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Computational methods for design of smart material morphing structures with localized activation and actuation.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Computational methods for design of smart material morphing structures with localized activation and actuation./
作者:	Wang, Shuang.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2014,
面頁冊數:	107 p.
附註:	Source: Dissertations Abstracts International, Volume: 76-09, Section: B.
Contained By:	Dissertations Abstracts International76-09B.
標題:	Civil engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3690858
ISBN:	9781321617337

Computational methods for design of smart material morphing structures with localized activation and actuation.
Wang, Shuang.

Computational methods for design of smart material morphing structures with localized activation and actuation. - Ann Arbor : ProQuest Dissertations & Theses, 2014 - 107 p.

Source: Dissertations Abstracts International, Volume: 76-09, Section: B.

Thesis (Ph.D.)--University of Pittsburgh, 2014.

This item must not be added to any third party search indexes.

There is significant ongoing interest to develop smart structure technologies, such as those that can automatically detect their condition and/or actively change their geometry or material behaviors to adapt to adverse conditions or otherwise improve operational efficiency. Of the structural materials under development for smart structure applications, active smart materials are attracting increasing attentions due to their abilities to exhibit controlled variable stiffness through activation (e.g., thermal, electrical, or light activation) and experience extremely large deformations and shape changes without damage. Active smart materials, such as shape memory polymers, are currently being explored and show promise as morphing skins, replacements to mechanical hinges, and other structural components. Moreover, in a general sense any structure or structural component that is fully composed of active smart materials could have limitless shape-changing functionality if provided sufficient activation and actuation. Towards the design or control of smart structures to utilize such functionality, it is of paramount importance to develop strategies to efficiently solve the coupled multi-physics inverse problems of identifying the optimal activation stimulus and mechanical actuation to achieve desired morphing processes. The objective of the present work is to develop and investigate a computational strategy for computationally efficient estimation of the parameters relating to the distribution and sequencing of activation and actuation for a morphing smart material structure or structural component to efficiently and effectively achieve a desired morphing function. This strategy combines a numerical representation of the morphing process with an optimization algorithm to estimate the activation and actuation parameters that best address cost functions and constraints relating to energy consumption, target shape change(s), morphing time, and/or damage prevention. In particular, the strategy is presented in the context of morphing structures or structural components composed of thermally responsive smart materials, and with specific properties based on thermally responsive shape memory polymers. First, as a proof of concept, an initial computational framework is presented which combines a numerical representation of linear thermo-mechanical behavior of conceptual smart material structures with a non-gradient based optimization technique to identify the activation and actuation parameters to achieve the desired morphing process. The computational inverse mechanics approach is shown through numerical tests to provide a generalized and flexible means to facilitate the use of smart material structures to achieve desired morphing processes with controllable localized activation and actuation. Towards improving the computational efficiency, a variation of the computational framework based on a gradient-based optimization algorithm using the adjoint method is then presented. Numerical examples are shown to verify and test the computational approach, in which the synchronization of multiple activation and actuation parameters is optimized with respect to the energy cost and target shape changes in morphing skeletal structural components. The computational design approach with the adjoint method is shown to provide the capability to efficiently identify activation and actuation parameters to achieve desired morphing capabilities. Moreover, the computational approach is shown to be capable of determining energy-efficient design solutions for a diverse set of target shape changes with fixed instrumentation, providing the potential for substantial functionality beyond what could be expected through traditional empirical design strategies. Finally, to establish the theories and implementation aspects that would be applicable to a variety of structural behaviors, material types and morphing concepts, the efficient computational framework using the adjoint method is generalized to be applicable to various thermally-responsive smart materials. Numerical tests are shown to verify the generalized computational framework, in which the synchronization of multiple activation and actuation parameters is optimized with respect to energy cost and target shape changes in morphing structures with nonlinear thermo-mechanical behaviors (rather than the purely linear behaviors considered previously). In addition, the significant influence of the nonlinearity in the thermal modeling on the morphing processes, and ultimately the design solutions is explored.

ISBN: 9781321617337Subjects--Topical Terms:

860360
Civil engineering.

Computational methods for design of smart material morphing structures with localized activation and actuation.
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100 1 $a Wang, Shuang. $3 3433284
245 1 0 $a Computational methods for design of smart material morphing structures with localized activation and actuation.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2014
300 $a 107 p.
500 $a Source: Dissertations Abstracts International, Volume: 76-09, Section: B.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Brigham, John C.
502 $a Thesis (Ph.D.)--University of Pittsburgh, 2014.
506 $a This item must not be added to any third party search indexes.
506 $a This item must not be sold to any third party vendors.
520 $a There is significant ongoing interest to develop smart structure technologies, such as those that can automatically detect their condition and/or actively change their geometry or material behaviors to adapt to adverse conditions or otherwise improve operational efficiency. Of the structural materials under development for smart structure applications, active smart materials are attracting increasing attentions due to their abilities to exhibit controlled variable stiffness through activation (e.g., thermal, electrical, or light activation) and experience extremely large deformations and shape changes without damage. Active smart materials, such as shape memory polymers, are currently being explored and show promise as morphing skins, replacements to mechanical hinges, and other structural components. Moreover, in a general sense any structure or structural component that is fully composed of active smart materials could have limitless shape-changing functionality if provided sufficient activation and actuation. Towards the design or control of smart structures to utilize such functionality, it is of paramount importance to develop strategies to efficiently solve the coupled multi-physics inverse problems of identifying the optimal activation stimulus and mechanical actuation to achieve desired morphing processes. The objective of the present work is to develop and investigate a computational strategy for computationally efficient estimation of the parameters relating to the distribution and sequencing of activation and actuation for a morphing smart material structure or structural component to efficiently and effectively achieve a desired morphing function. This strategy combines a numerical representation of the morphing process with an optimization algorithm to estimate the activation and actuation parameters that best address cost functions and constraints relating to energy consumption, target shape change(s), morphing time, and/or damage prevention. In particular, the strategy is presented in the context of morphing structures or structural components composed of thermally responsive smart materials, and with specific properties based on thermally responsive shape memory polymers. First, as a proof of concept, an initial computational framework is presented which combines a numerical representation of linear thermo-mechanical behavior of conceptual smart material structures with a non-gradient based optimization technique to identify the activation and actuation parameters to achieve the desired morphing process. The computational inverse mechanics approach is shown through numerical tests to provide a generalized and flexible means to facilitate the use of smart material structures to achieve desired morphing processes with controllable localized activation and actuation. Towards improving the computational efficiency, a variation of the computational framework based on a gradient-based optimization algorithm using the adjoint method is then presented. Numerical examples are shown to verify and test the computational approach, in which the synchronization of multiple activation and actuation parameters is optimized with respect to the energy cost and target shape changes in morphing skeletal structural components. The computational design approach with the adjoint method is shown to provide the capability to efficiently identify activation and actuation parameters to achieve desired morphing capabilities. Moreover, the computational approach is shown to be capable of determining energy-efficient design solutions for a diverse set of target shape changes with fixed instrumentation, providing the potential for substantial functionality beyond what could be expected through traditional empirical design strategies. Finally, to establish the theories and implementation aspects that would be applicable to a variety of structural behaviors, material types and morphing concepts, the efficient computational framework using the adjoint method is generalized to be applicable to various thermally-responsive smart materials. Numerical tests are shown to verify the generalized computational framework, in which the synchronization of multiple activation and actuation parameters is optimized with respect to energy cost and target shape changes in morphing structures with nonlinear thermo-mechanical behaviors (rather than the purely linear behaviors considered previously). In addition, the significant influence of the nonlinearity in the thermal modeling on the morphing processes, and ultimately the design solutions is explored.
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