edited Phys1 Lab2
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New York University *
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UA11
Subject
Mechanical_engineering
Date
May 14, 2024
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8
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Lab #2:
Motion II
PHYS-UA11
Objective and Description
In this lab, we are able to analyze the relationship between position (
x
), velocity (
v
), acceleration
(
a
) and time (
t
) in a physical sense. This is accomplished through the aid of the Capstone database, which
this lab allows us to become even more familiar with.
As in the previous motion lab, the black motion sensor that uses sound waves to detect the
distance of an object was used. By attaching an index card to two different gliders, the motion sensor was
able to track the motion of the index card as the glider traveled down an inclined air track as a function of
time. Both the incline,
𝜽
, and the size of the glider were manipulated in the experiment.
Theory
There are several theories that are applied in the functioning and understanding of the experiment.
For instance, we could make assumptions about what our graph should look like based on the knowledge
of the mathematical relationship of the values. It is known that velocity is the derivative of position and
acceleration is the derivative of velocity and therefore the second derivative of position. If acceleration is
constant the following equations can be obtained from the integrations:
x=x
0
+ v
0
t + ½at
2
v=v
0
+ at
Furthermore, if friction is neglected, we are able to use Newton’s second law to predict that the
acceleration of the glider is
g
•sin
𝜽
. This comes from the fact that
𝚺
F
X
=ma
x
. Since there is no friction, the
x component of gravity is the only force acting upon the glider. Since mg
x
=mg•sin
𝜽
:
Procedure
My partner and I followed the procedure in the write-up fairly closely, since it was mostly straight
forward. However, a few minor differences did arise as the experiment was being conducted. For one,
when initially leveling the track, we noticed that it was nearly impossible to get the glider at a state of not
moving at all. Rather, we leveled it to where the glider was moving back and forth very slightly, which
my instructor clarified is normal. Additionally, when switching from y
1
to y
2
, the initial graphs produced
did not demonstrate a constant acceleration. My partner and I needed to realign the sensor with the track
in order to fix this source of error. We also needed to make sure the index card was stable secure or else
it’s movement would cause sharp changes in the acceleration curve. Finally, we found that smoothing out
the acceleration curve anywhere from 7-11 units was a sufficient amount to get an accurate read without
oversmoothing.
Data and Calculations
Part I
Key
Symbol
Unit
Value
y
1
=thickness of thinner block
m
0.0191m
y
2
=thickness of thicker block
m
0.0371m
r=length of track
m
1.2857m
𝜽
1
=angle formed by r and y
1
rad
see calculation below
𝜽
2
=angle formed by r and y
2
rad
see calculation below
m
1
=smaller, yellow glider
m
2
=larger, red glider
a=acceleration (m/s
2
), m=slope of velocity graph, n=power function is raised to
Table 1.1
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→
?𝑖?Θ =
𝑦
?
Θ = ?𝑖?
−1
(
𝑦
?
)
Θ
1
= ?𝑖?
−1
(
𝑦
1
?
)
=
?𝑖?
−1
(
0.0191
1.2857
)
=0.01486
Θ
2
= ?𝑖?
−1
(
𝑦
2
?
)
=
?𝑖?
−1
(
0.0371
1.2857
)
=0.02886
Table 1.2
*Note:
sin
was selected rather than
tan
. This is because the track length was used as the
hypotenuse and the height of the block was opposite to the angle.
Acceleration (m/s
2
)
Combination
Trial #1
Trial #2
Trial #3
Trial #4
Trial #5
Average a
(m/s
2
)
𝜽
1
+m
1
a=0.1435
m=0.143
n=1.95
a=0.1429
m=0.127
n=1.85
a=0.1431
m=0.125
n=1.74
a=0.1385
m=0.121
n=1.71
a=0.1375
m=0.123
n=1.79
=0.1411
𝑎
𝜽
1
+m
2
a=0.1432
m=0.142
n=1.81
a=0.1365
m=0.147
n=1.57
a=0.1493
m=0.144
n=1.95
a=0.1499
m=0.148
n=1.72
a=0.1406
m=0.139
n=1.62
=0.1439
𝑎
𝜽
2
+m
1
a=0.2822
m=0.291
n=1.95
a=0.2911
m=0.304
n=1.67
a=0.2936
m=0.293
n=1.76
a=0.2814
m=0.279
n=1.89
a=0.2994
m=0.291
n=2.14
=0.2895
𝑎
𝜽
2
+m
2
a=0.3149
m=0.302
n=1.78
a=0.3744
m=0.320
n=1.80
a=0.2800
m=0.279
n=1.85
a=0.2798
m=0.279
n=1.89
a=0.2843
m=0.285
n=1.93
=0.3067
𝑎
Table 1.3
Acceleration: Theoretical vs. Experimental
𝜽
1
𝜽
2
Theoretical
Experimental
Theoretical
Experimental
a=g•sin
𝜽
1
=(9.81m/s
2
)(0.01486)
=0.1458 m/s
2
=0.1411 or 0.1439
a=g•sin
𝜽
=(9.81m/s
2
)(0.02886)
=0.2831
=0.2895 or .3067
Table 1.4
Part II
Figure 1.1
Analysis
In this part, the glider was allowed to run down the track, hit the end and bounce back three times. This
can best be seen in the velocity graph. From 0 to ~3 seconds, the glider’s velocity increases until ~3.5
seconds, when the velocity goes to zero, representing the first time it hit the end. The glider then begins to
move in the negative direction and then forwards again while the velocity increases until ~9.5 seconds
where the velocity is zero and the glider hit for a second time. Finally, the earlier pattern is repeated until
~14.5 seconds when the glider hit for the final time.
Questions
Part I
1. How will acceleration change when we double the mass of the glider? Explain.
Based on the fact that F=ma, if mass is doubled, acceleration should theoretically be halved.
However, based on the data in table 1.3, when the mass of the glider was doubled and traveled at the same
incline, the average accelerations were fairly similar. This suggests that the acceleration is not influenced
by the mass in this case, hene why a=g•sin
𝜽
is used instead (see derivation in “Theory” section).
2. Do the graphs illustrate what is predicted by the theory? How so and explain! What is the correlations
of all the graphs?
The graphs did illustrate what is predicted by theory. The position graph appeared as a positive,
concave up, parabola. The velocity curve then appeared as a straight line with a positive slope. This is
what is expected since velocity is the derivative of the position graph. Finally, the acceleration graph
appeared as a generally straight line. This is expected, not only because it is the derivative of velocity, but
because acceleration was expected to be constant.
3. The velocity curve is noisier than the position curve and the acceleration is noisier than the velocity
curve. Why?
Recall that Capstone produces these graphs based on the data collected by bouncing sound waves
off the object, in this case the index card. This is why it was stressed in the procedure to ensure that the
index card was stably secured. Otherwise, as the index card moved, any slight movements caused by air
resistance is detected in the velocity and acceleration but not as drastically in the position. Also, which
Capstone measures position, velocity and acceleration and calculated. Since these are done by taking the
derivative, more “noise” may be produced with each successive derivative.
4. For the velocity plot, the acceleration is given by the slope (m). Why?
Since acceleration is the derivative of velocity, recall that the definition of a derivative is the slope
of the tangent line to a point on a curve. As such, since the velocity is the straight line, it’s slope is it’s
own tangent and thus, its acceleration.
5. In the acceleration plot the average acceleration data in the box is given by the mean of (y). Compare
this to the slope (m).
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As demonstrated in table 1.3, after each individual trial, the mean acceleration value, while not
identical, was fairly similar to the slope of the velocity plot (m). This further supports what is predicted by
the theory.
6. What is your experiential n(power)? What does theory say it should be? Why is there a difference?
The n value, as demonstrated in table 1.3, are all approximately 2, either falling slightly below or
above, but never quite 2. According the equation
x=x
0
+v
0
t+½at
2
, theory suggests that the power should
be two, having the shape of a parabola. While all the n values would match this when rounded to the
nearest tenth, the slight variance may be attributed to the same reason there is more noise in the velocity
and acceleration graphs.
7. When the same
𝜽
is used for different gliders, is there a difference in acceleration? Why?
As demonstrated in table 1.3, when the same
𝜽
was used for different gliders, the accelerations,
while not identical, were fairly similar. Since a=g•sin
𝜽
was used (see derivation under “Theory”), this
observation supports what is expected.
Part II
1. Does the velocity curve cross the axis (velocity=0) where you expect it to?
The velocity curve crossed the axis each time the glider hit the end of the track, as expected.
Additionally, the glider also crossed the axis after hitting the end, when the velocity graph moves from the
negative region to the positive region, before dropping to 0 again. This suggests that the velocity was zero
as the glider changes direction from moving backwards to forwards.
2. Are the curves the same from bounce to bounce? If not, could you suggest why?
The curves become smaller from bounce to bounce. This could possibly be due to the decrease in
overall kinetic energy, resulting in less movement and the glider slowing down.
Error Analysis
Table 1.4 depicts the difference between the theoretical acceleration found with a=g•sin
𝜽
in
comparison to the actual calculated values. It is evident that they two vary only slightly and are generally
within an acceptable standard deviation.
Ex:
% 𝑒????
= (0.2895−0.2831)
0.2831
•100 = 2. 26%
Conclusion
Through the use of Capstone, the relationship between position, velocity, acceleration and time
became more apparent. The application of Newton’s second law in the absence of friction also became an
interesting one to observe. Prior to the experiment, I predicted that the acceleration would decrease when
we used the larger glider, but this was not observed. Other than that, the experiment matched my
expectations and the theory closely.