Phys lab report

Janik Zender

Sidd Rao

Christelle Mata

Physics 121

Prof. Trevor Gamble

June 11 , 2021

Lab Report - Torque

Introduction

The purpose of this experiment is to study the properties and mathematics behind torque, a rotational effect of a force. You might recall playing on a seesaw with a friend. The heavier you are, the larger the gravitational force. To balance the beam again, you need a counteracting force on the other side. One possibility is to place a second person at the same weight on the other side of the beam. Once the same force is pulling down on each side of the beam the seesaw is balanced. This example demonstrates the concept of torque. Torque, mentioned before as a rotational effect of a force, depends on the magnitude of the force applied, the distance (from the axis), and the angle at which the force is applied.

In this lab, a meter stick will be balanced on a support stand. Weights will then be added to the meter stick. These weights will create forces and torques on opposite sides of the meter stick. This lab will teach the concepts of rotational equilibrium and torques. It will increase understanding of the principals of rotational equilibrium because various rotational equilibrium scenarios will be tested.

Procedure

First, each member of the group did three torque balance experiments by setting up the meter stick and placing it to the center of the meter stick on a pencil (at 25 cm). Then, choose a fixed distance to place an amount of washers on the right side away from the center of the meter stick. Record the amount of the washers and the distance from the center. Do the same thing to the opposite end of the meter stick and make sure its distance from the center. Finally, make sure the meterstick is balanced by checking if it stays parallel to its flat surface and is not slanting. Then look at how each percentage of error differed with each trial and between trials 1, 2, & 3.

Data

Measured rL	Theoretical rL	rR	mL	mR	Uncertainty	Error	Sample
4.6	3.6	6	5	3	2%	27%	Sample 1
6.5	6.3	8	4	3	2%	0.833%	Sample 2
6.4	4.8	8	5	3	3%	33.33%	Sample 1
7.7	8	10	5	4	4%	3.75%	Sample 3
8.1	6	10	5	3	1%	35%	Sample 1
13.5	8.0	10	4	3	4%	8%	Sample 2
10	9.6	12	5	4	2%	4.167%	Sample 3
10.5	9.9	12	4	3	2%	1.668%	Sample 2
12	11.2	14	5	4	1%	7.14%	Sample 3

Analysis

In this lab there were 3 different samples done independently from each other with different equipment. In each sample there are 3 measurements with different Masses and measurements. When calculating the uncertainty, look at the different factors that might affect the measurements along the ruler. Assign each one of those factors an uncertainty percentage and add them together to calculate the total uncertainty in the measurements.

To calculate the theoretical length:

RL – Theoretical Length Left Side

MR – Mass Right Side

RR – Measured Length Right Side

ML – Mass Left Side

To calculate the percent error:

MRL – Measured Length Left Side

RL – Theoretical Length Left Side

Measured rL	Theoretical rL	rR	mL	mR	Uncertainty	Error	Sample
4.6	3.6	6	5	3	2%	27%	Sample 1
6.5	6.3	8	4	3	2%	0.833%	Sample 2
6.4	4.8	8	5	3	3%	33.33%	Sample 1
7.7	8	10	5	4	4%	3.75%	Sample 3
8.1	6	10	5	3	1%	35%	Sample 1
13.5	8.0	10	4	3	4%	8%	Sample 2
10	9.6	12	5	4	2%	4.167%	Sample 3
10.5	9.9	12	4	3	2%	1.668%	Sample 2
12	11.2	14	5	4	1%	7.14%	Sample 3

In this data table there are a wide variety of uncertainty errors, from as low as 7% to as high as 35%. This range was not expected at all during the experiment, it shows a lack of accuracy and precision in the data sample. A causing factor of the high percent error could be the weight differences between the sample collections, not every washer weighs the same. Another potential factor could be the unbalanced ruler, in all the samples each ruler was unbalanced when placed halfway on the fulcrum. The unbalanced ruler would affect our data by adding weight to one side that is unaccounted for in our data.

The one exception to this variable data is Sample 2. Sample 2 has very good accuracy and precision compared to Sample 1 and Sample 3. That could be attributed to a better-balanced ruler, a closer range of washer masses and more accurate measuring.

The data collected for this lab displays a variety of errors and flaws with the experiment. The lack of accuracy or precision between all the samples shows there are improvements that could be made in the lab in the future.

Conclusion

In conclusion, this lab didn’t really produce reliable or accurate data that could support any hypothesis. There were too many factors that weren’t sent and varied throughout the experiment which created a variety of percent errors. Without calculating the weight of each washer or having a balanced ruler it is difficult to get accurate or even precise data. Setting each variable factor and only changing one at a time will create a much more accurate and usable data set that can corroborate additional data or a hypothesis.

What would be interesting to find out is what exactly happened to make Sample 2 so accurate, and what exact methods were used to get this data. Then the additional experiments can use the same methods to get better data. In the end our data has a lot of errors and isn’t very good at all. There is one sample that has good data but that is only one third of our overall chart. The methods of Sample 2 should be implemented in further labs and studies to create a better data set that can corroborate a hypothesis or additional data.