate the improvement in the structural response of the system and convergence capability of the method. While the simulations showed great improvements in the structural response, the lack of thorough search of the solution space to keep the computation time within a reasonable time frame meant that the method was unable to determine confidently the reaching of a global minimum. Additionally, the time for convergence increased with the increase of the number of nodes that were optimized. In order to confidently reach the global minimum within a reasonable time frame, the computational efficiency of the PSO method must be improved such that the particles can thoroughly search the entire solution space. Additionally, the inclusion of additional constraints to ensure the continuity of the moduli across neighboring nodes must be done for the actual construction of the design.

Graduation Semester

2018-08

Type of Resource

text

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http://hdl.handle.net/2142/101597

Copyright and License Information

Copyright 2018 Yuta Saito

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