The Effect of Ramp Angle on Cart Acceleration: An Experimental Investigation, Summaries of Physics

This document details an experiment investigating the relationship between ramp angle and cart acceleration using a dynamics track, kinematics cart, and motion sensor. The study found that the model agreed with experimental data but the measurement of g did not.

Typology: Summaries

2021/2022

Uploaded on 12/13/2022

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The Effect of Ramp Angle on the Acceleration of a Cart Down a Ramp
Abstract: In this experiment we are investigating the effect that the angle of a ramp has on the
acceleration of a cart moving down the ramp. We used a dynamics track at several angles and a
kinematics cart. We found that our model agreed with the experimental data, but our measurement of g
did not.
Introduction: In this experiment we are investigating the effect that the angle of a ramp has on the
acceleration of a cart moving down the ramp.
Procedure: In this lab we used a dynamics track, a kinematics cart, and a motion sensor that was
connected to Pasco. We set the ramp at 5 different angles, which we measured with a meter stick. Then
we allowed the cart to roll down the ramp, catching it before it hit the stop at the end, so that it did not
alter the angle. We did 5 trials and we kept the mass constant for each trial. You can use either position
vs. time or velocity vs. time to get the acceleration.
Theory: We can derive the relationship between the acceleration of the cart and the angle of the ramp
using Newton’s Laws. The model is a=g*sin(θ), where g is the acceleration due to gravity. In order to
linearize this model, we plotted acceleration vs. sin(θ) and we expect the slope to be g. Our independent
variable was the acceleration, in units of m/s^2, and our dependent variable was sin(θ), in units of
radians. We expect the acceleration to increase with angle, so as sin(θ) goes to infinity, so will the
acceleration. The y intercept should be zero, because the cart won’t move if there is no angle.
Data:
0 0 . 0 5 0 . 1 0 . 1 5 0 . 2 0 . 2 5 0 . 3 0 . 3 5
0
0.5
1
1.5
2
2.5
3
3.5
Accelerati on Vs sin(θ)
Model
Linear (Model)
Experimental
Sinθ (radians)
Acceleration (m/s ^2)
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The Effect of Ramp Angle on the Acceleration of a Cart Down a Ramp Abstract: In this experiment we are investigating the effect that the angle of a ramp has on the acceleration of a cart moving down the ramp. We used a dynamics track at several angles and a kinematics cart. We found that our model agreed with the experimental data, but our measurement of g did not. Introduction: In this experiment we are investigating the effect that the angle of a ramp has on the acceleration of a cart moving down the ramp. Procedure: In this lab we used a dynamics track, a kinematics cart, and a motion sensor that was connected to Pasco. We set the ramp at 5 different angles, which we measured with a meter stick. Then we allowed the cart to roll down the ramp, catching it before it hit the stop at the end, so that it did not alter the angle. We did 5 trials and we kept the mass constant for each trial. You can use either position vs. time or velocity vs. time to get the acceleration. Theory: We can derive the relationship between the acceleration of the cart and the angle of the ramp using Newton’s Laws. The model is a=g*sin(θ), where g is the acceleration due to gravity. In order to linearize this model, we plotted acceleration vs. sin(θ) and we expect the slope to be g. Our independent variable was the acceleration, in units of m/s^2, and our dependent variable was sin(θ), in units of radians. We expect the acceleration to increase with angle, so as sin(θ) goes to infinity, so will the acceleration. The y intercept should be zero, because the cart won’t move if there is no angle. Data: 0 0. 0 5 0. 1 0. 1 5 0. 2 0. 2 5 0. 3 0. 3 5 0

1

2

3

Accelerati on Vs sin(θ)

Model Linear (Model) Experimental Sinθ (radians) Acceleration (m/s^2)

Analysis: Our data points lie close to our model, so our experiment proved that the model matches reality. The data agreed that as sin(θ) increases, a increases. The reason our data don’t match was probably friction or air resistance, which is a type of friction. These are random errors since the air in the room is random. Conclusion: We found that our predicted model, a=g*sin(θ), matched the actual data. Our measurement of g was not in agreement with the value 9.8. To improve the experiment, we should do more angles, so the slope would be measured from more points.