Introduction: (Initial Observation)
The Gauss Rifle also known as the Gaussian gun is a very simple experiment that uses a magnetic chain reaction to launch a steel marble at a target at high speed. This educational and amusing project is very simple to build (it only takes a few minutes), is is very simple to understand and explain, and yet fascinating to watch and to use.
The movie bellow shows a sample of the gauss rifle in action. In the beginning, a steel ball starts rolling towards a magnet taped to a plastic rail. As soon as the rolling ball hits the magnet, another ball in the opposite side is launched and leaves the device at a very high speed.
The Magnetic Accelerator makes a good science project because you can easily have a question, define variables, propose a hypothesis, and run scientific experiments about it.
You can also have a results table and graph and the presentation is exciting. Everyone loves to see a stationary ball that suddenly moves at fast speed without any visible cause for that.
Find out about magnets and magnetic force (the main cause of acceleration in this project). Read books, magazines or ask professionals who might know in order to learn about the factors affecting the acceleration rate. Keep track of where you got your information from.
What do you want to find out? Write a statement that describes what you want to do. Use your observations and questions to write the statement. This is a sample question:
How does the number of magnets affect the kinetic energy of the gauss rifle?
When you think you know what variables may be involved, think about ways to change one at a time. If you change more than one at a time, you will not know what variable is causing your observation. Sometimes variables are linked and work together to cause something. At first, try to choose variables that you think act independently of each other.
This is an example of how you may define variables:
Independent variable is the number of magnets, Dependent variable is the kinetic energy.
This is another example of how you may define variables:
Independent variable is the number of magnets, Dependent variable is the ejection distance.
Based on your gathered information, make an educated guess about what types of things affect the system you are working with. Identifying variables is necessary before you can make a hypothesis.
This is a sample hypothesis:
I hypothesize that each additional magnet will double the kinetic energy compare to the previous magnet.
Design an experiment to test each hypothesis. Make a step-by-step list of what you will do to answer each question. This list is called an experimental procedure. For an experiment to give answers you can trust, it must have a “control.” A control is an additional experimental trial or run. It is a separate experiment, done exactly like the others. The only difference is that no experimental variables are changed. A control is a neutral “reference point” for comparison that allows you to see what changing a variable does by comparing it to not changing anything. Dependable controls are sometimes very hard to develop. They can be the hardest part of a project. Without a control you cannot be sure that changing the variable causes your observations. A series of experiments that includes a control is called a “controlled experiment.”
In this experiment we will try the gauss rifle with different number of magnets and record the ejection distance.
Place your magnetic accelerator or Gauss Rifle horizontally on the edge of a table about 100 cm tall. Select the location of the table where you have at least 10 feet open space for the ejected ball.
Load it with one magnet, two balls in front of it and a third ball (call it trigger ball) rolling toward the magnet from the back. Measure the ground distance the ball is ejected and write it in your data table. Gauss Rifle with one magnet
Repeat this with 2, 3 and 4 magnets and record the ejection distance for each number of magnets.
Your data table may look like this:
Ejection distance data for Magnetic linear accelerator
|Number of accelerating magnets||Ejection Distance (Meter)|
Use the ejection distance to calculate the initial kinetic energy of the projectile. Calculating the kinetic energy of a projectile is fairly straight forward using the following equation:
KE=1/2 m * v2 or KE= 1/2 m * (d/t)2
where m is the mass of the projectile in kilograms and v is the velocity in meters per second and KE is energy in Joules. In the second formula d is the ejection distance (in meters) and t is the travel time (in seconds).
The m for 1/2″ steel ball is 8.4 grams or 0.0084 Kilogram. t is 0.45 seconds (This is the time it takes for any object to fall from one meter elevation, disregarding the air friction).
So by knowing m = 0.0084 kg and t = 0.45 seconds you can calculate the kinetic energy of a projectile that falls at d = 2.7 meters away from the table.
KE = 1/2 * 0.0084 * (2.7 / 0.45)2 = 0.1512 Joules
Kinetic Energy of our Magnetic Linear Accelerator
|Number of accelerating magnets||Ejection Distance (Meter)||Kinetic Energy (Joule)|
Make a graph:
Use the above table to make a bar graph for your results. Use one bar for each number of magnets from 1 to 4. The height of each bar will represent the kinetic energy you calculated with that number of magnets.
This is a sample graph, but it is not complete. You must make a graph using your own data.
Also please verify the accuracy of the calculations.
Materials and Equipment:
This is a sample list of materials:
- 4 super strong magnets (Part# N35.500.500)
- 10 steel balls (Part# SBALL)
- 2 wood dowels used to construct the rails.
The Standard Gauss Rifle kit of MiniScience contains all the above items. The wood dowels in the kit are short because of shipping restrictions. It is best if you make a different rail for the balls that are at least 3 to 4 feet long.
Results of Experiment (Observation):
Experiments are often done in series. A series of experiments can be done by changing one variable a different amount each time. A series of experiments is made up of separate experimental “runs.” During each run you make a measurement of how much the variable affected the system under study. For each run, a different amount of change in the variable is used. This produces a different amount of response in the system. You measure this response, or record data, in a table for this purpose. This is considered “raw data” since it has not been processed or interpreted yet. When raw data gets processed mathematically, for example, it becomes results.
If you do any calculations, write your calculations in this section of your report.
Summary of Results:
Summarize what happened. This can be in the form of a table of processed numerical data, or graphs. It could also be a written statement of what occurred during experiments.
It is from calculations using recorded data that tables and graphs are made. Studying tables and graphs, we can see trends that tell us how different variables cause our observations. Based on these trends, we can draw conclusions about the system under study. These conclusions help us confirm or deny our original hypothesis. Often, mathematical equations can be made from graphs. These equations allow us to predict how a change will affect the system without the need to do additional experiments. Advanced levels of experimental science rely heavily on graphical and mathematical analysis of data. At this level, science becomes even more interesting and powerful.
Using the trends in your experimental data and your experimental observations, try to answer your original questions. Is your hypothesis correct? Now is the time to pull together what happened, and assess the experiments you did.
Related Questions & Answers:
What you have learned may allow you to answer other questions. Many questions are related. Several new questions may have occurred to you while doing experiments. You may now be able to understand or verify things that you discovered when gathering information for the project. Questions lead to more questions, which lead to additional hypothesis that need to be tested.
If you did not observe anything different than what happened with your control, the variable you changed may not affect the system you are investigating. If you did not observe a consistent, reproducible trend in your series of experimental runs there may be experimental errors affecting your results. The first thing to check is how you are making your measurements. Is the measurement method questionable or unreliable? Maybe you are reading a scale incorrectly, or maybe the measuring instrument is working erratically.
If you determine that experimental errors are influencing your results, carefully rethink the design of your experiments. Review each step of the procedure to find sources of potential errors. If possible, have a scientist review the procedure with you. Sometimes the designer of an experiment can miss the obvious.