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

Abstract

The interaction between a diver and a diving board is one of the key factors of springboard diving performance. An accurate modelling 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 behaviour similar to that observed experimentally. The mechanical characterization method was based on motion capture data of the diver and the springboard. Firstly, 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 Article title experimental and numerical vertical displacements between 0.045 m and 0.060 m. An accurate model may help to better understand energy transfers and time synchronisation between the diver and the springboard, which are key points of the diving board performance.

Simulated Increase in Monoarticular Hip Muscle Strength Reduces the First Peak of Knee Compression Forces During Walking

“…This process was suitable for interaction between a human subject and a moving and/or non-horizontal structure. Secondly, the forces were distributed among them using an optimization approach (Demestre et al 2022). An inverse dynamics step was then carried out using the Matlab toolbox CusToM to compute joint torques .…”