Why swimming hydrodynamics?
Swimming performance couples body motion, hydrodynamic forces and the distribution of mechanical effort across a stroke. This project studies how selected movement parameters change the numerical response, while keeping the model and evaluation window consistent.
The research moved from an OpenFOAM route with substantial runtime and convergence costs to SWUM in July 2026. SWUM supplies a more tractable framework for repeated stroke and parameter studies; it does not remove the need to examine model assumptions and validation.
Baseline first, then comparisons
A repeatable baseline is the reference for every perturbation. Stroke definition, body model, initial conditions, cycle count and the statistical window are kept explicit so that a parameter comparison has a consistent meaning.
- 01
Baseline model
Establish the freestyle reference and inspect its cycle-to-cycle response.
- 02
Single-factor studies
Vary high-elbow (HE) and palm-pitch (SR) parameters separately.
- 03
Interaction studies
Extend to coupled parameters, including HE × SR, while retaining the reference definition.
- 04
Multi-cycle analysis
Use ten-cycle runs and an identified analysis window to inspect periodic stability.
- 05
Multiple objectives
Compare sensitivity and Pareto relationships using more than one mechanical metric.
Freestyle · high elbow, palm pitch & interactions
| Study element | Question | Interpretation boundary |
|---|---|---|
| High elbow / HE | How does a high-elbow parameter alter the modeled stroke response? | A model-parameter effect, not a universal coaching prescription. |
| Palm pitch / SR | How does changing palm orientation affect forces and mechanical response? | Depends on the motion definition and the chosen baseline. |
| HE × SR | Does the combined change differ from separate changes? | Interaction must be evaluated against the same statistical window. |
| Sensitivity / Pareto | Which changes matter, and which objectives trade off? | Ranking depends on metrics, parameter ranges and constraints. |
The freestyle parameter studies and multi-objective analysis stages have been archived. Numerical values are not reproduced here without the corresponding machine data and final statistical definitions.
Ten-cycle statistics & evidence
Ten-cycle simulations provide more material for assessing periodic stability than an isolated stroke. The useful comparison is made after examining transient behavior, cycle averages, fluctuations and phase relationships.
- Review time histories as well as cycle-averaged quantities.
- Inspect peak magnitude together with its phase; do not reduce the result to one peak.
- Keep force integrals or impulse, mean values and fluctuation measures tied to a defined cycle window.
- Use the same baseline and normalization when comparing cases.
A ten-cycle run is an analysis choice, not automatic proof of convergence. Stability and robustness must be justified by the recorded signals.
Sensitivity & multi-objective mechanics
Sensitivity analysis organizes how the selected parameters affect different response metrics. Interaction studies then ask whether combined changes behave additively. Pareto analysis identifies trade-offs among the selected objectives rather than declaring one movement optimal in every sense.
This page records the methodology and study scope. It does not recreate a Pareto front, publish unsupported efficiency gains, or infer causality beyond the numerical model.
Breaststroke extension
A breaststroke extension began in August 2026, with a v1.1 baseline and a frozen ten-cycle package. It provides a separate reference for another stroke rather than reusing freestyle conclusions without checking the movement and model differences.
Freestyle and breaststroke results need their own baseline identifiers, motion definitions and statistical windows before cross-stroke comparisons are meaningful.
Validation & limitations
SWUM results remain numerical results conditioned on the body model, motion inputs and force representation. Parameter sensitivity within the model does not establish a causal effect on real swimmers.
- Distinguish model consistency from validation against experiments.
- Check periodic stability and initial transients before summarizing cases.
- Record the parameter range and avoid extrapolating a ranking outside it.
- Keep any comparison to measurements tied to the actual dataset and uncertainty.
No experimental validation result or published-paper status is claimed here.
Research archive
Freestyle analyses & breaststroke baseline
Baseline and parameter-study records, interaction analyses, multi-cycle statistics and multi-objective mechanics; breaststroke v1.1 baseline and ten-cycle package.
Research writing and technical records are part of the project archive. This website update does not attach a manuscript or assign a publication status.
How the archive can grow
Attach verified result tables and figures together with the scripts that compute them. When a manuscript or dataset is made public, connect it here with its actual title, version and permanent link.
