P\'eclet-number dependence of optimal mixing strategies identified using multiscale norms
Conor Heffernan, Colm-cille Caulfield

TL;DR
This paper investigates how the initial scalar distribution and Péclet number influence optimal mixing strategies, revealing geometry-dependent stirring patterns and limitations of local Péclet number rescaling.
Contribution
It introduces a nonlinear optimization approach to analyze the impact of initial scalar geometry and Péclet number on mixing efficiency, highlighting nonlocal effects.
Findings
Optimal initial velocity perturbations depend on scalar geometry.
Scaling Péclet number locally does not fully capture flow dynamics.
Vortex structures in mixing vary with number of scalar drops.
Abstract
The optimization of the mixing of a passive scalar at finite P\'eclet number (where are characteristic velocity and length scales and is the scalar diffusivity) is relevant to many significant flow challenges across science and engineering. While much work has focused on identifying flow structures conducive to mixing for flows with various values of , there has been relatively little attention paid to how the underlying structure of initial scalar distribution affects the mixing achieved. In this study we focus on two problems of interest investigating this issue. Our methods employ a nonlinear direct-adjoint looping (DAL) method to compute fluid velocity fields which optimize a multiscale norm (representing the `mixedness' of our scalar) at a finite target time. First, we investigate how the structure of optimal initial velocity perturbations and the…
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