TARGET SHAPE OPTIMIZATION OF FUNCTIONALLY GRADED SHAPE MEMORY ALLOY COMPLIANT MECHANISM

被引:0
作者
Jovanova, Jovana [1 ]
Frecker, Mary [2 ]
Hamilton, Reginald F. [3 ]
Palmer, Todd A. [4 ]
机构
[1] Ss Cyril & Methodius Univ Skopje, Fac Mech Engn, Skopje, Macedonia
[2] Penn State Univ, Dept Mech & Nucl Engn, University Pk, PA 16802 USA
[3] Penn State Univ, Dept Engn Sci & Mech, 227 Hammond Bldg, University Pk, PA 16802 USA
[4] Penn State Univ, Dept Mat Sci & Engn, University Pk, PA 16802 USA
来源
PROCEEDINGS OF THE ASME CONFERENCE ON SMART MATERIALS, ADAPTIVE STRUCTURES AND INTELLIGENT SYSTEMS, 2016, VOL 2 | 2016年
关键词
TOPOLOGY OPTIMIZATION; MULTIPLE MATERIALS; DESIGN;
D O I
暂无
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
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 SM_A 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 dfferent 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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页数:10
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