====== Friction PHYS-141 ======
Collaborative Measurements of Frictional Effects
====== Introduction ======
In this lab you will work in collaboration with another group to develop independent experiments to measure the coefficient of friction (either sliding or static) between an iOLab device and a metal surface.
The physics of what determines the coefficient of friction μ between two objects is complex and there are no practical ways to calculate μ from theory. It is something which must be measured and for which there are no //known// values to compare your results with. In this way the experiments you will perform have a lot in common with experimental research.
====== Pedagogy Goals ======
Experiments are not done to measure something which you already know, or can look up. So the challenge, both in research and for this lab is, **how do you know that your experimental results are accurate when you are measuring something which is truly unknown**? A major goal of the instructional lab curriculum is to train you in how to answer this question. In this lab you will have to grapple with:
* How to make the best use of the tools at your disposal to make the best possible measurement of μ.
* How to identify and account for likely sources of bias in your data.
* How to rigorously compare the results of your experiment with those of your colleagues who are using different experimental techniques to measure the same thing.
Each of these bullet points addresses a fundamental aspect of scientific research.
There are three pedagogical goals for this lab:
* Experimental design.
* Comparison of results.
* Scientific communication.
====== Experimental Task ======
Your group will collaborate with one or two other groups in your section to investigate either the Dynamic (sliding) $\mu_{d}$ or static $\mu_{s}$ coefficient of friction between the red felt pads on the bottom of an iOLab device and the surface of a flat optical rail. Half of the class will measure $\mu_{d}$ and half will focus on $\mu_{s}$.
Each group has the following apparatus at their disposal.
* Two iOLab devices with their associated accessories such as springs, hooks, etc. The iOLabs provide you with an array of different sensors which can be used:
* Magnetometers.
* Accelerometers.
* Gyroscopes.
* Force sensor.
* Position encoders.
* Light and Sound sensors
* A computer for recording data from the sensors on the iOLab devices.
* An optical rail.
[[phylabs:lab_courses:phys-140-wiki-home:fall-experiments:conservation-laws-lab:introduction-to-the-iolab-device-phys-141|This link will take you to a short tutorial which will walk you through using the iOLab device.]]
You should spend 30 to 45 minutes working through it before moving on to the friction experiment. Note that you will be using this device a lot in the coming quarters of the PHYS140's lab sequence.
Additionally the lab room contains a wide variety of other pieces of apparatus which you are free to make use of, including but not limited to:
* A wide variety of masses, mass hangers, hooks, etc.
* Rulers, protractors, and mass scales.
* Ring stands along with a variety of rods, clamps and post holders.
* Nylon thread, string, and tape.
* Wooden blocks of different sizes.
====== Getting Started ======
Your TA will break the class up into two collaborations and determine which one investigates $\mu_{d}$ and which one investigates $\mu_{s}$.
===== Initial Experiment Design =====
Begin by brain storming different ways in which the apparatus at your disposal can be used to measure $\mu$. You need to come up with a **different** experimental technique for each group in your collaboration.
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**Pedagogy Note**
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An important dynamic in experimental science is that often you will find multiple groups using different experimental techniques to investigate the same phenomena. If different groups measure the same thing in different ways and arrive at the same answer the scientific community has more confidence in the results.
By different we are referring to the combination of measured parameters, measurement devices and methodology used which make up the experiment as a whole. As an example, two groups measuring the speed at which a can rolls down an inclined plane by timing how long it takes to travel a distance X, with each group using a different stopwatch app on their phone does not constitute different in this sense. But one group using the stopwatch technique and the other group recording a video of the motion of the can and using image analysis to measure the number of rotations unit time would constitute different.
Once the collaboration has come to agreement on the experimental techniques, each group should then setup and perform the experiment for one of the techniques.
===== Comparing Results =====
Since different groups are in principle making measurements of the same phenomena under the same conditions, all groups should obtain the same answer. It is of course not possible for all groups to arrive at exactly the same numerical value. So now the important question of how close is close enough to be in agreement arises.
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**Pedagogy Note**
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For this lab you **must** quantify the degree to which your results are in agreement, and you must be able to justify, using data derived from measurements, the uncertainties which you arrive at.
Statements such as //pretty close//, //human error//, or //within x% of each other// are meaningless and will earn you a zero for your grade on this lab.
This is where a careful estimate of the uncertainties in your measured values is critical. The size of your error bars gives you a way in which to determine the degree which your results are in agreement, or disagreement. It is entirely possible that you may spend more time taking data and performing sub-experiments for the purpose of quantifying how well you have measured a particular value, than the time it takes to measure the value itself. Many, if not most, research experiments do the same thing.
===== Iterating =====
When you first try to compare results among groups it is likely that you will not be in agreement within experimental uncertainties. This is fine. The measurement which you are making is full of potential biases and sources of systematic uncertainty, not all of which are within your ability to control. The value of $\mu$ may not be the same for each iOLab device or for each of the optical rail surfaces. Depending on how you performed the measurement it is possible that the manner in which you attached a hanging mass, or let go of the iOLab imparted some force or impulse which you have not accounted for. This is by design as one of the purposes of the lab is for you to gain experience identifying and minimizing or accounting for these sorts of systematic effects in your experiment.
If the results among your groups are **not** in agreement try to identify possible sources of bias in the data and come up with a way of accounting for them, either by modifying your experimental techniques, or by conducting additional experiments to quantify the impact of the bias. If there is time in the lab period continue to experiment, compare and refine your experiments.
If the results among your groups **are in** agreement your job is not done. The goal is NOT to come to agreement. The goal is to make the best possible measurement that you can. If there is time left in the lab period you should look for ways that both groups can reduce the size of your error bars by improving the quality of your measurements. Try to reduce your uncertainties to the point where your results are not in agreement.
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**Pedagogy Note**
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You can **never** make a measurement too precisely. As you reduce your uncertainties to the point where your data are in disagreement with other measured values, or theoretical predictions, you are actually advancing the scientific bar so to speak. The most scientifically significant experimental results are the ones which are in disagreement with what everyone expects, and turn out to be correct. However claiming that your experimental results have revealed new physics requires that you are confident that you understand all of the factors which could have biased your results, and that is one of the themes of today's lab.
====== Group Lab Notebook ======
Lab notebooks are a record of everything which you do over the course of an experiment. In the research environment lab notebooks serve multiple purposes including:
* Helping you remember accurately what you did an how you did it when communicating with other scientists including writing papers, attempting to reproducing results, continuing or extending the work.
* Keeping other members of a group or collaboration informed about the state of the experiment.
* Verifying the authenticity of your work.
* When working in industry lab notebooks are crucial in establishing and enforcing patents.
For the purposes of this lab your group notebook information necessary for comparing your results with other groups, for identifying possible sources of bias in your data, for instructing another group in how to reproduce your results, and for refreshing your memory when you sit down to write up your individual report.
Things which should make it into your group notebook include, but are not limited to:
* Diagrams and photos showing important details of your setup.
* Raw data, including measurements such as the length and height of a ramp or masses used.
* Estimates on uncertainties in measured quantities.
* Screen shots of data recorded from the iOLab which illustrate how regions of interest were determined or which show interesting features in the data.
* Results of calculations, plots and fits of data.
* Enough verbal description of your process and procedures that you could come back into the lab a year from now and reproduce the experiment.
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**Pedagogy Note**
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There is no recipe for what should go into a lab notebook. No one can teach you how to do it before you go into the lab. There are broad and general guidelines like those given above, but every experiment and every scientist is different. Learning how to keep a good lab notebook is a lifelong process which is never perfect. You simply have to get in the habit of taking notes when doing experiments, and learning painful lessons when you end up having to go back and retake all of your data because the notes in your notebook were inadequate when it came time to writeup your work for publication.