{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/113331"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/113331","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Multiphysics Topology Optimization of Programmable Shape Memory Alloy-Based Smart Structures","abstract":"\"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.\"","abstract_html":""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."","abstract_has_math":false,"creators":["Kang, Ziliang"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Aerospace Engineering","degree_department":null,"school":null,"contributors":["James, Kai A.","Tortorelli, Daniel A.","Geubelle, Philippe H.","Sottos, Nancy R."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-01-12T22:56:12Z","date_published":"2022-01-12T22:56:12Z","updated_at":"2026-07-22T22:24:53Z","subjects":["shape memory alloys (SMA), topology optimization, computational design optimization, smart materials, programmable smart structures"],"languages":["en"],"rights":["Copyright 2021 Ziliang Kang"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/113331","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["James, Kai A.","Tortorelli, Daniel A.","Geubelle, Philippe H.","Sottos, Nancy R."]},{"key":"dc:creator","label":"Author","values":["Kang, Ziliang"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2022-01-12T22:56:12Z","2024-01-12T22:56:20Z","2021-07-16","2021-08"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Aerospace Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["shape memory alloys (SMA), topology optimization, computational design optimization, smart materials, programmable smart structures"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2021 Ziliang Kang"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/113331"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["\"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.\"","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2023-08-01","The student, Ziliang Kang, accepted the attached license on 2021-07-16 at 13:28.","The student, Ziliang Kang, submitted this Dissertation for approval on 2021-07-16 at 13:36.","This Dissertation was approved for publication on 2021-07-16 at 14:59.","DSpace SAF Submission Ingestion Package generated from Vireo submission #16985 on 2022-01-12 at 13:05:13","Made available in DSpace on 2022-01-12T22:56:12Z (GMT). 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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.\"","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2023-08-01","The student, Ziliang Kang, accepted the attached license on 2021-07-16 at 13:28.","The student, Ziliang Kang, submitted this Dissertation for approval on 2021-07-16 at 13:36.","This Dissertation was approved for publication on 2021-07-16 at 14:59.","DSpace SAF Submission Ingestion Package generated from Vireo submission #16985 on 2022-01-12 at 13:05:13","Made available in DSpace on 2022-01-12T22:56:12Z (GMT). No. of bitstreams: 2 KANG-DISSERTATION-2021.pdf: 15575583 bytes, checksum: f610b40c29a728728d9669059f3aad0a (MD5) LICENSE.txt: 4214 bytes, checksum: 3a489159d8fbc38a92033d8718af0b35 (MD5) Previous issue date: 2021-07-16","Embargo set by: Seth Robbins for item 121260 Lift date: 2024-01-12T22:56:20Z Reason: Author requested closed access (OA after 2yrs) in Vireo ETD system","Author requested closed access (OA after 2yrs) in Vireo ETD system","Limited"],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/2142/113331"],"dc:language":["en"],"dc:rights":["Copyright 2021 Ziliang Kang"],"dc:subject":["shape memory alloys (SMA), topology optimization, computational design optimization, smart materials, programmable smart structures"],"dc:title":["Multiphysics Topology Optimization of Programmable Shape Memory Alloy-Based Smart Structures"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Aerospace Engineering"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:53Z"}