Lab 4

1.      Lab 4: Modeling the fall of an object falling with air resistance.

a.      Lab conducted by Mohammed Karim, Lynel, and Curtis on September 14^th and 19^th, 2016

2.     Objective – Find an equation that relates air resistance force, weight, and speed.

3.      Theory/Introduction – We know that air resistance is dependent on weight, shape, and speed. However, in this lab, we derived an equation that relates the air resistance force with terminal velocity and weight using a power law:

F=kv^n

4.      Apparatus/Procedure –

For this lab, we ventured to building 13 with coffee filters and dropped them from the ledge and recorded the terminal velocity of multiple coffee filters. First we dropped 1 alone and continued until we dropped five together to see the relation of weight on air resistance.

After returning to lab, we plotted the velocity from each fall using LoggerPro and found values for k and n. Next, we incorporated the values into a mathematical model on Excel by inputting values for time, velocity, etc. Upon plugging in these values, excel predicts the terminal velocity for the different weights and gives us the respective values. The excel was extra. We recieved all the needed data from LoggerPro, but it was done to show us the power of excel.

5. Data Tables/Analysis

Uncomfortable Physics students attempting to record falling coffee filters.

One of five plotted graphs of the falling coffee filters. The other 4 can be provided if needed. It seemed redundant to add all 5 when the plotted points can be seen on the graph.

Final graph modeling the force of air resistance in relation to velocity. Weight of coffee filter was also another variable that was used to help find the relation.

Excel sheet displaying the terminal velocity. The time interval was 1/60 of a second to be precise.

6.      Conclusion

     This lab was still near the beginning of the course, meaning that while it may contain a bit of new physics, it mainly is for students to get to know how to use different programs, like LoggerPro and Excel. We learned its comprehensive abilities. The model we used worked very well. The only problems is that there are many factors we didn’t take into account. 

     Though we were looking for air resistance, we did not take into account the added air resistance that was in the room, due to the air conditioning or opened doors. They may be minute, but they may affect our data. Uncertainties in height, positioning of the filter when plotted on the graph, timing, and the averaged data due to linear fit may also play a role in the slight margin of error.