Downhill skateboard aerodynamics

Abstract

Computational Fluid Dynamics has been used to perform a detailed aerodynamic analysis of a downhill skateboarder. The modelled geometry is that of a British downhill skateboarder, acquired using non contact laser scanning. Three helmets used by the skater were also compared, which revealed how each helmet directed the flow of air around and onto the body of the skateboarder. A study was also conducted into the influence of drafting, a tactical manoeuvre used in the race by skateboarders. This revealed how drafting skaters should position themselves behind a lead skater to minimize the drag force acting upon them.

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Procedia Engineering 00 (20 09) 000–000
Procedia
Engineering
www.elsevier.com/loc ate/procedia
8
th
Conference of the International Sports Engineering Association (ISEA)
Downhill skateboard aerodynamics
J.H. Hart
a
*, T. Allen
a
, M. Holroyd
b
a
Sports Engineering, CSES, Sheffield Hallam University, Sheffield, S1 1WB, UK
b
Sheffield Hallam University, Sheffield, S1 1WB, UK
Received 31 January 2010 ; revised 7 March 2010; accept ed 21 March 2010
Abstract
Computational Fluid Dynamics has been used to perform a detailed aerodynamic analysis of a downhill skateboarder. The
modelled geometry is that of a British downhill skateboarder, acquired using non contact laser scanning. Three helmets used by
the skater were also compared, which revealed how each helmet directed the flow of air aro und and onto the body of the
skateboarder. A study was also conducted into the influence of drafting, a tactical manoeuvre used in the race by skateboarders.
This revealed how drafting skaters sh ould position themselves behind a lead skater to minimize the drag force acting upon them.
© 2009 Published by Elsevier Ltd.
Keywords: skateboard, aerodynamics, CFD, helmets;
1. Introduction
Downhill skateboarding is an extreme gravity sport of increasing popularity, yet it is still very much a minority
sport and unsurprisingly has not been subject of significant research to date. Indeed, engineering aspects of
skateboarding in general are a very under researched area, despite the high popularity of the sport amongst
teenagers. Studies on skateboard dynamics have been reported by Hubbard [1,2], and a study into the composite
structure of a slalom board was presented by Endruweit [3]. However research in the sport is largely driven by
enthusiasts, Shah [4], and it was due to an enthusiast that this research originated. Sports Engineering were
approached by a British downhill skateboarder studying at the university, who was looking for support in improving
his aerodynamics.
Aerodynamics play a significant role in this gravity sport, as speeds in excess of 75 mph are reached in
competition. Skaters try to adopted aerodynamic tuck positions to minimize aerodynamic drag as much as possible.
The tucks are similar in fashion to those adopted by speed skiers, and the skaters are starting to use a range of aero
helmets very much modeled on those as worn by speed skiers. These helmets are typically of fibre glass
construction, with an existing certified helmet fitted internally. Skaters who do not use these typically pick a sky
diving, or ski helmet, that they feel has an appropriate aerodynamic shape.
* Corresponding author. Tel.: +44-114-225-4405; fax: +44-114-225-4356.
E-mail address: john.hart@shu.ac.uk
c
2010 Published by Elsevier Ltd.
Procedia Engineering 2 (2010) 2523–2528
www.elsevier.com/locate/procedia
1877-7058 c
2010 Published by Elsevier Ltd.
doi:10.1016/j.proeng.2010.04.026

2J.H.Hart et al. / Procedia Engineering 00 (2010) 000–000
Sports Engineering have conducted an initial investigation using computational fluid dynamics (CFD) into the
aerodynamics of a British downhill skateboarder. The general aerodynamics of the racing tuck position has been
investigated. Three race helmets currently worn by the British skaters, have also been studied to ascertain their
aerodynamic performance. Further to this the tactical maneuver of drafting has also been investigated, to feed into
future helmet design studies.
2. Modeling & Simulation
2.1. Geometry
The basic geometry of a single skater comprised; skater in typical tuck position, racing longboard, race helmet.
All the modeled geometry was acquired using non-contact laser scanning. A Metris ModelMaker D100 laser scanner
fitted to a CimCore Infinite Series precision measurement arm was used to accomplish this. The scanning of the
skater took in the region of 40 minutes to complete, excluding multiple rest periods for the skater. Holding a
stationary racing tuck position is extremely tiring for the skater. The quality of the scanned data decreases the longer
this pose is held as the rider begins to exhibit involuntary muscle twitching and general movement due to tiredness,
thus necessitating multiple breaks. Methodologies have been developed in-house to ensure as accurate a geometry as
possible is captured when scanning human forms. Captured data was cleaned and surfaced using Geomagic Studio 8
to create a high quality NURBS model. Full details of scanning and surfacing procedure will not be recounted here
but can be found in Hart [5].
Fig. 1. (a) Non-contact laser scanning skater; (b) Fully surfaced scanned model of skater
2.1.1. Helmet Geometry
Three helmet shells have been scanned for this investigation comprising two aero shells, fitted with cores from
other helmets, and designed specifically for downhill skateboarding. These will be referred to as Aero 1 and Aero 2.
An Icaro skydiving helmet has also been included in the study. Aero 1 is the race helmet currently favored by the
skater. The scanned helmet geometries are shown in Fig. 2.(A).
Fig. 2. (a) Modeled helmet geometry; (b) Dual skater drafting geometry
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J.H.Hart et al. / Procedia Engineering 00 (2010) 000–000 3
2.1.2. Rider Drafting Geometry
When conducting rider drafting studies the geometry of the second skater was simply created by duplicating and
offsetting the original skater geometry. A baseline representative position for the second skater was decided upon
having consulted with the British skaters. The baseline position for the second skater was 1.4H inline downstream of
the first skater, where H is the maximum height of the skater in the tuck position. As shown in Fig. 2.(b).
2.2. Mesh
The geometry was placed in a flow domain, generated during the meshing process, with a cross section of 10H x
5H. An inlet velocity boundary was placed 5H upstream of the modeled geometry and a pressure outflow boundary
condition 8.5H downstream.
The surface of the modeled geometry was meshed, using the pre-processor Gambit 2.3.16, with approximately
355000 triangular elements, refined in regions of high surface curvature. Volume mesh was then created using
TGrid 5.0.6. Five layers of prismatic mesh were extruded from the geometry surface to ensure that surface boundary
layers were adequately captured during simulation. The surrounding flow domain was then predominantly filled
with structured hexahedral elements concentrated and refined in the wake region. Infill of tetrahedral mesh was used
to bridge the hexahedral and prismatic mesh elements, but its use was minimized. The final volume mesh comprised
5.5 million computational cells for a single rider simulation, as shown in Fig.4.(b), and in the region of 11.4 million
cells for a dual rider drafting simulation.
Fig. 4. (a) Modeled flow domain; (b) Computational mesh detail
2.3. Numerical Model & Setup
All simulations were conducted using the commercially available code ANSYS Fluent 6.3.26. The simulations
were performed as steady RANS using a second order spatial discretisation, and a segregated solver formulation
which solves the governing equations sequentially. Turbulence closure was provided through use of the k-ω SST
turbulence model. Initial turbulence intensity at flow boundaries was set as 3 %. An inlet flow velocity of 22.352
m/s (50 mph) was applied, and the ground was fixed with an equivalent translational speed.
2.4. Simulations
Simulations were conducted upon 8 nodes of a SGI Altix cluster. Each node is equipped with two Quad-Core
2.33 GHz Xeon 5300 series processors. Only two cores of each processor were utilised, as the author has found this
to be an optimum configuration for solution upon this cluster system. This resulted in the simulations being
distributed over 32 cores in total. Simulations were run until a statistical steady state had been achieved. This state
was determined by monitoring the drag force values for the modeled geometry. The computational cost of the
simulations to reach this state was approximately 8~10 hours.
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4J.H.Hart et al. / Procedia Engineering 00 (2010) 000–000
3. Results & Discussion
3.1. Single Rider General Flow Analysis
The statistical steady state drag coefficient for a single skater in the tuck position, wearing Aero 1 the current
favored race helmet, was found to be C
d
= 0.6 (C
d
A = 0.177 m
2
, where A is the frontal area). Splitting the overall
measured drag force down into specific components reveals that the helmet accounts for 25.4 % of the total drag, the
skaters body 62.3 % and the longboard 12.3 %. The drag measured for the skater is considerably higher than the
value for a speed skier, C
d
≈ 0.16, as reported by Thompson [6]. This is notable considering that the helmet shell is
very much based on that of a speed skiing type shape, and that the skaters try to tuck in a similar fashion to a speed
skier. The predominant reason for this difference, omitting the fact that the skater uses a longboard instead of skis, is
the leg position of the skater, inline and crossed as opposed to apart and parallel for a skier. This results in a
significant amount of drag force being generated by the legs, and feet of the skater, 48 % of the total measured drag
force. Another major contributing factor is the suit worn by the skater. Fitted seamless smooth race suits as worn by
skiers, are not permitted in downhill skateboard, and the race leathers that are worn wrinkle causing localized flow
separation points and increasing overall drag.
Fig. 5. (a) Time averaged pressure wake iso surface at 40 % free stream velocity; (b) Flow lines showing swirling flow
Fig. 5.(a) shows an iso surface of time-averaged wake structures that reveals some of the complex flow around
the skater. Significant wake structure is seen to form behind the legs, and feet of the skater as flow breaks and swirls
away from this region, Fig.5.(b). The helmet is also seen to create two large vortex cores that run from the chin
guard and along the underside of the skaters arm. Flow detaches from the helmet in this region, as the chin guard
does not fit into the body of the skater unlike at the shoulders, and starts to circulate between the chest and legs. In
comparison flow over the top of the helmet, shoulders, and back is relatively smooth, however a wake is seen to
form along the spine of the skater forming at the rear top of the helmet.
3.2. Single Rider Helmet Comparison
Three helmets currently used by the British skaters were tested in the standard tuck position. Drag coefficient
area values of the helmets were found to be; Aero 1 C
d
A = 0.177, Aero 2 C
d
A = 0.154, and Icaro C
d
A = 0.173. This
shows that the current helmet favored by the skaters, Aero 1, has the worst aerodynamic performance. The
performance can be explained by viewing contours of pressure coefficient. It can be seen that a high pressure region
not only exists on the lead front surface of Aero 1, but also on the sides shielding the shoulders. This is due to this
region being concave, and providing a surface upon which flow stagnates. Aero 2 is fully convex in form, and only
exhibits a stagnation region on the lead surface. Due to the wide shape of Aero 1 & 2 both helmets shield the skaters
body and deflect oncoming flow as shown in Fig.6.(b). The wider chin region of Aero 2 however shields more of the
skaters legs, which are the major drag source, and thus it performed best. The Icaro helmet does not shield the body
of the skater, as shown in Fig.6.(b), yet it still outperformed Aero 1. Drag force acting upon the skaters body
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J.H.Hart et al. / Procedia Engineering 00 (2010) 000–000 5
wearing the Icaro is 30 % higher, however overall drag force acting upon the Icaro is nearly 80 % less than that on
Aero 1. This is due to the smaller frontal surface area of the Icaro, and the overall rounded shape to the oncoming air
flow in this position. It should also be noted that this study only considered a single head position in the racing tuck.
The analysis needs to be expanded to include a range of head positions in the racing tuck stance to assess the
influence of head movement on helmet performance. This is important as the Icaro has a flat back with a series of
ridges, which will affect this helmets overall performance in other positions.
Fig. 6. (a) Contours of pressure coefficient upon helmets; (b) Flow lines around helmets
3.3. Skater Drafting Analysis
Ten drafting positions have been investigated. The geometry of Skater 2 was moved forwards (-0.25H),
backwards (0.5H, 1H), left (0.25H), and right (0.25H), of the baseline drafting position as detailed in section 2.1.2.
Results are shown in Fig. 7.(b) It is clear from these results that the best location for Skater 2 when drafting is
directly inline with Skater 1. Drag values for Skater 2 fall to an average of C
d
≈ 0.42 in this position, though further
savings can be made if Skater 2 moves in closer to Skater 1, by -0.25H. However this level of proximity between
skaters may not be feasible in racing. Interestingly the measured drag value for Skater 1 decreases, when drafted by
a second skater, by as much as 13% as the proximity of Skater 2 can affect the air flow and separations from the lead
skater.
Fig.7. (a) Positional movement of second skater; (b) C
d
for second skater based on position
Fig.8.(a) clearly shows how Skater 2 sits within the wake that forms behind Skater 1. Skater 2 is nearly fully
submerged within this wake with the exception of the top front of the helmet. As the wake leaves the back of Skater
1 it is forced down beneath Skater 2 leaving this part of the helmet exposed. Moving Skater 2 forwards towards
Skater 1 places more of the second skater into this wake reducing drag. Moving Skater 2 to the left hand side (LHS)
of Skater 1 produces a similar drag value to the central position. This is due to the fact that the majority of the wake,
flows off the LHS of Skater 1, due to the crossed leg position. This can be seen by viewing flow lines released
behind Skater 1 from a head on position as shown in Fig.8.(b). It can be clearly seen that the majority of the swirling
flow from the legs passes to the skaters LHS. Moving Skater 2 to the RHS of Skater 1 produces a higher drag force
Cd ≈ 0.53, however this is still less than the measured drag on Skater 1. The majority of the wake from Skater 1 on
the skaters RHS is at shoulder level, leaving the legs of Skater 2 exposed and higher drag results. Understanding this
could be important tactically to Skater 2 as the skater could position themselves on the LHS or RHS dependant upon
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which leg Skater 1 leads with in the tuck position. Skater 1 leading with the left leg in the tuck is causing the wake
to form and flow to the left, leading with the right leg should reverse this.
Fig.8. (a) Time averaged pressure wake iso surface at 80 % free stream velocity; (b) Flow lines showing swirl behind lead skater
4. Conclusions
Sports Engineering @ CSES, Sheffield Hallam University, have used computational fluid dynamics to perform
an aerodynamic analysis of a downhill skateboarder. The analysis was conducted using the geometry of the current
British #1 downhill skateboarder, and was used to understand the behavior of air flow around the skater in a
standard racing tuck position. Three helmet designs are currently used by the British skaters and the performance of
these were assessed. The results of this analysis revealed that the current race helmet favored by the skater had the
worst performance in the analyzed position. However this work needs to be expanded to account for alternative head
positions. Simulations of a second skater drafting a lead skater were also conducted. These revealed that significant
drag savings can be made by the second skater positioning themselves as close as possible directly behind the lead
skater. The analysis also revealed how the second skater may be able to study the leg position of the lead skater to
best position themselves tactically.
5. References
[1] Hubbard M. Human control of the skateboard. J Biomechanics 1980;13:745-754
[2] Hubbard M. Lateral dynamics and stability of th e skateboard. J Appl Mech 1979;46:931-936
[3] Endruweit A, Ermanni P. Experimental and numerical investigations regarding the deformation adapted design of a composite flex slalom
skateboard. J Sports Eng 2002;5:141-154
[4] Shah SK. From innovation to firm formation: contributions by sports enthusiasts to the windsurfing, snowboarding, and skateboarding
industries. In: Proc of the 6
th
Int Conf on Sports Engineering, Munich – Germany, 2006;3:29-34
[5] Hart JH, Curtis D, Hamilton NDR, Haake SJ. Scanning large geometries for use in computational fluid dynamic analysis. In: Proc of the 5
th
Int Conf on Sports Engineering, UC Davis – California, 2004;1:601-607
[6] Thompson BE, Friess WA, Knapp II KN. Aerodynamics of speed skiers. J Sports Eng 2001;4:103-112
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