Computational fluid dynamics analysis of cyclist aerodynamics: Performance of different turbulence-modelling and boundary-layer modelling approaches

This study aims at assessing the accuracy of computational fluid dynamics (CFD) for applications in sports aerodynamics, for example for drag predictions of swimmers, cyclists or skiers, by evaluating the applied numerical modelling techniques by means of detailed validation experiments. In this study, a wind-tunnel experiment on a scale model of a cyclist (scale 1:2) is presented. Apart from three-component forces and moments, also high-resolution surface pressure measurements on the scale model’s surface, i.e. at 115 locations, are performed to provide detailed information on the flow field. These data are used to compare the performance of different turbulence-modelling techniques, such as steady Reynolds-averaged Navier–Stokes (RANS), with several k–ε and k–ω turbulence models, and unsteady large-eddy simulation (LES), and also boundary-layer modelling techniques, namely wall functions and low-Reynolds number modelling (LRNM). The commercial CFD code Fluent 6.3 is used for the simulations. The RANS shear-stress transport (SST) k–ω model shows the best overall performance, followed by the more computationally expensive LES. Furthermore, LRNM is clearly preferred over wall functions to model the boundary layer. This study showed that there are more accurate alternatives for evaluating flow around bluff bodies with CFD than the standard k–ε model combined with wall functions, which is often used in CFD studies in sports.     

Aerodynamic study of time-trial helmets in cycling racing using CFD analysis

The aerodynamic drag of three different time-trial cycling helmets was analyzed numerically for two different cyclist head positions. Computational Fluid Dynamics (CFD) methods were used to investigate the detailed airflow patterns around the cyclist for a constant velocity of 15 m/s without wind. The CFD simulations have focused on the aerodynamic drag effects in terms of wall shear stress maps and pressure coefficient distributions on the cyclist/helmet system. For a given head position, the helmet shape, by itself, obtained a weak effect on a cyclist’s aerodynamic performance (<1.5%). However, by varying head position, a cyclist significantly influences aerodynamic performance; the maximum difference between both positions being about 6.4%. CFD results have also shown that both helmet shape and head position significantly influence drag forces, pressure and wall shear stress distributions on the whole cyclist’s body due to the change in the near-wake behavior and in location of corresponding separation and attachment areas around the cyclist.     

The impact of arm-crank position on the drag of a paralympic hand-cyclist

The aerodynamic features associated with the rotation of a cyclist’s legs have long been a research topic for sport scientists and engineers, with studies in recent years shedding new light on the flow structures and drag trends. While the arm-crank rotation cycle of a hand-cyclist bears some resemblance to the leg rotation of a traditional cyclist, the aerodynamics around the athlete are fundamentally different due to the proximity and position of the athlete’s torso with respect to their arms, especially since both arm-cranks move in phase with each other. This research investigates the impact of arm-crank position on the drag acting on a hand-cyclist and is applied to a hill descent position where the athlete is not pedalling. Four primary arm-crank positions, namely 3, 6, 9, and 12 o’clock of a Paralympic hand-cyclist were investigated with CFD for five yaw angles, namely 0°, 5°, 10°, 15°, and 20°. The results demonstrated that the 3 and 12 o’clock positions (when observed from the left side of the hand-cyclist) yielded the highest drag area at 0° yaw, while the 9 o’clock position yielded the lowest drag area for all yaw angles. This is in contrast to the 6 o’clock position traditionally held by hand-cyclists during a descent to reduce aerodynamic drag.     

Computational fluid dynamics analysis of drag and convective heat transfer of individual body segments for different cyclist positions

This study aims at investigating drag and convective heat transfer for cyclists at a high spatial resolution. Such an increased spatial resolution, when combined with flow-field data, can increase insight in drag reduction mechanisms and in the thermo-physiological response of cyclists related to heat stress and hygrothermal performance of clothing. Computational fluid dynamics (steady Reynolds-averaged Navier-Stokes) is used to evaluate the drag and convective heat transfer of 19 body segments of a cyclist for three different cyclist positions. The influence of wind speed on the drag is analysed, indicating a pronounced Reynolds number dependency on the drag, where more streamlined positions show a dependency up to higher Reynolds numbers. The drag and convective heat transfer coefficient (CHTC) of the body segments and the entire cyclist are compared for all positions at racing speeds, showing high drag values for the head, legs and arms and high CHTCs for the legs, arms, hands and feet. The drag areas of individual body segments differ markedly for different cyclist positions whereas the convective heat losses of the body segments are found to be less sensitive to the position. CHTC-wind speed correlations are derived, in which the power-law exponent does not differ significantly for the individual body segments for all positions, where an average value of 0.84 is found. Similar CFD studies can be performed to assess drag and CHTCs at a higher spatial resolution for applications in other sport disciplines, bicycle equipment design or to assess convective moisture transfer.     

Comparison of LES of steady transitional flow in an idealized stenosed axisymmetric artery model with a RANS transitional model

In this study, two different turbulence methodologies are investigated to predict transitional flow in a 75% stenosed axisymmetric experimental arterial model and in a slightly modified version of the model with an eccentric stenosis. Large eddy simulation (LES) and Reynolds-averaged Navier-Stokes (RANS) methods were applied; in the LES simulations eddy viscosity subgrid-scale models were employed (basic and dynamic Smagorinsky) while the RANS method involved the correlation-based transitional version of the hybrid k-ε/k-ω flow model. The RANS simulations used 410,000 and 820,000 element meshes for the axisymmetric and eccentric stenoses, respectively, with y(+) less than 2 viscous wall units for the boundary elements, while the LES used 1,200,000 elements with y(+) less than 1. Implicit filtering was used for LES, giving an overlap between the resolved and modeled eddies, ensuring accurate treatment of near wall turbulence structures. Flow analysis was carried out in terms of vorticity and eddy viscosity magnitudes, velocity, and turbulence intensity profiles and the results were compared both with established experimental data and with available direct numerical simulations (DNSs) from the literature. The simulation results demonstrated that the dynamic Smagorinsky LES and RANS transitional model predicted fairly comparable velocity and turbulence intensity profiles with the experimental data, although the dynamic Smagorinsky model gave the best overall agreement. The present study demonstrated the power of LES methods, although they were computationally more costly, and added further evidence of the promise of the RANS transition model used here, previously tested in pulsatile flow on a similar model. Both dynamic Smagorinsky LES and the RANS model captured the complex transition phenomena under physiological Reynolds numbers in steady flow, including separation and reattachment. In this respect, LES with dynamic Smagorinsky appeared more successful than DNS in replicating the axisymmetric experimental results, although inflow conditions, which are subject to caveats, may have differed. For the eccentric stenosis, LES with Smagorinsky coefficient of 0.13 gave the closest agreement with DNS despite the known shortcomings of fixed coefficients. The relaminarization as the flow escaped the influence of the stenosis was amply demonstrated in the simulations, graphically so in the case of LES.     

Computational modeling and validation of human nasal airflow under various breathing conditions

The human nose serves vital physiological functions, including warming, filtration, humidification, and olfaction. These functions are based on transport phenomena that depend on nasal airflow patterns and turbulence. Accurate prediction of these airflow properties requires careful selection of computational fluid dynamics models and rigorous validation. The validation studies in the past have been limited by poor representations of the complex nasal geometry, lack of detailed airflow comparisons, and restricted ranges of flow rate. The objective of this study is to validate various numerical methods based on an anatomically accurate nasal model against published experimentally measured data under breathing flow rates from 180 to 1100 ml/s. The numerical results of velocity profiles and turbulence intensities were obtained using the laminar model, four widely used Reynolds-averaged Navier-Stokes (RANS) turbulence models (i.e., k-ε, standard k-ω, Shear Stress Transport k-ω, and Reynolds Stress Model), large eddy simulation (LES) model, and direct numerical simulation (DNS). It was found that, despite certain irregularity in the flow field, the laminar model achieved good agreement with experimental results under restful breathing condition (180 ml/s) and performed better than the RANS models. As the breathing flow rate increased, the RANS models achieved more accurate predictions but still performed worse than LES and DNS. As expected, LES and DNS can provide accurate predictions of the nasal airflow under all flow conditions but have an approximately 100-fold higher computational cost. Among all the RANS models tested, the standard k-ω model agrees most closely with the experimental values in terms of velocity profile and turbulence intensity.     

Aerodynamic investigation of the thermo-dependent flow structure in the wake of a cyclist

The main purpose of this study was to assess the influence of the environmental temperature on both the aerodynamic flow evolving around the bicycle and cycling power output. The CFD method was used to investigate the detailed flow field around the cyclist/bicycle system for a constant speed of 11.1 m/s (40 km/h) without wind. In complement, a mathematical model was used to determine the temperature-dependent power output in the range [−10; 40 °C]. The numerical investigation gives valuable information about the turbulent flow field in the cyclist's wake which evolves accordingly the surrounding temperature. A major result of this study is that the areas of overpressure upstream of the cyclist and of underpressure downstream of him are less extensive for a temperature of 40 °C compared to −10 °C. The results suggest that the aerodynamic braking effect of the bicycle is minimized when the air temperature is high, as a lower air density results in a reduction in drag on the cyclist. This study showed that the power required to maintain a constant speed is reduced when the temperature is high, the reason being a lower aerodynamic resistance.     

Large Eddy Simulation and Reynolds-Averaged Navier-Stokes modeling of flow in a realistic pharyngeal airway model: an investigation of obstructive sleep apnea

Computational fluid dynamics techniques employing primarily steady Reynolds-Averaged Navier-Stokes (RANS) methodology have been recently used to characterize the transitional/turbulent flow field in human airways. The use of RANS implies that flow phenomena are averaged over time, the flow dynamics not being captured. Further, RANS uses two-equation turbulence models that are not adequate for predicting anisotropic flows, flows with high streamline curvature, or flows where separation occurs. A more accurate approach for such flow situations that occur in the human airway is Large Eddy Simulation (LES). The paper considers flow modeling in a pharyngeal airway model reconstructed from cross-sectional magnetic resonance scans of a patient with obstructive sleep apnea. The airway model is characterized by a maximum narrowing at the site of retropalatal pharynx. Two flow-modeling strategies are employed: steady RANS and the LES approach. In the RANS modeling framework both k-epsilon and k-omega turbulence models are used. The paper discusses the differences between the airflow characteristics obtained from the RANS and LES calculations. The largest discrepancies were found in the axial velocity distributions downstream of the minimum cross-sectional area. This region is characterized by flow separation and large radial velocity gradients across the developed shear layers. The largest difference in static pressure distributions on the airway walls was found between the LES and the k-epsilon data at the site of maximum narrowing in the retropalatal pharynx.     

Validation of computational fluid dynamics methodology used for human upper airway flow simulations

An anatomically accurate human upper airway model was constructed from multiple magnetic resonance imaging axial scans. This model was used to conduct detailed Computational Fluid Dynamics (CFD) simulations during expiration, to investigate the fluid flow in the airway regions where obstruction could occur. An identical physical model of the same airway was built using stereo lithography. Pressure and velocity measurements were conducted in the physical model. Both simulations and experiments were performed at a peak expiratory flow rate of 200 L/min. Several different numerical approaches within the FLUENT commercial software framework were used in the simulations; unsteady Large Eddy Simulation (LES), steady Reynolds-Averaged Navier-Stokes (RANS) with two-equation turbulence models (i.e. k?ε, standard k?ω, and k?ω Shear Stress Transport (SST)) and with one-equation Spalart–Allmaras model. The CFD predictions of the average wall static pressures at different locations along the airway wall were favorably compared with the experimental data. Among all the approaches, standard k?ω turbulence model resulted in the best agreement with the static pressure measurements, with an average error of ～20% over all ports. The highest positive pressures were observed in the retroglossal regions below the epiglottis, while the lowest negative pressures were recorded in the retropalatal region. The latter is a result of the airflow acceleration in the narrow retropalatal region. The largest pressure drop was observed at the tip of the soft palate. This location has the smallest cross section of the airway. The good agreement between the computations and the experimental results suggest that CFD simulations can be used to accurately compute aerodynamic flow characteristics of the upper airway.     

Numerical investigation of inspiratory airflow in a realistic model of the human tracheobronchial airways and a comparison with experimental results

In this article, the results of numerical simulations using computational fluid dynamics (CFD) and a comparison with experiments performed with phase Doppler anemometry are presented. The simulations and experiments were conducted in a realistic model of the human airways, which comprised the throat, trachea and tracheobronchial tree up to the fourth generation. A full inspiration/expiration breathing cycle was used with tidal volumes 0.5 and 1 L, which correspond to a sedentary regime and deep breath, respectively. The length of the entire breathing cycle was 4 s, with inspiration and expiration each lasting 2 s. As a boundary condition for the CFD simulations, experimentally obtained flow rate distribution in 10 terminal airways was used with zero pressure resistance at the throat inlet. CCM+ CFD code (Adapco) was used with an SST k-\(\upomega \) low-Reynolds Number RANS model. The total number of polyhedral control volumes was 2.6 million with a time step of 0.001 s. Comparisons were made at several points in eight cross sections selected according to experiments in the trachea and the left and right bronchi. The results agree well with experiments involving the oscillation (temporal relocation) of flow structures in the majority of the cross sections and individual local positions. Velocity field simulation in several cross sections shows a very unstable flow field, which originates in the tracheal laryngeal jet and propagates far downstream with the formation of separation zones in both left and right airways. The RANS simulation agrees with the experiments in almost all the cross sections and shows unstable local flow structures and a quantitatively acceptable solution for the time-averaged flow field.     

Drag of suction cup tags on swimming animals: Modeling and measurement

Bio‐logging tags are widely used to study the behavior and movements of marine mammals with the tacit assumption of little impact to the animal. However, tags on fast‐swimming animals generate substantial hydrodynamic forces potentially affecting behavior and energetics adversely, or promoting early removal of the tag. In this work, hydrodynamic loading of three novel tag housing designs are compared over a range of swimming speeds using computational fluid dynamics (CFD). Results from CFD simulation were verified using tag models in a water flume with close agreement. Drag forces were reduced by minimizing geometric disruptions to the flow around the housing, while lift forces were reduced by minimizing the frontal cross‐sectional area of the housing and holding the tag close to the attachment surface. Hydrodynamic tag design resulted in an experimentally measured 60% drag force reduction in 5.6 m/s flow. For all housing designs, off‐axis flow increased the magnitude of the force on the tag. Experimental work with a common dolphin (Delphinus delphis) cadaver indicates that the suction cups used to attach the types of tags described here provide sufficient attachment force to resist failure to predicted forces at swimming speeds of up to 10 m/s.     

Quantitative comparison of CFD predicted and MRI measured velocity fields in a carotid bifurcation phantom

Steady flow of a blood mimicking fluid in a physiologically realistic model of the human carotid bifurcation was studied using both magnetic resonance imaging (MRI) and computational fluid dynamics (CFD) modelling techniques. Quantitative comparisons of the 3D velocity field in the bifurcation phantom were made between phase contrast MRI measurements and CFD predictions. The geometry for the CFD model was reconstructed from T(1) weighted MR imaging of the test phantom. It was found that the predicted velocity fields were in fair agreement with MR measured velocities. In both the internal and external carotid arteries, the agreement between CFD predictions and MRI measurements was better along the inner-outer wall axis with a correlation factor C>0.897 (average 0.939) where the velocity profiles were skewed, than along the anterior-posterior axis (average correlation factor 0.876) where the velocity profiles were in M-shape.     

Numerical investigation of airflow in an idealized human extra-thoracic airway: a comparison study

Large eddy simulation (LES) technique is employed to numerically investigate the airflow through an idealized human extra-thoracic airway under different breathing conditions, 10, 30, and 120 l/min. The computational results are compared with single and cross hot-wire measurements, and with time-averaged flow field computed by standard $k\text{- }\omega $ and $k\text{- }\omega $ -SST Reynolds-averaged Navier–Stokes (RANS) models and the Lattice Boltzmann method (LBM). The LES results are also compared to root-mean-square (RMS) flow field computed by the Reynolds stress model (RSM) and LBM. LES generally gives better prediction of the time-averaged flow field than RANS models and LBM. LES also provides better estimation of the RMS flow field than both the RSM and the LBM.     

An open 3D CFD model for the investigation of flow environments experienced by freshwater fish

Computational fluid dynamics (CFD) provides a powerful numerical tool to simulate and study many of the complex fluid-body interactions experienced by freshwater fish. However, major gaps remain in the application of CFD to study the fluid-body interactions of fish, including the absence of an openly available reference body geometry, the lack of a detailed study on suitable numerical methods and a deficit of available velocity laboratory measurements for model calibration and validation. To address these gaps, we provide a set of numerical models based on the open-source CFD toolkit OpenFOAM. The contributions of this work are two-fold: First, to provide a validated openly available numerical setup using a realistic fish model geometry including laboratory velocity measurements. Second, to determine the best-performing turbulence models and near-wall treatments using Reynolds-Averaged Navier-Stokes (RANS) numerical simulations. Finally, we conclude with a critical evaluation of the effects and trade-offs of resolving or modelling the boundary layer (BL) in numerical studies of fish-shaped bodies.     

Simulated and experimental estimates of hydrodynamic drag from bio-logging tags

Drag force acting on swimming marine mammals is difficult to measure directly. Researchers often use simple modeling and kinematic measurements from animals, or computational fluid dynamics (CFD) simulations to estimate drag. However, studies that compare these methods are lacking. Here, computational simulation and physical experiments were used to estimate drag forces on gliding bottlenose dolphins (Tursiops truncatus). To facilitate comparison, variable drag loading (no-tag, tag, tag + 4, tag + 8) was used to increase force in both simulations and experiments. During the experiments, two dolphins were trained to perform controlled glides with variable loading. CFD simulations of dolphin/tag geometry in steady flow (1–6 m/s) were used to model drag forces. We expect both techniques will capture relative changes created by experimental conditions, but absolute forces predicted by the methods will differ. CFD estimates were within a calculated 90% confidence interval of the experimental results for all but the tag condition. Relative drag increase predicted by the simulation vs. experiment, respectively, differed by between 21% and 31%: tag, 4% vs. 33%; tag + 4, 47% vs. 68%; and tag + 8, 108% vs. 77%. The results from this work provide a direct comparison of computational and experimental estimates of drag, and provide a framework to quantify uncertainty.     

The optimum finger spacing in human swimming

Competitive swimmers spread fingers during the propulsive stroke. Due to the inherent inefficiency of human swimming, the question is: does this strategy enhance performance or is it just a more comfortable hand posture? Here we show, through computational fluid dynamics (CFD) of a 3D model of the hand, that an optimal finger spacing (12°, roughly corresponding to the resting hand posture) increases the drag coefficient (+8.8%), which is ‘functionally equivalent’ to a greater hand palm area, thus a lower stroke frequency can produce the same thrust, with benefits to muscle, hydraulic and propulsive efficiencies. CFD, through flow visualization, provides an explanation for the increased drag associated with the optimum finger spacing.     

Turbulence model choice for the calculation of drag forces when using the CFD method

The aim of this work is to specify which model of turbulence is the most adapted in order to predict the drag forces that a swimmer encounters during his movement in the fluid environment. For this, a Computational Fluid Dynamics (CFD) analysis has been undertaken with a commercial CFD code (Fluent^®). The problem was modelled as 3D and in steady hydrodynamic state. The 3D geometry of the swimmer was created by means of a complete laser scanning of the swimmer’s body contour. Two turbulence models were tested, namely the standard k–ε model with a specific treatment of the fluid flow area near the swimmer’s body contour, and the standard k–ω model. The comparison of numerical results with experimental measurements of drag forces shows that the standard k–ω model accurately predicts the drag forces while the standard k–ε model underestimates their values. The standard k–ω model also enabled to capture the vortex structures developing at the swimmer’s back and buttocks in underwater swimming; the same vortices had been visualized by flow visualization experiments carried out at the INSEP (National Institute for Sport and Physical Education in Paris) with the French national swimming team.     

PIV-measured versus CFD-predicted flow dynamics in anatomically realistic cerebral aneurysm models

Computational fluid dynamics (CFD) modeling of nominally patient-specific cerebral aneurysms is increasingly being used as a research tool to further understand the development, prognosis, and treatment of brain aneurysms. We have previously developed virtual angiography to indirectly validate CFD-predicted gross flow dynamics against the routinely acquired digital subtraction angiograms. Toward a more direct validation, here we compare detailed, CFD-predicted velocity fields against those measured using particle imaging velocimetry (PIV). Two anatomically realistic flow-through phantoms, one a giant internal carotid artery (ICA) aneurysm and the other a basilar artery (BA) tip aneurysm, were constructed of a clear silicone elastomer. The phantoms were placed within a computer-controlled flow loop, programed with representative flow rate waveforms. PIV images were collected on several anterior-posterior (AP) and lateral (LAT) planes. CFD simulations were then carried out using a well-validated, in-house solver, based on micro-CT reconstructions of the geometries of the flow-through phantoms and inlet/outlet boundary conditions derived from flow rates measured during the PIV experiments. PIV and CFD results from the central AP plane of the ICA aneurysm showed a large stable vortex throughout the cardiac cycle. Complex vortex dynamics, captured by PIV and CFD, persisted throughout the cardiac cycle on the central LAT plane. Velocity vector fields showed good overall agreement. For the BA, aneurysm agreement was more compelling, with both PIV and CFD similarly resolving the dynamics of counter-rotating vortices on both AP and LAT planes. Despite the imposition of periodic flow boundary conditions for the CFD simulations, cycle-to-cycle fluctuations were evident in the BA aneurysm simulations, which agreed well, in terms of both amplitudes and spatial distributions, with cycle-to-cycle fluctuations measured by PIV in the same geometry. The overall good agreement between PIV and CFD suggests that CFD can reliably predict the details of the intra-aneurysmal flow dynamics observed in anatomically realistic in vitro models. Nevertheless, given the various modeling assumptions, this does not prove that they are mimicking the actual in vivo hemodynamics, and so validations against in vivo data are encouraged whenever possible.     

Swimming performance is reduced by reflective markers intended for the analysis of swimming kinematics

The present study aimed to clarify whether swimming performance is affected by reflective markers being attached to the swimmer’s body, as is required for a kinematic analysis of swimming. Fourteen well-trained male swimmers (21.1 ± 1.7 yrs) performed maximal 50 m front crawl swimming with (W) and without (WO) 25 reflective markers attached to their skin and swimwear. This number represents the minimum required to estimate the body’s center of mass. Fifty meter swimming time, mid-pool swimming velocity, stroke rate, and stroke length were determined using video analysis. We found swimming time to be 3.9 ± 1.6% longer for W condition. Swimming velocity (3.3 ± 1.8%), stroke rate (1.2 ± 2.0%), and stroke length (2.1 ± 2.7%) were also significantly lower for W condition. To elucidate whether the observed reduction in performance was potentially owing to an additional drag force induced by the reflective markers, measured swimming velocity under W condition was compared to a predicted velocity that was calculated based on swimming velocity obtained under WO condition and an estimate of the additional drag force induced by the reflective markers. The mean prediction error and ICC (2,1) for this analysis of measured and predicted velocities was 0.014 m s⁻¹ and 0.894, respectively. Reducing the drag force term led to a decrease in the degree of agreement between the velocities. Together, these results suggest that the reduction in swimming performance resulted, at least in part, from an additional drag force produced by the reflective markers.