Shape Memory Alloy (SMA) as a Potential Damper in Structural Vibration Control

2018 ◽  
pp. 485-492 ◽  
Author(s):  
Sekhar Chandra Dutta ◽  
Rohan Majumder
Keyword(s):  
Shape Memory Alloy ◽  
Shape Memory ◽  
Vibration Control ◽  
Structural Vibration ◽  
Structural Vibration Control

Structural vibration control by shape memory alloy damper

2003 ◽  
Vol 32 (3) ◽  
pp. 483-494 ◽  
Author(s):  
Yu-Lin Han ◽  
Q. S. Li ◽  
Ai-Qun Li ◽  
A. Y. T. Leung ◽  
Ping-Hua Lin
Keyword(s):  
Shape Memory Alloy ◽  
Shape Memory ◽  
Vibration Control ◽  
Structural Vibration ◽  
Structural Vibration Control

Application of Magnetic Control Shape Memory Alloy in Structural Vibration Control

2014 ◽  
Vol 577 ◽  
pp. 66-70
Author(s):  
Jin Sheng He ◽  
She Liang Wang ◽  
Guang Yaun Weng
Keyword(s):  
Shape Memory Alloy ◽  
Shape Memory ◽  
Vibration Control ◽  
Civil Engineering ◽  
Structural Vibration ◽  
Engineering Structure ◽  
Civil Engineering Structure ◽  
Structural Vibration Control ◽  
Development Direction ◽  
Control Application

In order to effectively use Magnetically Controlled Shape Memory Alloy (MSMA) for vibration control in civil engineering structure, the deformation mechanism and dynamic characteristics of the MSMA were studied; research methods apply to the constitutive relation of vibration control in civil engineering structure is given. Based on the study about MSMA vibration controller and its application in structural vibration control in engineering, MSMA in structure vibration control application prospect and development direction are introduced. At the same time, for the difficulties existing in the application are discussed in this paper. The results prove that MSMA materials in structural vibration control are of important value.

Structural Vibration Control of Shape Memory Alloy in Martensite-Austenite Coexisting

2012 ◽  
Vol 253-255 ◽  
pp. 518-523
Author(s):  
Zhen Yu Liang ◽  
Bo Xing
Keyword(s):  
Computer Simulation ◽  
Numerical Analysis ◽  
Shape Memory Alloy ◽  
Shape Memory ◽  
Vibration Control ◽  
Mechanical Model ◽  
Simulation Analysis ◽  
Structural Vibration ◽  
Structural Vibration Control ◽  
Basic Characteristics

This essay introduced that shape memory alloy in martensite-austenite coexisting was use to control the structural vibration. The proportion of martensite and austenite in shape memory alloy was selected which could realize the two basic characteristics of shape memory alloy. Based on Liang model, the mechanical model of shape memory alloy was established. The computer simulation analysis of the structure was achieved by using Matlab, and the result of numerical analysis proved that shape memory alloy in martensite-austenite coexisting could effect structural vibration control.

Study on Structural Vibration Control by Using Shape Memory Alloy

2009 ◽  
Vol 417-418 ◽  
pp. 229-232 ◽  
Author(s):  
Bo Zhou ◽  
Yan Ju Liu ◽  
Guang Ping Zou ◽  
Jin Song Leng
Keyword(s):  
Phase Transformation ◽  
Energy Dissipation ◽  
Shape Memory Alloy ◽  
Shape Memory ◽  
Passive Control ◽  
Transformation Model ◽  
Basic Knowledge ◽  
Structural Vibration ◽  
Beam Structure ◽  
Structural Vibration Control

Shape memory alloy is a good candidate for realizing the passive control of structural vibration due to its excellent characteristic of energy dissipation. In this paper, the damping characteristic of shape memory alloy is quantitatively described based on Liang’s phase transformation model and thermo-mechanical constitutive equation for shape memory alloy. The vibration performances of a beam structure with shape memory alloy damper are investigated based on basic knowledge of vibration theorem. Numerical calculations show that the vibration of beam structure is well reduced by using the shape memory alloy damper.

scholarly journals Experimental Study on Temperature Effects on NiTi Shape Memory Alloys under Fatigue Loading

Materials ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 573
Author(s):  
Caikui Lin ◽  
Zeqiang Wang ◽  
Xin Yang ◽  
Haijun Zhou
Keyword(s):  
Fatigue Life ◽  
Shape Memory ◽  
Vibration Control ◽  
Fatigue Loading ◽  
Structural Vibration ◽  
Fatigue Properties ◽  
Hysteresis Curve ◽  
Niti Shape Memory Alloy ◽  
Structural Vibration Control ◽  
Key Factor

NiTi Shape Memory Alloy (SMA) has been widely studied in the field of structural vibration control, and the results show that the fatigue life of the SMA is a key factor of the vibration control system. In this paper, the fatigue test is carried out in Dynamic Mechanical Analyzer (DMA + 1000) to analyze how the changes of temperature and strain amplitude affecting the main fatigue parameters. The test results show that when the test temperature is higher than Austenite finish temperature (Af), the fatigue properties of SMAs are significantly affected by temperature. With the increase of temperature, the fatigue life becomes shorter and the energy consumption decreases, while the area of hysteresis curve, the stress amplitude, and effective modulus increase.

scholarly journals Optimized Neural Network Prediction Model of Shape Memory Alloy and Its Application for Structural Vibration Control

Materials ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 6593
Author(s):  
Meng Zhan ◽  
Junsheng Liu ◽  
Deli Wang ◽  
Xiuyun Chen ◽  
Lizhen Zhang ◽  
...  
Keyword(s):  
Neural Network ◽  
Mathematical Model ◽  
Shape Memory Alloy ◽  
Prediction Model ◽  
Shape Memory ◽  
Structural Vibration ◽  
Absorption Effect ◽  
Structural Vibration Control ◽  
Neural Network Prediction ◽  
Network Prediction

The traditional mathematical model of shape memory alloy (SMA) is complicated and difficult to program in numerical analysis. The artificial neural network is a nonlinear modeling method which does not depend on the mathematical model and avoids the inevitable error in the traditional modeling method. In this paper, an optimized neural network prediction model of shape memory alloy and its application for structural vibration control are discussed. The superelastic properties of austenitic SMA wires were tested by experiments. The material property test data were taken as the training samples of the BP neural network, and a prediction model optimized by the genetic algorithm was established. By using the improved genetic algorithm, the position and quantity of the SMA wires were optimized in a three-storey spatial structure, and the dynamic response analysis of the optimal arrangement was carried out. The results show that, compared with the unoptimized neural network prediction model of SMA, the optimized prediction model is in better agreement with the test curve and has higher stability, it can well reflect the effect of loading rate on the superelastic properties of SMA, and is a high precision rate-dependent dynamic prediction model. Moreover, the BP network constitutive model is simple to use and convenient for dynamic simulation analysis of an SMA passive control structure. The controlled structure with optimized SMA wires can inhibit the structural seismic responses more effectively. However, it is not the case that the more SMA wires, the better the shock absorption effect. When SMA wires exceed a certain number, the vibration reduction effect gradually decreases. Therefore, the seismic effect can be reduced economically and effectively only when the number and location of SMA wires are properly configured. When four SMA wires are arranged, the acceptable shock absorption effect is obtained, and the sum of the structural storey drift can be reduced by 44.51%.

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