论文标题
格林功能的随机估计，并应用于扩散和对流扩散反应问题
Stochastic estimation of Green's functions with application to diffusion and advection-diffusion-reaction problems
论文作者
论文摘要
描述了一种随机方法，用于估计格林功能（GF），该功能适用于线性对流扩散反应的转运问题，并在任意几何形状中演变。通过在任何几何形状中，允许直接构建近似值，尽管高准确的GF，但该技术解决了获得Green功能解决方案的核心挑战。与蒙特卡洛解决方案相反，在特定条件和强迫的情况下，该提议的技术可产生可使用的近似GF，可以使用：a）以（随机和确定性的）边界，初始和内部强迫的任何组合（无限）解决方案集合，作为较高的效果质量和c的高质量和c的质量和C的高品质和c的质量较高的过程，并且是构成质量和C的高品质和C的高质量，并且是较高的过程。
A stochastic method is described for estimating Green's functions (GF's), appropriate to linear advection-diffusion-reaction transport problems, evolving in arbitrary geometries. By allowing straightforward construction of approximate, though high-accuracy GF's, within any geometry, the technique solves the central challenge in obtaining Green's function solutions. In contrast to Monte Carlo solutions of individual transport problems, subject to specific sets of conditions and forcing, the proposed technique produces approximate GF's that can be used: a) to obtain (infinite) sets of solutions, subject to any combination of (random and deterministic) boundary, initial, and internal forcing, b) as high fidelity direct models in inverse problems, and c) as high quality process models in thermal and mass transport design, optimization, and process control problems.
