Abstract
A slightly simplified form of Thomson’s Lagrangian stochastic model (LSM) is presented for dispersion applications in three-dimensional (3D) flow fields. It is found that the Lagrangian velocity of a particle in 3D inhomogeneous Gaussian turbulence can be decomposed into the local Eulerian mean velocity UEi at the particle position and a velocity perturbation u′i. The Eulerian mean wind can be predicted by 3D wind field models, whereas the u′i is obtained from Thomson’s model and depends on the turbulence field. The UEi, u′i decomposition was used earlier in a two-dimensional particle model for a canopy (by Flesch and Wilson) and in models with 3D mean winds but with u′i based on LSM forms differing from that of Thomson. This note shows that the UEi, u′i decomposition is consistent with Thomson’s LSM for general 3D flow fields and is a simpler solution that should lead to improved computational efficiency for dispersion applications.
Determining 3D Flow Fields via Multi-camera Light Field Imaging