金属材料超高周疲劳行为的Monte-Carlo模拟

<正>基于Tanaka-Mura的微观位错模型并结合结构可靠性及灵敏度的统计理论,采用MATLAB自编程序对金属材料S-N曲线的分散特性进行了Monte-Carlo模拟分析,并对比了SUJ2钢的旋转弯曲疲劳实验数据,最后根据结构可靠性灵敏度理论分析了超高周疲劳失效概率的各影响因素的敏感性。

HIRFL-CSRm内靶实验终端上TPC性能的Monte-Carlo研究

基于Monte Carlo方法对HIRFL CSRm上的TPC的性能进行了模拟.研究了磁场、读出电极几何尺寸、灵敏丝距以及读出电极平面与灵敏丝平面之间的距离等参数对TPC性能的影响,给出了TPC的一些最佳设计参数.

复合式高能γ探测器优化设计Monte Carlo模拟计算

用MonteCarlo方法系统模拟计算了以NaI晶体与BGO晶体为探测介质的clover与cluster复合式高能γ探测器的效率 .对于相同的介质几何 ,BGO复合式探测器的全能峰效率远高于相应的NaI复合式探测器 .用多块76× 1 2 7BGO晶体制作成的clover与cluster复合式高能γ探测器对 2 2 0MeV的γ光子的全能峰特征效率仍然高于 40 % ,绝对效率增加因子达 2 4与 2 7.

Self-assembly of diblock copolymer mixtures in confined states: A Monte Carlo study

The self-assembly of diblock copolymer mixtures (A-b-B/A-b-C or A-b-B/B-b-C mixtures) subjected to cylindrical confinement (two-dimensional confinement) was investigated using a Monte Carlo method. In this study, the boundary surfaces were configured to attract blocks A but repel blocks B and C. Relative to the structures of the individual components, the self-assembled structures of mixtures of the diblock copolymers were more complex and interesting. Under cylindrical confinement, with varying cylinder diameters and interaction energies between the boundary surfaces and the blocks, we observed a variety of interesting morphologies. Upon decreasing the cylinder's diameter, the self-assembled structures of the A(15)B(15)/A(15)C(15) mixtures changed from double-helix/cylinder structures (blocks B and C formed double helices, whereas blocks A formed the outer barrel and inner core) to stacked disk/cylinder structures (blocks B and C formed the stacked disk core, blocks A formed the outer cylindrical barrel), whereas the self-assembled structures of the A(15)B(7)/B7C15 mixtures changed from concentric cylindrical barrel structures to screw/cylinder structures (blocks C formed an inside core winding with helical stripes, whereas blocks A and B formed the outer cylindrical barrels) and then finally to the stacked disk/cylinder structures.

Ukryty punkt krytyczny w mieszaninach binarnych – badania metodami symulacji Monte – Carlo

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