Nonlinear differential equation approach for the two-way shape memory effects of one-dimensional shape memory alloy structures

Author(s):  
Linxiang Wang ◽  
Changquan Zhou ◽  
Changshui Feng
2012 ◽  
Vol 5 (1) ◽  
pp. 15-28 ◽  
Author(s):  
Toyohiko Aiki ◽  
◽  
Martijn Anthonissen ◽  
Adrian Muntean ◽  
◽  
...  

Materials ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2278 ◽  
Author(s):  
Min Kyoung Kim ◽  
Dong Joo Kim ◽  
Young-Soo Chung ◽  
Eunsoo Choi

The feasibility of the crack closure of cementitious composites reinforced with shape memory alloy (SMA) fibers was investigated by performing single-fiber pullout tests. To demonstrate the fast crack closing ability, in this study, a heat treatment (300 °C) was applied for a short time (10 min). A short heat treatment was applied for 10 min, after the slip reached 0.5 mm, to activate the shape memory effects of cold-drawn SMA fibers. Two types of alloys were investigated, NiTi and NiTiNb, with two geometries, either smooth or dog-bone-shaped. During the heat treatment, the pullout stress of the SMA fibers initially decreased due to thermal extension, and then increased after heating for 1–3 min, resulting from the shape memory effects. However, their pullout stress recovery during and after the heat treatment was different for the different alloys and fiber geometries. The NiTi fibers generally produced a higher and faster recovery in terms of their pullout stress than the NiTiNb fibers, while the dog-bone-shaped fibers showed a faster pullout stress recovery than the smooth fibers.


2006 ◽  
Vol 326-328 ◽  
pp. 1475-1478
Author(s):  
Jong Ha Chung ◽  
Jin Seok Heo ◽  
Myoung Sik Won ◽  
Woo Yong Lee ◽  
Jung Ju Lee

The transformation kinetics formulation is the principal factor underlying the constitutive model of shape memory alloys. Therefore, the transformation kinetics formulation, which is applicable to any status of stress and temperature, is essential for predicting the material behavior of SMAs. In this work, we show that the transformation kinetics of the Brinson model, which is the most widely used 1-dimensional model, has shortcomings under certain stress and temperature histories. In addition, we propose a modified transformation kinetics model that can be used for any stress or temperature conditions. The martensite transformation kinetics is modified so that the transformation from austenite into temperature-induced martensite, due to the decrement of temperature, is coupled with a transformation from austenite or temperature-induced martensite into stress-induced martensite, due to the increment of the stress. Through this modification, the suggested model can simulate the behavior of shape memory alloy materials under arbitrarily changed circumstances at every stress-temperature region.


AIAA Journal ◽  
2003 ◽  
Vol 41 (1) ◽  
pp. 100-109 ◽  
Author(s):  
S. Marfia ◽  
E. Sacco ◽  
J. N. Reddy

2011 ◽  
Vol 299-300 ◽  
pp. 562-565
Author(s):  
Xing Jiang Liu ◽  
Yan Gao ◽  
Jin Gang Qi

This paper studies the electric-pulse applied in the solidification process of the FeMnSiCrNi shape memory alloy, by applying different pulse frequency and polarity on the FeMnSiCrNi shape memory alloy to improve the shape memory effects. The results show : electric-pulse was conducive to FeMnSiCrNi alloys grain refinement, the alloy can improve the shape memory effect of Compression deformation, the absolute shape recovery rate is improved from 2% to 3.2% which is not treated by the electric-pulse ; when the liquid metal was connected with the anode of the pulse, it is easy to get the columnar grain structure and the column spacing is smaller; when the liquid metal was connected with the cathode of the pulse, the column spacing is larger; Columnar grain is conducive to FeMnSiCrNi alloy specimens compressed shape recovery, it has the smaller column spacing, yet the shape recovery rate is higher; equiaxed is favor in bending back, columnar crystals impede the bending response.


2004 ◽  
Author(s):  
Ganesh K. Kannarpady ◽  
Steve Trigwell ◽  
Abhijit Bhattacharyya ◽  
Ivan Viahhi ◽  
Sergei Pulnev

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