The goal of this experiment is to experimentally determine the drag coefficients of stacked coffee filters. Additionally, the position of the coffee filters as a function of time will be compared to the results of solving Newton's equations analytically and solving them numerically using a neural network (as opposed to using numerical differential equation solvers).
The theoretical component of this experiment has two parts. Part 1 involves developing analytical expressions for the position of a falling object with and without air resistance. Part 2 involves predicting the position of an object falling with air resistance using a neural network to solve the relevant second-order differential equations. A full description of the theoretical component of this lab can be found here.
The experimental component of this lab involves using an Arduino with a distance sensor to determine the position as a function of time of several stacks of coffee filters. A thorough description of the experimental component can be found here.
Data Analysis Component
Finally, the data analysis component of this lab involves comparing the positions of the falling coffee filters from the theoretical and experimental components and extracting experimental values for the coefficients of drag for the coffee filters. The full explanation can be found here.