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首页> 外文期刊>Magnetics, IEEE Transactions on >A Generalized Domain-Decomposition Stochastic FDTD Technique for Complex Nanomaterial and Graphene Structures
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A Generalized Domain-Decomposition Stochastic FDTD Technique for Complex Nanomaterial and Graphene Structures

机译:复杂纳米材料和石墨烯结构的广义域分解随机FDTD技术

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摘要

The systematic and accurate design process of realistic nanocomposite applications and finite-sized graphene setups with arbitrary media uncertainties is presented in this paper by a 3-D covariant/contravariant stochastic finite-difference time-domain method. The new technique uses extra nodes pertinent to a convex combination of all obtainable spatial increments and introduces a robust domain-decomposition formulation combined with Lagrange multipliers to considerably decrease the system overhead. In this way, the mean value and the standard deviation of field components are evaluated in a single run. The performance of the proposed algorithm is validated by various statistically varying nanoscale applications.
机译:本文通过3-D协变/反变随机有限差分时域方法,提出了具有现实意义的纳米复合材料应用和具有任意介质不确定性的有限尺寸石墨烯装置的系统,准确的设计过程。新技术使用了与所有可获得的空间增量的凸组合有关的额外节点,并引入了与Lagrange乘法器结合的鲁棒的域分解公式,以显着减少系统开销。这样,可以在一次运行中评估场分量的平均值和标准偏差。所提出算法的性能通过各种统计上变化的纳米级应用得到了验证。

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