Target shape optimization of functionally graded shape memory alloy compliant mechanism

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Nickel Titanium (NiTi) shape memory alloys (SMAs) exhibit shape memory and/or superelastic properties, enabling them to demonstrate multifunctionality by engineering microstructural and compositional gradients at selected locations. This paper focuses on the design optimization of NiTi compliant mechanisms resulting in single-piece structures with functionally graded properties, based on user-defined target shape matching approach. The compositionally graded zones within the structures will exhibit an on demand superelastic effect (SE) response, exploiting the tailored mechanical behavior of the structure. The functional grading has been approximated by allowing the geometry and the superelastic properties of each zone to vary. The superelastic phenomenon has been taken into consideration using a standard nonlinear SMA material model, focusing only on 2 regions of interest: the linear region of higher Young's modulus of elasticity and the superelastic region with significantly lower Young's modulus of elasticity. Due to an outside load, the graded zones reach the critical stress at different stages based on their composition, position and geometry, allowing the structure morphing. This concept has been used to optimize the structures' geometry and mechanical properties to match a user-defined target shape structure. A multi-objective evolutionary algorithm (NSGA II - Non-dominated Sorting Genetic Algorithm) for constrained optimization of the structure's mechanical properties and geometry has been developed and implemented.

Original languageEnglish (US)
Title of host publicationModeling, Simulation and Control; Bio-Inspired Smart Materials and Systems; Energy Harvesting
PublisherAmerican Society of Mechanical Engineers
ISBN (Electronic)9780791850497
DOIs
StatePublished - Jan 1 2016
EventASME 2016 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2016 - Stowe, United States
Duration: Sep 28 2016Sep 30 2016

Publication series

NameASME 2016 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2016
Volume2

Other

OtherASME 2016 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2016
CountryUnited States
CityStowe
Period9/28/169/30/16

Fingerprint

Compliant mechanisms
Shape optimization
Shape memory effect
Elastic moduli
Geometry
Titanium
Nickel
Mechanical properties
Constrained optimization
Sorting
Evolutionary algorithms
Loads (forces)
Genetic algorithms
Chemical analysis

All Science Journal Classification (ASJC) codes

  • Building and Construction
  • Civil and Structural Engineering
  • Control and Systems Engineering
  • Mechanics of Materials

Cite this

Jovanova, J., Frecker, M. I., Hamilton, R. F., & Palmer, T. (2016). Target shape optimization of functionally graded shape memory alloy compliant mechanism. In Modeling, Simulation and Control; Bio-Inspired Smart Materials and Systems; Energy Harvesting [V002T03A006] (ASME 2016 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2016; Vol. 2). American Society of Mechanical Engineers. https://doi.org/10.1115/SMASIS2016-9070
Jovanova, Jovana ; Frecker, Mary I. ; Hamilton, Reginald Felix ; Palmer, Todd. / Target shape optimization of functionally graded shape memory alloy compliant mechanism. Modeling, Simulation and Control; Bio-Inspired Smart Materials and Systems; Energy Harvesting. American Society of Mechanical Engineers, 2016. (ASME 2016 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2016).
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abstract = "Nickel Titanium (NiTi) shape memory alloys (SMAs) exhibit shape memory and/or superelastic properties, enabling them to demonstrate multifunctionality by engineering microstructural and compositional gradients at selected locations. This paper focuses on the design optimization of NiTi compliant mechanisms resulting in single-piece structures with functionally graded properties, based on user-defined target shape matching approach. The compositionally graded zones within the structures will exhibit an on demand superelastic effect (SE) response, exploiting the tailored mechanical behavior of the structure. The functional grading has been approximated by allowing the geometry and the superelastic properties of each zone to vary. The superelastic phenomenon has been taken into consideration using a standard nonlinear SMA material model, focusing only on 2 regions of interest: the linear region of higher Young's modulus of elasticity and the superelastic region with significantly lower Young's modulus of elasticity. Due to an outside load, the graded zones reach the critical stress at different stages based on their composition, position and geometry, allowing the structure morphing. This concept has been used to optimize the structures' geometry and mechanical properties to match a user-defined target shape structure. A multi-objective evolutionary algorithm (NSGA II - Non-dominated Sorting Genetic Algorithm) for constrained optimization of the structure's mechanical properties and geometry has been developed and implemented.",
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Jovanova, J, Frecker, MI, Hamilton, RF & Palmer, T 2016, Target shape optimization of functionally graded shape memory alloy compliant mechanism. in Modeling, Simulation and Control; Bio-Inspired Smart Materials and Systems; Energy Harvesting., V002T03A006, ASME 2016 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2016, vol. 2, American Society of Mechanical Engineers, ASME 2016 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2016, Stowe, United States, 9/28/16. https://doi.org/10.1115/SMASIS2016-9070

Target shape optimization of functionally graded shape memory alloy compliant mechanism. / Jovanova, Jovana; Frecker, Mary I.; Hamilton, Reginald Felix; Palmer, Todd.

Modeling, Simulation and Control; Bio-Inspired Smart Materials and Systems; Energy Harvesting. American Society of Mechanical Engineers, 2016. V002T03A006 (ASME 2016 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2016; Vol. 2).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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T1 - Target shape optimization of functionally graded shape memory alloy compliant mechanism

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N2 - Nickel Titanium (NiTi) shape memory alloys (SMAs) exhibit shape memory and/or superelastic properties, enabling them to demonstrate multifunctionality by engineering microstructural and compositional gradients at selected locations. This paper focuses on the design optimization of NiTi compliant mechanisms resulting in single-piece structures with functionally graded properties, based on user-defined target shape matching approach. The compositionally graded zones within the structures will exhibit an on demand superelastic effect (SE) response, exploiting the tailored mechanical behavior of the structure. The functional grading has been approximated by allowing the geometry and the superelastic properties of each zone to vary. The superelastic phenomenon has been taken into consideration using a standard nonlinear SMA material model, focusing only on 2 regions of interest: the linear region of higher Young's modulus of elasticity and the superelastic region with significantly lower Young's modulus of elasticity. Due to an outside load, the graded zones reach the critical stress at different stages based on their composition, position and geometry, allowing the structure morphing. This concept has been used to optimize the structures' geometry and mechanical properties to match a user-defined target shape structure. A multi-objective evolutionary algorithm (NSGA II - Non-dominated Sorting Genetic Algorithm) for constrained optimization of the structure's mechanical properties and geometry has been developed and implemented.

AB - Nickel Titanium (NiTi) shape memory alloys (SMAs) exhibit shape memory and/or superelastic properties, enabling them to demonstrate multifunctionality by engineering microstructural and compositional gradients at selected locations. This paper focuses on the design optimization of NiTi compliant mechanisms resulting in single-piece structures with functionally graded properties, based on user-defined target shape matching approach. The compositionally graded zones within the structures will exhibit an on demand superelastic effect (SE) response, exploiting the tailored mechanical behavior of the structure. The functional grading has been approximated by allowing the geometry and the superelastic properties of each zone to vary. The superelastic phenomenon has been taken into consideration using a standard nonlinear SMA material model, focusing only on 2 regions of interest: the linear region of higher Young's modulus of elasticity and the superelastic region with significantly lower Young's modulus of elasticity. Due to an outside load, the graded zones reach the critical stress at different stages based on their composition, position and geometry, allowing the structure morphing. This concept has been used to optimize the structures' geometry and mechanical properties to match a user-defined target shape structure. A multi-objective evolutionary algorithm (NSGA II - Non-dominated Sorting Genetic Algorithm) for constrained optimization of the structure's mechanical properties and geometry has been developed and implemented.

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M3 - Conference contribution

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BT - Modeling, Simulation and Control; Bio-Inspired Smart Materials and Systems; Energy Harvesting

PB - American Society of Mechanical Engineers

ER -

Jovanova J, Frecker MI, Hamilton RF, Palmer T. Target shape optimization of functionally graded shape memory alloy compliant mechanism. In Modeling, Simulation and Control; Bio-Inspired Smart Materials and Systems; Energy Harvesting. American Society of Mechanical Engineers. 2016. V002T03A006. (ASME 2016 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, SMASIS 2016). https://doi.org/10.1115/SMASIS2016-9070