Mixing of Gaussian Solute Plumes

TL;DR

This paper develops a comprehensive framework for understanding the mixing of Gaussian solute plumes across various flow regimes, highlighting the role of initial conditions, flow deformation, and the Protean coordinate system in predicting plume evolution.

Contribution

It introduces a unified approach to model Gaussian plume mixing using the deformation tensor in Protean coordinates, simplifying analysis across diverse flow types.

Findings

Evolution of Gaussian plumes depends on initial distribution, dispersion tensor, and deformation history.

Protean coordinates simplify the deformation tensor, linking plume evolution to Lyapunov exponents and shear rates.

Results enable efficient numerical methods for solute transport in complex flows.

Abstract

We consider the general problem of mixing of Gaussian solute plumes arising across a range of different flows ranging from two-dimensional (2D) to three-dimensional (3D), steady to unsteady, regular to chaotic, Stokes to turbulent. We consider a a range of infinitesimal injection protocols (point or line sources, continuous or pulsed) which generate solute points, lines and sheets and their finite-sized counterparts (blobs, tubes and slabs). We show that evolution of this broad family of Gaussian plumes is solely governed by the initial solute distribution, the dispersion tensor and the Lagrangian history of the deformation gradient tensor. Significant simplifications arise when the deformation tensor is placed in the Protean (Lester et al, JFM, 2018) coordinate frame (which aligns with the maximum and minimum fluid stretching directions and renders the deformation tensor upper triangular), allowing evolution of the Gaussian covariance matrix to be expressed in physically relevant terms such as Lyapunov exponents, longitudinal and transverse shear rates. We couch these results in terms of evolution of the maximum concentration and scalar entropy of Gaussian plume for a range of flows and injection protocols. These results provide significant insights into the processes that govern mixing in a broad range of flows and provide the building blocks of efficient numerical methods using e.g. radial basis functions for solute transport and mixing in arbitrary flows.