原子动力学蒙特卡洛程序OpenKMC在反应堆压力容器钢缺陷损伤研究中的优化与应用

将具有体心立方结构的Fe-Cu二元合金作为RPV模型材料，分别采用基于Pair势和嵌入原子势(EAM)的动力学蒙特卡洛方法，以引入空位点缺陷的方式模拟了热时效下系统中富铜团簇的析出过程。同时对程序实现了计算优化，并验证了算法的正确性与有效性。利用高性能计算资源对优化后的程序进行了性能分析。数值实验结果表明，通过引入一定数量的空位点缺陷，体系内可以同时析出富铜团簇和铜-空位复合体团簇，并且这种复合体团簇更易成为体系内尺寸最大的团簇。增加体系内的空位数量可以加快沉淀的析出过程。另外，增加空位数量不会对体系总的团簇数量密度产生显著影响，但是能够促进团簇粗化，使其成长为尺寸更大的沉淀。

Optimization and application of atomic Kinetic Monte Carlo program OpenKMC in defect damage of reactor pressurevessel steel

The Fe-Cu binary alloy with BCC structure is used as the RPV simulation steel. The kinetic Monte Carlo method based on Pair potential and EAM potential is adopted to simulate the precipitation process of Cu-rich clusters in the system under thermal aging by introducing vacancy point defects. At the same time, the program is optimized, and the correctness and validity of the algorithm are verified. The performance of the optimized program is analyzed by using high performance computing resources. The numerical results show that, by introducing a certain number of vacancy point defects, Cu-rich clusters and Cu-vacancy complex clusters can be precipitated simultaneously in the system, and the complex clusters are more likely to become the largest clusters in the system. The precipitation process can be accelerated by increasing the number of vacancies in the system. In addition, increasing the number of vacancies does not have a significant impact on the total number and density of clusters in the system, but it can promote the coarsening of clusters and make them grow into larger size precipitates.