The DOI matches its Crossref record; 66 of the 66 references it cites were found in a registry or an index.
Hydrodynamics of self-propulsion near a boundary: predictions and accuracy of far-field approximations
Open accessAbstract
The swimming trajectories of self-propelled organisms or synthetic devices in a viscous fluid can be altered by hydrodynamic interactions with nearby boundaries. We explore a multipole description of swimming bodies and provide a general framework for studying the fluid-mediated modifications to swimming trajectories. A general axisymmetric swimmer is described as a linear combination of fundamental solutions to the Stokes equations: a Stokeslet dipole, a source dipole, a Stokeslet quadrupole, and a rotlet dipole. The effects of nearby walls or stress-free surfaces on swimming trajectories are described through the contribution of each singularity, and we address the question of how accurately this multipole approach captures the wall effects observed in full numerical solutions of the Stokes equations. The reduced model is used to provide simple but accurate predictions of the wall-induced attraction and pitching dynamics for model Janus particles, ciliated organisms, and bacteria-like polar swimmers. Transitions in attraction and pitching behaviour as functions of body geometry and propulsive mechanism are described. The reduced model may help to explain a number of recent experimental results.
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Cites
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Self-citationCatalytic Nanomotors: Autonomous Movement of Striped Nanorods
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Metadata
- Authors
- Spagnolie, S. E., & Lauga, E.
- Venue
- Journal of Fluid Mechanics
- Publisher
- Cambridge University Press (CUP)
- Published
- 2012-04-16
- Volume
- 700
- Pages
- 105-147
- ISSN
- 0022-1120 (ISSN-L)
- 1469-7645
- OpenAlex
- W2132820483
- Cited by
- 522
- References
- 66
- FWCI
- 15.86
- Type
- journal article
- Language
- en
- Open access
- green
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- Spagnolie, S. E., & Lauga, E. (2012). Hydrodynamics of self-propulsion near a boundary: predictions and accuracy of far-field approximations. Journal of Fluid Mechanics. https://doi.org/10.1017/jfm.2012.101
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
