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Measuring Magnetic Field Fluctuations
10 years ago
For this year's science fair project, I want to figure out how to predict earthquakes. I did a lot of research, and so far, I have found out that many earthquakes occur after magnetic field fluctuations within the earth. I actually came across a theory that fluctuations in the Earth's magnetic field might occur hours or even days before an earthquake. In order to test this, I want to create a Wolfram Mathematica program that can detect changes and fluctuations in the magnetic field. I want to be able to put in the initial conditions of earth, and then I want to be able to generate a graph or a display of Earth's magnetic field at that moment. By analyzing the model, I can find the fluctuations in the graph, and I can predict earthquakes from the fluctuations in the magnetic field. I got my idea from this person:
Sensing Danger by Ananya Mukundan
and I want to be able to create a program that could recreate a model. Does anyone know how to extract data about magnetic fields from Mathematica? Or can anyone help me with writing this program?
10 years ago
First of all, thank you very much for your help.
I have not contacted her yet, but I believe that on one of the links you provided, her email was listed. I will contact her about this idea as soon as possible.
Since the software of Mathematica does not measure anything as previously stated, I believe that both of your ideas are valid and interesting ways to proceed with my project. I was also thinking of possibly creating a smartphone app that would be able to detect small changes in the ultra low frequency magnetic field, thus allowing the user to be aware of a possible earthquake (since many scientific papers have already been published that show the relationship between ultra low frequency magnetic variations and earthquakes). I think that this idea would also possibly be feasible because a smartphone does have a magnetometer and an accelerometer.
Thank you for your advice,
Vitaliy Kaurov, WOLFRAM Research
10 years ago
First of all let me tell you that the PDF you linked to is very interesting reading. I also found another related publications from same person:
Novel nanotesla magnetic field sensors for an early warning system for earthquakes
Quake Shake Network
Below are some quotes from the references we both gathered. Reading through them it is clear that the point of the research Ananya Mukundan did was developing magnetific field sensor. To clarify, Mathematica is software, a programing environment that lets you do a lot of powerful computations with
. But software itself is not a sensor or physics laboratory device. So the software itself does not measure anything.
On the other hand software allows for analysis of your measured data, which is an important part for extracting useful signals from background noise. This is why Bruce recommended looking into
But first you need the sensor that Ananya Mukundan developed. Have you thought of contacting her and asking if she thinks it is a manageable project on the scale of science fair?
It is well known that low-frequency (0.0110 Hz), 10100 nanotesla (nT) magnetic fluctuations occur hours or days before an earthquake. This article reports the development of ultrasensitive, low-cost, room-temperature, magnetic sensors that may enable the deployment of such sensors and sensor networks for recording these magnetic precursors to earthquakes. The sensors are based on magnetoelectric (ME) composites that produce a voltage response to the magnetic field fluctuations. The composites have two components: a ferromagnetic layer that responds to the magnetic field by producing a mechanical strain and a piezoelectric layer that converts the mechanical strain to a voltage. Several ferromagnetic-piezoelectric composites were prepared and characterized, and we found the best response in terms of low noise and sensitivity from sensors constructed of Metglas lead zirconate titanate (PZT). The data indicate that the samples can measure 0.1 nT at 0.110 Hz, a sensitivity ideal for the detection of 10100 nT field fluctuations that precede an earthquake. Suggested follow-up efforts include a large-scale deployment of the sensors and sensor networks in earthquake-prone regions for field tests and ultimately the development of a sensor-based early warning system.
the most reliable warning system today can provide only four to five seconds of lead-time, and that is only for places kilometers away from the epicenter of the earthquake. I started my research by scouring online journals looking for any ideas that I might be able to develop. I came across the theory that fluctuations in the Earths magnetic field might occur hours or even days before an earthquake. Recently, scientists have begun using magnetometers, devices that can measure the strength and direction of a magnetic field, to test this theory.
Existing magnetometers are capable of measuring changes in magnetic fields on the scale of 10 to 100 nanoTesla (nT), which is not precise enough to rule out environmental noise. The only existing device precise enough to measure what would be a minute change in the Earths magnetic field is called a SQUID magnetometer; however, because it uses liquid nitrogen, it operates only at extremely low temperatures and would thus not be practical for use in the field.
I decided to create a device that could precisely sense extremely small changes in magnetic field and that could operate at room temperature. I was going to need some help.
I developed a sensor made up of two components: a magnetostrictive part and a piezoelectric part. A magnetostrictive material is one that changes dimension when exposed to a changing magnetic field, and a piezoelectric material is one that produces an electrical charge when it is deformed (twisted or stretched). The magnetostrictive and piezoelectric materials available to meMetglas and PZT, respectivelywere not the most effective materials of their kind, but they were the only ones the laboratory was able to give me, so I had to try to make them work. The Metglas and the PZT components were connected with an epoxy binder. The idea was that when the device was exposed to a changing magnetic field, the Metglas portion would change its dimensions, causing the PZT portion to change shape and thus produce a measurable voltage.
Bruce Miller, Wolfram Research
10 years ago
There is no existing database of this in Mathematica. It seems likely that there is an archive of this sort of information
. I do not know where.
For how to get Mathematica to measure and record magnetic field data, you might start with the recent posts about
on the community and google the web for pages about simple projects to measure the Earth's magnetic field. I suspect that the simple electronics for field measurements could be connected to an R.Pi computer and that connected to a computer running Mathematica.
That is beyond what I have experience with.
To clarify, (a) was not a option, it was part of the whole, large project.
10 years ago
Thank you for your reply!
I was wondering, for the option (a) you provided, does Wolfram Mathematica record magnetic field data? Is there an existing database of this in Wolfram Mathematica?
Bruce Miller, Wolfram Research
10 years ago
This is a big research project. For a school science fair project, would just a demonstration of the idea be enough?
Think about breaking the project into sections:
a) obtain accurate measurements of the Earth's magnetic field over a long time for many locations where earthquakes have happened,
b) mark when earthquakes happened, and look for similar changes in the magnetic field measurements before
eathquakes in different places,
c) write a Mathematica code that filters data for that sort of change.
The data for (a) is probably available, but you might have to write a lot of letters asking how to obtain copies.
The author of the paper at http://cty.jhu.edu/imagine/docs/Sensing_Danger.pdf might be willing to give suggestions,
or the references at the end might point to web sites with it.
A lot of people are working on (b) already.
A demonstration of (c) might be enough. Take sample data from a paper and show how you could look for unusual changes.
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