# Alignment of elongated swimmers in a laminar and turbulent Kolmogorov flow

Source: [Alignment of elongated swimmers in a laminar and turbulent Kolmogorov flow](<https://www.sota2.com/research/paper/68fa42201e209131ce8fff76>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T03:38:09.340Z

Authors: M. Borgnino, G. Boffetta, M. Cencini, F. De Lillo, K. Gustavsson

Published: 2022-03-09T16:06:27.000Z

## Abstract

Many aquatic microorganisms are able to swim. In natural environments they typically do so in the presence of flows. In recent years it has been shown that the interplay of swimming and flows can give rise to interesting and biologically relevant phenomena, such as accumulation of microorganisms in specific flow regions and local alignment with the flow properties. Here, we consider a mechanical model for elongated microswimmers in a Kolmogorov flow, a prototypic shear flow, both in steady and in turbulent conditions. By means of direct numerical simulations, supported by analytical calculation in a simplified stochastic setting, we find that the alignment of the swimming direction with the local velocity is a general phenomenon. We also explore how the accumulation of microorganisms, typically observed in steady flows, is modified by the presence of unsteady fluctuations.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [Glass Segmentation on RGB-T dataset Images with glass 1.0 (test)](<https://www.sota2.com/research/sota/glass-segmentation-on-rgb-t-dataset-images-with-glass-1-0-test.md>): Glass Segmentation; RGB-T dataset Images with glass 1.0 (test); MAE: 3.1.

- [Glass Segmentation on RGB-T dataset Images without glass 1.0 (test)](<https://www.sota2.com/research/sota/glass-segmentation-on-rgb-t-dataset-images-without-glass-1-0-test.md>): Glass Segmentation; RGB-T dataset Images without glass 1.0 (test); MAE: 0.004.

- [Glass Segmentation on RGB-T dataset All images 1.0 (test)](<https://www.sota2.com/research/sota/glass-segmentation-on-rgb-t-dataset-all-images-1-0-test.md>): Glass Segmentation; RGB-T dataset All images 1.0 (test); MAE: 0.029.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2203.04833>)

[PDF](<https://arxiv.org/pdf/2203.04833.pdf>)