Brock University Physics Department PHYS 1P93 Laboratory Manual

Brock University Physics DepartmentSt. Catharines, Ontario, Canada L2S 3A1

PHYS 1P93 Laboratory Manual

Physics Department

Copyright c© Brock University, 2015-2016

Contents

1 Calorimetry and heat capacitance 1

2 The Stirling engine 8

3 Refraction of light 18

4 Archimedes’ principle 26

5 Viscosity and drag 32

A Review of math basics 42

B Error propagation rules 45

C Graphing techniques 47

i

ii

(ta initials)

first name (print) last name (print) brock id (ab17cd) (lab date)

Experiment 1

Calorimetry and heat capacitance

In this Experiment you will learn

• some basic methods of heat exchange between materials and the Leidenfrost Effect;

• that the heat exchange between matrials is described by Newton’s Law of Cooling;

• how to determine the heat capacity of brass by performing a computer analysis of a cooling curve;

• to visualize data in different ways in order to improve the undwerstanding of a physical system;

• to apply different methods of error analysis to experimental results.

Prelab preparation

Print a copy of this Experiment to bring to your scheduled lab session. The data, observations andnotes entered on these pages will be needed when you write your lab report and as reference materialduring your final exam. Compile these printouts to create a lab book for the course.

To perform this Experiment and the Webwork Prelab Test successfully you need to be familiar with thecontent of this document and that of the following FLAP modules (www.physics.brocku.ca/PPLATO).Begin by trying the fast-track quiz to gauge your understanding of the topic and if necessary review themodule in depth, then try the exit test. Check off the box when a module is completed.

FLAP PHYS 1-1: Introducing measurement

FLAP PHYS 1-2: Errors and uncertainty

FLAP PHYS 1-3: Graphs and measurements

FLAP MATH 1-1: Arithmetic and algebra

FLAP MATH 1-2: Numbers, units and physical quantities

WEBWORK: the Prelab Heat Capacity Test must be completed before the lab session☛✡

✟✠! Important! Bring a printout of your Webwork test results and your lab schedule for review by theTAs before the lab session begins. You will not be allowed to perform this Experiment unless therequired Webwork module has been completed and you are scheduled to perform the lab on that day.

☛✡

✟✠! Important! Be sure to have every page of this printout signed by a TA before you leave at the endof the lab session. All your work needs to be kept for review by the instructor, if so requested.

CONGRATULATIONS! YOU ARE NOW READY TO PROCEED WITH THE EXPERIMENT!

1

2 EXPERIMENT 1. CALORIMETRY AND HEAT CAPACITANCE

Heat capacitance

Heat is a form of energy, and the heat capacitance of a body is a measure of the amount of this thermalenergy that the body can hold. Heat capacitance depends on the material the body is made of, andmeasuring it can help to identify the material.

Heat naturally flows from hotter to colder bodies, and in general it is not easy to stop this flow of heat.There are several ways in which heat can be transported. One is direct contact of two bodies; the rateof direct heat conduction varies a great deal for different materials. Also, the rate of heat flow is roughlyproportional to the temperature difference between the two bodies: the greater the difference, the fasterthe heat flow. For example, in very hot weather, as the temperature difference between the car’s radiatorand the air flowing past it is decreased, the effectiveness of cooling is diminished.

When one of the bodies is a gas or a liquid that flow away from the other body after making a thermalcontact, the heat is said to be transported by convection. When the differences in temperature are great,radiative heat transfer becomes important; all bodies above absolute zero emit thermal radiation, and theamount of this radiated energy grows very rapidly with temperature.

Even if the temperature is constant, heat energy may flow in and out of the system, if an internalrearrangement of atoms is taking place, such as a change of state from liquid to gas (evaporation) or fromsolid to liquid (melting). This so-called latent heat of evaporation or of melting again depends a great dealon the material in question, and can be used to identify the material.

Liquid nitrogen and safety

In this experiment, you will use liquid nitrogen as a handy source of a large temperature difference. Nitrogengas becomes liquid at 77 K or −196◦C, more than 200◦C below room temperature. When liquid nitrogencomes into contact with room-temperature objects, a small amount of if evaporates very quickly and formsa thin layer of nitrogen gas. The formation of this gas layer is known as the Leidenfrost Effect.

Since the heat conduction in gas is much slower than that in a solid or a liquid, this gas acts as a barrierto heat conduction, and it allows the remaining nitrogen to remain in liquid form. One could spill a smallamount of liquid nitrogen directly onto skin, and live to tell the tale. But if a drop of liquid nitrogen istrapped in the folds of the skin, or if the skin comes into contact with a metal or glass container holdingthe liquid nitrogen, a serious injury will result. That is why you must:

Always wear gloves and goggles when handling liquid nitrogen!

Also, open-toed footwear will not be permitted in the laboratory!

Procedure and analysis

A computer-connected precise digital weight scale will allow you to monitor the weight of a Styrofoam cupcontaining liquid nitrogen. As the heat is slowly transferred from the room-temperature environment, oras we add a known amount of room-temperature material into the cup, the added heat will turn some ofthis liquid nitrogen into gas. As a result, the mass reported by the scale will decrease as a function of time.As you analyze the nature of this time dependence, you should be able to extract several relevant physicalquantities with considerable precision.

• Turn on the digital weight scale and wait for the display to read zero. Place the empty Styrofoamcup onto the scale. Note the reported mass, how quickly the scale reading settles to a constant value,the precision of the scale. Note what effect vibrations due to your footsteps or leaning of the tablehave on the readings, and plan the rest of your experiment accordingly.

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mcup = ......................± .....................

• Fill the Styrofoam cup to about two thirds with liquid nitrogen, then place it on the scale. Close anyrunning Physicalab software, then restart the program and enter your email address. Set the inputchannel to Adam, select scatter plot.

• Choose to collect a data point every 5 seconds for at least 20 minutes, then press Get data to start

the data acquisition. You can click Draw at anytime to graph the data set acquired so far.

• Try a simple linear fit, A*x+B, and note the resulting χ2 misfit value. Over short time intervals, alinear function might be appropriate, but as the level of liquid nitrogen in the cup changes, so doesthe slope of the curve m(x), where x represents time. Label the axes and include the fit equation as

part of the title, then press the Send to: button to email every member of the group a copy of thegraph for inclusion in the lab report.

? What do you note when comparing the curve from fitting equation to the points from your data set?

• Now try an exponential fit, A*exp(-x/B) and note again the χ2 misfit. Your plot should look similarto the one shown in Fig. 1.1.

? Compare once again the curve from the fitting equation to the trend in your data set. What changesdo you note from the previous graph?

Figure 1.1: Mass of a cup of liquid nitrogen decreases with time due to boil-off

? What is the dimension and the physical meaning of the fit parameter B in the exponential fit?

? What value does this fitting equation converge to as time progresses toward infinity? Is this resultconsistent with what you would expect?

• If the liquid-nitrogen level falls below approximately one-third-full, the exponential function maybecome insufficient to describe the time dependence you observe, and an additional constant off-set parameter may need to be added to the exponential function. Try fitting your data set toA*exp(-x/B)+C and make a note of the reported χ2 values.


? Evaluate the result form this fit. What changes do you note from the previous graph?

? What is the dimension and the physical meaning of the fit parameter C?

? What value does this fitting equation converge to as time progresses toward infinity?

? Is the result from the fit consistent with your expectation? Why might this be so?

• Use paper towels to wipe down the frost and accumulated condensation from the Styrofoam cup andthe digital scale plate.

• Determine the weight of the provided brass block with the highest possible precision.

mbrass = ......................± .....................

• Use the room thermostat thermometer to determine the “room temperature” which is the initialtemperature of the brass block. Handle the block by the attached string to prevent it from absorbingyour body heat.

Troom = ......................± .....................

• Refill the Styrofoam cup to two-thirds-full and place it and the brass block on the weight scale thenstart your data acquisition run. Get a point every 5 seconds over approximately 15–20 mins. Fiveminutes should be enough to establish the initial shape of the mass-as-a-function-of-time curve.

• After five minutes, transfer the brass block into the Styrofoam cup, leaving the string to dangleoutside the cup. Be careful to prevent splashing and avoid touching the surface of the liquid nitrogenwith anything but the brass block itself. You can expect a significant cloud of cold gas to be generatedwhen the brass is rapidly cooled by the liquid nitrogen to 77 K.

Try to perform this transfer in between the data points to avoid picking up erratic readings; this isnot essential, however.

• Continue the data acquisition and carefully monitor the process to note the rapid boil-off as the brassplug reaches the temperature of the liquid Nitrogen, after which the boiling stops. Acquire data foranother five minutes, to establish the trailing slope of the curve.

Note: At the end of the run the brass block is at 77 K and is extremely dangerous. Carefullytransfer the brass block into the sink and run tap water over it until all traces of ice are gone. Wipedry and return it to your station.

? What do you suppose might be the cause of this rapid boil-off as the plug reaches 77 K?

• Establish through a visual inspection of the graph the two time points T1 and T2 that correspond tothe beginning and the end of the rapid boil-off interval.

• Fit your data to (A*exp(-x/B)+C)*(x<T1)+((A-D)*exp(-x/B)+C)*(x>T2) using the values of T1

and T2 determined above. To get a valid χ2 value, the constraint equation (x < T1) + (x > T2) mustbe entered in the constraint box. Examine the quality of the fit, and note the χ2 misfit value.

• Repeat several times, changing the values of T1 and T2 slightly to move away from the edges of theregion of the rapid boil-off. Ideally, the value of D reported by the fit should not depend on theprecise choice of T1 and T2.

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T1, s T2, s D ± dD χ2

Best D value: (least χ2)

D = ......................± .....................

The fit parameter D represents the “extra” liquid nitrogen boiled off to cool down the brass block fromTroom to 77 K. It takes 208 kJ to boil off 1 kg of liquid nitrogen. Your task is to calculate the average

specific heat of brass, cbrass i.e. the amount of heat that is required to raise the temperature of 1 kg of brassby 1 K. Proceed as follows:

• The temperature change experienced by the brass plug in going from room temperature to that ofthe liquid nitrogen is:

dT = ..................... = ..................... = .....................

• The error in this temperature change ∆(dT ), assuming that there is no error associated with theboiling temperature of the liquid Nitrogen, is given by:

∆(dT ) = ..................... = ..................... = .....................

• Convert D into the total amount of heat discharged by the brass plug dQ

dQ = ..................... = ..................... = .....................

• The error in this heat change, ∆(dQ), is given by:

∆(dQ) = ..................... = ..................... = .....................

• Calculate the heat capacity of brass cbrass and the associated error using dQ = cbrassmbrassdT .

This result is only an average value because the heat capacitance is not constant in brass between77 K and the room temperature.

cbrass = ..................... = ..................... = .....................

∆(cbrass) = ..................... = ..................... = .....................

cbrass = ......................± .....................


• Convert your result to the units of the accepted value, cbrass = 0.093± 0.002 calg ◦C

at 20◦C, so that a

dirce comparison can be made:

cbrass = ..................... = ..................... = .....................

∆(cbrass) = ..................... = ..................... = .....................

cbrass = ......................± .....................

IMPORTANT: BEFORE LEAVING THE LAB, HAVE A T.A. INITIAL YOUR WORKBOOK!

Lab report

Go to your course homepage on Sakai (Resources, Lab templates) to access the online lab report worksheetfor this experiment. The worksheet has to be completed as instructed and sent to Turnitin before the labreport submission deadline, at 11:00pm six days following your scheduled lab session. Turnitin will notaccept submissions after the due date. Unsubmitted lab reports are assigned a grade of zero.

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Check your schedule!

This is a reminder that Experiment 2 does not necessarily follow Experiment 1.

You need to login to your course homepage on Sakai and check your lab schedule to determine theexperiment rotation that you are to follow.

My Lab dates: Exp.2:......... Exp.3:......... Exp.4:......... Exp.5.........

Note: The Lab Instructor will verify that you are attending on the correct date and have prepared for thescheduled Experiment; if the lab date or Experiment number do not match your schedule, or the reviewquestions are not completed, you will be required to leave the lab and you will miss the opportunity toperform the experiment. This could result in a grade of Zero for the missed Experiment.

To summarize:

• There are five Experiments to be performed during this course, Experiment 1, 2, 3, 4, 5.

• Everyone does the first experiment on their first scheduled lab session.

• The next four experiments are scheduled concurrently on any given lab date.

• To distribute the students evenly among the scheduled experiments, each student is assigned to oneof four groups, by the Physics Department. Your schedule is shown in your course homepage onSakai.

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(ta initials)


Experiment 2

The Stirling engine

A friendly reminder: Is this your scheduled experiment? See the previous page.


• some of the principles of thermodynamics, power, work, coefficient of performance;

• that the work performed by an engine can be measured using a P-V diagram;

• about thermal inertia and the times required for a heat engine to reach equilibrium;


Prelab preparation








WEBWORK: the Prelab Stirling Test must be completed before the lab session☛✡


☛✡



8

9

The Stirling Engine

It is said that the plight of poor workmen, often injured by the explosions of the early steam engineswere the inspiration for Rev. Robert Stirling’s engineering efforts that led to the development of whatwe now call “the Stirling engine” in 1816. However, Rev. Stirling’s life-long interest in engineering, hisfather’s profession, suggests that the technical challenges fascinated him as well. He is the author of severalpatents, from the “Heat Economizer” (regenerator) to various optical devices, his “air engine” being themost famous.

Stirling engines are typically external combustion engines, as opposed to the open-cycle internal com-bustion engines prevalent today. The Stirling cycle involves moving a working fluid, typicallly a gas,between two reservoirs that are maintained at different temperatures, mediating the heat transfer from thehot to the cold side and extracting mechanical work in the process. In this way, the Stirling engines arevery similar to the idealized heat engines textbooks on Thermodynamics.

The designs of Stirling engines vary considerably, but they all share the inherent safety of a muchlower operating pressure of the working gas, and fairly high heat-to-work conversion efficiency, especiallycompared to a standard gasoline engine. Their dynamic properties — the ability to rev up quickly, forexample — are quite poor, so they are not well suited for motor vehicle use, but there are marine engines,hand-held toys, and deep-space probe electrical generators that all use Stirling engines.

Figure 2.1: The U10050 Stirling Motor. Reproduced from the 3B Scientific manual.

The engine used in this lab is a displacement-type engine that uses two separate pistons, connectedto a common flywheel (see Fig. 2.1). One piston is the working piston; it fits snugly into the cylinderand maintains the seal on the working gas. The other, a displacement piston, is moving freely inside itscylinder, shifting the working gas through the gap between the piston and the cylinder from the hot to thecold end of the cylinder, and back again. The full Stirling cycle can be approximately divided into fourparts:

1. the gas is shifted to the hot end by the displacement piston; it expands as it heats up, and pushesthe working piston which in turn rotates the flywheel;

2. the displacement piston moves, shifting the gas toward the cold end; heat is lost from the gas;

3. cooled gas is re-compressed by the inertia of the flywheel pushing the working piston.

4. with the gas compressed by the working piston, the displacement piston shifts it to the hot end,where the heat is absorbed into the gas.

10 EXPERIMENT 2. THE STIRLING ENGINE

Figure 2.2: The Stirling cycle. Reproduced from the 3B Scientific manual.

The four parts of the cycle are illustrated schematically in Fig. 2.2.

On the left, four snapshots 1–4 show the relative positions of the displacement (A) and working (B)pistons that correspond approximately to the four parts of an idealized Stirling cycle.

On the right, A more realistic plot of the positions of the two pistons during the continuous rotationof the flywheel. The grey region in part 2 shows the part of the cycle where the working piston is nearits lowest point and the gas volume is approximately at its maximum. The area above the dashed linerepresents the fraction of the total volume that is above the displacement piston, in thermal contact withthe hot end of the cylinder.

Since it takes less work to compress the gas when it is cold (against lower gas pressure) than the workdone by the gas on the piston when it is hot (gas exerting higher pressure over the same piston traveldistance), there is a net conversion of heat into mechanical work.

Dividing the cycle into four discreet parts is an idealization. A more realistic plot is shown in theright-hand frame of Fig. 2.2, where the positions of both pistons vary continuosly throughout the cycle.Both pistons are attached to the same flywheel, but at 90◦ to each other. As a consequence, the solid andthe dashed line are a quarter of a cycle out of phase with each other.

Figure 2.3: The pV -diagrams of the Stirling cycle. The idealized cycle in the left frame is made up of fourdistinct parts. In a realistic Stirling engine the parts of the cycle are not completely separate, and thepV -diagram looks more like the one in the right frame.

Fig. 2.3 illustrates the thermodynamics of the Stirling cycle. As we follow along the curve made by themeasured pairs of (pi, Vi), the area on the pV -diagram inside the cyclical trajectory of the working cycle

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of the engine represents the amount of mechanical work performed by it:

W =∑

i

Fi∆xi =∑

i

(piA)∆xi =∑

i

pi(A∆xi) =∑

i

pi∆Vi

The work is being done by the gas on the flywheel along the upper curve, and by the flywheel on the gasalong the lower curve; the difference is the net work done by the engine. In our example, one can estimategraphically the area inside the curve of Fig. 2.3 (right frame) to be about three–four large squares, 20 kPaby 0.25cm3 = 0.25 × 10−6m3, and therefore, about 15–20 mJ per cycle.

Stirling engines, in general, have excellent coefficients of performance (CoP), reaching as high as twicethe thermal efficiency of internal-combustion gasoline engines. When used to drive electric generators, asin this experiment, the thermal efficiency, though high, is just one of many of the CoP’s that need to bemultiplied together to get the overall CoP: that of the mechanical efficiency of the flywheel-piston system,that of the conversion efficiency of mechanical into electrical energy, etc.

The overall efficiency of the process of conversion of the internal chemical energy of the fuel into theusable electrical energy that can turn on a lighbulb, is only of the order of 10%. Increasing the difference inthe operating temperatures of the hot and cold ends, changing the working gas, or the compression ratio,can dramatically affect that number, but the cost and complexity of the engine may also increase.

Stirling engines, long a domain of tinkerers and enthusiasts, are making a comeback. Six Swedishsubmarines are equipped with Stirling engine propulsion units, enabling them to conduct long-range divesfueled by a chemical source of energy that does not involve a conventional burning of liquid fuel, withoutthe use of nuclear power. Long-range space probes make use of a Stirling-cycle electric power generatorsfueled by the heat of radioisotope heat sources. Combined heat-and-power generators based on a Stirlingengine are commercially available in the 100 kW power range, and their miniature cousins may one dayreplace laptop and cell phone batteries.

The Stirling engine as a heat pump

The many advantages of the Stirling engines are well described in the excellent Wikipedia article (recom-mended reading), one of which is their flexibility: their ability to act as heat pumps as well as engines.

If one uses an external motor to drive the Stirling engine through its thermal cycle, the net effect isthe reverse conversion from mechanical energy into thermal one, heating up one end and cooling down theother end of the cylinder: following the pV -curve of Fig. 2.3 in the counterclockwise direction means achange of sign of the difference between the upper and lower halves of the cycle.

Even more interesting is the ability of the Stirling engine to reverse the direction of this heat flow, ifthe direction of rotation of the engine is reversed. Thus the same Stirling-cycle thermal pump can act asa heat source in winter and a cooling device in the summer!

Procedure

The Stirling Engine U10050 used in this experiment is a single-cyclinder demonstration model made ofglass and clear plastic so that the movement of the internal components can be easily seen. Typically, theStirling Engine is used as a heat engine; an alcohol flame is applied to the round end of the glass tubeicontaining the displacer piston and the engine uses some of this heat energy to perform mechanical work.If the engine is connected to a direct current (DC) generator, some of this mechanical energy is convertedto electrical energy. As a heat engine, the Stirling Engine will always turn in the same direction, followingthe heat cycle shown in Figure 2.3.

In this experiment, the Stirling engine is used as a heat pump, the opposite of a heat engine. A DCvoltage is applied to the electric motor that rotates the flywheel and moves the pistons. The electricalenergy is expended to transfer heat and thus to create a temperature difference between the two ends ofthe cylinder. The direction of the transfer of heat depends on the direction of rotation, and thus the engine


can heat as well as cool the round end of the glass tube, relative to the other end that has a large metalheat reservoir attached to it, which is in turn exchanging heat with the surrounding air.

The heat pump system consists of the following parts (please refer to Fig. 2.1 for Stirling engine parts):

1. a glass displacer piston that pumps air between the hot and cold sides of the engine. The pistonis enclosed by a glass tube with a brass socket at each end; these are the temperature monitoringpoints of the engine;

2. a brass working piston that compresses the gas or is pushed by the expanding gas, making theconversion between mechanical and heat energy;

3. a driveshaft with balancing cams and linkages that converts to rotary motion the reciprocating motionof the working piston and also drives the displacer piston;

4. a flywheel on the driveshaft that provides rotational inertia to couple different parts of the Stirlingcycle and to maintain a consistent rotational speed through the cyclical variations in the gas pressureinside the engine;

5. a direct current (DC) motor/generator that drives the engine flywheel by means of a rubber belt.

6. a DC power supply that is used to vary the rotations per minute (RPM) of the motor by varying theapplied voltage;

The operation of the engine is monitored with a variety of sensors. This data is sent to the PhysicaLabsoftware and is displayed as a pV (pressure-volume) diagram. The work done per cycle, engine RPM, andthe power output of the heat pump are also measured and reported by the software. Here is a summaryof the sensors:

• the absolute pressure p inside the engine is monitored with a pressure sensor that outputs a readingin Pascals. This sensor typically has a resolution better than 1% of the range of pressure experiencedby the engine;

• the temperatures T1 and T2 at each end of the displacer cylinder are measured in ◦C. These sensorsare currently not installed on the engine;

• the volume change V , in m3, is calculated from a series of markings on the flywheel of the enginethat determine the angle of rotation relative to a reference mark that represents the start of a pVcycle when the volume is at a maximum.

Part 1: Coefficient of performance

In this exercise you will estimate the coefficient of performance of the stirling engine heat pump. As theheat pump requires some time to reach a new operating equilibrium after a change in RPM is made, youshould pay close attention to the behaviour of the engine during this time. You should document how thework done per cycle and engine power values change during these transitional periods after a change inRPM is made; you should also note and explain any systematic changes in these variables as the engineRPM is increased from a manimum to the maximum. You will be required to discuss these issues as partof your discussion.

• Review and identify all the parts of the apparatus in front of you. Rotate the engine slowly byturning the flywheel clockwise abd then counterclockwise and note the relative movement of theworking piston to the displacer piston. The two pistons are offset by 90◦.

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• Connect the two wires between the DC electric motor and the power supply, red to red and black toblue. The voltage that is applied to the motor is adjusted by turning a knob and monitored on thecorresponding digital display in volts (V). The current flowing through the motor is shown on theother meter in Amperes (A). Be sure that the current limit knob is turned fully clockwise.

1. Check that the switch next to the motor is pointing downward, then turn on the power supply andincrease the voltage to around 5.5 V. The engine should start to rotate and the 7-segment displayshould show the current engine RPM. Lets define rotation as CW when the flywheel rotates clockwiseas viewed from the side with the markings; CCW defines a counter-clockwise rotation.

? In which direction is the heat pump turning?

2. Close any running PhysicaLab programs, then start a new session by clicking on the Desktop iconor by typing physicalab followed by the Enter key. Login with your email address; you will emailyourself all graphs for later inclusion in your lab report.

Click on the SE input to select the Stirling Engine interface. Press the Get data button to begingraphing pV cycles. In this mode, the data collection parameters are ignored; the graph updates ata rate that is determined by the speed of the engine.

3. To output a steady set of values, the Stirling engine needs some time to adjust thermally to the newoperating conditions. Capture a copy of the pV cycle at the start of this equilibration process by

pressing the Stop button to temporarily freeze the graph display, then click Send to: to email

yourself a copy of the graph.

4. Let the engine equilibrate for several minutes, until the RPM, work and power values appear steady,then record for each variable the maximum and minimum value that occurs over the course of 60seconds in order to determine a nominal error estimate ∆(X) = (Xmax − Xmin)/2 for the threequantities:

∆(RPM) = ...................... = ................... = ....................

∆(Pse) = ......................... = ................... = ....................

∆(W ) = ......................... = ................... = ....................

5. Email yourself a copy of the graph representing the pV cylce of an equilibrated Stirling engine.

? Are there any notable differences in these two graphs?

? Review the data set in order to match the data points to the oval display of the corresponding pVcycle. At which point of the oval does the pV cycle begin?

? For a given value of volume V , there are two corresponding pressure values p. Does the lower orhigher pressure value occur first during the cycle?

? Is the pV cycle being drawn in a clockwise or counter-clockwise direction? Is this what you expect?

? Feel the ends of the displacer cylinder, near the brass plugs. To which side is heat being pumped?

? Looking at Figure 2.2, is the engine following steps 1-2-3-4 or 4-3-2-1? Is this what you expect?


V (V) I (A) Pm (W) RPM W (J) Pse (W) COP

Table 2.1: Stirling heat pump data for Part 1

6. Record in Table 2.1 the motor voltage V and current I displayed on the power supply, then calculatethe electrical power Pm used by the motor to turn the heat pump. Estimate the errors in V and Ias ∆(V ) = 0.01 V and ∆(i) = 0.01 A.

7. Record from the pV graph the heat pump RPM and work done per heat pump rotation, then calculatethe power output Pse of the heat pump at the current RPM.

8. Determine the COP for the heat pump at the current RPM: COP = Pse/Pm.

9. Increase the voltage by 1 V and repeat the equilibration and data recording procedure up to a voltageof 12.5 V. When the table is complete, terminate the transmission of data but keep the engine running.

Be sure to allow enough time for the engine to settle to a thermal equlilbrium as determined fromthe previous estimate of this required settling time.

10. You will now plot a curve representing the coefficient of performance for the heat pump as a functionof RPM. Enter your values for COP and RPM in the data window, then select Scatter plot and

press Draw . Email yourself a copy of the graph.

? How does the COP vary with RPM? Is there a value of RPM where the COP seens to be a maximum?

Part 2: Heat Pump equilibration

The Stirling Engine should currently be in equilibrium at V = 12.5 V. You will now observe how the heatpump RPM, Work and Power converge to new values following a change in the voltage of the driving motorfrom 12.5 V to 5.5 V. To do this, you will record the elapsed time t, RPM , W and P every thirty secondsfor a period of fifteen minutes.

• Check that the clock at the bottom right corner of the Desktop is displaying time in seconds. If not,right click on the Clock, select Properties and set the Format to display seconds.

• Restart the graph update. Wait until the seconds advance to zero, the decrease the voltage to 5.5 Vand begin recording data in Table 2.2, as outlined above, until the table is filled.

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t (s) RPM W (J) Pse (W) t (s) RPM W (J) Pse (W) t (s) RPM W (J) Pse (W)

30 330 630

60 360 660

90 390 690

120 420 720

150 450 750

180 480 780

210 510 810

240 540 840

270 570 870

300 600 900

Table 2.2: Stirling heat pump parameter convergence data

• Turn off the power supply, then switch the two wires at the power supply. Turn power supply backon and set the voltage to 5.5 V as before. The heat pump should begin to rotate in the oppositedirection.

As you wait for the engine to equilibrate, graph as a function of time the three variables in Table 2.2.

? Looking at the convergence graphs, how long does it take for the Stirling engine to equilibrate?

? Is this time representative of the equilibration time required as you step through the 1 V changes inTable 2.1?

Part 3: Coefficient of performance, opposite direction

V (V) I (A) Pm (W) RPM W (J) Pse (W) COP

Table 2.3: Stirling heat pump data for Part 3, opposite direction


• Repeat the above steps and record your data in Table 2.3. Make notes of all the observations, as inthe previous section, to include in your lab report.

? Feel the ends of the displacer cylinder, near the brass plugs. To which side is heat being pumped?

? Does the lower or higher pressure value occur first during the cycle? Is the pV cycle being drawn ina clockwise or counter-clockwise direction? Is this what you expect?


Lab report


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Experiment 3

Refraction of light


• that the bending of light crossing the boundary of two different materials is given by Snell’s Law;

• that the dispersion of light is dependent on the wavelength of the emitted light;

• some basic concepts of potics such as refraction, reflection, dispersion, critical angle;



Prelab preparation








WEBWORK: the Prelab Refraction Test must be completed before the lab session☛✡


☛✡



18

19

Refraction

Figure 3.1: Geometry of refraction

The phenomenon of refraction can be explained ge-ometrically with the aid of Figure 3.1. A beam oflight incident on a boundary surface is composed ofwavefronts that are perpendicular to the directionof propagation of the beam. This beam will prop-agate more slowly through a dense medium than itdoes through air.

If the incident beam is not normal to the bound-ary surface, one edge of the wavefront will enter thedenser material first and be slowed down. This ef-fect will propagate across the wavefront, changingthe direction of the refracted beam relative to theincident beam.

This change in direction is always toward thenormal to the boundary surface when the lightbeam crosses into a denser medium. It will bethe opposite for a beam crossing into a less densemedium.

The mathematical relationship between the in-cident angle i and the refracted angle r of the lightbeam is given by Snell’s Law:

sin i

sin r=

nII

nI(3.1)

The angles i and r are measured from the nor-mal or perpendicular direction to the boundary.The numbers nI and nII are characteristic of eachmedium, and are called the refractive indices. For a vacuum n = 1, the refractive index of air is approxi-mately unity, and all other materials have n > 1.

The refractive index is also a function of the wavelength of the light, therefore light rays of differentcolour have different angles r for identical angles i. This effect, called the dispersion of light, is observedwhen a source of white light such as sunlight or a light bulb, crosses the boundary. Light from a source ofmonochromatic light such as a laser, consists of a single wavelength and therefore will not be dispersed.

Note that when a ray travels from a medium to a more dense medium (e.g. air to plastic), it alwaysrefracts towards the normal (r ≤ i). Conversely, when a ray travels from a medium to a less dense medium(e.g. plastic to air), it always refracts away from the normal (r ≥ i).

Part 1: Refraction into a denser medium

You will verify Snell’s Law using a semi-circular plastic prism as the second medium, as shown in Figure 3.2.Arrange the prism so that it is concentric with the paper protractor, with the flat surface lined up withthe 90◦ line so that the normal (0◦) is perpendicular to the flat face of the prism.

Since the incident beam of light has a finite width, the same edge of the beam should be used to setthe incident angle i and to measure the refracted angle r. Make sure that this edge of the beam passesthrough the centre point of the protractor, otherwise your angle measurements will be incorrect.

? Does the refracted beam display any notable dispersion? Which color of light is refracted the most?Which is refracted the least?

20 EXPERIMENT 3. REFRACTION OF LIGHT

• Vary the incident angles i by rotating the prism/protractor combination, in 10◦ increments from 0◦

to 80◦, and measure the corresponding refracted angle r values. Enter your results in Table 3.1.

? What is the resolution of the protractor scale? How well can you estimate a value for an angle withthis scale? Did you express the above measurements to this precision?

• Calculate the values of sin i for the incident angles i and sin r for the refracted angles r. Enter theresults in Table 3.1.

Figure 3.2: Refraction into a denser medium

Equation 3.1 can be rearranged to give sin i =(nII/nI) sin r. This is the equation of a line withslope (nII/nI). Since in our case the incidentmedium is air, with index of refraction nI ≈ 1, aplot of sin i as a function of sin r will yield a line ofslope nII .

• Close any running Physicalab windows, thenstart a new session by clicking on the Desktopicon and login with your Brock student ID.You will email yourself all the graphs for laterinclusion in your lab report.

• Enter the pairs of values (sin r, sin i) in thePhysicalab data window. Select scatter

plot. Click Draw to generate a graph ofyour data. The displayed data should approx-imate a straight line.

• Select fit to: y= and enter A*x+B in the fitting equation box. Click Draw to fit a straight lineto your data. Label the axes and title the graph with your name and a description of the data being

graphed. Click Send to: to save a copy of the graph.

• Record the values for the slope and the standard deviation of the slope obtained from the graph.

nII = ....................± ....................

i◦ 0 10 20 30 40 50 60 70 80

r◦

sin i

sin r

Table 3.1: Exprimental results for Part 1

21

Part 2: Refraction from a denser medium

? The refractive index n for the plastic was determined in Part 1 using light travelling from air toplastic. Should n for the plastic prism the same if it is measured using a light ray passing fromplastic to air? On what line of reasoning do you base your conclusion?

• To test your hypothesis, place the light source on the opposite side of the prism, as shown in Figure 3.3.Aim the beam of light so that it passes through the curved prism face (surface B).

Make sure that you use the side of the beam that is closer to the normal as your reference edgeand that this edge goes through the centre point of the protractor. The angle of incidence i is nowmeasured inside the prism while angle r is outside.

• Vary the angle i of the incident beam in 5◦ increments from 0◦ to 40◦ and measure the correspondingvalues of r.

• Calculate the values of sin i for the incident angles i and sin r for the refracted angles r. Enter yourresults in Table 3.

Figure 3.3: Refraction from a denser medium

Remember that now the index of the refractedbeam nII is that of air, hence NII ≈ 1. With thisin mind, we can conclude that the calculated valueof the slope from the graph will be the inverse ofthe refractive index nI of the incident medium.

• Use the Physicalab software to graph thepairs of values (sin r, sin i).

• Summarize below the values for the slope andthe standard deviation of the slope displayedin the fitting parameter window, and fromthese determine a value and error for the in-dex of refraction of the prism nI .

slope = .............± .............

nI = .................. = .................. = ..................

∆(nI) = .................. = .................. = ..................

nI = ..................± ..................


i◦ 0 5 10 15 20 25 30 35 40

r◦

sin i

sin r

Table 3.2: Exprimental results for Part 2

Part 3: Critical angle for total internal reflection

Figure 3.4: Critical angle setup for Part 3

For light incident on a boundary from a densermedium, Snell’s Law indicates that there is a cer-tain angle of incidence i for which the reflected an-gle will be r = 90◦. This angle of incidence is knownas the critical angle θc. If i > θc, there will be norefracted beam and the incident ray will exhibit atotal internal reflection from the boundary, into thedenser medium. For this special case, Snell’s Lawmay be written as:

n =1

sin θc. (3.2)

Using the experimental setup of Part 2:

• Observe the refracted beam and adjust theangle i of the incident beam to set the angle ofrefraction r at 90◦so that the refracted beamdisappears as in Figure 3.4.

? How well were you able to estimate a critical angle measurement?

• Repeat this measurement of θc several times to fill Table 3.3.

? What is the point of repeating the same measurement so many times?

trial 1 2 3 4 5 6 7 8 9 〈θ〉c σ(θc)

θc

Table 3.3: Critical angle results for Part 3

• Close any open Physicalab windows, then start a new Physicalab session by clicking on the desktopicon and login with your Brock student ID. You will be emailing yourself all the graphs that youcreate for later inclusion in your lab report.

23

• In Physicalab, click File, New to clear the data entry window, then enter in a column the criticalangle values. Click Options, Insert X index to insert a column of indices to yout data points.

Select bellcurve, click bargraph then Draw to view the distribution of your data. Click Send to:to email yourself a copy of the graph.

• Physicalab has calculated the average 〈θ〉c and standard deviation σ(θc) of your data set and thesevalues are shown in the graph window as 〈θ〉c ± σ(θc). Enter these two values in the 〈θ〉c and σ(θc)columns of Table 3.3.

• From these results converted to radians, calculate a value of n for the prism from Equation 3.2 andthe error ∆(n) using the appropriate error propagation relation, then report properly rounded finalresults for θc and n:

n = .................. = .................. = ..................

∆(n) = .................. = .................. = ..................

θc = ...............± ...............

n = ...............± ...............

Part 4: Minimum angle of deviation

Figure 3.5: Angle of deviation, Part 4

For this part of the experiment you will use theequilateral triangle prism. Let a ray be incident onthe entrance face of the prism at an angle φ1, as inFigure 3.5. It will leave the prism at the exit facewith an angle φ2. We define the deviation angle δas the total change in light direction, as shown inFigure 3.5.

The angle δ is given by a complicated relation-ship between φ1, the index n, and the apex angleα of the prism. If we define δm as the value of theangle δ when φ1 = φ2 = φ, the angle δm and therefractive index of the prism are given by:

δm = 2φ− α, (3.3)

n =sin(12α+ 1

2δm)

sin(12α). (3.4)

It can be shown that if φ1 = φ2, then δm is the minimum value of the angle δ for all values of δ. Hence,δm is called the minimum angle of deviation.

• Set up the prism and light source as shown in Figure 3.5, and use the two protractors to measure φ1

and φ2. Move the source around until you have φ1 and φ2 equal within 0.5◦. Make sure that bothbeams are lined up properly and that they are going through the origin of each protractor. Enterthis result in Table 3.4,


• Repeat the previous step, starting each time with a disturbed alignment of the prism, until the datatable is full.

trial 1 2 3 4 5 6 7 8 9 〈φ〉 σ(φ)

φ

Table 3.4: Minimum angle of deviation results for Part 4

• Enter your data set into Physicalab as was done in Part 3, then record the values for 〈φ〉 and σ(φ)in the appropriate columns of Table 3.4. Save a copy of the graph.

• Use Equation 3.3 to calculate a value and error for the minimum angle of deviation δm.

? The apex angle of the prism is α±∆(α) = 60.0 ± 0.3◦. Does this value seem reasonable? Why?

δm = .................. = .................. = ..................

∆(δm) = .................. = .................. = ..................

• Use Equation 3.4 to calculate the index of refraction n and the error ∆(n) of the prism, expressingall angles in radians, then report properly rounded final values for the minimum angle of deviationφ and the corresponding index n:

n =sin(12α+ 1

2δm)

sin(12α)= .......................= ...........................

∆(n) = n

(

cos(α)∆α

sin(α)

)2

+

cos(

(α+δ)2

)√∆α2 +∆δ2

2 sin(

(α+δ)2

)

2

0.5

= ...............................= ...................................

φ = ...............± ...............

n = ...............± ...............


25

Lab report


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Experiment 4

Archimedes’ principle


• the basic physical concepts of buoyancy, density, specific gravity;

• that the specific gravity of materials can be used to determine the composition of an alloy;

• that an object displaces an equal volume of liquid in which it is submerged;



Prelab preparation








WEBWORK: the Prelab Archimedes Test must be completed before the lab session☛✡


☛✡



26

27

Archimedes’ principle

Everybody knows the story’s punch line: a man is so excited by the idea that came to him in a bathtubthat he runs naked to the Emperor’s palace, screaming “Eureka!” But what exactly was the idea thatmade Archimedes forget the dress code? Survey your friends who are not taking this Physics course, andmost are likely to respond with some description of buoyancy : a body immersed in a fluid experiences abuoyant force equal to the weight of the displaced fluid.

That’s important enough, and Archimedes did author a very concise formulation of the buoyancyprinciple. However, boats floated long before Archimedes came along. Why would a better formulation ofan old idea excite the respected philosopher so?

The true story of “Eureka!” is somewhat more subtle. Archimedes figured out a way to use the buoyantforce to solve a very important practical problem of catching the crooks who were defrauding the treasuryby passing a gold-silver alloy coins as pure gold ones. Before you continue reading the next paragraph,spend a few minutes trying to think of a solution to this challenge. It’s not an easy one!

Archimedes’ solution (which brought him both the satisfaction of resolving a intellectual challenge anda considerable monetary reward) could be implemented quickly and easily and required only the simplestof tools: a balance scale, weights made of pure silver and pure gold, and a tub of water.

First, you had to use the weights made of gold balance out the unknown material. Then you wouldsubmerge both sides of the balance in water. If the two arms remained balanced, then the unknownmaterial was also gold since the same mass of the material displaced the same volume of water on bothsides and thus both sides experienced the same buoyant force equal to the weight of that water.

If, however, the material was not really gold, its density was slightly different from that of the puregold, and the same mass would displace a different volume of water. The buoyant force would be slightlydifferent on the two sides of the balance scale, and the submerged balance would tilt.

In fact, by replacing the pure gold weights with a mix of gold and silver weights and adjusting theirratio until the balance scale remained level in and out of water, one could measure the exact make-up ofthe alloy — and to catch the crooks!

In this experiment you will determine the unknown ratio of copper (Cu) to aluminum (Al) in a simulated“alloy” of the two metals, resolving essentially the same conundrum.

With the density of the material defined as the ratio of its mass m to its volume V , ρ = m/V (inkg/m3), and the so-called specific gravity of the material being the dimensionless ratio of the density ofthe material to that of water,

Sx =ρx

ρH2O,

it is easy to see that a convenient practical way to measure the specific gravity, which is an importantidentifying characteristic of a material, is as a ratio

Sx =weight of object in air

apparent weight loss when submerged in water(4.1)

The equation for the density of an alloy follows from the definition of ρ and is simply the ratio of thesum of the masses and the volumes of the alloy components. For an alloy of Al and Cu,

ρalloy =mAl +mCu

VAl + VCu

. (4.2)

Equation 4.2 can be re-arranged to compare a theoretical result, the mass ratio of the two metals, to thatobtained from the experimentally determined specific gravities of the various materials:

mAl

mCu

= −1− Salloy/SCu

1− Salloy/SAl

. (4.3)

28 EXPERIMENT 4. ARCHIMEDES’ PRINCIPLE

Procedure

The experimental apparatus consists of a precise digital weight scale, a volumetric flask, a pipette, distilledwater, a long bar of Cu, a long bar of Al, and a simulated Al/Cu “alloy” made up of two short bars of Aland a Cu.

For each of the three metals (Al, Cu and the Al/Cu “alloy”) you will need to perform three separatemeasurements, as summarized in Fig. 4.1:

Figure 4.1: The three steps must be repeated for each metal

(a) weight wa of the piece of metal;

(b) weight wb of the piece of metal and of the volumetric task filled with distilled water to the exactmark on the neck of the flask;

(c) weight wc of the piece of metal submerged in the volumetric task filled with distilled water to theexact same mark.

You will need to withdraw some water from the volumetric flask between steps (b) and (c). This is bestachieved by simply pouring off some water and then adding the required amount back, drop-by-drop fromthe pipette when the level gets close to the target mark.

These weight measurements rely heavily on your experimental technique. To avoid introducing errors,be careful not to have any stray water droplets on the piece of metal, on the body of the flask or on thescale platform itself. To get a feeling for how these experimental errors affect your results, you will repeatsteps (a)–(c) several times and perform a statistical analysis of the data to determine the sample average〈w〉 and the standard deviation σ(w) that is a measure of how closely your data is distributed around 〈w〉.

Part 1: Aluminum bar

? A major source of random error in this experiment is the precision with which you can reproduce theexact same water level time after time. How much does the water level rise after a drop is added?

• Starting with the Aluminum bar, fill in Table 4. Proceed column by column.

• Close any open Physicalab windows, then start a new Physicalab session by clicking on the desktopicon and login with your Brock student ID. You will be emailing yourself all the graphs that youcreate for later inclusion in your lab report.

29

Al 1 2 3 4 5 6 7 8 9 〈w〉 σ(w)

Metal bar, wa

Metal & flask, wb

Metal in flask, wc

Table 4.1: Experimental data for Aluminum bar

• In Physicalab, click File, New to clear the data entry window, then enter in a column the data pointsfrom step (a) for the Aluminum metal bar. Click Options, Insert X index to insert a column of

indices to yout data points, then select scatter plot and click Draw to view the variation in yourdata.

• Select bellcurve and click bargraph to view the distribution of your data. Physicalab has calculatedthe average 〈w〉 and standard deviation σ(w) of your data set and these values are shown in the graphwindow as 〈w〉 ± σ(w). Enter these two values in the 〈w〉 and σ(w) columns of Table 4.

• Repeat the above steps for the Metal & flask data set and the Metal in flask data set.

• You can now determine the specific gravity SAl of Aluminum with the aid of Equation 4.1 and yourresults from Table 4:

SAl = ..................... = ..................... = .....................

∆(SAl) = ..................... = ..................... = .....................

Part 2: Copper bar

• Proceed to acquire data and fill in Table 4 for the Copper bar.

Cu 1 2 3 4 5 6 7 8 9 〈w〉 σ(w)

Metal bar, wa

Metal & flask, wb

Metal in flask, wc

Table 4.2: Experimental data for Copper bar

SCu = ..................... = ..................... = .....................

∆(SCu) = ..................... = ..................... = .....................

30 EXPERIMENT 4. ARCHIMEDES’ PRINCIPLE

Part 3: Alloy bar

• Complete Table 4 for the Al/Cu alloy bar composed of the two short Al, Cu bars.

Alloy 1 2 3 4 5 6 7 8 9 〈w〉 σ(w)

Metal bar, wa

Metal & flask, wb

Metal in flask, wc

Table 4.3: Experimental data for Al/Cu alloy bar

Salloy = ..................... = ..................... = .....................

∆(Salloy) = ..................... = ..................... = .....................

Part 4: Results

• Measure the weight mAl of the short bar of Aluminum and the weight mCu of the short bar of Copperthat make up the alloy bar. Include the error in these measurements. These are the theoretical valuesthat will be used to compare to your experimental results based on the previously calculated specificgravities of the various materials.

mAl = ...............± ............... mCu = ...............± ...............

• From these measurements, determine the theoretical mass ratio of your “alloy” and the magnitudeof uncertainty, or error, in this result:

mAl

mCu

= ..................... = ..................... = .....................

∆

(

mAl

mCu

)

= ..................... = ..................... = .....................

• Use Equation 4.3 to calculate the experimental mass ratio and the associated error for your “alloy”:

mAl

mCu

= ..................... = ..................... = .....................

∆

(

mAl

mCu

)

= ..................... = ..................... = .....................


31

Lab report


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Experiment 5

Viscosity and drag


• that the motion of an object through a fluid is governed by a complex set of parameters;

• that the Reynolds number R and drag coefficient Cd are central to the physics of fluid dynamics;

• to determine the drag coefficient of a sphere by performing a computer analysis of the velocity curve;

• to visualize data in different ways in order to improve the understanding of a physical system;


Prelab preparation








WEBWORK: the Prelab Viscosity Test must be completed before the lab session☛✡


☛✡



32

33

Viscosity and drag

Drag force arises when an object moves through a fluid or, equivalently, when fluid flows past an object.In general, the drag force grows larger with increased flow velocity, but viscosity is a complex phenomenonthat cannot be reduced to the simple relationship “drag force is proportional to velocity”.

The origin of the drag force Fd lies in the need to displace the particles of the fluid out of the wayof a moving object. At low velocities the movement of the fluid is smooth (laminar) and the faster theobject moves, the greater is the amount of fluid that has to get out of the way, giving rise to the linearrelationship

F(viscous)d = aηv

where v is the velocity of the object relative to the fluid, η is the coefficient of viscosity , and a is the “size”of the object; for a sphere of radius r, a = 6πr. The larger the size, the greater is the amount of fluid thatneeds to get out of the way, hence it is not surprising that the relationship is linear with respect to a aswell.

The story gets far more complicated for higher velocities, unusual object shapes, of unusual fluids. Athigher velocities or around oddly-shaped objects the flow stops being smooth and turns turbulent , whichrequires more energy and causes the drag force to switch to the quadratic regime, where Fd ∝ v2,

F(inertial)d = S

ρ0v2

2.

Note that this expression represents an inertial rather than a viscous force, and instead of the the viscosity,η, the fluid density, ρ0, enters the formula. S is the cross-sectional area of the moving object.

An empirical parameter called the Reynolds number determines which of the above two terms domi-nates:

R =dρv

η

where for a simple sphere, the diameter d(= 2r) is the obvious definition of the “size” of the particle1. ForR < 1, the viscous drag dominates (and thus there is no inertial coasting), while for R > 1000 the viscousdrag is completely negligible as compared to the inertial drag.

At higher velocities still, in compressible fluids one needs to account for the compression waves that getcreated (e.g. the sonic boom of a supersonic aircraft), and in incompressible fluids the surface layer of thefluid may lose contact with the rapidly moving object creating local vacuum (e.g. cavitation on the surfaceof the blades of naval propellers). Unusual fluids such as solutions of long polymers may experience flow indirections other than the direction of motion, as the entangled polymer molecules transmit the movementof the object to remote areas of the fluid and back. The fluid constrained into finite-size channels and tubesalso behaves differently from an infinitely-broad medium through which a small-size sphere is traveling.There are corrections that must account for all of these details.

A convenient way to express just such a correction is through an empirical factor called “the coefficientof drag”, Cd, which can be measured experimentally and account for the details of shape, size, and thenature of the media through which an object is traveling. This dimensionless coefficient is well-known andits tabulated values can be found in handbooks. As a function of the Reynolds number, the experimentallymeasured values of the drag coefficient, Cd, constitute the so-called “standard drag curve” shown in Fig. 5.1.For a small sphere traveling through an infinitely broad fluid, this Cd provides an excellent agreement withthe experimental drag force:

Fd = Kf Cd Sρ0v

2

2, Cd = Cd(R) (5.1)

The finite-size correction coefficient, Kf , describes how this equation is modified by the boundary conditionsof a fluid confined in a finite-size vessel. For a sphere of diameter d traveling axially through a fluid channel

1For other shapes, an equivalent “hydrodynamic radius” rh is used instead of r

34 EXPERIMENT 5. VISCOSITY AND DRAG

Figure 5.1: Drag coefficient on a sphere in an infinite fluid, as a function of the Reynolds number

(a pipe) of diameter D, a dimensionless ratio x = d/D can be used to approximate this correction coefficientto within 6% via2

Kf =1

1− αxα, α = 1.60 for x ≤ 0.6 , (5.2)

in the range of Reynolds number values of 102 < R < 105.For an object at rest, there is no drag force. As we apply a force to an object, it experiences an

acceleration, its velocity grows, and with it grows the drag force that is directed opposite the velocity. Thisdrag force counteracts the applied force and reduces the net force and the object’s acceleration. Eventually,velocity increases to the point where the drag force is exactly matched to the applied force, bringing thenet force to zero. From this point on, the object is in equilibrium, there is no acceleration, and the velocityremains constant, equal to its steady-state value called the terminal velocity , or vt. For example, if anobject is in a free fall through a fluid, this equilibrium condition corresponds to the weight of the objectexactly equal to the drag force:

Fd = W .

When the fluid in question is a gas such as air, the buoyant force Fb — equal to the weight of the displacedgas — is tiny and can be neglected. When the fluid is a more dense substance such as water, the aboveequation may need to be modified to include the buouyant correction due to the displacement of the fluidby the object

Fd = W − Fb = mobjectg −mfluidg = mobjectg(1 − ρ0/ρ) (5.3)

where ρ is the density of the material of the object and ρ0 is the density of the fluid. As you can see,only the ratio of the two densities enters into the expression since the volumes of the object and of thefluid it displaces are the same. For example, for an Al sphere in water, ρ0 = 1.00 × 103 kg/m3 andρ = 2.70 × 103 kg/m3.

2R.Clift, J.R.Grace, and M.E.Weber. Bubbles, Drops, and Particles, p.226. Academic Press, 1978

35

Apparatus

The experimental apparatus consists of two different-size metal spheres, a long cylindrical container filledwith water, a pulley system with a weight platform and variable weights, an ultrasonic position sensor, adigital weight scale, a micrometer.

From the free-body diagram of Fig.5.2, drawn for the case of the sphere traveling downward as appro-priate for the small pull mass of the counterweight, when v = vt = const,

+T −Wcounterweight −Wplatform = 0,

Fd + Fb +Wcounterweight +Wplatform −Wsphere = 0 .

Figure 5.2: Drag force measurement apparatus

Denoting the pull mass of the counter-weight as m, the mass of the weight plat-form as mp, the mass of the sphere as ms,and using the expressions of Eqs. 5.1 and5.3 we obtain

Kf Cd Sρ0v

2t

2= msg

(

1− ρ0ρ

)

−mpg−mg

Dividing through by g we obtain

m = m0 −KfCdSρ0

2gv2t , (5.4)

where m0 = ms(1− ρ0/ρ)−mp.

Procedure

In this experiment you will evaluate the drag coefficient for two different spheres using the setup in Fig.5.2.

• Using a digital scale, weigh separately both spheres and the weight platform. As you weigh differentweights from the weight set, you may notice small differences in the measured weight of weights thathave the same nominal value.

Wsmall = ..............± ............. Wlarge = ..............± .............

Wplatform = ..............± ............. W“1 g” = ..............± .............

W“2 g” = ..............± ............. W“2 g” = ..............± .............

W“5 g” = ..............± ............. W“5 g” = ..............± .............

W“10 g” = ..............± ............. W“10 g” = ..............± .............


W“20 g” = ..............± ............. W“20 g” = ..............± .............

? Is the variation in the measured weight between weights of the same nominal value significant? Howdoes it compare with the precision of the measuring instrument, the digital scale?

• Use a Vernier caliper or a micrometer to measure the diameter d of the two spheres:

dsmall = ..............± ............. dlarge = ..............± .............

? Are these two spheres ”spherical” within the limits of your measuring instrument? How would youcheck this experimentally?

• Measure and record the inner diameter D of the plastic cylinder filled with water. Verify that thecross-section is circular by measuring the diameter in a few different directions across the cylinder.

D = .............± .............

Part 1: Determination of Cd for the small sphere

• Select the small sphere, adjust the length of the string so that the weight platform is at around 30 cmabove the ultrasonic detector at its lowest position, and a few cm below the pulley at its highestposition (i.e. when the sphere hits the bottom of the cylinder).

• Determine the range of masses from m1 to m2, in 1g resolution, for which the sphere does not moveand hence v = 0. This result is related to the drag of the pulley system, typically spanning a fewgrams. Enter these two results (m5, 0) and (m6, 0) in Table 5.1.

To complete Table 5.1, start with a value of m1 = 0 and increase m to get four reasonably spaced datapoints in each direction of motion about the region where v = 0. Note that the sign of the terminal velocitydiffers depending on the direction of travel.

trial, i 1 2 3 4 5 6 7 8 9 10

mi, pull mass

vt,i, small sphere 0 0

Table 5.1: Terminal velocity data for small sphere

? You may have noticed that there are small differences in the measured weight of weights that havethe same nominal value. Do you need a precise value for the pull mass m? Do you need an estimatefor ∆(m), the uncertainty in the value of the pull mass?

• Close any open Physicalab windows, then start a new session by clicking on the Desktop icon. Loginwith your Brock email address. Your graphs are sent there for later inclusion in your online labreport. In Physicalab, check the Dig1 input channel to select the rangefinder as the data source,choose to collect 50 points at 0.025 s per point, then select scatter plot.

37

• Place a mass m on the platform and move the sphere to the starting point of the travel regime. Pressthe Get data button, then release the string to record a trace of the sphere position in the tube asa function of time.

Your graph should display a upwardly curved region when the sphere is accelerating, followed by alinear region of constant slope near the end of the motion when the sphere is moving at a constantspeed. The trajectory ends with a roughly horizontal line that represents the motion of the ball afterit is suddenly stopped when it reaches an end of the tube.

• If the sphere flutters or wanders erratically as it moves along the tube, repeat the run. Do not includeany trials where the sphere fails to reach terminal velocity; repeat the trial using a different pull mass.

Note that the sign of the slope, and thus of the terminal velocity vt that you record, changes as thesphere switches directions of travel.

• Click Send to: to email yourself a copy of the graph. You should save a copy of all the trials forlater analysis, but you only need to include one sample graph in your report.

• For each trial, identify the region of terminal velocity from x = Xmin to x = Xmax at the end of thesphere trajectory where the position-time graph is a straight line. A series of 8-10 points is sufficient,if properly chosen.

? Did you select only the region of your graph just before the end of the trajectory where the datashould be changing at a constant rate and thus fit to a straight line?

• Use A*(x-B)*(x>Xmin)*(x<Xmax) to fit a straight line segment to your data in the limited rangeXmin<x<Xmax. To get a correct error value, you must also enter (x>Xmin)*(x<Xmax) in the con-straint box.

? How well was the fitted straight line segment placed over your data points? What would cause amismatch between our data and the fitted line segment?

• If the fitted line segment did not overlap the data points completely, redo the fit using more appro-priate limits. Following a good result, record the terminal velocity vt as a function of m in Table 5.1.

• Enter the values of (vt,m) for the small sphere into Physicalab and click Draw to make a scatterplot of the data set. The relationship between m and vt is given by Equation 5.4. Fit your data tothe equivalent quadratic expression, A+B*sign(x*x,x), where the function sign() here accounts fora change in the direction of the drag force as vt changes sign. Save a properly labelled graph of yourresulting fit of the small sphere data.

? How does your fit look, especially in the region where vt = 0? How might you explain this mismatchbetween the velocity data and the fitting equation?

• As you previously noted, there is a region over several grams of mass where v = 0. To accountfor the effect of this drag on the system, repeat the previous fit, and use the following equation:(A+B*x**2)*(x<0)+((A-C)-B*x**2)*(x>0) with constraint ((x<0)+(x>0). The added fit param-eter C compensates for the offset in the data set at v = 0 and hence this value represents theapproximate drag of the pulley system. Save the graph and record the fit parameters below:

A = ..........± .......... B = ..........± .......... C = ..........± ..........

• Determine values for the cross-sectional area S, the sphere to pipe diameter ratio x, the finite-sizecorrection coefficient Kf and their associated errors ∆(S),∆(x) and ∆(Kf ):


S = ...................... = ....................... = .......................

∆(S) = ...................... = ....................... = .......................

x = ...................... = ....................... = .......................

∆(x) = ...................... = ....................... = .......................

Kf = ...................... = ....................... = .......................

∆(Kf ) =α2xα−1∆x

(1− αxα)2= ...................... = .......................

• Extract from Equation 5.4 the term corresponding to the fit parameter B, then rearrange this termto solve for Cd and finally calculate a value for the drag coefficient Cd and error ∆(Cd) for the smallsphere:

B = ......................

Cd = ...................... = ....................... = .......................

∆(Cd) = ...................... = ....................... = .......................

Part 2: Determination of Cd for the large sphere

trial, i 1 2 3 4 5 6 7 8 9 10

mi, pull mass

vt,i, large sphere 0 0

Table 5.2: Terminal velocity data for large sphere

• Repeat the procedure of Part 1, using the large sphere. Save all the graphs, then summarize the fitresults from your graph that included the drag term C,

A = ..........± .......... B = ..........± .......... C = ..........± ..........

39

S = ...................... = ....................... = .......................

∆(S) = ...................... = ....................... = .......................

x = ...................... = ....................... = .......................

∆(x) = ...................... = ....................... = .......................

Kf = ...................... = ....................... = .......................

∆(Kf ) = ...................... = ....................... = .......................

Cd = ...................... = ....................... = .......................

∆(Cd) = ...................... = ....................... = .......................

Part 3: Summary of results

• Summarize in Table 5.3 the correctly rounded results from Parts 1 and 2: with the correct units:

Table 5.3: Drag coefficient results

small sphere large sphere

S ±∆S

x±∆x

KF ±∆Kf

Cd ±∆Cd

C±∆C

• Finally, calculate an average value for the drag coefficient Cd and the pulley drag given by the fitparameter C:

〈Cd〉 = ...................= ...................= ...................

〈C〉 = ...................= ...................= ...................



Lab report


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Appendix A

Review of math basics

Fractions

a

c+

b

d=

ad+ bc

cd; If

a

c=

b

d, then ad = cb and

ad

bc= 1.

Quadratic equations

Squaring a binomial: (a+ b)2 = a2 + 2ab+ b2

Difference of squares: a2 − b2 = (a+ b)(a− b)

The two roots of a quadratic equation ax2 + bx+ c = 0 are given by x =−b±

√b2 − 4ac

2a.

Exponentiation

(ax)(ay) = a(x+y) ,ax

ay= ax−y , a1/x = x

√a , a−x =

1

ax, (ax)y = a(xy)

Logarithms

Given that ax = N , then the logarithm to the base a of a number N is given by logaN = x.For the decimal number system where the base of 10 applies, log10 N ≡ logN and

log 1 = 0 (100 = 1)

log 10 = 1 (101 = 10)

log 1000 = 3 (103 = 1000)

Addition and subtraction of logarithms

Given a and b where a, b > 0: The log of the product of two numbers is equal to the sum of the individuallogarithms, and the log of the quotient of two numbers is equal to the difference between the individuallogarithms .

log(ab) = log a+ log b

log

(

a

b

)

= log a− log b

The following relation holds true for all logarithms:

log an = n log a

42

43

Natural logarithms

It is not necessary to use a whole number for the logarithmic base. A system based on “e” is often used.Logarithms using this base loge are written as “ln”, pronounced “lawn”, and are referred to as natural

logarithms. This particular base is used because many natural processes are readily expressed as functionsof natural logarithms, i.e. as powers of e. The number e is the sum of the infinite series (with 0! ≡ 1):

e =∞∑

n=0

1

n!=

1

0!+

1

1!+

1

2!+

1

3!+ · · · = 2.71828 . . .

Trigonometry

Pythagoras’ Theorem states that for a right-angled triangle c2 = a2 + b2.Defining a trigonometric identity as the ratio of two sides of the triangle,there will be six possible combinations:

sin θ =b

ccos θ =

a

ctan θ =

b

a=

sin θ

cos θ

csc θ =c

bsec θ =

c

acot θ =

a

b=

cos θ

sin θ

sin(θ ± φ) = sin θ cosφ± cos θ sinφ sin 2θ = 2 sin θ cos θ 180◦ = π radians = 3.15159 . . .

cos(θ ± φ) = cos θ cosφ∓ sin θ sinφ cos 2θ = 1− 2 sin2 θ 1 radian = 57.296 . . .◦

tan(θ ± φ) =tan θ ± tanφ

1∓ tan θ tan φtan 2θ =

2 tan θ

1− tan2 θsin2 θ + cos2 θ = 1

To determine what angle a ratio of sides represents, calculate the inverse of the trig identity:

if sin θ =b

c, then θ = arcsin

(

b

c

)

For any triangle with angles A,B,C respectively opposite the sides a, b, c:

a

sinA=

b

sinB=

c

sinC, (sine law) c2 = a2 + b2 − 2ac cosC. (cosine law)

The sinusoidal waveform

Consider the radius vector that describes the circumference of a circle, as shown in Figure A.1 If we increaseθ at a constant rate from 0 to 2π radians and plot the magnitude of the line segment b = c sin θ as afunction of θ, a sine wave of amplitude c and period of 2π radians is generated.

Relative to some arbitrary coordinate system, in this case the X-Y axis shown, the origin of this sinewave is located at a offset distance y0 from the horizontal axis and at a phase angle of θ0 from the verticalaxis.

The sine wave referenced from this (θ, y) coordinate system is given by the equation

y = y0 + c sin(θ + θ0)

44 APPENDIX A. REVIEW OF MATH BASICS

Figure A.1: Projection of a circular motion to an X-Y plane to generate a sine wave

Appendix B

Error propagation rules

• The Absolute Error of a quantity Z is given by ∆Z, always ≥ 0.

• The Relative Error of a quantity Z is given by ∆ZZ , always ≥ 0.

• If a constant k has no error associated with it: constant factors out of relative error

Z = kA ∆Z = k∆A and∆Z

Z=

∆A

A

• Addition and subtraction: note that error terms always add

Z = kA±B ± . . . ∆(Z) =√

(k∆A)2 + (∆B)2 + . . .

• Multiplication and division: constants factor out of relative errors

Z =kA×B × . . .

C ×D × . . .

∆Z

Z=

√

(

∆A

A

)2

+

(

∆B

B

)2

+

(

∆C

C

)2

+

(

∆D

D

)2

. . .

• Functions of one variable: if the quantity A is measured with uncertainty ∆A and is then used tocompute F (A), then the uncertainty ∆F in the value of F (A) is given by

∆F =

(

dF

dA

)

∆A

Function F (A) Derivative, dFdA

Error equation

An nAn−1 ∆FF = n∆A

A

logeA A−1 ∆F = ∆AA

exp(A) exp(A) ∆FF = ∆A

sin(A) cos(A) ∆F = cos(A)∆A

cos(A) − sin(A) ∆F = − sin(A)∆A

tan(A) sec(A)2 ∆F = sec(A)2∆A

All trigonometric functions and the errors in the angle variables are evaluated in radians

45

46 APPENDIX B. ERROR PROPAGATION RULES

How to derive an error equation

Let’s use the change of variable method to determine the error equation for the following expression:

y =M

m

√

0.5 kx (1− sin θ) (B.1)

• Begin by rewriting Equation B.1 as a product of terms:

y = M ∗ m−1 ∗ [ 0.5 ∗ k ∗ x ∗ (1− sin θ)] 1/2 (B.2)

= M ∗ m−1 ∗ 0.51/2 ∗ k1/2 ∗ x1/2 ∗ (1− sin θ)1/2 (B.3)

• Assign to each term in Equation B.3 a new variable name A,B,C, . . . , then express v in terms ofthese new variables,

y = A ∗ B ∗ C ∗ D ∗ E ∗ F (B.4)

• With ∆(y) representing the error or uncertainty in the magnitude of y, the error expression for y iseasily obtained by applying Rule 4 to the product of terms Equation B.4:

∆(y)

y=

√

(

∆(A)

A

)2

+

(

∆(B)

B

)2

+

(

∆(C)

C

)2

+

(

∆(D)

D

)2

+

(

∆(E)

E

)2

+

(

∆(F )

F

)2

(B.5)

• Select from the table of error rules an appropriate error expression for each of these new variables asshown below. Note that F requires further simplification since there are two terms under the squareroot, so we equate these to a variable G:

A = M , ∆(A) = ∆(M)

B = m−1,∆(B)B = −1

∆(m)m = −∆(m)

m

C = 0.51/2,∆(C)C = 1

2∆(0.5)|0.5| = 0

D = k1/2,∆(D)D = 1

2∆(k)k =

∆(k)2k

E = x1/2,∆(E)E = 1

2∆(x)x =

∆(x)2x

F = G1/2,∆(F )F = 1

2∆(G)G =

∆(G)2G

G = 1− sin θ, ∆(G) =√

(∆(1))2 + (∆(sin θ))2 = cos θ∆θ

• Finally, replace the error terms into the original error Equation B.5, simplify and solve for ∆(y) bymultiplying both sides of the equation with y:

∆(y) = y

√

(

∆M

M

)2

+

(

∆m

m

)2

+

(

∆k

2k

)2

+

(

∆x

2x

)2

+

(

cos θ∆θ

2− 2 sin θ

)2

(B.6)

Appendix C

Graphing techniques

Figure C.1: Proper scaling of axes

Figure C.2: Improper scaling of axes

A mathematical function y = f(x) describes the one to onerelationship between the value of an independent variable xand a dependent variable y. During an experiment, we analysesome relationship between two quantities by performing a se-ries of measurements. To perform a measurement, we set somequantity x to a chosen value and measure the correspondingvalue of the quantity y. A measurement is thus representedby a coordinate pair of values (x, y) that defines a point on atwo dimensional grid.

The technique of graphing provides a very effective methodof visually displaying the relationship between two variables.By convention, the independent variable x is plotted along thehorizontal axis (x-axis) and the dependent variable y is plottedalong the vertical axis (y-axis) of the graph. The graph axesshould be scaled so that the coordinate points (x, y) are welldistributed across the graph, taking advantage of the maxi-mum display area available. This point is especially impor-tant when results are to be extracted directly form the datapresented in the graph. The graph axes do not have to startat zero.

Scale each axis with numbers that represent the range ofvalues being plotted. Label each axis with the name and unitof the variable being plotted. Include a title above the graph-ing area that clearly describes the contents of the graph beingplotted. Refer to Figure C.1 and Figure C.2.

The line of best fit

Suppose there is a linear relationship between x and y, so thaty = f(x) is the equation of a straight line y = mx + b where m is the slope of the line and b is the valueof y at x = 0. Having plotted the set of coordinate points (x, y) on the graph, we can now extract a valuefor m and b from the data presented in the graph.

Draw a line of ’best fit’ through the data points. This line should approximate as well as possible thetrend in your data. If there is a data point that does not fit in with the trend in the rest of the data, youshould ignore it.

47

48 APPENDIX C. GRAPHING TECHNIQUES

The slope of a straight line

Figure C.3: Slope of a line

The slope m of a straight-line graph is determined bychoosing two points, P1 = (x1, y1) and P2 = (x2, y2),on the line of best fit, not from the original data, andevaluating Equation C.1. Note that these two pointsshould be as far apart as possible.

m =rise

run

m =∆y

∆x=

y2 − y1x2 − x1

(C.1)

Error bars

Figure C.4: Error Bars for Point (x, y)

All experimental values are uncertain to some degree dueto the limited precision in the scales of the instrumentsused to set the value of x and to measure the result-ing value of y. This uncertainty σ of a measurement isgenerally determined from the physical characteristics ofthe measuring instrument, i.e. the graduations of a scale.When plotting a point (x, y) on a graph, these uncertain-ties σ(x) and σ(y) in the values of x and y are indicatedusing error bars.

For any experimental point (x± σ(x), y ± σ(y)), theerror bars will consist of a pair of line segments of length2σ(x) and 2σ(y), parallel to the x and y axes respec-tively and centered on the point (x, y). The true value lies within the rectangle formed by using the errorbars as sides. The rectangle is indicated by the dotted lines in Figure C.3. Note that only the error bars,and not the rectangle are drawn on the graph.

The uncertainty in the slope

Figure C.5: Determining slope error

Figure C.5 shows a set of data points for a linear rela-tionship. The slope is that of line 2, the line of best fitthrough these points. The uncertainty in this slope istaken to be one half the difference between the line ofmaximum slope line 1 and the line of miinimum slope,line 3:

σ(slope) =slopemax − slopemin

2(C.2)

The lines of maximum and minimum slope should gothrough the diagonally opposed vertices of the rectanglesdefined by the error bars of the two endpoints of thegraph, as in Figure C.5.

49

Logarithmic graphs

In science courses you will encounter a great number of functions and relationships, both linear and non-linear. Linear functions are distinguished by a proportional change in the value of the function with a changein value of one of the variables, and can be analyzed by plotting a graph of y versus x to obtain the slope mand vertical intercept b. Non-linear functions do not exhibit this behaviour, but can be analyzed in a similarmanner with some modification. For example, a commonly occuring function is the exponential function,

Figure C.6: The exponential function y = aebx.

y = aebx, (C.3)

where e = 2.71828 . . ., and a and b are constants.Plotted on linear (i.e. regular) graph paper, thefunction y = aebx appears as in Figure C.6. Tak-ing the natural logarithm of both sides of equa-tion (C.3) gives

ln y = ln(

aebx)

ln y = ln a+ ln(

ebx)

ln y = ln a+ bx ln e

ln y = ln a+ bx (since ln e = 1)

Equation (C.4) is the equation of a straight linefor a graph of ln y versus x, with ln a the verticalintercept, and b the slope. Plotting a graph of ln yversus x (semilogarithmic, i.e. logarithmic on the vertical axis only) should result in a straight line, whichcan be analyzed.

There are two ways to plot semilogarithmic data for analysis:

1. Calculate the natural logarithms of all the y values, and plot ln y versus x on linear scales. The slopeand vertical intercept can then be determined after plotting the line of best fit.

2. Use semilogarithmic graph paper. On this type of paper, the divisions on the horizontal axis areproportional to the number plotted (linear), and the divisions on the vertical axis are proportional tothe logarithm of the number plotted (logarithmic). This method is preferable since only the naturallogarithms of the vertical coordinates used to determine the slope of the lines best fit, minimum andmaximum slope need to be calculated.

Semilogarithmic graph paper

The horizontal axis is linear and the vertical axis is logarithmic. The vertical axis is divided into a seriesof bands called decades or cycles.

• Each decade spans one order of magnitude, and is labelled with numbers 1, 2, 3, 4, 5, 6, 7, 8, 9, 1.

• the second “1” represents 10× what the first “1” does, the third 10× the second, et cetera, and

• there is no zero on the logarithmic axis since the logarithm of zero does not exist.

A logarithmic axis often has more than one decade, each representing higher powers of 10. In Figure C.7,the axis has 3 decades representing three consecutive orders of magnitude. For instance, if the data to beplotted covered the range 1 → 1000, the lowest decade would represent 1 → 10 (divisions 1, 2, 3, . . . , 9),

50 APPENDIX C. GRAPHING TECHNIQUES

Figure C.7: A 3-Decade Logarithmic Scale.

the second decade 10 → 100 (divisions 10, 20, 30, . . . , 90) and the third decade 100 → 1000 (divisions 100,200, 300, . . . 900, 1000).

Another advantage of using a logarithmic scale is that it allows large ranges of data to be plotted. Forinstance, plotting 1 → 1000 on a linear scale would result in the data in the lower range (e.g. 1 → 100)being compressed into a very small space, possibly to the point of being unreadable. On a logarithmicscale this does not occur.

Calculating the slope on semilogarithmic paper

The slope of a semilogarithmic graph is calculated in the usual manner:

m = slope

=rise

run

=∆(vertical)

∆(horizontal).

For ∆(vertical) it is necessary to calculate the change in the logarithm of the coordinates, not the changein the coordinates themselves. Using points (x1, y1) and (x2, y2) from a line on a semilogarithmic graph ofy versus x and Equation C.4, the slope of the line is obtained.

m =rise

run

m =ln y2 − ln y1x2 − x1

m =ln (y2/y1)

x2 − x1(C.4)

Note that the units for m will be (units of x)−1 since ln y results in a pure number.

Analytical determination of slope

There are analytical methods of determining the slope m and intercept b of a straight line. The advantageof using an analytical method is that the analysis of the same data by anyone using the same analyticalmethod will always yield the same results. Linear Regression determines the equation of a line of best fitby minimizing the total distance between the data points and the line of best fit.

To perform “Linear Regression” (LR), one can use the preprogrammed function of a scientific calculatoror program a simple routine using a spreadsheet program. Based on the x and y coordinates given to it, aLR routine will return the slope m and vertical intercept b of the line of best fit as well as the uncertaintiesσ(m) and σ(b) in these values. Be aware that performing a LR analysis on non-linear data will producemeaningless results. You should first plot the data points and determine visually if a LR analysis is indeedvalid.

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Brock University Physics Department PHYS 1P93 Laboratory Manual

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