Thermal Properties of Matter Activities (2/26/2015)

Our expectation and explanation of what will happen when a metal ring is heated to allow a sphere to pass through.

Prof Mason is heating the ring to allow the metal sphere next to him to pass through the ring.

Our answer as to what four variables will affect the expansion of an object.

Predictions as to which direction the bimetallic strip will bend after heating each side separately.

Prof Mason heating the bimetallic strip, showing that it bends towards the invar side (right).

The bimetallic strip was then placed in ice and we predicted that it would then bend toward the brass (left) side, which it did due to contracting.

Calculations for the linear thermal expansion demo. This part consisted of figuring out the angular displacement caused by the heated rod as well as the coefficient of thermal expansion.

The apparatus used for the first linear thermal expansion demo. The device on the left sent steam through the metal rod, and the rotary motion sensor measured the change in distance.

Data gathered from heating water and sending steam through the metal rod.

Pictured above are the calculations for the actual value of alpha from the linear thermal expansion demo, as well as the calculation of its uncertainty. The final values were found to be 18.7*10^-6 1/C +/- 9.35*10^-6 1/C.

Predictions for the second linear thermal expansion demo, which involved heating a mix of water and ice for 5 mins.

Ice and water mixture being heated using an immersion heater.

Data gathered from the heating of the ice and water mixture.

Calcuations for the heating of the ice/water mixture, showing how much liquid remained and how much heat was produced.

Answer to the problem in the previous picture.

Video for the "Pressure of a Column of Liquid" activity, showing Noe blowing into a tube with water to analyze what happens.

Calculations for analyzing how much pressure is used when blowing into the tube with water.

Calculations showing how much pressure Noe produced in the tube of water.

Calorimetry Temperature and Heat Activities (2/24/2015)

The entire class estimated the temperature of the room, and using the estimates we calculated an uncertainty for the temperature. This is my group's calculations with an uncertainty of +/-1.64 C. 

 A calorimetry example was done using logger pro and heat sensors. A cup of cold water was mixed with a cup of hot water, and it's final temp was calculated to be 47.9C +/-5.63C. The mass of the hot water was calculated to be 147g +/-3g. The calculations and answers are shown, but are difficult to see with the blue marker.

 A second calorimetry example was done, but this time cold water was placed in a cup, while hot water was placed in an aluminum can, which was then placed in the cold water. This graph shows how the equilibrium process occurred, after which we were asked to figure out why the top curve has such a drastic drop.

Here is the work done trying to answer the question of the previous graph. The conductivity of the can is what messes up the graph, so we had to find the specific heat of the can. The entire class got a wrong answer, and we had to figure out why. Our group concluded that heat is escaping through the can and is throwing off the readings and calculations. Also, the masses used attribute to significant error since they were very loosely guessed. Based on calculations, the C of the aluminum can should be 16.3+/-11.27.

We were asked to guess what things in a room would affect the rate at which liquids cool or heat, and these are the answers my group put.

Here, Prof Mason is explaining conductivity and translating an equation for it into terms that will help us understand the equation.

We were asked to think about what variables affect the rate at which dQ/dt changes.

 This is work Prof Mason did to show the amount of heat flow (123W) through the copper/aluminum rod, as well as the R values for each end of the rod.

 This is work my table did to figure out the answers to the two previous questions. The class was moving fast due to lack of time, so not everything was able to be written down.

Next, we used an immersion heater (which was calibrated to reveal a 292.8W output) to heat water. We also calculated how much heat we'd expect to have after running the heater for 20 seconds.

This is a graph showing the rate at which the immersion heater heated the water using axes of Temperature vs Time.

The graph was then inverted to show what Heat vs Temperature looks like. This shows a linear relationship, ignoring the drop and spikes at the ends.

This is work that was done while translating the data to figure out what the physical meanings of each parameter were.