Tag Archives: Constant Velocity Particle Model

We Have Lift Off!

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This is a follow up post to Modeling A Rocket’s Journey – A Synthesis where I described how the students in the first year program were engaged in creating a predictive report for their model rockets. I want to emphasize that these model rockets were not kits. Each rocket was designed using 3D CAD software, and each component was either fabricated from raw material, or was created from material that was not intended for use in model rocketry. The only exception to this is the actual rocket motor.

The next step was to launch the rockets and have the altimeter payload collect altitude data.

Launch Conditions – A Bit Soggy

Unfortunately the week of our scheduled launch happened to be a week of some pretty hefty rains. We rescheduled the launch twice before finally accepting the soggy launch conditions. With umbrellas and rain jackets, we trudged out to the baseball diamond and got to work setting up for the launch. We had some minor difficulties in the wet weather, but eventually had a very successful launch day.

Most of the rockets were able to launch and deploy their valuable payload – the Pnut Altimeter.


The students seemed very excited to finally see the rockets launch, and to see the successful deployment of the parachutes. Although we all got a little wet and muddy, we had a great time!

The Altimeter Data

The altimeters use a small barometric pressure sensor to collect altitude data (the altimeters also contain a small temperature sensor and voltage sensor). The altitude is recorded in feet every .05 seconds. Here is an example of one rocket’s recorded flight data:



The students were then asked to use the data to create a comparative analysis report. I will detail how the assignment was set up and also discuss how the students performed on this assignment. That will be for another post.

I want to also thank Mr. Kainz for his amazing photos that are displayed here.

Deploying The Constant Velocity Particle Model


Proof is In The Deployment (Prediction)

This week the first year Academy students put their knowledge to the test. One of the key elements of the modeling pedagogy is that students are given a chance to test their predictive powers using the model that they have built. This stage of the modeling cycle is called deployment. When a model is deployed, the students describe, represent and most importantly predict the behavior of a situation they have not previously encountered.

In this case, the model the students were deploying is the constant velocity particle model. This analytical model describes, represents and predicts the behavior of a particle moving at a constant velocity. For the past few weeks, students have been building the model, informed through experimentation/observation and some guidance from staff.

In this deployment activity, students were asked to predict the location where two constant velocity buggies would collide. The two buggies had different velocities and were separated a distance of 1.2 meters. The students were asked to describe, represent and quantitatively determine the position where the two buggies would collide.

The students seemed to be satisfied with the results, and so next stop…the constant acceleration particle model.

First Year Students Begin Learning About Constant Velocity Particles


And The White Boarding Begins

We are off to a great start with our new students. They did an exceptional job tackling our first observational “lab” (the Buggy Lab without motion detectors), and they got the hang of white boarding pretty quickly. As can be expected, some students were very quiet, but many participated in the group discussion, and everyone was engaged with their individual groups.

One thing discovered by the students was how important it is to draw your graph axis scale correctly. Some of the graphs created were not linear due to the fact that students tried to “squeeze” points onto the graph by effectively warping the axis. This was a good learning opportunity and I explained that in the future we would first be creating our graphs on a computer and that they were to translate the shape and not be too concerned with precisely placing their points according to the imprecisely drawn graph axis.

This also brought up the point made by one student whose team had created a graph that looked like the buggy had gone backward in time! This prompted some great discussions about time and position, but more importantly it allowed me to ask the students if it made sense to “connect the dots” on their graph. A student perceptively commented that it didn’t really make sense because it gave the impression that all the data had been gathered in one trial. We then identified that a better way to show that each data point represented a different trial would be to NOT connect them. Nice work class.