The DOI matches its Crossref record.
Dynamic simulation of hydrodynamically interacting particles
Abstract
A general method for computing the hydrodynamic interactions among N suspended particles, under the condition of vanishingly small particle Reynolds number, is presented. The method accounts for both near-field lubrication effects and the dominant many-body interactions. The many-body hydrodynamic interactions reproduce the screening characteristic of porous media and the ‘effective viscosity’ of free suspensions. The method is accurate and computationally efficient, permitting the dynamic simulation of arbitrarily configured many-particle systems. The hydrodynamic interactions calculated are shown to agree well with available exact calculations for small numbers of particles and to reproduce slender-body theory for linear chains of particles. The method can be used to determine static (i.e. configuration specific) and dynamic properties of suspended particles that interact through both hydrodynamic and non-hydrodynamic forces, where the latter may be any type of Brownian. colloidal, interparticle or external force. The method is also readily extended to dynamically simulate both unbounded and bounded suspensions.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Numerical Simulation of Flowing Blood Cells
Freund, J. B. (2014) · Annual Review of Fluid Mechanics · doi:10.1146/annurev-fluid-010313-141349 · Cited by 323
Stokesian Dynamics simulation of Brownian suspensions
Phung, T. N., Brady, J. F., & Bossis, G. (1996) · Journal of Fluid Mechanics · doi:10.1017/s0022112096002170 · Cited by 323
Self-citationYu, I., Mori, T., Ando, T., Harada, R., Jung, J., Sugita, Y., & Feig, M. (2016) · eLife · doi:10.7554/elife.19274 · Cited by 294
Vortex flows impart chirality-specific lift forces
Hermans, T. M., Bishop, K. J. M., Stewart, P. S., Davis, S. H., & Grzybowski, B. A. (2015) · Nature Communications · doi:10.1038/ncomms6640 · Cited by 52
Metadata
- Authors
- Durlofsky, L., Brady, J. F., & Bossis, G.
- Venue
- Journal of Fluid Mechanics
- Publisher
- Cambridge University Press (CUP)
- Published
- 1987-07
- Volume
- 180
- Pages
- 21-49
- ISSN
- 0022-1120 (ISSN-L)
- 1469-7645
- OpenAlex
- W2104547497
- Cited by
- 597
- References
- 0
- FWCI
- 56.23
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Dynamic simulation of hydrodynamically interacting particles. https://app.cochat.ai/papers/10.1017/s002211208700171x
- The paper
- Durlofsky, L., Brady, J. F., & Bossis, G. (1987). Dynamic simulation of hydrodynamically interacting particles. Journal of Fluid Mechanics. https://doi.org/10.1017/s002211208700171x
Data sources
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.