Micromechanical Modeling and Analysis of Intelligent Materials

一个包含智能材料的TiNi纤维的微机械模型是通过采用转换链来考虑光纤存在的总数量到光纤收缩的总数量。在建模中，TNi纤维和基质之间的热扩展系数不匹配的热扩展链也是被考虑的。“总潜力能量可以获得， Hence，材料中的裂缝尖端的压力强度因子K和材料的全部弹性模块可以完全地表达在纤维转化链和材料中的热扩展链的持续时间。”我们可以看到K值的减少，因为纤维的收缩链增加了。温度在K中的变化与实验结果是一致的，具有温度和转换应变的宏观弹性模块中的变化也同样存在。Moreover， micromechanical modeling of a intelligent material containing shape memory polymer particles is also performed by considering that the values of glass transition temperature of particles in the material，T-D2 g-D2， is various and then overall elastic modulus of the material is formulated as a function of the probability distribution of T-D2 of particles。When the distribution of TイイD2gイD2 is a Bi-modal type， we can see that the overall elastic modulus of the material is constant irrespective of temperature within the temperature range between both values of TイD2gイD2 and whose value depends only upon the ratio between two？ability densities of TイD2 of particles in the material。For a uniform type of TイイD2gイD2 distribution， overall elastic modulus of the material decreases with increasing in temperature and whose decreasing rate becomes more large as the difference between maximum value and minimum one of TイイD2gイD2 becomes small。

Micromechanical modeling of a intelligent material containing TiNi fibers is performed by taking into consideration of the existence of fibers with transformation strain which corresponds to the total amount of shrinkage of the fiber. In modeling, thermal expansion strain due to the mismatch of thermal expansion coefficients between TiNi fiber and matrix is also considered. The total potential energy can be obtained, hence, the stress intensity factor K at the crack tip in the material and the overall elastic modulus of the material can be expressed successfully in terms of the transformation strain of fibers and the thermal expansion strain occurred in the material. We can see that the K value decreases with increasing in the shrink strain of fibers. The change in K with temperature is consistent with the experimental result and the change in macroscopic elastic modulus with temperature and transformation strain can be also obtained. Moreover, micromechanical modeling of a intelligent material containing shape memory polymer particles is also performed by considering that the values of glass transition temperature of particles in the material, TィイD2gィエD2, is various and then overall elastic modulus of the material is formulated as a function of the probability distribution of TィイD2gィエD2 of particles. When the distribution of TィイD2gィエD2 is a Bi-modal type, we can see that the overall elastic modulus of the material is constant irrespective of temperature within the temperature range between both values of TィイD2gィエD2 and whose value depends only upon the ratio between two probability densities of TィイD2gィエD2 of particles in the material. For a uniform type of TィイD2gィエD2 distribution, overall elastic modulus of the material decreases with increasing in temperature and whose decreasing rate becomes more large as the difference between maximum value and minimum one of TィイD2gィエD2 becomes small.