Tag Archives: angular acceleration

Simulate, Test, Analyze: A Framework For Rigor

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trebuchet-launch---08_23970235271_o

“Have Fun Storming The Castle!”

At the end of this fall semester, the second year students in the Academy rolled and carried their medieval mechanisms of mayhem to the SRHS track and we spent the afternoon watching the devices hurl lacrosse balls across the athletic field.This project was the final performance assessment of the semester and required that students design a gravitationally powered projectile launcher. This is an age old engineering/applied physics project.

Like many engineering projects done in high school, the physics principles governing the dynamics of the project are quite complicated, and ultimately the actual “application” of the science principles is often cursory. Students don’t have the background or mathematical abilities to to do the complex calculations needed to make an optimization adjustment to their mechanical device.This leads to the disconnection between the science content and engineering practice. Students don’t have the ability to make an informed decision about design choices. This is because it is difficult, very difficult.

Over the past few years I have been very interested in addressing this problem. This post discusses a framework that I have been working on to incorporate science into engineering projects. I think this framework allows high school students to engage in difficult scientific analysis without overwhelming them.

A Framework For Rigor

I won’t claim that this is a perfect solution, but so far I think we have experienced some success in creating a tighter relationship between science and engineering.  Last December I helped conduct a workshop at the NCCPA Professional Development Conference in Petaluma, CA. The name of the workshop was “NGSS, Prediction Reports and Your Science Class” and the point of this workshop was to give the attendees a framework for incorporating the Engineering standards into the science curriculum.  My co-presenter (Vipul Gupta) and I focused on the creation of prediction reports using computer simulations as a way to address two very important standards in the NGSS framework:

Using Simulations with Informed Input

Computer simulations are very popular in the educational space. They give teachers and students a virtual space where students can interact with virtual lab equipment or virtual objects that behave similarly to physical objects in the real world. With that said, they can fail to address students misconceptions because they do not always succeed in linking a conceptual model to the physical behavior. I also believe that the best simulations are ones that output data that can be analyzed with other scientific/mathematical tools. I also think that a good simulation requires that students provide meaningful input that gives them opportunities for analyzing the relationship between the input and the output.

Simulations used in engineering projects can be extremely helpful in addressing one of the main problems in engineering education. Students often design and build mechanical devices without understanding the physical principles that govern the design. The design process becomes an exercise in trial and error, or simply is reduced to copying a design from the internet.

To do a predictive analysis of a rocket’s flight, or a bridge’s structural performance is extremely difficult and often requires advanced mathematics and physics. Simulations can give the students the ability to analyze their designs and understand how changing the design inputs affects the output. Once again, it is important to find a simulation that requires students to understand the inputs and outputs.

Virtual Trebuchet

For example, in our project, students were introduced to an online Trebuchet simulation tool. This simulation tool is great because it requires that the student learn how to measure and calculate certain inputs. The students must have a working knowledge of rotational inertia, center of mass, and other concepts before they use the simulation. This was ideal for our project because it gave students a relevance and motivation . They had learn about these concepts in order to actually use the simulation. The students could then change certain inputs and see how that would change the efficiency of the design, or the range of the projectile. The point is that they needed physics knowledge in order to use the tool. They might not have the ability to know how the simulation eventually calculated the output, but they knew that the simulation required an understanding of the inputs.

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Example Report

The Prediction Report

The next step is to ask the students to prepare a prediction report. This report is designed to get students to demonstrate their understanding of the inputs, display evidence of the required calculations or measurements needed to create the inputs and then analyze the simulation outputs. In the report for this project, I asked students to show a set of calculations and measurements for determining the center of mass of their throwing arm and the rotational inertia (moment of inertia). Students also had to provide similar information for the counterweight.  The students then had to run the simulation and document the outputs from the simulation.

The Test:  Data is Needed

The next step is to test the device. To make this step more rigorous and to be able to relate the scientific analytical process to the engineering process, it is crucial for the students to collect data that can be used to analyze the performance of their device/product and then reflect on how they would improve their design.

For this project, we decided to use high-speed video and Vernier’s LoggerPro video analysis software to plot the position of the projectile as it was launched from the device.

The Analysis

The analysis is actually broken into two parts. The first part requires a collection of calculations while the second part uses those calculations to make some qualitative assessments.

For example, in the above project, students had to use the collected position data from the video analysis tool to calculate the kinetic energy of the projectile and then the efficiency of the device. They had to be proficient at the analytical tool, which in itself requires physics content knowledge, providing once again an opportunity to apply scientific models in the analysis portion of this engineering project.

I have included the instructions for the analysis report here: Projectile Launcher Analysis Report.

Finally, students are given the opportunity to use the information gathered in the analysis report to reflect on their design, and more importantly use the information to inform how they would improve on a future design. I have included below the set of questions that I asked my students:

  1. Compare the efficiency calculation of the simulation to the efficiency rating that you calculated for your actual performance. Please describe why you think these values are not the same.
  2. Consider the design of your trigger. What design and fabrication decisions would you change in order to improve your trigger, AND explain WHY you would make those changes.
  3.  Consider the design of your sling. What design and fabrication decisions would you change in order to improve your sling, AND explain WHY you would make those changes.
  4. Consider the design of your release mechanism (called the nose). What design and fabrication decisions would you change in order to improve this mechanism, AND explain WHY you would make those changes.
  5. Consider the design of your arm. What design and fabrication decisions would you change in order to improve your arm, AND explain WHY you would make those changes.
  6. Consider the design of all other components and the overall design. What design and fabrication decisions would you change in order to improve your device (other than the trigger, sling and arm), AND explain WHY you would make those changes.

Conclusion

The overall design of this framework can be boiled down to this:

  • Engage students in a computer simulation that simplifies the process of modeling and analyzing a complex physical/chemical/biological process, but be sure that the simulation requires some conceptual and computational thinking.
  • When testing the performance of the design (bridge, rocket, etc.) make sure that the students are required to  collect data that can be analyzed and that once again demands that they apply their theoretical models.
  • Design an assessment that uses the analysis and gives the students an opportunity to make informed judgements of their designs for the purpose of redesign.

Testing Motors For The Solar Dragster Race

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Torque/Speed Curves

In this post I’m going to describe our attempt to measure the power curve for the DC motors used in the Solar Dragster race this year. I’m going to be honest, our efforts weren’t really that successful, but I can at least say that I learned some things that might help for next year, and I think the students were able to do some authentic device testing – a part of being an engineer.

Last year I was a bit concerned that the DC motors that we were using in the Solar Dragster Race were not actually outputting the same power. I wanted to devise a way to measure the motor power, and then have each team do their own analysis. I wanted the students to do this without understanding the electrical power parameters involved because we were at this point only looking at motors as being a black box that gets energy from a source and transfers that energy into a rotational device – i.e. an axle, then to a gear, then to another axle, and finally to a wheel. I looked into getting a torque sensor, but quickly found out that these cost a fortune!

I came across this interesting website from MIT, which was a nice resource for the theory about DC motor performance. The site does a nice job in explaining torque/speed curves, and how the graph of torque vs angular speed is essentially linear for DC motors. That meant that all the students really needed to do was to measure stall torque and the no load speed of their motors and then we would have the torque/speed curve. The website identifies a device that they custom built for testing motors, and it looks interesting, but I didn’t have time to reverse engineer what they had built and unfortunately the images and videos aren’t clear enough to easily understand how the device works – something perhaps for summer tinkering…

One of the issues with the little DC motors that you buy is that the arbor is really small, and it has no index, so its really hard to attach anything. Generally, you have to go with a friction fitting, and I was worried that doing a stall torque test was going to be difficult. Mr. Holt and I designed and printed out a little lever arm to attach to the motors. This little arm could then be attached to a force meter to measure the stall torque and then also used to help measure the rotational velocity using a Photogate. The final “test-bench” looked like this:

Torque-speed test bench

The motors were clamped to a lab stand that was then placed so that the little lever arm would rotate and block the Photogate laser as it spun. This is how the students measured the no load speeds. Then they attached a string to the little hole in the arm, and then attached this to a force meter to get the stall torque. All the motors were tested with essentially the same power source – two AA batteries.

I then had the students share their data using a Google Spreadsheet and I compiled the data – here it is on Plotly:

dc_motor_tests

There is obviously some variability in the motor performance, but its hard to tell if any of the motors give a distinctive advantage over the others because I suspect that the data is not that reliable unfortunately. I do suspect that the angular speed data might be inaccurate due to the fact that we were getting some very differing results from the Photogate. Although we made the sampling rate as rapid as possible, I still am not confident that the Photogate was able to read the blocking of the laser accurately – the motors spin VERY fast (upwards of 5000 RPM’s when not loaded). I’m also not sure if the data then could then be used in any instructive way to help students make design decisions about their dragsters.

Although this may seem like a failure, it did allow the students to identify at least two motors that we knew were malfunctioning, so we were able to swap those out before the competition.

For Next Year

I think at this point I would want to make some changes to this activity. Although it was somewhat helpful in giving the students a direct interaction with data associated with the performance of a DC motor, and how that performance is calculated at the product of the torque and angular velocity, I’m not sure that the activity supplied data that was good enough to then use as an input factor in the competition. For example, I didn’t feel confident about allowing students to use the calculated maximum input power as a scaling factor for their dragster race time.

Perhaps next year, we can find the funds to purchase a high precision, digital torque meter, or find the time and money to build our own “analog” torque/speed meter like the one that MIT designed. All in all, I’d say this activity was partially successful.

Building The Net Torque Model – Part 3

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Appending The Conservative Models

After investigating the causal relationship between torque and angular acceleration, I introduced the possibility to the class that perhaps we also needed to revisit the Energy Transfer Model and the Momentum Transfer Model. The students agreed that an object that is rotating must have energy. This was pretty easy to demonstrate.

I set up a situation in the class where two of the variable inertia disks that we created on the 3D printers were placed at the top of an inclined ramp. The internal marbles were placed at two different configurations inside the disks and then the students predicted which disk would reach the end of the ramp first. I was pleased to find out that the class appeared to agree that the disk with the marbles located closer to the radius would be the winner. I really think that our investigation with the variable inertia disks solidified the students’ conceptual understanding of rotational inertia and the importance of mass distribution.

I have not yet found a good experiment where students could discover the rotational kinetic energy relationship, so I decided to take them through a derivation based on linear kinetic energy. I then asked the students to do some whiteboard work. I asked them to demonstrate that the disks would indeed reach the end of the ramp at different times. Although this wasn’t strictly a constructivist approach, it was good practice in doing some fairly difficult algebra without numerical values – something the students traditionally are not very good at.

We then moved onto momentum. Again, I started by reviewing the Momentum Transfer Model for a particle. At this point the pattern had been fairly well established. The relationship between angular and linear quantities seemed to have taken hold because the students were quick to propose a mathematical definition for angular momentum. Our next goal was to figure out whether this was a conserved quantity.

Mr Holt and I had created a set of metal disks that could be attached to the rotary sensors. I decided to create our own, rather than (sorry Vernier) buy them as I thought that the commercial kit was over priced. It wasn’t too hard to create the disks, especially when you have access to a CNC plasma cutter!

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The students attached one disk to the rotary motion sensor and then got that disk spinning. They then took a second disk that had small magnets attached to it, and dropped this disk onto the spinning disk. The students compared the angular velocity before and after the disks were combined and then calculated the angular momentum of the system before and after. The data we got was quite good with the class getting in the range of only about a 5% to 6% difference.

Wrapping it Up (or Un-Rolling It Down)

As a final deployment, I decided to try the deployment activity that Frank Nochese did with his students. It seemed like a good (and fun) way to wrap up our model (or as I have already argued – models).

Before doing the deployment activity, I reviewed all the model specifics with the students. My point here was to impress on them that what we had not really built a new model, but rather had extended many of the prior particle models to include rigid extended bodies. This generally only required that we consider the moment arm in all the particle models. I think this really helped a number of students see the connection between models that they felt they understood and all this rotational stuff that seemed a bit confusing.

I then set them up with the deployment activity, but I asked them to specifically solve the problem using both energy and net torque. There was some success, but I realized that the task was a bit much for the class. Once again, it is clear that I need to give them more practice with these problems that require multiple steps and that involve algebraic manipulation of symbols without numbers. Plenty of time to practice that!

Building The Net Torque Model – Part 2

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Investigating An Unbalanced Net Torque

We started by looking at the fact that a disk experiencing a net unbalanced torque also experienced a change in rotational or angular velocity. The students used a rotary motion sensor to measure the angular position and the angular velocity of a disk experiencing a constant torque and the students immediately recognized the similarity between a particle experiencing constant linear acceleration and a rigid body experiencing constant angular acceleration.

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So, the natural next step in our investigation was to determine the causal relationship between a net unbalanced torque and the angular motion state of a rigid body. The students discussed how we might set up an investigation that would help us understand this relationship, and I helped guide them towards a final investigation design where we used a rotary motion sensor attached to the wooden disk we had used in a previous investigation.

The rotary sensors from Vernier are rather expensive, but also quite nice. They come with a plastic spindle with three different pulley radii. The only issue that I have with these is that they do not include a useful screw for attaching objects to the pulley – they expect you to purchase their completely over priced accessory kit. I don’t suggest this. Instead, you can create your own and then use a 6/32 screw to attach them to the pulley – just be careful not strip the threads!

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Working off a similar investigation when studying the causal relationship between a net unbalanced force and linear acceleration, the students recognized that we needed to include a force sensor for measuring the applied force. The students then had LoggerPro plot the points for the calculated torque (using a calculated column) and the measured angular acceleration.  The data isn’t super clean, but its good enough for the students to conclude that the relationship is most likely linear.

Dimensional Analysis – Inferring Rotational Inertia

I was amazed to discover that some students in the class set off to understand what the units of the slope could be reduced to. They immediately saw that the proportional constant (slope) included kg (mass) but that wasn’t all. After some work, the class had determined that the units for the slope were kg * m^2.

This led to a qualitative discussion about the inertia of rotating objects. We discussed hoops and disks primarily, and the class seemed to agree that the units made sense. Although I didn’t have any hoop-disk sets like the ones you can buy from various vendors, we did perform some thought experiments around mass distribution and rotation, but we needed to be sure that we were on the right track.

A Better Variable Inertia Disk

So last year I was looking for an investigation that would really help the students discover the importance of mass distribution for a rotating object. Reading the material on the AMTA website regarding the unit on rotational motion, the researches stressed the importance of connecting mass distribution to the rotational inertia. I found this variable inertia disk from Fischer Scientific and decided to purchase it. I commend these guys on making this, but frankly I decided that I could make a better one.

My colleague and I set about redesigning these disks. The improvements we made included a) better compartments for the metal marbles so that they didn’t move around, b) an index and lip so that the two sides fit more securely together, and c) more compartments so that we can test more mass configurations. After we made our designs, we used our Makerbot 3D printer to print out ten copies of the disks.

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With these disks attached to the rotary motion sensors, the students were able to confirm that although the total mass of the disk did not change, the angular acceleration declined as the mass was moved outward from the radius of rotation. This was more of a qualitative investigation, but I think the students were able to clearly see how moving the mass farther from the axis affected the rotational inertia of the disk.

Deploying The Model (So far)

Now that the students had built a predictive model that described the quantitative relationship between rotational inertia, angular acceleration and net torque, they were ready to test it.

We returned to the investigation setup with the disk, but this time attached a hanging mass to the string and they attempted to predict the angular acceleration. The students immediately made the mistake (as I thought they might) in considering only the disk in the system. This gave me a chance to review with them the following process:

  1. Identify the system schema (now it includes things that can rotate!)
  2. Draw your force vector (free body/particle) diagrams and now also your force-moment arm (rigid body) diagrams.
  3. Write the summation of forces AND the summation of torques for the system.
  4. Do some algebra.

The trickiest part to figuring this out is getting the signs right due to interaction pairs and making sure that they agree. I ask the students to start with a diagram and then go through and label each force + or – by picking a force and then finding its partner and then making sure that the rest of the force directions agree.

Once they were able to get a prediction that we all agreed seemed correct, they ran the experiment. The class was able to predict the angular acceleration within about 10% error. We discussed the possible reason for discrepancy which led to some interesting discussions around modeling the rotational inertia of the attachment screw and washer, and also the frictional forces at work.

The students were pretty convinced that the model worked, and so next stop – energy and momentum in systems with rotational motion.