Data-driven mathematical modelling of particle dynamics in opaque fluid flows

检验由弱可压缩流平流的两个粒子的弥散，使用将惯性粒子动力学简化为通过弱可压缩流的被动平流或在弱可压缩海洋表面流中使用非惯性粒子的近似值。其主要目的是从流动的拉格朗日统计数据中表征颗粒的聚集，使用重要性抽样方法来实现否则将难以处理的高效计算。

Examining the dispersion of both particles advected by weakly compressible flow, using an either approximation that reduces inertial-particle dynamics to passive advection by a weakly compressible flow or with non-inertial particles in weakly compressible ocean surface flow. The principal aim is characterisation of the clustering of particles from Lagrangian statistics of the flow, using importance sampling methods to allow efficient computation that would otherwise be intractable.