# Relationship Between Static And Kinetic Friction

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Based on the Force - Time graph generated by slowly pulling the cart with weights, we get measurement of static and kinetic friction to calculate the coefficients of frictions. From the graph, the maximum static force is peak force value before kinetic friction takes place.Then get µs according to equation fsmax = µs N. From the average kinetic friction from the Force -Time graph and equation fk = µk N, calculate its coefficient. This lab leads to a conclusion that the coefficient of static friction is usually larger than that of kinetic friction. Our experimental value of coefficient of static and kinetic friction for plastic cart is ( 0.183 ± 0.003 ) N and ( 0.098 ± 0.001 ) N. For the cork cart is ( 0.250 ± 0.003 ) N and ( 0.217 ± 0.002 ) N. For the felt cork cart is ( 0.203 ± 0.003 ) N and ( 0.165 ± 0.002 )

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Then attach the cart to the force sensor with a string around 10cm. Tape the masses onto the cart to prevent its slipping. Measure the weight of the whole cart system to calculate the normal force. Then use the force sensor to pull the car slowly and carefully in a constant velocity. Let the sensor record the data while pulling the cart and creates a Force vs Time graph in the Capstone. Repeat 5 trials for each different weight combination. Repeat the process for each different types of cart, cork cart, felt cart and plastic cart respectively.

(Figure 1. Lab setup. Force sensor (PASCO) is connected to the plastic cart with masses taped inside the cart on the leveled ground) From the diagram of the force data recorded by the sensor, maximum static friction value can be obtained by finding the peak of the graph. Kinetic Friction is the constant force after the peak while the cart moves in a constant velocity. Then plot the average Kinetic Friction vs Normal Force and Maximum Static Friction vs Normal force diagram for different scenarios for the same type of cart. The slope of the best line fit is µs and µf. For all the data discussed in this lab report, if there is multiplication or division involved, we use the larger percentage uncertainty as the whole data’s uncertainty. If there is addition or subtraction, choose the largest uncertainty as its