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首页> 外文期刊>Jorunal of computational and theoretical transport >Application of the Transport-Driven Diffusion Approach for Criticality Calculations
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Application of the Transport-Driven Diffusion Approach for Criticality Calculations

机译:运输驱动的扩散方法在临界计算中的应用

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The work presents the application of the transport-driven diffusion (TDD) approximation for the determination of the fundamental eigenvalue of multiplying systems. TDD, recently proposed for source-driven problems by Picca and Furfaro (2014), is a solution method which combines multi-collision transport with diffusion to approximate neutral particle transport in scattering and multiplying media. The method is here extended to deal with eigen-problems (i.e., source-free problems), embedding TDD in the power iteration cycle. The solution approach is assessed on a selection of 1D benchmarks from the literature comparing its performances against diffusion and transport reference solutions. A test on a 2D configuration is also provided to demonstrate the feasibility to extend this approach to more realistic problems. Results show the competitive performance of TDD and, once validated in more general problem settings, this method appears to be particularly interesting in applications where fast evaluations of several configurations are required (e.g., core loading problems). On the basis of its convergence property (for T going to infinity, TDDT tends the transport solution, Picca and Furfaro, 2014), the methodology also offers the opportunity to seek highly accurate solutions by combining a sequence of low-order TDD solutions with powerful non-linear extrapolation techniques, as tested in the paper.
机译:该工作呈现了运输驱动的扩散(TDD)近似的应用,以确定乘法系统的基本特征值。最近提出了Picca和Furfaro(2014)的来源驱动问题的TDD,是一种解决多碰撞传输,其与扩散到散射和倍增介质中的中性粒子传输。此方法在此扩展到处理特征问题(即,无源问题),在功率迭代周期中嵌入TDD。解决方案方法是在从文献中选择的1D基准测试,比较其对扩散和传输参考解决方案的性能。还提供了对2D配置的测试以证明将这种方法扩展到更现实的问题的可行性。结果显示TDD的竞争性能,一旦在更一般的问题设置中验证,该方法似乎特别有趣的应用程序需要多种配置的快速评估(例如,核心加载问题)。在其趋同性的基础上(对于无限,TDDT倾向于运输解决方案,Picca和Furfaro,2014),该方法还提供了通过将一系列具有强大的低阶TDD解决方案来寻求高度准确的解决方案的机会如本文中的测试,非线性外推技术。

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