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材料导报  2020, Vol. 34 Issue (10): 10082-10087    https://doi.org/10.11896/cldb.19050092
  金属与金属基复合材料 |
NiTi形状记忆合金丝的约束回复应力输出特性及本构模型
刘博1, 王社良1, 何露1, 李昊1, 杨涛2, 李彬彬1,3
1 西安建筑科技大学土木工程学院,西安 710055
2 西安工程大学城市规划与市政工程学院,西安 710048
3 西安建筑科技大学结构工程与抗震教育部重点实验室,西安 710055
Constrained Recovery Stress Output Characteristics and Construction of Constitutive Model of NiTi Shape Memory Alloy Wire
LIU Bo1, WANG Sheliang1, HE Lu1, LI Hao1, YANG Tao2, LI Binbin1,3
1 School of Civil Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
2 School of Urban Planning and Municipal Engineering, Xi'an Polytechnic University, Xi'an 710048, China
3 Key Laboratory of Structural Engineering and Earthquake Resistance, Ministry of Education, Xi'an University of Architecture and Technology, Xi'an 710055, China
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摘要 为促进工程结构领域对形状记忆合金(SMA)这一智能驱动材料的应用,研究了预应变大小和热循环次数对Ti-50.8(质量分数,%)Ni SMA丝的约束回复应力-温度曲线、最大约束回复应力、逆相变特征温度、相变温度区间和相变滞后温度区间等约束回复应力输出特性的影响,并在试验数据集合的基础上建立以温度和完全热循环次数为输入、约束回复应力为输出的BP神经网络(即按照误差逆向传播训练的神经网络算法)迟滞模型。结果表明:最大约束回复应力和马氏体逆向变特征温度随预应变的增加而增加;6%预应变的NiTi SMA丝在第一次热循环中约束回复应力最大,逆向变特征温度值最高。经过五次热循环后,NiTi SMA丝的约束回复应力-温度曲线逐渐稳定。该神经网络迟滞模型的数值计算结果与试验数据较为吻合,平均绝对误差不超过5%,且简单实用、精确度高,具有一定的工程指导意义。
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刘博
王社良
何露
李昊
杨涛
李彬彬
关键词:  形状记忆合金  形状记忆效应  约束回复应力  相变特征温度  相变滞后  BP神经网络    
Abstract: In order to promote the application of the shape memory alloy (SMA) as an intelligent driving material in the field of engineering structure, the effect of pre-strain and thermal cycle times on the constrained recovery stress-temperature curve, maximum constrained recovery stress, inverse phase transition characteristic temperature, phase transition temperature range and phase transition hysteresis temperature range of Ti-50.8wt% Ni SMA wires were studied. Based on the experimental data set, the hysteresis model of BP neural network (neural network algorithm trained according to error reverse propagation) with temperature and complete thermal cycle times as input and constrained recovery stress as output was established. The results show that the maximum constrained recovery stress and the characteristic temperature of martensite reverse transformation increase with the increase of pre-strain. In the first thermal cycle, NiTi SMA wire with 6% pre-strain exhibits the highest constrained recovery stress and the highest characteristic temperature of reverse variation. After five times of thermal cycle, the recovery stress-temperature curve of NiTi SMA wire gradually reached stability. The numerical results of neural network hysteresis model are in good agreement with the experimental data, and the mean absolute error of the calculated results is less than 5%.The hysteresis model of BP network is simple, pratical and accurate, and has certain engineering guiding significance.
Key words:  shape memory alloy    shape memory effect    constrained recovery stress    phase transition characteristic temperature    phase transformation hysteresis    BP neural network
                    发布日期:  2020-04-26
ZTFLH:  TG139.6  
基金资助: 国家自然科学基金(51678480);陕西省自然科学基础研究计划(2019JQ-578);陕西省教育厅项目(18JK0332);陕西省教育厅重点实验室科学研究计划项目(17JS071);陕西省科技统筹创新工程重点实验室项目(2014SZS04-P04)
通讯作者:  王社良,西安建筑科技大学教授,博士研究生导师。主要从事智能材料和智能结构方面的研究。现任中国建筑学会抗震防灾分会理事,中国基建优化研究会结构工程专业委员会副主任委员,陕西省“三秦人才”,国家自然科学基金、博士后基金和陕西省自然科学基金函评专家。主持完成国家自然科学基金重大研究计划项目1项、973前期研究专项1项、973子课题1项、国家自然科学基金重点项目1项;主持完成国家自然科学基金面上项目5项。在国内外学术刊物上发表学术论文300余篇,其中180余篇被SCI或EI等收录。sheliangw@163.com   
作者简介:  刘博,西安建筑科技大学土木工程学院结构工程专业博士研究生,在王社良教授的指导下进行研究。目前主要研究领域为智能材料/结构及振动控制。
引用本文:    
刘博, 王社良, 何露, 李昊, 杨涛, 李彬彬. NiTi形状记忆合金丝的约束回复应力输出特性及本构模型[J]. 材料导报, 2020, 34(10): 10082-10087.
LIU Bo, WANG Sheliang, HE Lu, LI Hao, YANG Tao, LI Binbin. Constrained Recovery Stress Output Characteristics and Construction of Constitutive Model of NiTi Shape Memory Alloy Wire. Materials Reports, 2020, 34(10): 10082-10087.
链接本文:  
http://www.mater-rep.com/CN/10.11896/cldb.19050092  或          http://www.mater-rep.com/CN/Y2020/V34/I10/10082
1 Lagoudas D C. Shape memory alloys : modeling and engineering applications, Springer Science & Business Media Press, US, 2008.
2 Gholampour A A,Ozbakkaloglu T. Composite Structures, 2018, 202,943.
3 Tran H, Balandraud X, Destrebecq J F. Archives of Civil and Mechanical Engineering, 2015, 15(1),292.
4 Li H, Liu Z Q, Ou J P. Smart Materials and Structures, 2006, 15(4),1039.
5 Moser K, Bergamini A. Materials & Structures, 2005, 38(5),593.
6 Wang J Q, Shen X, Li J F. Journal of Vibration and Shock, 2017,36(20),59(in Chinese).
王进强,沈星,李杰锋. 振动与冲击, 2017,36(20),59.
7 Madangopal K, Krishnan G R, Banerjee S. Scripta Metallurgica, 1988, 22(10), 1593.
8 Cui L S, Qi M, Shi P, et al. Material Science and Technology ,1996(3),1(in Chinese).
崔立山,齐民,石萍,等. 材料科学与工艺, 1996(3),1.
9 Cui L S, Qi M, Shi P, et al. Journal of Functional Materials and Devices,1996(2),78(in Chinese).
崔立山,齐民,石萍,等. 功能材料与器件学报, 1996(2),78.
10 Jin W, Wang J, Cao M Z, et al. Chinese Journal of Materials Research, 2000(6),573(in Chinese).
金伟,王健,曹名洲, 等. 材料研究学报, 2000(6),573.
11 Li Y F, Mi X J, Yin X Q, et al. Journal of Alloys & Compounds, 2014, 588(7),525.
12 Cui D. Research on shape memory alloy and shape memory alloy reinforced intelligent concrete structure. Ph.D Thesis, Dalian University of Technology, China,2007(in Chinese).
崔迪. 形状记忆合金及其智能混凝土结构研究.博士学位论文, 大连理工大学, 2007.
13 Liu Z Q, Li H. Journal of Funcitonal Materials, 2004, 35(z1), 3131(in Chinese).
刘志强, 李惠. 功能材料, 2004, 35(z1), 3131.
14 Wang Y J. Study on vibration characteristics of shape memory alloy composite structure. Ph.D Thesis, Harbin Engineering University, China, 2010(in Chinese).
王永军. 含形状记忆合金复合结构振动特性研究.博士学位论文,哈尔滨工程大学,2010.
15 Dong E B, Xu M, Li Y X, et al. China Mechanical Engineering, 2010, 21(23),2857(in Chinese).
董二宝, 许旻, 李永新, 等. 中国机械工程, 2010, 21(23),2857.
16 GB/T 228.1-2010, 金属材料 拉伸试验 第1部分:室温试验方法[S].
17 GB/T 228.2-2015, 金属材料 拉伸试验 第2部分:高温试验方法[S].
18 Wang Y Q, Zhang T, Guo S G, et al. Rare Metal Materials and Enfinee-ring,2017,46(1),117(in Chinese).
王伊卿,张腾,郭善光, 等. 稀有金属材料与工程, 2017,46(1),117.
19 Liu Y, Xie Z, Humbeeck J V, et al. Scripta Materialia, 1999, 41(12),1273.
20 Falk F. Acta Metallurgica, 1980, 28(12),1773.
21 Maugin G A, Cadet S. International Journal of Engineering Science, 1991, 29(2),243.
22 Abeyaratne R, Knowles J K. Archive for Rational Mechanics & Analysis, 1991, 114(2),119.
23 Wu C H. International Journal of Solids & Structures, 1995, 32(3-4),525.
24 Sun Q P, Hwang K C. Journal of the Mechanics & Physics of Solids, 1993, 41(1),19.
25 Boyd J G, Lagoudas D C. International Journal of Plasticity, 1996, 12(6),805.
26 Tanaka K. RES Mechanica, 1986, 18,251.
27 Liang C, Rogers C. Journal of Intelligent Material Systems & Structures, 1990, 1(2),207.
28 Boyd J G, Lagoudas D C. Journal of Intelligent Material Systems and Structures, 1994, 5(3), 333.
29 Ivshin Y, Pence T J. International Journal of Engineering Science, 1994, 32(4),681.
30 Brinson L C, Lammering R. International Journal of Solids & Structures, 1993, 30(1993), 3261.
31 Bertram A. Nuclear Engineering & Design, 1983, 74(2),173.
32 Cong Shuang. Neural network theory and applications based on MATLAB toolboxes, Press of University of Science and Technology of China, China, 2009(in Chinese).
丛爽. 面向MATLAB工具箱的神经网络理论与应用,中国科学技术大学出版社, 2009.
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