MATERIALS AND
SCIENCE IN SPORTS
Edited by:
EH. (Sam) Fmes and S.J. Haake
Dynamics
Laboratory, Computational, and Field
Study of Snowboard Dynamics
Keith W. Buffington, StevenB. Shooter,
Ira J. Thorpe and Jason J. Krywicki
Pgs. 171-183
TIMIS
184 Thorn Hill Road
Warrendale, PA 15086-7514
(724) 776-9000
LABORATORY, COMPUTATIONAL, AND FIELD STUDY
OF SNOWBOARD DYNAMICS
Keith W. Buffinton, Steven B. Shooter, Ira J. Thorpe, and Jason J. Krywicki
Department of Mechanical Engineering
Bucknell University
Lewisburg, Pennsylvania 17837
Abstract
While many studies have documented the dynamical behavior of skis, similar studies for
snowboards have been rare. Characteristics such as board stiffness and damping are
acknowledged to be linked to performance, but a quantitative determination of corresponding
natural frequencies and damping ratios has to date not been published. The present work uses
laboratory, computational, and field studies to develop and document an in-depth understanding
and quantification of snowboard dynamics. In particular, laboratory tests are used to determine
the first three bending and first two torsional natural frequencies and modal damping ratios for
eight snowboards from two manufacturers. Computer models are developed using the software
packages Pro/ENGINEER and Pro/MECHANICA that allow the effects of design changes on
natural frequencies to be investigated and that facilitate visualization of mode shapes. Field
tests are presented that provide insights into the strains and accelerations experienced by
snowboards while subject to turns, stops, and jumps. Results show that quantitative results
correlate well with qualitative descriptions offered by manufacturers and riders. Mediumquality boards designed for beginner riders and characterized as "soft" have lower natural
frequencies and larger damping ratios than similar boards designed for advanced riders and
characterized as "stiff." Moreover, boards designed for advanced riders and characterized as
"high-quality" have natural frequencies higher than "medium-quality" boards while still
exhibiting high damping ratios.
Materials and Science in Sports
Edited by F.H. (Sam) Froes
IMS (The Minerals, Metals & Materials Society), 2001
172
Introduction
Numerous studies have been performed on the dynamical characteristics and performance of
snow skis. One of the earliest is Piziali and Mote in 1972 [1] in which they present laboratory
and field measurements of frequency response, running pressure distribution, and static system
characteristics as a guide to future ski research and design. Over the last 30 years, numerous
other physics-and-engineering-based investigations have been conducted of snow ski
performance, many of which were documented in 1996 by Lind and Sanders [2] with a more
recent investigation by Nordt, Springer, and Kollar in 1999 [3]. Although Lind and Sanders
offer extensive information on various aspects of the physics of skiing, very little information is
offered on the physics of snowboarding.
With the rapid growth in recent years of the snowboard industry, investigations have begun to
focus attention on the physics-and-engineering-based characteristics that are unique to
snowboards. In 1994, Swinson [4] presented a primarily qualitative discussion of both the basic
physics of snowboarding and the similarities between snowboarding and skiing. In a more
recent article, Michaud and Duncumb [5] give a theoretical, although greatly simplified,
description of the physics of snowboard turning. Their analysis is primarily based on a simple
balance offerees and does not offer any quantitative data from either laboratory or field tests.
Three articles that do refer to quantitative measurements and analyses of snowboard
performance are given in [6], [7], and [8]. Dosch [6] describes the construction and
performance of a high-resolution piezoelectric strain sensor, and as an application, its use in a
structural dynamics laboratory "to analyze the dynamic behavior of a new composite snowboard
and find the optimal location for a passive damper." Reference [7] provides additional
information on the analysis referred to in [6] and states:
K2 Corporation, Vashon, WA engaged the structural dynamics lab at Boeing to
conduct strain testing on K2 snowboards and skis. Model 740A02 Strain Sensors
were placed in various locations on the snowboard and skis to find nodes of
maximum strain. Damping devices were then installed in areas of greatest strain
to minimize vibrations, giving the user greater control.
In [8], Sutton refers to work done for Walbridge Design & Manufacturing (now Dimension
Snowboards) similar to that done for K2. Although Sutton's article does not offer any
quantitative results, he does describe both laboratory tests of snowboard vibration characteristics
and field measurements of snowboard strain and acceleration. The present paper is a detailed
elaboration of the snowboard analysis conducted for Dimension and in particular provides
details of the collection of snowboard vibration data and documents the natural frequencies and
damping ratios obtained. The goal of this work is to provide a baseline of information to guide
further studies of snowboard characteristics and to suggest methods of evaluating potentially
fruitful snowboard design modifications.
Presented in the sections below are the results of laboratory tests, computer analyses, and field
tests of a total of eight snowboards from two manufacturers. Procedures and results of static and
dynamic laboratory tests are discussed first. These are followed by a description of the
development of a computer model used to simulate characteristics seen in the laboratory and to
give additional insights into behavior. Next are presented the procedures and results of strain
and acceleration measurements taken during field tests. Finally, concluding comments are
offered and discussed regarding the ways in which the data presented here can be used to guide
further snowboard research and development.
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Laboratory Tests
Static Characteristics
Initial laboratory tests were conducted to obtain overall measures of snowboard static
characteristics and to provide dimensional information for computer models. Beyond standard
measurements such as length, waist width, sidecut, and contact length, measurements of board
thickness (at several locations along the board length), tip radius, tip height, tail radius, tail
height, camber, and weight were obtained. Material specifications given by one of the
manufacturers include an Isosport PBT gloss top sheet, a Durasurf 2001 sublimated sintered
base, continuous linear strand full-length wood cores, thermoset and tri-axial e-glass
composites, full-wrap pre-stressed Rockwell 48C edges, and for several of the boards,
longitudinally lain carbon strips for added stiffness.
To perform static tests, a board was clamped at its widest point across either the tail or the tip.
Weights were then hung from the board and the deflection measured at the center of the widest
point of the opposite end of the board. Although a snowboard is a complex composite structure,
an estimate of the effective stiffness of the board is easily calculated using simple beam theory.
Specifically, for a uniform cantilever beam, the stiffness El is equal to PL3/3y, where P is the
applied load, L is distance from the support to the load application point, and y is the deflection
at the load point. For a typical board, a series of trials produced an effective value of El equal to
85.8 N-m. Since the cross-section of the board varies from approximately 0.5 cm thick and 30
cm wide at the heel to 1 cm thick and 25 cm wide at the waist, an approximate range for
Young's modulus E is 27.5 to 4.1 GPa. This range serves as a starting point for more accurate
iterative procedures described below in the section entitled Computational Modeling.
2
Dynamic Characteristics
Free vibration tests were performed on the eight boards available for testing in order to
characterize snowboard natural frequencies and damping ratios. Natural frequencies and
damping ratios are two of the key parameters characterizing snowboard ride, "feel," and
performance. In particular, damping ratios as well as the proximity of bending and torsional
natural frequencies directly relate to snowboard controllability and handling. Moreover, a
knowledge of the natural frequencies and damping ratios of both high performance boards and
those judged more pedestrian ultimately provide quantitative measures that allow laboratory
characteristics to be directly related to performance on the slopes. Although the loading,
stresses, and strains experienced by snowboards in the field are different than those induced in
the laboratory, a correlation between laboratory measurements and measures of performance in
the field can nonetheless be developed.
The results described below are all based on free vibration tests in which each board is clamped
across the widest part of the tail. In each test, the board was manually deflected and released,
and a recording was made with an HP-35665A dynamic signal analyzer of the signal produced
by an accelerometer mounted on the board. Measurements were made with the accelerometer at
nine different locations on the board (three distributed along the centerline and three distributed
along each edge). At each location, data was automatically taken and averaged by the signal
analyzer over a total of 10 trials for each of two initial shapes: one which would primarily result
in bending vibrations and one which would primarily result in torsional vibrations. For bending
tests, the board was simply deflected vertically at the tip, such that its shape was similar to the
first bending mode, and released. For torsion tests, the board was twisted at the free end into a
shape similar to the first torsional mode and then carefully released. These initial conditions did
not, of course, result in either pure bending or pure torsional responses, but they did allow for a
174
determination of the natural frequency corresponding to a particular mode shape by considering
the relative amplitudes in the frequency response spectra.
Once the averaged data were available, they were saved and analyzed with a custom-written
MATLAB program. This program produces a plot of the accelerometer response versus time,
performs a fast Fourier Transform (FFT) of the accelerometer response, plots the frequency
spectrum, and calculates values for the amplitudes and frequencies of the dominant peaks in the
response and for the modal damping ratio corresponding to each peak (see reference [9] for
complete details on the theory underlying modal analysis).
The measured natural frequencies and modal damping ratios for the first five modes of vibration
of the eight boards investigated are listed below in Tables I and II, respectively. The
correspondences between natural frequencies and mode shapes were done based on a knowledge
of the initial conditions (bending versus twisting), the results of previous tests, and the
experience gleaned through testing as well as through the computational modeling described in
the next section. Note in interpreting the table of damping ratios that the algorithm used to
calculate them is based on the half-power point method and thus is sensitive to the proximity of
peaks in the response spectra. For the results presented here, response spectra peaks were
judged to be sufficiently separated to give meaningful values.
Table I. Modal Natural Frequencies [Hz]
Boaai
lsl Beading
™~3™r~——JJj^~
4
2,33
'"J"~ —— ^J^^
1st Torsion
2nd Bending
3^Bending
17.0
44.3
15.8
40.5
17.9
44.0 ^^^ 293~~ ' '7:54-8
17.5
43.8
17.1
17.6
45.5
43.9 ~^^~ ™fe$~~~ ~^J^l
2*:lolsion
;
19.9
55.75
7
2,375
17.4
43.4
19.6
53.6
8
2.125
17.0
42.9
19.4
54.25
1st Torsion
2B(i Torsion
Table II. Modal Damping Ratios
Board
lstleaiiBg
2nd Bending
3rd Bending
0.013
0.015
~^~~ ——Qjfcg—
4
0.074
^~$^ ^^0^4^
0.011
0.020
^M3T~ ~~~QMl
0.013
0.010
0.014
0.012
0.015
0.012
0.023
aoog — ~^ Oil4
~~~®mi
7
0.047
0.013
0.014
0.015
0.015
8
0.068
0.011
0.008
0.015
0.011
175
As mentioned above, a total of eight snowboards were studied. Subjective characteristics of the
boards numbered 1, 2, and 5, as offered by the staff of one of the manufacturers, are listed below
in Table III. These three boards were those also used in the field tests described below in the
section entitled "Field Tests."
Table III. Subjective Board Descriptions
Board
Length (cm)
Carbon Strips
Description
1
155
Yes
"Stiff," intended for advanced riders
2
155
No
"Soft," intended for beginner riders
5
156
n/a
"High-quality," intended for advanced riders
For the boards used in field testing (indicated in the shaded regions of Tables I and II), one can
observe definite correlations between the subjective descriptions given in Table III and the
natural frequencies and damping ratios given in Tables I and II. Table III describes board 2 as
"soft" and intended for beginner riders, board 1 as "stiff and intended for more advanced riders,
and board 5 as "high-quality" and also intended for advanced riders. Table I shows that the
natural frequencies for the "soft" board 2 are in fact significantly lower than the natural
frequencies of the other two boards, particularly beyond the frequencies corresponding to the
first bending and torsional modes. It also shows that the torsional mode frequencies for the
"high-quality" board 5 are significantly higher than those of the other two and that it thus has the
higher torsional stiffness desired by an expert rider. In considering Table II, note that although
the "stiff board 1 has higher natural frequencies than the "soft" board 2 for modes beyond the
first, it does not have larger damping ratios and in fact has a significantly lower damping ratio
for the first bending mode. This is an indication that although the stiffness of board 1 makes it
more desirable than board 2 for an advanced rider, its relatively low levels of damping may limit
its performance and perhaps make it prone to chatter. In contrast, board 5 not only has the
natural frequencies indicative of the stiffness desired by an advanced rider but also has damping
ratios that would lead to a more rapid attenuation of undesirable behavior than those of board 1.
Computational Modeling
The dimensional, natural frequency, and damping information described in the preceding section
was used in conjunction with the software package Pro/ENGINEER to construct a solid model
for five of the eight snowboards investigated in the preceding section. These models were then
used for finite element analyses performed using Pro/MECHANICA to investigate both static
and dynamic characteristics. In performing these analyses, relatively simple material properties
were used. Although the actual structure of a typical snowboard is a built-up laminate
composite, and in fact Pro/MECHANICA allows for the analysis of such structures, the boards
were modeled as having uniform mass density and transversely isotropic stiffness properties.
This greatly simplified the modeling and property determination processes, as well as
significantly reducing computation time, while still yielding results in close agreement with
experimental observations.
For a completely general transversely isotropic material, there are six material parameters that
must be specified independently. These six parameters are mass density (/?), Young's moduli
(Ei and E2=Ei), Poisson's ratios (vii=v$i and v§2), and the shear modulus [Gu=Gi3i note
G23=£j/2(l+Vj^)]. Further simplification was achieved in the modeling process here by letting
176
E\=E2=E$ and y^= v$\=v$2- This reduced the number of independent parameters to four yet still
lead to computational results that were in close agreement with those observed experimentally.
To determine a value for p, the mass of the board was measured and then divided by the volume
calculated by Pro/MECHANICA from the measured dimensions used to create the model. In
this way, the total mass of the each model was always equal to the actual mass of each of the
boards. A value for Poisson's ratio (v= vz\= v$\= 1^2) was not determined experimentally but was
simply set to 0.3, which is typical of most materials. Values for Young's modulus
(E=E\=E2=E3) and the shear modulus (G=Gi2=Gu) were determined by matching values of
natural frequency calculated with Pro/MECHANICA to those measured experimentally. This
was an iterative process begun by selecting a reasonable initial value for E (such as that
determined in the Static Characteristics subsection of the Laboratory Tests section above),
calculating a corresponding initial value for G such that Gmmai = Einitiai I 2(1+v), and then using
these values in Pro/MECHANICA to calculate the first five natural frequencies. The frequency
calculated for the first bending mode was then compared to the first bending frequency
determined experimentally. For a fully isotropic material of uniform cross-section, an exactly
correct updated value for E could be calculated from the selected initial value of EmMai, the
calculated frequency (fcaic), and the corresponding experimentally determined frequency (fexp)
using E = Einitiai (fexplfcaic)2- This relationship, and a similar one for G, were used in an iterative
way (with a bit of manual tweaking) to converge on values of E and G that yielded natural
frequencies that were in close agreement with experimental results. Here "close agreement"
means within 0.125 Hz (the resolution of the experimental measurements) with occasional
slightly greater variations for the third bending and second torsional modes. The values
determined for Young's modulus and the shear modulus for the five boards studied are given
below in Table IV.
Table IV. Young's Modulus and Shear Modulus
Board
Young's Modulus (GPa)
Shear Modulus (GPa)
1
18.74
3.60
2
17.85
3.47
3
18.70
3.53
4
17.50
3.53
7
16.60
3.25
Beyond simply calculating natural frequencies, Pro/MECHANICA also enabled the modes of
vibration to be easily visualized. Typical mode shapes for the first four modes of vibration of an
unconstrained board are shown in Figure 1. Shown in the upper left is the first bending mode,
while the second and third bending modes are shown in the lower left and upper right,
respectively. The first torsional mode is shown in the lower right. The lighter tones in the
figures correspond to larger displacements; note that the displacements are exaggerated to
emphasize the characteristic shapes of the modes.
177
Figure 1: Mode shapes.
Field Tests
Field testing was undertaken to develop a database of strain and acceleration information that
would quantify typical snowboard maneuvers and provide input for future laboratory testing
equipment (see the Discussion and Conclusions section below). Field testing was done with
boards numbered 1, 2, and 5, as identified above, after 7 MicroMeasurements strain gages and
one accelerometer (PCS model 3 53 A) were attached to each. A photograph of one of the boards
with strain gages and accelerometer attached is shown in Figure 2.
Figure 2: Strain gage locations.
As shown in the figure, three strain gages, numbered 1, 3, and 6, are located along the
longitudinal centerline of the board and measure strain along the longitudinal axis. Gage 1 is at
the center of the board, gage 3 is at the widest point of the tail, and gage 6 at the widest point of
the tip. Two gages are located along each edge of the board and measure strain perpendicular to
the longitudinal axis of the board. On one edge these gages are numbered 2 and 5, and on the
other, they are numbered 4 and 7. An accelerometer is located on the longitudinal axis of the
board at its center and measures acceleration perpendicular to the surface of the board. Cables
connect each of the gages and accelerometer to a 24-pin connector mounted near the center of
the board on an L-bracket. The cables were attached to the board and coated with a heavy-duty
adhesive; the strain gages were coated with a thin layer of polyurethane before being coated
with a silicone rubber. The cables were also coated with a layer of waterproof tape.
178
The locations of the strain gages were chosen to provide an accurate indication of the bending
and torsion that the board experiences during use. The gages placed along the centerline
measure bending strains at the tip, center, and tail of the board. The gages placed along the
edges are strained when the board is in torsion or when riding on one edge and bent
transversely. The accelerometer was added to give a measure of the overall excitation of board
as it traverses the snow.
During testing the connector mounted on each of the boards was mated to a cable that
communicated the strain gage and accelerometer signals to an IBM ThinkPad laptop computer
carried in a padded backpack worn by a professional snowboarder performing the testing. The
computer was equipped with data acquisition hardware and custom software written in Visual
Basic. The Visual Basic program controlled data acquisition commencement, rate, and duration;
provided a time-stamp for each data set; and plotted the data on the screen at the conclusion of
each run. The program and laptop computing environment provided a powerful tool for data
collection, storage, and analysis yet was still robust enough to tolerate the low temperatures and
rough jostling experienced during runs.
A variety of scenarios were investigated during field tests. Of primary importance were
measures of performance during turning, stopping, and jumping. A total of 6 scenarios were
developed and executed by one of our professional riders over a two-day period. On the first
day, relatively gentle turning and stopping maneuvers were done on a beginner's slope on
groomed man-made snow. The day was overcast and windy with the temperature at
approximately 38°; the rider weighed approximately 150 Ibs. First, a series of gentle wideradius turns around cones placed on the slope were performed, and these were followed by a
series of narrow-radius turns (Figure 3 shows the rider executing a wide-radius turn). Stopping
maneuvers were also investigated, using both the toe-side and heel-side of the boards. Data was
collected at the rate of 100 Hz over a period of 25 to 30 seconds, which was typically slightly
longer than the total run time. Each run was video recorded, which also provided an audio
record of times at which turns were executed as read aloud from a digital timer.
Figure 3: Wide-radius turn.
Typical results for a series of wide turns using board 5 are shown in Figure 4. The graph
displays the readings obtained from the seven strain gages and the one accelerometer. The
vertical axis of the graph has units of micro-strain, and the horizontal axis has units of seconds.
Note that each of the strain gage readings has been offset from zero for clarity of presentation.
The topmost line (corresponding to gage 1) has been offset by 8000 micro-strain from its
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average value, the second line (corresponding to gage 2) by 7000 micro-strain, and so on
through the seventh gage, which has been offset by 2000 micro-strain. For clarity, the
accelerometer output has been scaled by a factor of 1000, with the actual peak voltage recorded
equal to approximately 1.25V.
When viewed closely, the graph gives quite a wealth of information about the behavior of the
board. The beginning of each run started at the top of a small ridge (see the upper left corner of
Figure 3), about 3 to 4 feet above the slope. As the rider dropped down from the ridge to begin
his ran, the board was bent significantly, as registered by the compressive strains measured by
gage 1 in the middle of the board and as indicated in Figure 4 at approximately 3 seconds. The
compressive strains produced on alternating edges of the board as the rider traversed back and
forth across the slope can also be clearly seen in Figure 4. The first turn is at approximately 8
seconds, at which time the compressive strains registered by gages 4 and 7 on one edge of the
board switch to the other edge of the board as measured by gages 2 and 5. The next turn at
approximately 11 seconds returns the strains to gages 4 and 7 and so on for the turns at
approximately 15 and 20 seconds. Also note that the accelerometer registers the greatest
vibration when the board is on edge and that the vibration greatly diminishes during the
transitions between edges when the running surface is relatively flat on the snow [see the
accelerometer signal (the bottom-most line on the graph) at approximately 8, 11, 15 and 20
seconds].
Wide Turns w/ Board 5 (1/11@4:15:27)
Turns @ 8,11,15, 20 Seconds
Time (s)
Figure 4: Wide-radius turn data.
On the second day of testing, more aggressive maneuvers were investigated. These were all
performed in a snowboard park and included steep descents with a large jump, riding a halfpipe, and riding a quarter-pipe. Snow conditions were again groomed, man-made powder. The
day was sunny, although breezy, with the temperature at approximately 32°. The second day of
tests were done by a professional snowboarder who weighed approximately 160 Ibs. Data was
again collected at the rate of 100 Hz over a period of 30 seconds. Each ran was video taped and
jump times were recorded.
Data collected during a half-pipe ran are shown in Figure 5. The strain gage readings have
again been offset for clarity. The top seven curves correspond to the seven gages, numbered
consecutively from the top. The curve representing the accelerometer output is at the bottom
and is again scaled by a factor of 1000. The most readily discernible features of this figure
180
correspond to jumps that occur as the rider exits and re-enters the half-pipe. These jumps take
place at 7.5, 10, 13, 16, 19, 22, and 24.5 seconds. As can be seen, the output of the
accelerometer is approximately constant throughout the time when the rider is in the air. The
outputs of the strain gages are also relatively quiet during air time. Unfortunately, because of
the aggressiveness of these maneuvers, a problem was encountered with the connection to the
battery supplying the excitation voltage to the strain gages, which can be seen at the points
where all seven gage output voltages simultaneously drop.
Half Pipe w/ Board 5 (1/12@1:38:50)
Jumps @ 7.5,10,13,16,19, 22, and 24.5 Seconds
Time(s)
Figure 5: Half-pipe data.
Discussion and Conclusions
One of the primary goals of this research has been to correlate relatively vague qualitative
descriptions of board performance, such as "soft," "stiff," or "high-quality," with the
quantitative measures of board characteristics represented by modal frequencies and damping
ratios. These data have also been shown to provide the basis for the parameter identification
necessary for the development of accurate computational models. The data presented here have
not been available before and will serve as a foundation for further studies.
There are a number of refinements and extensions to this work that could be pursued. Beyond
simply more testing of more boards, a greater effort could be made to develop a database of
quantitative performance characteristics and rider observations. In particular, a directed survey
of rider commentary should be done that collects input from a number of riders on the same and
different boards. An attempt should be made to elicit input that goes beyond comments such as
"soft9 and "stiff and asks the rider to focus on issues such as bending, twisting, damping, and
chatter.
Another avenue for further research is forced excitation. As has been done for skis, a
snowboard could be attached to an electro-dynamic shaker and subjected to excitation through a
range of frequencies. This would allow for more definitive determinations of natural
frequencies and damping ratios beyond those based simply on free vibration tests.
Another area for further investigation that builds on the results presented here is stiffness and
damping control. Ski manufacturers, such as K2, have had active stiffness and damping control
in ski products for a number of years and stiffness and damping control have recently appeared
in snowboards [7]. Optimal placement of stiffness and damping controlling materials could be
181
determined through computer simulation and then the actual effect on natural frequencies and
damping ratios measured both in the laboratory and in the field.
As mentioned in the Computational Modeling section, more elaborate computer models beyond
those described here can easily be envisioned that represent a board as a true composite laminate
structure. Such a model would require significantly more development time, as well as a much
more in-depth determination of material properties, but would allow for more detailed tracking
of the effects of changes in the design of the structure of board. Whether the effort associated
with the development of such a model would yield sufficient additional insight to make it
justifiable however is unclear.
One continuation of the current work that could be undertaken even with the current computer
models is a study of the effect of adding stiffeners, such as carbon strips or Kevlar strands, to the
snowboard structure. While determining the exact net effect of such additions using the current
models is not feasible, identifying trends in changes in the relative frequencies of bending and
torsional modes is. Such studies would accelerate the design process and allow for the
consideration of a much wider range of design modifications.
Not discussed in this paper is work that has already occurred that extends the foundation of the
snowboard research presented here. In particular, a dynamic testing machine was developed at
Bucknell University that simulates the behavior of a snowboard, as actually observed in field
tests, while turning, stopping, and jumping. A photograph of the testing machine simulating a
heel-side turn is displayed in Figure 6. The four pneumatic actuators simulate the ability of a
rider to apply forces either at the toes or heels of either leg. The displacement of each actuator,
and the force applied, is controlled through a Visual-Basic-based graphical user interface. The
user can select either manual mode for development of a particular maneuver or scenario mode
that allows for continuous execution of already developed and stored maneuvers. While a
maneuver is being performed, data from strain gages and accelerometers can be recorded to
ensure that the maneuver recreates that seen on the slopes and to track changes in behavior as
modifications are made to board design.
Figure 6: Snowboard testing machine.
182
Acknowledgements
Many individuals contributed to the work described in this paper beyond those listed as authors.
Bucknell mechanical engineering students Michael E. Morris and Christopher V. Nowakowski
contributed to the laboratory testing. Chris and fellow mechanical engineering student E. Blair
Sutton used their expertise with Pro/ENGINEER to aid in the development of the computer
models. Mike, Chris, and Blair with mechanical engineering students Frederick E. Luchsinger
and Timothy J. Nageli worked as a well-coordinated team while enduring the discomfort of
winter temperatures during field testing. Bucknell College of Engineering Development
Engineer Wade A. Hutchison contributed greatly to the collection of field data through the
development of Visual Basic software that communicated with data collection hardware.
College of Engineer Electronics Technician Thomas J. Thul, Laboratory Technologist James B.
Gutelius, Jr., and Product Development Laboratory Technician Daniel G. Johnson provided
electronics expertise, strain gage preparation, and machining skills that were important elements
in the success of the project. The project would never have taken place without the
entrepreneurial spirit and commitment to innovation of Walbridge Design & Manufacturing,
Inc. (now Dimension Snowboards) of York, Pennsylvania. Professional snowboarders Jay
Smith and Todd Aldridge contributed their skill, expertise, and patience in performing the
maneuvers requested in field testing. Seven Springs Mountain Resort in Champion,
Pennsylvania graciously provided accommodations, lift privileges, and slope access for the field
testing. Financial support for the project was provided through a grant from the Ben Franklin
Technology Center of Northeast Pennsylvania for which the Small Business Development
Center at Bucknell handled administrative support.
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