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Characterization of the dynamic behavior of a diving board using motion capture data

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Abstract

The interaction between a diver and a diving board is one of the key factors of springboard diving performance. An accurate modeling of this interaction could provide new tools to better understand springboard diving performance. This study presents a finite element model of a springboard driven by motion capture data. The aim was to identify springboard mechanical parameters allowing to obtain a model with a mechanical behavior similar to that observed experimentally. The mechanical characterization method was based on motion capture data of the diver and the springboard. First, these data were used to estimate the interaction forces and moments between the diver and the springboard using an optimization approach. The interaction forces and moments were then applied to the springboard model to be characterized. Finally, the model parameters were identified minimizing the discrepancy between the experimental and numerical vertical displacements of the springboard. The best model obtained from this method led to a maximal mean absolute error between the experimental and numerical vertical displacements between 0.045 and 0.060 m. An accurate model may help to better understand energy transfers and time synchronization between the diver and the springboard, which are key points of the diving board performance.

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Acknowledgements

This study is supported by the ANR within the framework of the PIA EUR DIGISPORT project (ANR-18-EURE-0022). The authors wish to thank François May for his help in developing the IF&M computation method.

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Author notes

  1. Stéphane Grange, Cécile Dubois, Nicolas Bideau, Guillaume Nicolas, Charles Pontonnier and Georges Dumont have contributed equally to this work.

Authors and Affiliations

  1. Univ Rennes, Inria, IRISA-UMR 6074, 35000, Rennes, France

    Louise Demestre, Cécile Dubois, Charles Pontonnier & Georges Dumont

  2. Univ Lyon, INSA-Lyon, GEOMAS, 69100, Villeurbanne, France

    Stéphane Grange

  3. Univ Rennes, Inria, M2S, 35000, Rennes, France

    Nicolas Bideau & Guillaume Nicolas

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  1. Louise Demestre
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  2. Stéphane Grange
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  3. Cécile Dubois
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  4. Nicolas Bideau
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  5. Guillaume Nicolas
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  7. Georges Dumont
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Correspondence to Louise Demestre.

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The participant signed an informed consent form in agreement with the ethical committee of Rennes 2 University (Reference 2022-006).

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Demestre, L., Grange, S., Dubois, C. et al. Characterization of the dynamic behavior of a diving board using motion capture data. Sports Eng 25, 21 (2022). https://doi.org/10.1007/s12283-022-00388-z

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