Optimal Stirring Strategies for Passive Scalars in a Domain with a General Shape and No-Flux Boundary Condition

Authors

DOI:

https://doi.org/10.4208/aamm.OA-2024-0218

Keywords:

Mixing, flow control and optimization, passive scalar

Abstract

Multiscale metrics such as negative Sobolev norms are effective for quantifying the degree of mixedness of a passive scalar field advected by an incompressible flow in the absence of diffusion. In this paper, we adopt a mix norm that is motivated by the Sobolev norm $H^{-1}$ for a general domain with a no-flux boundary. We then derive an explicit expression for the optimal flow that maximizes the instantaneous decay rate of the mix norm under fixed energy and enstrophy constraints. Numerical simulations indicate that the mix norm decays exponentially or faster for various initial conditions and geometries and the rate is closely related to the smallest non-zero eigenvalue of the Laplace operator. These results generalize previous findings restricted to a periodic domain for its analytical and numerical simplicity. Additionally, we observe that periodic boundaries tend to induce a faster decay in mix norm compared to no-flux conditions under the fixed energy constraint, while the comparison is reversed for the fixed enstrophy constraint. In the special case of even initial distributions, two types of boundary conditions yield the same optimal flow and mix norm decay. These insights provide a broader framework for understanding scalar mixing across different boundary conditions, offering practical implications for optimizing flow in various physical and engineering systems.

Author Biographies

  • Sirui Zhu

    School of Mathematical Sciences, Zhejiang University, Hangzhou, Zhejiang 310027, China

  • Zhi Lin

    School of Mathematical Sciences, Zhejiang University, Hangzhou, Zhejiang 310027, China

  • Liang Li

    School of Mathematical Sciences, Zhejiang University, Hangzhou, Zhejiang 310027, China

  • Lingyun Ding

    Department of Mathematics, University of California Los Angeles, Los Angeles, CA 90095, United States

Published

2025-10-29

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