The aim of this study was to analyse the effect of depth on drag during the underwater gliding. CFD simulations were applied to the flow around a 3D model of a male adult swimmer in a prone gliding position with the arms extended at the front. The domain to perform the simulations was created with 3.0 m depth, 3.0 m width and 11.0 m length. The drag coefficient and the hydrodynamic drag force were computed, using a steady flow velocity of 2.50 m/s for depths of 0.20, 0.50, 1.0, 1.50, 2.01 2.50 and 2.80 m. As the depth increased, the drag coefficient and drag force decreased. The water depth seems to have a positive effect on reducing hydrodynamic drag during the gliding after starts and turns, although a compromise between decreasing drag (by increasing water depth) and gliding travel distance should be a main concern of swimmers.

The purpose of this study was to analyze the hydrodynamic characteristics of a realistic model of an elite swimmer hand/forearm using three-dimensional computational fluid dynamics techniques. A three-dimensional domain was designed to simulate the fluid flow around a swimmer hand and forearm model in different orientations (0°, 45°, and 90° for the three axes Ox, Oy and Oz). The hand/forearm model was obtained through computerized tomography scans. Steady-state analyses were performed using the commercial code Fluent. The drag coefficient presented higher values than the lift coefficient for all model orientations. The drag coefficient of the hand/forearm model increased with the angle of attack, with the maximum value of the force coefficient corresponding to an angle of attack of 90°. The drag coefficient obtained the highest value at an orientation of the hand plane in which the model was directly perpendicular to the direction of the flow. An important contribution of the lift coefficient was observed at an angle of attack of 45°, which could have an important role in the overall propulsive force production of the hand and forearm in swimming phases, when the angle of attack is near 45°.

The aim of this study was to assess the effects of 8-weeks of training on active drag in young swimmers of both genders. Eight girls and twelve boys’ belonging to the same swimming team and with regular competitive participation in national and regional events for the previous two seasons participated in this study. Active drag measurements were conducted in two different evaluation moments: at the beginning of the season and after 8 weeks of training (6.0 ± 0.15 training units per week, 21.00 ± 3.23 km per week and 3.50 ± 0.23 km per training unit). The maximal swimming velocity at the distance of 13 m, active drag and drag coefficient were measured on both trials by the method of small perturbations with the help of an additional hydrodynamic body. After 8 weeks of training, mean active drag (drag force and drag coefficient) decreased in girls and boys, although no significant differences were found between the two trials. It seems that 8 weeks of swimming training were not sufficient to allow significant improvements on swimming technique.

Swimming performance is affected by several factors including the swimming technique, the swimmer’s functional and metabolic characteristics and the level of training accomplishment. However, performance is also depending on the swimmer’s anthropometrical characteristics. The body shape, body size and body composition can play an important role to achieve higher performances.

In the sports field, numerical simulation techniques have been shown to provide useful information about performance and to play an important role as a complementary tool to physical experiments. Indeed, this methodology has produced significant improvements in equipment design and technique prescription in different sports (Kellar et al., 1999; Pallis et al., 2000; Dabnichki & Avital, 2006). In swimming, this methodology has been applied in order to better understand swimming performance. Thus, the numerical techniques have been addressed to study the propulsive forces generated by the propelling segments (Rouboa et al., 2006; Marinho et al., 2009a) and the hydrodynamic drag forces resisting forward motion (Silva et al., 2008; Marinho et al., 2009b). Although the swimmer’s performance is dependent on both drag and propulsive forces, within this chapter the focus is only on the analysis of the propulsive forces. Hence, this chapter covers topics in swimming propelling force analysis from a numerical simulation technique perspective. This perspective means emphasis on the fluid mechanics and computational fluid dynamics methodology applied in swimming investigations. One of the main aims for performance (velocity) enhancement of swimming is to maximize propelling forces whilst not increasing drag forces resisting forward motion, for a given trust. This chapter will concentrate on numerical simulation results, considering the scientific simulation point-of-view, for this practical application in swimming.

A propulsão no meio aquático é baseada na interacção entre o movimento do nadador e o meio envolvente. Neste âmbito, o objectivo principal dos movimentos propulsivos é o de transmitir momento linear ao meio. Esta transferência de momento entre o corpo do nadador e o meio aquático é mediada pela 3ª Lei de Newton (Lei da acção reacção). A forma mais fácil e económica de gerar propulsão seria pela utilização de pontos de apoio rígidos, nos quais a mão se pudesse fixar, permitindo o deslocamento do corpo do nadador para a frente, tal como sucede no MAD System (Measuring Active Drag System; Hollander et al., 1986).

Hydrodynamic drag is the force that a swimmer has to overcome in order to maintain his movement through water and is influenced by velocity, shape, size and the frontal surface area Thus, the aim of this study was to assess the effects of 8 weeks of training on active drag in young female swimmers. 8 female age group swimmers belonging to the same swimming club participated in this study. Active drag measurements were conducted in two different trials: at the beginning of the season and after 8 weeks of training. The velocity perturbation method was used to determine active drag in front crawl swimming. After 8 weeks of training, mean active drag decreased, although no significant differences were found between the two trials. No significant differences were observed in swimming velocity between the two trials. It seems that 8 weeks of swimming training were not enough to allow significant improvements on swimming technique. One can recommend that specific training sets concerning technique correction and improvement in young swimmers should be a main aim during training planning.

Physical activity plays a paramount role on children growth and schools emerged as a key setting for pro- moting physical activity during childhood. The aim of this study was to verify the effects of a high intensi- ty circuit training performed during regular physical education classes at schools. One hundred and five children aged 11–14 years (71 boys and 34 girls) were evaluated. The participants were split into a control group (boys: N = 47; girls: N = 16) and an experimental group (boys: N = 24; girls: N = 18). Besides the normal physical education classes, the experimental group also performed a high intensity circuit training for eight weeks, twice a week, at the beginning of the lesson. A pre- post-test was performed. Cardiorespiratory (20 m shuttle run test ) and a set of strength variables were evaluated. Percentage of fat mass was used as a somatic indicator. The 20 m shuttle run test presented a significant time effect, but not a time X sex, time X group, and time X weight status interactions. Conversely, the strength variables presented a significant time X group interaction (significant differences between groups). Percentage of fat mass presented a significant time effect, but not a significant time X group interaction. Data showed that adding a high intensity circuit training to physical education classes would result in a significant increase in muscular fitness performance in children, but cardiorespiratory fitness may not present the same magnitude of improvement. High in- tensity circuit training programs (performed during regular physical education classes at schools) seem to present a positive and significant effect in physical fitness parameters as well as reducing the percentage of fat mass.

Swimming assessment is one of the most complex but outstanding and fascinating topics in biomechanics. Computational fluid dynamics (CFD) methodology is one of the different methods that have been applied in swimming research to observe and understand water movements around the human body and its application to improve swimming performance. CFD has been applied attempting to understand deeply the biomechanical basis of swimming. Several studies have been conducted willing to analyze the propulsive forces produced by the propelling segments and the drag force resisting forward motion. CFD technique can be considered as an interesting new approach for evaluation of swimming hydrodynamic forces, according to recent evidences. In the near future, as in the present, CFD will provide valorous arguments for defining new swimming techniques or equipments.

The main aim of this study was to investigate the effect of finger spread on the propulsive force production in swimming using computational fluid dynamics. Computer tomography scans of an Olympic swimmer hand were conducted. This procedure involved three models of the hand with differing finger spreads: fingers closed together (no spread), fingers with a small (0.32 cm) spread, and fingers with large (0.64 cm) spread. Steady-state computational fluid dynamics analyses were performed using the Fluent code. The measured forces on the hand models were decomposed into drag and lift coefficients. For hand models, angles of attack of 0°, 15°, 30°, 45°, 60°, 75°, and 90°, with a sweep back angle of 0°, were used for the calculations. The results showed that the model with a small spread between fingers presented higher values of drag coefficient than did the models with fingers closed and fingers with a large spread. One can note that the drag coefficient presented the highest values for an attack angle of 90° in the three hand models. The lift coefficient resembled a sinusoidal curve across the attack angle. The values for the lift coefficient presented few differences among the three models, for a given attack angle. These results suggested that fingers slightly spread could allow the hand to create more propulsive force during swimming.