Cutoff value for predicting success in triathlon mixed team relay

IntroductionThe Mixed-Team-Relay (MTR) triathlon is an original race format present on the international scene since 2009, which became an Olympic event at the Tokyo 2020 Games. The aim of this study was to define the probabilities of reaching a victory, a podium, or a finalist rank in a relay triathlon, according to the position of any of the four relayers (Women/Men/Women/Men) during each of the four segments (leg) of the race.MethodsAll MTR results from the World Series, Continental Championships, World Championships from 2009 to 2021 and Tokyo 2020 Olympics have been collected. We calculated the set of probability frequencies of reaching a given final state, according to any transient state during the race. All results are compared with a V' Cramer method.ResultsThe frequency of winning is similar at the end of Leg 1 for TOP1 (first position) and TOP2-3 (second and third positions). Then, a difference in the winning-associated frequencies is first observed after the Bike stage of Leg 2, where 47% of TOP1 athletes will win, vs 13% of the TOP2-3.DiscussionThis difference continually increases until the end of the race. Legs 2 and 3 are preponderant on the outcome of the race, the position obtained by each triathlete, especially in swimming and cycling, greatly influences the final performance of the team. Leg 1 allows to maintain contact with the head of the race, while Leg 4 sets in stone the position obtained by the rest of the team

Low computational cost semi-analytical magnetostatic model for magnetocaloric refrigeration systems

The analysis of the active magnetic refrigeration (AMR) cycle for different waveforms of both the magnetic field and the velocity of the heat transfer fluid is an essential challenge in designing and implementing heating and cooling systems based on the magnetocaloric effect. One of the most important issue is the correct modelling of the magnetic and thermal behavior of the active magnetocaloric materials (MCM) in order to estimate precisely cooling capacity of the magnetocaloric system. As the multiphysics coupling implies successive calls for both the thermal and the magnetic modelling subroutines, the execution time of these subroutines has to be as short as possible. For this purpose, a new magnetostatic model based on reluctance network has been performed to calculate the internal magnetic field and the internal magnetic flux density of the active magnetocaloric material (gadolinium, Gd) inside the air gap of the magnetic circuit. Compared to a 3D Finite Element Model (FEM), our magnetostatic semi-analytical model leads to a sharp drop of the computation time, while offering a similar precision for all magnetic quantities in the whole magnetocaloric system