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首页> 外文期刊>International Journal of Theoretical and Applied Multiscale Mechanics >Adaptive multiple super fast simulated annealing for stochastic microstructure reconstruction
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Adaptive multiple super fast simulated annealing for stochastic microstructure reconstruction

机译:随机微观结构重构的自适应多超快速模拟退火

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摘要

Fast microstructure reconstruction from statistical information is critical to create high resolution image with large domain for materials property prediction. Large structural data generated from multimodality chemical imaging instrumentation also calls for fast microstructure reconstruction for evaluation and interpretation. Stochastic methods in microstructure reconstruction from two-point correlation function have been applied widely in materials and mechanical engineering community. The main challenge is to increase the efficiency of large data reconstruction and reconstruction. A novel simulated annealing method, adaptive multiple super fast simulated annealing, is proposed for fast solution to improve efficiency. Combining the advantage of very fast cooling schedules, dynamic adaption and parallelisation, the new simulation annealing algorithm increases the efficiencies by several orders of magnitude, making the large domain image fusion feasible.
机译:从统计信息快速重建微结构对于创建具有大范围用于材料特性预测的高分辨率图像至关重要。从多峰化学成像仪器生成的大型结构数据还要求快速进行微观结构重建,以进行评估和解释。从两点相关函数重建微观结构的随机方法已广泛应用于材料和机械工程领域。主要挑战是提高大数据重建和重建的效率。为了提高效率,提出了一种新颖的模拟退火方法,即自适应多重超快速模拟退火。结合非常快的冷却时间表,动态自适应和并行化的优点,新的模拟退火算法将效率提高了几个数量级,从而使大区域图像融合变得可行。

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