论文标题
通过动态模式分解和顺序的奇异值分解的热辐射传输计算的数据驱动加速度
Data-Driven Acceleration of Thermal Radiation Transfer Calculations with the Dynamic Mode Decomposition and a Sequential Singular Value Decomposition
论文作者
论文摘要
我们提出了一种加速离散的方法，以辐射转移的辐射转移计算。与大多数加速度方案相比，我们的方法可与非线性阳性固定一起使用。该方法基于动态模式分解（DMD），并使用一系列排名一的更新来计算DMD所需的奇异值分解。使用顺序方法使我们能够自动确定在DMD加速度中包含的解决方案向量的数量。我们提出了平板几何学离散的结果，以标准温度线性化来计算计算。与积极来源迭代相比，我们的结果表明，在标准扩散的Marshak波问题上，我们的加速度方法减少了解决问题所需的运输量数量约为3，而在冷却问题上，有效散射率在冷却问题上有几千倍因素，其中有效散射率接近统一性，而在逼真的，多层材料的辐射辐射冲击问题中提高了20倍。
We present a method for accelerating discrete ordinates radiative transfer calculations for radiative transfer. Our method works with nonlinear positivity fixes, in contrast to most acceleration schemes. The method is based on the dynamic mode decomposition (DMD) and using a sequence of rank-one updates to compute the singular value decomposition needed for DMD. Using a sequential method allows us to automatically determine the number of solution vectors to include in the DMD acceleration. We present results for slab geometry discrete ordinates calculations with the standard temperature linearization. Compared with positive source iteration, our results demonstrate that our acceleration method reduces the number of transport sweeps required to solve the problem by a factor of about 3 on a standard diffusive Marshak wave problem, a factor of several thousand on a cooling problem where the effective scattering ratio approaches unity, and a factor of 20 improvement in a realistic, multimaterial radiating shock problem.
