1718 Application of Preisach Model to Three-Phase Reorientation of Shape Memory Alloys

2005 ◽  
Vol 2005.6 (0) ◽  
pp. 181-182
Author(s):  
Masashi AKITA ◽  
Tadashige IKEDA ◽  
Tetsuhiko UEDA
Keyword(s):  
Shape Memory Alloys ◽  
Shape Memory ◽  
Preisach Model ◽  
Three Phase

Modeling Smart Materials Using Hysteretic Recurrent Neural Networks

2009 ◽  
Author(s):  
Arun Veeramani ◽  
John Crews ◽  
Gregory D. Buckner
Keyword(s):  
Shape Memory Alloys ◽  
Shape Memory ◽  
Smart Materials ◽  
Real Time Control ◽  
Ferromagnetic Shape Memory Alloys ◽  
Two Phase ◽  
Time Control ◽  
Novel Approach ◽  
Three Phase ◽  
Ferromagnetic Shape Memory

This paper describes a novel approach to modeling hysteresis using a Hysteretic Recurrent Neural Network (HRNN). The HRNN utilizes weighted recurrent neurons, each composed of conjoined sigmoid activation functions to capture the directional dependencies typical of hysteretic smart materials (piezoelectrics, ferromagnetic, shape memory alloys, etc.) Network weights are included on the output layer to facilitate training and provide statistical model information such as phase fraction probabilities. This paper demonstrates HRNN-based modeling of two- and three-phase transformations in hysteretic materials (shape memory alloys) with experimental validation. A two-phase network is constructed to model the displacement characteristics of a shape memory alloy (SMA) wire under constant stress. To capture the more general thermo-mechanical behavior of SMAs, a three-phase HRNN model (which accounts for detwinned Martensite, twinned Martensite, and Austensite phases) is developed and experimentally validated. The HRNN modeling approach described in this paper readily lends itself to other hysteretic materials and may be used for developing real-time control algorithms.

A Three-Phase Constitutive Model for TiNiNb Shape Memory Alloys

2010 ◽  
Vol 97-101 ◽  
pp. 660-666
Author(s):  
Jun Wang ◽  
Zhi Ming Hao ◽  
Ping An Shi ◽  
Shao Rong Yu ◽  
Wei Fen Li
Keyword(s):  
Phase Transition ◽  
Constitutive Model ◽  
Shape Memory Alloys ◽  
Shape Memory ◽  
Shape Memory Effect ◽  
Conventional Theory ◽  
Material Parameters ◽  
Three Phase ◽  
The Individual

A three-phase constitutive model for TiNiNb shape memory alloys (SMAs) is proposed based on the fact that TiNiNb SMAs are dynamically composed of austenite, martensite and -Nb phases. In the considered ranges of stress and temperature, the behaviors of austenite, martensite and -Nb phases are assumed to be elastoplastic, and the behavior of an SMA is regarded as the dynamic combination of the individual behavior of each phase. Then a macroscopic constitutive description for TiNiNb SMAs is obtained by the conventional theory of plasticity, the theory of mixture, the theory of inclusion, and the description of phase transition by Tanaka. The method for determination of the material parameters is given. This constitutive model can describe the main characteristics of SMAs, such as ferrcelasticity, pseudoelasticity and shape memory effect.

Evolutions of Microstructure and Phase Transformation in Cu-Al-Fe-Nb/Ta High-Temperature Shape Memory Alloys

2015 ◽  
Vol 833 ◽  
pp. 67-70
Author(s):  
Shui Yuan Yang ◽  
Cui Ping Wang ◽  
Yu Su ◽  
Xing Jun Liu
Keyword(s):  
Phase Transformation ◽  
High Temperature ◽  
Martensitic Transformation ◽  
Shape Memory Alloys ◽  
Shape Memory ◽  
Transformation Behavior ◽  
Two Phase ◽  
Phase Transformation Behavior ◽  
Three Phase

The evolutions of microstructure and phase transformation behavior of Cu-Al-Fe-Nb/Ta high-temperature shape memory alloys under the quenched and aged states were investigated in this study, including Cu-10wt.% Al-6wt.% Fe, Cu-10wt.% Al-4wt.% Fe-2wt.% Nb and Cu-10wt.% Al-4wt.% Fe-2wt.% Ta three types alloys. The obtained results show that after quenching, Cu-10wt.% Al-6wt.% Fe alloy exhibits two-phase microstructure of β′1 martensite + Fe (Al,Cu) phase; Cu-10wt.% Al-4wt.% Fe-2wt.% Nb alloy also has two-phase microstructure of (β′1 + γ′1 martensites) + Nb (Fe,Al,Cu)2 phase; Cu-10wt.% Al-4wt.% Fe-2wt.% Ta alloy is consisted of three-phase of (β′1 + γ′1 martensites) + Fe (Al,Cu,Ta) + Ta2(Al,Cu,Fe)3 phases. However, α (Cu) phase precipitates after aging for three alloys; and Fe (Al,Cu,Nb) phase is also present in Cu-10wt.% Al-4wt.% Fe-2wt.% Nb alloy. All the studied alloys exhibit complicated martensitic transformation behaviors resulted from the existence of two types martensites (β′1 and γ′1).

A Thermodynamically Based Model of the Superelastic Behavior of Shape Memory Alloys Using a Discrete Preisach Model

2009 ◽  
Author(s):  
Srikrishna Doraiswamy ◽  
Mrinal Iyer ◽  
Arun R. Srinivasa ◽  
Srinivasan M. Sivakumar
Keyword(s):  
Shape Memory Alloys ◽  
Shape Memory ◽  
Vibration Control ◽  
Stress And Strain ◽  
Preisach Model ◽  
Thermomechanical Response ◽  
Superelastic Behavior ◽  
Seismic Applications

Shape Memory Alloys are increasingly being used in aeronautic [1], vibration control and seismic applications [2–6]. These applications require models that faithfully represent the full thermomechanical response of SMA wires but which at the same time are simple and fast to implement. In this paper we present a model for the superelastic behavior of Shape Memory Alloys that combines a thermodynamical framework with a Preisach model. This approach allows us to easily account for both stress and strain controlled responses as well as changes in termperature in a simple and straightforward way.

scholarly journals Distributed-element Preisach model for hysteresis of shape memory alloys

2001 ◽  
Vol 215 (6) ◽  
pp. 673-682 ◽  
Author(s):  
C Song ◽  
J A Brandon ◽  
C A Featherston
Keyword(s):  
Numerical Simulation ◽  
Parameter Identification ◽  
Shape Memory Alloys ◽  
Shape Memory ◽  
Physical Model ◽  
Model Prediction ◽  
High Order ◽  
Preisach Model ◽  
And Inversion ◽  
Transition Curves

The paper describes the development of distributed-element models for non-linear hysteresis in materials and structures. The physical model is based on an approach that views the system as comprising a series of ideal elastoplastic elements. Parameter identification, numerical simulation and inversion of the model through the application of the Preisach model for hysteresis are discussed. Experimentally obtained data using Nitinol are compared with the model prediction, thus establishing the effectiveness of distributed-element Preisach elements for predicting complex hysteresis effects including high-order hysteresis transition curves.

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