Multiphysics Topology Optimization of Programmable Shape Memory Alloy-Based Smart Structures

"Smart structures can achieve lighter and simpler mechanisms than traditional apparatuses, by exploiting the stimuli-responsive properties of smart materials. However, the lack of specialized design tools has prevented the advancement of smart structures to the next level of ""mechanical intelligence"", with predictable and programmable active responses. This dissertation, leveraging shape memory alloys (SMAs) as an example, focuses on developing a comprehensive framework for the analysis and design of smart materials and structures to address the challenge of programming targeted multiphysics response into the material distribution. Central to this dissertation is a computational design optimization technique called topology optimization, which enables programming of the structural response by optimally selecting and distributing various material candidates to leverage their respective material responses. We investigate four major research topics that are crucial for successfully developing the proposed computational design framework. First, we present a generalized topology optimization algorithm that can simultaneously design for optimal thermal and elastic performance of structures. Second, we study accurate and efficient modeling of SMA-based smart structures. Third, we develop a transient, path-dependent sensitivity analysis to direct the programming of the thermomechanical response of the SMA structures. Last, we propose a multiphysics, multimaterial topology optimization scheme that can optimize the nonlinear thermomechanical performance of SMA-based smart structures. Based on this framework, we show that designs of SMA-based actuators for soft robotics can achieve an all-in-one solution for multiple functionalities with simple geometries, by programming their motion patterns into their material distribution. Results and Examples of this work suggest that the proposed framework provides a viable approach for developing SMA-based smart structures, and can be adopted in various application scenarios that require synthetic, intelligent mechanisms for use in natural, unstructured environments."

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Aerospace Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2022

Author dc:creator

• Kang, Ziliang

Contributors dc:contributor

• James, Kai A.
• Tortorelli, Daniel A.
• Geubelle, Philippe H.
• Sottos, Nancy R.

• shape memory alloys (SMA), topology optimization, computational design optimization, smart materials, programmable smart structures

Statement dc:rights

• Copyright 2021 Ziliang Kang

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/113331

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/113331