Pedro Forte

A Comparison of Experimental and Analytical Procedures to Measure Passive Drag in Human Swimming.

The aim of this study was to compare the swimming hydrodynamics assessed with experimental and analytical procedures, as well as, to learn about the relative contributions of the friction drag and pressure drag to total passive drag. Sixty young talented swimmers (30 boys and 30 girls with 13.59±0.77 and 12.61±0.07 years-old, respectively) were assessed. Passive drag was assessed with inverse dynamics of the gliding decay speed. The theoretical modeling included a set of analytical procedures based on naval architecture adapted to human swimming. Linear regression models between experimental and analytical procedures showed a high correlation for both passive drag (Dp = 0.777*Df+pr; R2 = 0.90; R2 a = 0.90; SEE = 8.528; P<0.001) and passive drag coefficient (CDp = 1.918*CDf+pr; R2 = 0.96; R2 a = 0.96; SEE = 0.029; P<0.001). On average the difference between methods was -7.002N (95%CI: -40.480; 26.475) for the passive drag and 0.127 (95%CI: 0.007; 0.247) for the passive drag coefficient. The partial contribution of friction drag and pressure drag to total passive drag was 14.12±9.33% and 85.88±9.33%, respectively. As a conclusion, there is a strong relationship between the passive drag and passive drag coefficient assessed with experimental and analytical procedures. The analytical method is a novel, feasible and valid way to gather insight about one’s passive drag during training and competition. Analytical methods can be selected not only to perform race analysis during official competitions but also to monitor the swimmer’s status on regular basis during training sessions without disrupting or time-consuming procedures.

Technologic Appliance and Performance Concerns in Wheelchair Racing – Helping Paralympic Athletes to Excel

Numerical simulations have provided useful evidence in helping several sportsmen to excel in their field. This methodology aims to have a deeper understanding on the influence of equipment and sports techniques on sports performance. In wheelchair racing, technology was used without considering specific sport (some of the Paraly‐ mpic sports used the same technology of their Olympic counterparts). It has induced unique changes in prosthetic and wheelchair devices. Eventually, technology has become an essential part of Paralympic sports, wheelchair-racing being one of the most popular events. Numerical simulations can help us gather evidence on the effects of drag force acting upon the athlete-chair system. Different types of wheelchairs are designed for racing (track and road races), net, and invasion sports. One of the various strategies to enhance performance is to minimize the aerodynamic drag of the frame, tires, helmet, sports outfit, and body posture. Numerical simulations can be used to predict the fluid dynamics. The goal of this chapter is to review the state-of-the-art numerical simulations and suggest further studies in wheelchair racing. The chapter will include sections covering: (i) main determinants in wheelchair racing; (ii) the effect of aerodynamic force in in wheelchair racing performance; (iii) analytical models, experimental testing, and numerical simulations in wheelchair racing; and (iv) numerical simula‐ tions on equipment and techniques.

Comparison by computer fluid dynamics of the drag force acting upon two helmets for wheelchair racers

The aim of this study was to compare the drag force created by two helmets (time trial and road)used by a wheelchair racer. The head and helmet of the racer were scanned to obtain the3D models. Numerical simulation was run on Fluent, having as output the drag force for both helmets (road and time trial) in two different positions (0° and 90°) and increasing velocities (from 2.0 to 6.5 m/s). The greatest aerodynamic drag was noted wearing a time trial helmet in 90° ranging from 0.1025N to 0.8475N; this was also the position with the highest drag. The velocity with higher drag for booth helmets was at 6.5 m/s. The time trial helmet at 0° had the lower aerodynamic drag, compared with the same position of road helmet. The drag force seems to be lower wearing the time trial helmet and keeping the 0° position and, thus, should be considered for sprinting events.

Correction: A Comparison of Experimental and Analytical Procedures to Measure Passive Drag in Human Swimming

[This corrects the article DOI: 10.1371/journal.pone.0130868.].

The variations on the aerodynamics of a world-ranked wheelchair sprinter in the key-moments of the stroke cycle: A numerical simulation analysis

Biomechanics plays an important role helping Paralympic sprinters to excel, having the aerodynamic drag a significant impact on the athlete’s performance. The aim of this study was to assess the aerodynamics in different key-moments of the stroke cycle by Computational Fluid Dynamics. A world-ranked wheelchair sprinter was scanned on the racing wheelchair wearing his competition gear and helmet. The sprinter was scanned in three different positions: (i) catch (hands in the 12h position on the hand-rim); (ii) the release (hands in the 18h position on the hand-rim) and; (iii) recovery phase (hands do not touch the hand-rim and are hyperextended backwards). The simulations were performed at 2.0, 3.5, 5.0 and 6.5 m/s. The mean viscous and pressure drag components, total drag force and effective area were retrieved after running the numerical simulations. The viscous drag ranged from 3.35 N to 2.94 N, pressure drag from 0.38 N to 5.51 N, total drag force from 0.72 N to 8.45 N and effective area from 0.24 to 0.41 m2. The results pointed out that the sprinter was submitted to less drag in the recovery phase, and higher drag in the catch. These findings suggest the importance of keeping an adequate body alignment to avoid an increase in the drag force.

Aerodynamics of a wheelchair sprinter racing at the 100m world record pace by CFD

The aim of this study was to analyze aerodynamics in a racing position of a wheelchair-racing sprinter, at the world record speed. The athlete and wheelchair were scanned at the beginning of the propulsive phase position (hands near the handrims at 12h) for the 3D model acquisition. Numerical simulation was run on Fluent, having as output the pressure, viscosity and total drag force, and respective coefficients of drag at the world record speed in T-52 category. Total drag was 7.56N and coefficient of drag was 1.65. This work helped on getting a deeper insight about the aerodynamic profile of a wheelchair-racing athlete, at a 100m world record speed.

CFD analysis of head and helmet aerodynamic drag to wheelchair racing

Wheelchair racing, an important event in Paralympics, it requires huge effort from its athletes to overcome the resistive forces. The resistive forces in wheelchair racing are aerodynamic drag and rolling friction. CFD methodology can play a determinant role in aerodynamic analysis. The aim of this study was to analyses the aerodynamic drag at different speeds and attack angles of a human head with a helmet, whilst extrapolating results to better suit the needs of wheelchair racing athletes. Computer Fluid Dynamics methodology was used in this study. A 3D head and helmet scan was obtained from a Paralympics athlete. The 3D model was exported to fluent software generating the aerodynamic drag after numerical simulation. Regardless the velocity, 90° attack angle (subject looking down) presented higher aerodynamic drag (0.732 N) Wheelchair racing athletes should maintain a 0° attack angle (looking forward) mainly at speeds greater than 3.5 m/s.

The changes in fractal dimension after a maximal exertion in swimming

Quite often linear variables are not sensitive enough to explain the changes in the motor behavior of elite athletes. So, non-linear variables should be selected. The aim was to compare the fractal dimension before and after a maximal bout swimming front-crawl. Twenty-four subjects performed an all-out 100m trial swimming front-crawl. Immediately before (Pre-test) and after the trial (Post-test) a speed-meter cable was attached to the swimmers waist to measure the hip speed from which fractal dimension was derived. The fractal dimension showed a significant decrease with a moderate effect size between pre- and post-tests. Twenty-one out of 24 swimmers decreased the fractal dimension. As a conclusion, there is a decrease in the fractal dimension and hence in the swimming behavior complexity being under fatigue after a maximal trial.