Simulation of Mechanical Behaviour of Martensites using Multicore Technology

马氏体-奥氏体相变是冶金学中最重要的相变之一，存在于许多材料中。通常，它涉及从高温、韧性（奥氏体）相到低温、硬质（马氏体）相的脆性断裂。相变过程涉及应变，在钢和超弹性形状记忆合金等实际应用中，相变过程是两相共存的，且相变速度快，微观结构是纳米尺度的，因此分子动力学研究是合适的。然而，应变影响相稳定性，并且在转变相之间存在不合理的界面（习惯面），因此需要灵活的初始和边界条件。优雅的数学分析假设完全刚性的边界得出结论，结构是由最小化边界能量。然而，我们的初步模拟表明，这是边界条件的一个伪像：如果允许软奥氏体变形以适应不断生长的马氏体，则会出现非常不同的结果。描述适当的周围材料以匹配弹性和原子细节，使得这些模拟非常计算密集。并行超级计算机是一种选择，但通过专用的多核处理器，一个更具成本效益的解决方案正在变得可用，标准的桌面硬件将在未来几年进入我们的团队。充分利用共享内存多核机器需要对代码进行相当大的修改：信息需要在处理器之间传输，而有效地做到这一点需要并行编码专业知识。电子化策略也随原子间相互作用势的类型而变化。金属是最好的描述多体，短程相互作用，这需要一个不同的策略，从潜在的固定债券或离子forces.We建议重新设计一个模拟代码，适合研究马氏体如何转变，了解什么样的结构之间的奥氏体和马氏体的界面，以及这是如何受到材料参数的影响。要做到这一点，我们将利用我们在并行编码，分子动力学和潜在的设计经验。

The martensite-austenite phase transformation is one of the most important in metallurgy, existing in many materials. Typically, it involves a symmetry-breaking from a high temperature, ductile (austenite) phase to a low temperature, hard (martensite) phase. The transformation involves strain, and in practical applications such as steels and superelastic shape memory alloys both phases coexist.The transformation process is fast, and the microstructures are nanoscaled, so molecular dynamics study is appropriate. However, strain affects phase stability, and there are irrational interfaces between transforming phases (habit plane) so flexible initial and boundary conditions are required. Elegant mathematical analysis assuming perfectly rigid boundaries concluded that the structure is determined by minimising boundary energy. However, our preliminary simulations shows this to be an artifact of the boundary conditions: if the soft austenite is allowed to deform to accommodate the growing martensite very different results occur.Describing adequate surrounding material to match both elasticity and atomistic detail, makes these simulations very computationally intense. A parallel supercomputer is an option, but a far more cost-effective solution is becoming available through dedicated multicore processors, the standard desktop hardware coming into our group over the next few years. Fully utilising a shared-memory multicore machine requires considerable modification to the code: information needs to be transferred between processors, and doing this efficiently requiresparallel coding expertise. Parallelisation strategies also vary withthe type of interatomic potential. Metals are best described by many-body, short ranged interactions which call for a different strategy from potentials involving fixed bonds or ionic forces.We propose to re-engineer a simulation code suitable for study of how martensites transform, to understand what structure the interfaces between austenite and martensite takes, and how this is affected by material parameter. To do so we will use our experience in parallel coding, molecular dynamics and potential design.