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Multiscale Structural Optimization for Applications in Thermal Stability and Actuation.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Multiscale Structural Optimization for Applications in Thermal Stability and Actuation./
Author:	Snyder, Isabella.
Description:	1 online resource (70 pages)
Notes:	Source: Masters Abstracts International, Volume: 86-01.
Contained By:	Masters Abstracts International86-01.
Subject:	Mechanical engineering. -
Online resource:	click for full text (PQDT)
ISBN:	9798383206287

Multiscale Structural Optimization for Applications in Thermal Stability and Actuation.
Snyder, Isabella.

Multiscale Structural Optimization for Applications in Thermal Stability and Actuation. - 1 online resource (70 pages)

Source: Masters Abstracts International, Volume: 86-01.

Thesis (M.S.)--Drexel University, 2024.

Includes bibliographical references

This thesis outlines a novel multiscale optimization framework for designing multifunctional structures that must withstand mechanical and thermal loads. The objective is to exploit the unique potential of spatially varying microstructures for enhanced thermal stability and actuation capabilities. The methodology hinges on a three-phase material design within the microstructure, composed of materials with high and low coefficients of thermal expansion (CTE) and void material, to achieve a spectrum of CTE from negative to positive. By optimizing the layout of these microstructures within a macrostructure, it is possible to induce desired thermomechanical behaviors, accommodating extreme conditions and precise deformations.To address the computational challenges inherent in designing complex multiscale structures, the research utilizes a deep neural network (DNN) surrogate model for numerical homogenization, significantly reducing the computational cost. The surrogate model predicts effective material properties, which are confirmed against traditional finite element analysis. The structure is optimized using an objective function and a constraint function. This paper analyzes how the use of compliance as the objective function and displacement as a component of the constraint function affects the results. Presented examples validate the optimization approach for thermal stability, where the target displacement is zero, and actuation, where the target displacement is non-zero.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798383206287Subjects--Topical Terms:

557493
Mechanical engineering.
Subjects--Index Terms:

ActuationIndex Terms--Genre/Form:

554714
Electronic books.

Multiscale Structural Optimization for Applications in Thermal Stability and Actuation.
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500 $a Source: Masters Abstracts International, Volume: 86-01.
500 $a Advisor: Najafi, Ahmad Raeisi.
502 $a Thesis (M.S.)--Drexel University, 2024.
504 $a Includes bibliographical references
520 $a This thesis outlines a novel multiscale optimization framework for designing multifunctional structures that must withstand mechanical and thermal loads. The objective is to exploit the unique potential of spatially varying microstructures for enhanced thermal stability and actuation capabilities. The methodology hinges on a three-phase material design within the microstructure, composed of materials with high and low coefficients of thermal expansion (CTE) and void material, to achieve a spectrum of CTE from negative to positive. By optimizing the layout of these microstructures within a macrostructure, it is possible to induce desired thermomechanical behaviors, accommodating extreme conditions and precise deformations.To address the computational challenges inherent in designing complex multiscale structures, the research utilizes a deep neural network (DNN) surrogate model for numerical homogenization, significantly reducing the computational cost. The surrogate model predicts effective material properties, which are confirmed against traditional finite element analysis. The structure is optimized using an objective function and a constraint function. This paper analyzes how the use of compliance as the objective function and displacement as a component of the constraint function affects the results. Presented examples validate the optimization approach for thermal stability, where the target displacement is zero, and actuation, where the target displacement is non-zero.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2024
538 $a Mode of access: World Wide Web
650 4 $a Mechanical engineering. $3 557493
650 4 $a Mechanics. $3 527684
650 4 $a Computer engineering. $3 569006
650 4 $a Thermodynamics. $3 596513
653 $a Actuation
653 $a Computational cost
653 $a Deep neural network
653 $a Multiscale structures
653 $a Optimization
653 $a Thermal stability
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710 2 $a Drexel University. $b Mechanical Engineering and Mechanics (College of Engineering). $3 1180351
773 0 $t Masters Abstracts International $g 86-01.
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