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Time-varying sensitivity analysis for mixing in chaotic flows: a comparison study

Carla Feistner; Francesca Ziliotto; Barbara Wohlmuth; Gabriele Chiogna
Stochastic Environmental Research and Risk Assessment · Vol. 40, Issue 3 · 2026

Abstract

Engineered injection and extraction systems that create chaotic advection are promising procedures for enhancing mixing between two species. Mixing efficiencies vary considerably, so carefully selecting the design parameters, like pumping rates, well locations, or operation times, is crucial. While numerous studies investigate the conditions required to achieve chaotic flow, sensitivity analyses addressing its impact on mixing have rarely been performed. However, selecting a suitable sensitivity analysis method depends on the underlying system and is often restricted by the computational cost, especially when considering complex, high-dimensional models. Moreover, the most appropriate metric to quantify mixing (e.g., plume area, peak concentration) can also be system-specific. We perform a time-varying sensitivity analysis on the mixing enhancement of two chaotic flow fields with different complexities. The rotated potential mixing (RPM) flow is parametrized using two or four hyperparameters, while the quadrupole flow utilizes $$16$$ hyperparameters. We compare three global sensitivity analysis methods: Sobol indices, Morris scores, and a modification of the activity scores. We evaluate the temporal evolution of the sensitivity of the design parameters, compare the performance of the three methods, and highlight their potential in analyzing parameter interactions. The analysis of the RPM flow shows comparable sensitivities for all methods. Additionally, our numerical experiments show that Morris is the cheapest method, needing at most four times fewer model evaluations than Sobol to reach convergence. This motivates us to only use the computationally cheaper but as reliable Morris and activity scores on the $$16$$ -dimensional model, yielding again consistent results.

Bibliographic Information

JournalStochastic Environmental Research and Risk Assessment
PublisherSpringer
Publication Date2026-03-01
Publication Year2026
Volume40
Issue3
Document TypeJournal Article
Print ISSN1436-3240
eISSN1436-3259
DOI10.1007/s00477-025-03125-7

Access Information

NARA Access Coverage1987-01-01~Current
Journal Homepagehttps://www.springer.com/journal/477
Publisher PageOpen Publisher Page
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