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A coupled kinetic Monte Carlo–finite element mesoscale model for thermoelastic martensitic phase transformations in shape memory alloys

机译:形状记忆合金中热弹性马氏体相变的耦合动力学蒙特卡罗有限元中尺度模型

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摘要

A mesoscale modeling framework integrating thermodynamics, kinetic Monte Carlo (KMC) and finite element mechanics (FEM) is developed to simulate displacive thermoelastic transformations between austenite and martensite in shape memory alloys (SMAs). The model is based on a transition state approximation for the energy landscape of the two phases under loading or cooling, which leads to the activation energy and rate for transformation domains incorporating local stress states. The evolved stress state after each domain transformation event is calculated by FEM, and is subsequently used in the stochastic KMC algorithm to determine the next domain to transform. The model captures transformation stochasticity, and predicts internal phase and stress distributions and evolution throughout the entire incubation, nucleation and growth process. It also relates the critical transformation stresses or temperatures to internal activation energies. It therefore enables quantitative exploration of transformation dynamics and transformation–microstructure interactions. The model is used to simulate superelasticity (mechanically induced transformation) under both load control and strain control in single-crystal SMAs under uniaxial tension.
机译:建立了一个中尺度建模框架,该框架集成了热力学,动力学蒙特卡洛(KMC)和有限元力学(FEM),以模拟形状记忆合金(SMAs)中奥氏体和马氏体之间的位移热弹性转变。该模型基于负载或冷却条件下两相能量分布的过渡态近似,从而得出包含局部应力状态的转换域的活化能和速率。通过有限元法计算每个域转换事件之后的应力状态,然后将其用于随机KMC算法中以确定要转换的下一个域。该模型可捕获转化的随机性,并预测整个孵化,成核和生长过程中的内部相,应力分布和演化。它还将临界转变应力或温度与内部活化能相关。因此,它可以定量探索转变动力学和转变-微观结构的相互作用。该模型用于模拟单轴SMA下单轴SMA的载荷控制和应变控制下的超弹性(机械诱导的转变)。

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