CFD for sport: experimental and computational investigation of drag profiles in swimming

Abstract

Contextually in elite level competitive swimming, minimising drag and maximising propulsion is a necessity. In age-group swimming, athletes in the same programme are often instructed to swim with the same technique, with said technique based on coach opinion and historical practice. These practices must change in order to maximise athlete potential. The use of data and research to drive training in swimming is not new, but is reserved for top level club and national programmes, often times still giving way to the coach’s opinions. The aim of this thesis is to develop novel experimental and computational methodologies capable of predicting the drag profile in front crawl swimming, with simulations able to display the impact of technical changes on the drag profile. In this thesis, a novel method for experimentally predicting the active drag across a full stroke cycle is presented, allowing visualisation of how drag varies across a front crawl stroke cycle. Scrutiny of literature showed the need for further methods that allow investigation into the active drag profile as, currently, there are few methods capable of producing this profile. Results from the novel method detailed in this thesis, although matching reasonably well with literature, will need further validation and repeatability studies. Secondly, using a novel immersed boundary surface method approach, the impact of front crawl technical changes on the active drag profile was evaluated. This method was validated against literature, with simulation results showing some agreement with experimental results. The impact of changing kick rate on the drag profile is a highlight, although further grid refinement studies are required to improve result accuracy. Further investigation of technical changes and the improvement of the simulation results can be completed by considering the multi-phase physics of the problem.

Thesis is embargoed until 31 July 2028.

Date of Award	Jul 2026
Original language	English
Awarding Institution	Queen's University Belfast
Sponsors	Department for the Economy
Supervisor	Adrian Murphy (Supervisor) & Alex Lennon (Supervisor)