Numerical Simulation of Two-Phase Flow Around Flatwater Competition Kayak Design-Evolution Models

The aim of the current study was to analyze the hydrodynamics of three kayaks: 97-kg-class, single-rower, flatwater sports competition, full-scale design evolution models (Nelo K1 Vanquish LI, LII, and LIII) of M.A.R. Kayaks Lda., Portugal, which are among the fastest frontline kayaks. The effect of kayak design transformation on kayak hydrodynamics performance was studied by the application of computational fluid dynamics (CFD). The steady-state CFD simulations where performed by application of the k-omega turbulent model and the volume-of-fluid method to obtain two-phase flow around the kayaks. The numerical result of viscous, pressure drag, and coefficients along with wave drag at individual average race velocities was obtained. At an average velocity of 4.5 m/s, the reduction in drag was 29.4% for the design change from LI to LII and 15.4% for the change from LII to LIII, thus demonstrating and reaffirming a progressive evolution in design. In addition, the knowledge of drag hydrodynamics presented in the current study facilitates the estimation of the paddling effort required from the athlete during progression at different race velocities. This study finds an application during selection and training, where a coach can select the kayak with better hydrodynamics.info:eu-repo/semantics/publishedVersio

The Computational Fluid Dynamics Study of Orientation Effects of Oar Blade

The distribution of pressure coefficient formed when the fluid contacts with the kayak oar blade is not been studied extensively. The CFD technique was employed to calculate pressure coefficient distribution on the front and rear faces of oar blade resulting from the numerical resolution equations of the flow around the oar blade in the steady flow conditions (4 m/s) for three angular orientations of the oar (45°, 90°, 135°) with main flow. A three-dimensional (3D) geometric model of oar blade was modeled and the k-ε turbulent model was applied to compute the flow around the oar. The main results reported that, under steady state flow conditions, the drag coefficient (Cd = 2.01 for 4 m/s) at 90° orientation has the similar evolution for the different oar blade orientation to the direction of the flow. This is valid when the orientation of the blade is perpendicular to the direction of the flow. Results indicated that the angle of oar strongly influenced the Cd with maximum values for 90° angle of the oar. Moreover, the distribution of the pressure is different for the internal and external edges depending upon oar angle. Finally, the difference of negative pressure coefficient Cp in the rear side and the positive Cp in the front side, contributes toward propulsive force. The results indicate that CFD can be considered an interesting new approach for pressure coefficient calculation on kayak oar blade. The CFD approach could be a useful tool to evaluate the effects of different blade designs on the oar forces and consequently on the boat propulsion contributing toward the design improvement in future oar models. The dependence of variation of pressure coefficient on the angular position of oar with respect to flow direction gives valuable dynamic information, which can be used during training for kayak competition.info:eu-repo/semantics/publishedVersio

Analysis of wind velocity and release angle effects on discus throw using computational fluid dynamics

The aim of this paper is to study the aerodynamics of discus throw. A comparison of numerical and experimental performance of discus throw with and without rotation was carried out using the analysis of lift and drag coefficients. Initial velocity corresponding to variation angle of around 35.5° was simulated. Boundary condition, on the top and bottom boundary edges of computational domain, was imposed in order to eliminate external influences on the discus; a wind resistance was calculated for the velocity values of 25 and 27 m/s. The results indicate that the flight distance (D) was strongly affected by the drag coefficient, the initial velocity, the release angle and the direction of wind velocity. It was observed that these variables change as a function of discus rotation. In this study, results indicate a good agreement of D between experimental values and numerical results.info:eu-repo/semantics/publishedVersio

Modelling Propelling Force in Swimming Using Numerical Simulations

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

Analysis of drafting effects in swimming using computational fluid dynamics

The purpose of this study was to determine the effect of drafting distance on the drag coefficient in swimming. A k-epsilon turbulent model was implemented in the commercial code Fluent(®) and applied to the fluid flow around two swimmers in a drafting situation. Numerical simulations were conducted for various distances between swimmers (0.5-8.0 m) and swimming velocities (1.6-2.0 m.s(-1)). Drag coefficient (Cd) was computed for each one of the distances and velocities. We found that the drag coefficient of the leading swimmer decreased as the flow velocity increased. The relative drag coefficient of the back swimmer was lower (about 56% of the leading swimmer) for the smallest inter-swimmer distance (0.5 m). This value increased progressively until the distance between swimmers reached 6.0 m, where the relative drag coefficient of the back swimmer was about 84% of the leading swimmer. The results indicated that the Cd of the back swimmer was equal to that of the leading swimmer at distances ranging from 6.45 to 8. 90 m. We conclude that these distances allow the swimmers to be in the same hydrodynamic conditions during training and competitions. Key pointsThe drag coefficient of the leading swimmer decreased as the flow velocity increased.The relative drag coefficient of the back swimmer was least (about 56% of the leading swimmer) for the smallest inter-swimmer distance (0.5 m).The drag coefficient values of both swimmers in drafting were equal to distances ranging between 6.45 m and 8.90 m, considering the different flow velocities.The numerical simulation techniques could be a good approach to enable the analysis of the fluid forces around objects in water, as it happens in swimming.info:eu-repo/semantics/publishedVersio

Hydrodynamic Drag during Gliding in Swimming

This study used a computational fluid dynamics methodology to analyze the effect of body position on the drag coefficient during submerged gliding in swimming. The k-epsilon turbulent model implemented in the commercial code Fluent and applied to the flow around a three-dimensional model of a male adult swimmer was used. Two common gliding positions were investigated: a ventral position with the arms extended at the front, and a ventral position with the arms placed along side the trunk. The simulations were applied to flow velocities of between 1.6 and 2.0 m x s(-1), which are typical of elite swimmers when gliding underwater at the start and in the turns. The gliding position with the arms extended at the front produced lower drag coefficients than with the arms placed along the trunk. We therefore recommend that swimmers adopt the arms in front position rather than the arms beside the trunk position during the underwater gliding.info:eu-repo/semantics/publishedVersio

THE EFFECT OF WEARING A CAP ON THE SWIMMER PASSIVE DRAG

The purpose of this study was to analyse the effect of wearing a cap on swimmer passive drag. A computational fluid dynamics analysis was carried-out to determine the hydrodynamic drag of a female swimmer’s model: (i) wearing a swimming cap and; (ii) with no cap. The three-dimensional surface geometry of a female swimmer’s model with cap and with no cap was acquired through standard commercial laser scanner. Passive drag force and drag coefficient were computed with the swimmer in a streamlined position. Higher hydrodynamic drag values were determined when the swimmer was with no cap in comparison with the situation when the swimmer was wearing a cap. In conclusion, one can state that wearing a swim cap may positively influence swimmer’s hydrodynamics

The use of neural network technology to model swimming performance

to identify the factors which are able to explain the performance in the 200 meters individual medley and 400 meters front crawl events in young swimmers, to model the performance in those events using non-linear mathematic methods through artificial neural networks (multi-layer perceptrons) and to assess the neural network models precision to predict the performance. A sample of 138 young swimmers (65 males and 73 females) of national level was submitted to a test battery comprising four different domains: kinanthropometric evaluation, dry land functional evaluation (strength and flexibility), swimming functional evaluation (hydrodynamics, hydrostatic and bioenergetics characteristics) and swimming technique evaluation. To establish a profile of the young swimmer non-linear combinations between preponderant variables for each gender and swim performance in the 200 meters medley and 400 meters font crawl events were developed. For this purpose a feed forward neural network was used (Multilayer Perceptron) with three neurons in a single hidden layer. The prognosis precision of the model (error lower than 0.8% between true and estimated performances) is supported by recent evidence. Therefore, we consider that the neural network tool can be a good approach in the resolution of complex problems such as performance modeling and the talent identification in swimming and, possibly, in a wide variety of sports. Key pointsThe non-linear analysis resulting from the use of feed forward neural network allowed us the development of four performance models.The mean difference between the true and estimated results performed by each one of the four neural network models constructed was low.The neural network tool can be a good approach in the resolution of the performance modeling as an alternative to the standard statistical models that presume well-defined distributions and independence among all inputs.The use of neural networks for sports sciences application allowed us to create very realistic models for swimming performance prediction based on previous selected criterions that were related with the dependent variable (performance).info:eu-repo/semantics/publishedVersio

Hydrodynamic analysis of different finger positions in swimming: a computational fluid dynamics approach

The aim of this research was to numerically clarify the effect of finger spreading and thumb abduction on the hydrodynamic force generated by the hand and forearm during swimming. A computational fluid dynamics (CFD) analysis of a realistic hand and forearm model obtained using a computer tomography scanner was conducted. A mean flow speed of 2 m · s(-1) was used to analyze the possible combinations of three finger positions (grouped, partially spread, totally spread), three thumb positions (adducted, partially abducted, totally abducted), three angles of attack (a = 0°, 45°, 90°), and four sweepback angles (y = 0°, 90°, 180°, 270°) to yield a total of 108 simulated situations. The values of the drag coefficient were observed to increase with the angle of attack for all sweepback angles and finger and thumb positions. For y = 0° and 180°, the model with the thumb adducted and with the little finger spread presented higher drag coefficient values for a = 45° and 90°. Lift coefficient values were observed to be very low at a = 0° and 90° for all of the sweepback angles and finger and thumb positions studied, although very similar values are obtained at a = 45°. For y = 0° and 180°, the effect of finger and thumb positions appears to be much most distinct, indicating that having the thumb slightly abducted and the fingers grouped is a preferable position at y = 180°, whereas at y = 0°, having the thumb adducted and fingers slightly spread yielded higher lift values. Results show that finger and thumb positioning in swimming is a determinant of the propulsive force produced during swimming; indeed, this force is dependent on the direction of the flow over the hand and forearm, which changes across the arm's stroke.info:eu-repo/semantics/publishedVersio

The Effect of Depth on Drag During the Streamlined Glide: A Three-Dimensional CFD Analysis

The aim of this study was to analyze the effects of depth on drag during the streamlined glide in swimming using Computational Fluid Dynamics. The Computation Fluid Dynamic analysis consisted of using a three-dimensional mesh of cells that simulates the flow around the considered domain. We used the K-epsilon turbulent model implemented in the commercial code Fluent(®) and applied it to the flow around a three-dimensional model of an Olympic swimmer. The swimmer was modeled as if he were gliding underwater in a streamlined prone position, with hands overlapping, head between the extended arms, feet together and plantar flexed. Steady-state computational fluid dynamics analyses were performed using the Fluent(®) code and the drag coefficient and the drag force was calculated for velocities ranging from 1.5 to 2.5 m/s, in increments of 0.50m/s, which represents the velocity range used by club to elite level swimmers during the push-off and glide following a turn. The swimmer model middle line was placed at different water depths between 0 and 1.0 m underwater, in 0.25m increments. Hydrodynamic drag decreased with depth, although after 0.75m values remained almost constant. Water depth seems to have a positive effect on reducing hydrodynamic drag during the gliding. Although increasing depth position could contribute to decrease hydrodynamic drag, this reduction seems to be lower with depth, especially after 0.75 m depth, thus suggesting that possibly performing the underwater gliding more than 0.75 m depth could not be to the benefit of the swimmer.info:eu-repo/semantics/publishedVersio