The martensitic transformation temperature is the basis for the application of shape memory alloys(SMAs),and the ability to quickly and accurately predict the transformation temperature of SMAs has very important prac...The martensitic transformation temperature is the basis for the application of shape memory alloys(SMAs),and the ability to quickly and accurately predict the transformation temperature of SMAs has very important practical significance.In this work,machine learning(ML)methods were utilized to accelerate the search for shape memory alloys with targeted properties(phase transition temperature).A group of component data was selected to design shape memory alloys using reverse design method from numerous unexplored data.Component modeling and feature modeling were used to predict the phase transition temperature of the shape memory alloys.The experimental results of the shape memory alloys were obtained to verify the effectiveness of the support vector regression(SVR)model.The results show that the machine learning model can obtain target materials more efficiently and pertinently,and realize the accurate and rapid design of shape memory alloys with specific target phase transition temperature.On this basis,the relationship between phase transition temperature and material descriptors is analyzed,and it is proved that the key factors affecting the phase transition temperature of shape memory alloys are based on the strength of the bond energy between atoms.This work provides new ideas for the controllable design and performance optimization of Cu-based shape memory alloys.展开更多
针对调谐质量阻尼器(tuned mass damper,TMD)系统应用于轻型结构时易失调从而导致减振效果下降的问题,提出了一种新型形状记忆合金半主动TMD系统。该系统利用钢索悬吊质量块并承担其全部重量,使用有效截面为矩形的大尺寸镍钛形状记忆合...针对调谐质量阻尼器(tuned mass damper,TMD)系统应用于轻型结构时易失调从而导致减振效果下降的问题,提出了一种新型形状记忆合金半主动TMD系统。该系统利用钢索悬吊质量块并承担其全部重量,使用有效截面为矩形的大尺寸镍钛形状记忆合金棒材,提供TMD系统水平面2个方向不同的抗弯刚度。为了研究该系统的半主动性能,进行了足尺形状记忆合金半主动TMD系统的自由振动试验,通过改变形状记忆合金的工作温度,研究了温度变化对TMD系统频率及阻尼比的影响。研究结果表明,控制形状记忆合金工作温度从-40~+80℃,TMD系统的频率随温度升高呈现升高趋势,而阻尼比随温度升高呈现下降趋势。将该新型形状记忆合金半主动TMD系统应用于受控结构中,一旦TMD失调,可以通过改变形状记忆合金的温度使其重新调谐。因此,设计的新型形状记忆合金TMD系统在轻型结构减振研究中具有一定的工程应用价值和前景。展开更多
基金supported by the National Natural Science Foundation of China (No. 52271168)the Natural Science Foundation of Heilongjiang, China (No. YQ2022E011)+1 种基金0-1 Exploration of “High level Scientific Research Guidance Special Project” of Harbin Engineering University, China (No. 3072022TS1003)Central University Fund, China (No. 3072023WD1002)。
基金partial financial support from the National Natural Science Foundation of China (No. 52101231)the Science Fund of Shandong Laboratory of Yantai Advanced Materials and Green Manufacturing,China (No. AMGM2021F09)the Natural Science Foundation of Shandong Province,China (No. ZR2021QE044)。
基金financially supported by the National Natural Science Foundation of China(No.51974028)。
文摘The martensitic transformation temperature is the basis for the application of shape memory alloys(SMAs),and the ability to quickly and accurately predict the transformation temperature of SMAs has very important practical significance.In this work,machine learning(ML)methods were utilized to accelerate the search for shape memory alloys with targeted properties(phase transition temperature).A group of component data was selected to design shape memory alloys using reverse design method from numerous unexplored data.Component modeling and feature modeling were used to predict the phase transition temperature of the shape memory alloys.The experimental results of the shape memory alloys were obtained to verify the effectiveness of the support vector regression(SVR)model.The results show that the machine learning model can obtain target materials more efficiently and pertinently,and realize the accurate and rapid design of shape memory alloys with specific target phase transition temperature.On this basis,the relationship between phase transition temperature and material descriptors is analyzed,and it is proved that the key factors affecting the phase transition temperature of shape memory alloys are based on the strength of the bond energy between atoms.This work provides new ideas for the controllable design and performance optimization of Cu-based shape memory alloys.
文摘针对调谐质量阻尼器(tuned mass damper,TMD)系统应用于轻型结构时易失调从而导致减振效果下降的问题,提出了一种新型形状记忆合金半主动TMD系统。该系统利用钢索悬吊质量块并承担其全部重量,使用有效截面为矩形的大尺寸镍钛形状记忆合金棒材,提供TMD系统水平面2个方向不同的抗弯刚度。为了研究该系统的半主动性能,进行了足尺形状记忆合金半主动TMD系统的自由振动试验,通过改变形状记忆合金的工作温度,研究了温度变化对TMD系统频率及阻尼比的影响。研究结果表明,控制形状记忆合金工作温度从-40~+80℃,TMD系统的频率随温度升高呈现升高趋势,而阻尼比随温度升高呈现下降趋势。将该新型形状记忆合金半主动TMD系统应用于受控结构中,一旦TMD失调,可以通过改变形状记忆合金的温度使其重新调谐。因此,设计的新型形状记忆合金TMD系统在轻型结构减振研究中具有一定的工程应用价值和前景。
