Good afternoon.
This is a great conference,
it takes a huge amount of work and an effort to organize an event like this,
so, to all the organizers, thank you very much.
I'm glad...
I'm glad to be here today and talk to you about the instrumentation,
data acquisition, data transformation and analysis.
My job with the SAFIRE team is to not only collect data from the experiment
but the collect it in such a way
so that it can be used after an experiment has been done
for our team to more easily see relationships between various events
that are occurring during the experiment.
Further to this point is to also be able to pull the data from an experiment,
so we can do detailed analysis on those relationships.
In these data and the integrity...
it is these data and the integrity of these data,
which is vital to the quality of the work that we do.
But first, I would like to talk to you about what is an experiment,
how experiments were done in the past and how the SAFIRE team does them today.
An experiment is a procedure to test a concept or hypotheses.
The reasons why we do experiment is to gain insight
into what causes are involved in an observed effect,
which may support the hypothesis or show that the hypothesis is false.
Galileo's hypothesis was that on Earth all object fall at the same rate,
but prior to these most people thought that the heavy ball should drop faster.
Galileo found that his hypothesis was correct,
but the big question became, why?
Why are they dropping at the same rate?
It was not until Sir Isaac Newton defined the law of gravity,
that scientists started to understand why the balls fell and the same rate.
So, as science progresses and experiments become more sophisticated
the causes of effects become more difficult to determine.
This also means it is more important to conduct a robust or repeatable experiments
and use measurement devices capable of high degree of accuracy.
It also becomes more challenging to clearly show to everyone
the causes of a particular effect.
I want to introduce the important concept of time in an experiment
we start over the beaker of cold water and we are going to heat the water one way
and then we will hit the water by any another method
you need to add a stopwatch
and the thermometer,
so we can see how long it takes to boil the water.
Now if you added the heat
we will watch and document how long it takes the water to boil.
After approximately 10 minutes, the water comes to full boil.
But then I ask myself, is there more effective and quicker way to hit the water?
I had the idea that if you could use the afterburner of an American F18
that might be a more effective method to heat the water.
I discovered that, in fact I was right.
It took approximately 0.05 nanoseconds, to not only hit the water, but vaporize it.
and the beaker with it.
I suggested to Monte that we should keep the F18,
but he was mumbling something about budget constraints.
Now, back in today, when scientists work in the laboratory
they had to document everything manually,
as experiments got more complex
it required more scientists to record and collect data
they created procedures on how to collect the data.
Aligning the data to the same time line was a challenge in the past
as it is today.
Then plott of the data and finally do analysis of the data
to determine the cause of the effects.
So, as experiments become more complex
the necessity of more sophisticated methods of measurement
become vital to the success of the experiment.
Let us have a look at the progress of the data acquisition
specifically in this case capturing of what have seen.
This picture of the Egyptian Sun was most likely creative with a hammer and chisel.
In the mid 1800's an astronomer and physicist Warren de La Rue
design and built the first cube photograph, used to photograph the sun's corona.
For his time this was a major scientific breakthrough,
since up until this time no known photographs of the sun's corona ever existed.
But as we all know advances in the technology of the ions have help humanity in many ways
and we now have through the hard work of Lockheed Martin and NASA
the Solar Dynamics Observatory.
What we are looking at
is a full disk multi-wavelength Extreme Ultra Violet image of the Sun,
taken by SDO on March 30th 2010.
For scholars trace different gas temperatures,
and these temperatures are represented in their own images
as the Olight spectrometer returns this light spectra.
At the top of this graph we are looking at the SDO broad light spectrum from the Sun.
Below we are looking at the actual light spectra
converted to specific light wavelength peaks,
every element and it's very specific light spectral signature, when it is ionized.
And it is by using optical spectroscopy you can tell
what elements make up the light from the Sun.
or, in our case, the light is coming from SAFIRE
this is a SAFIRE plasma discharge and the light we get.
And this is an example of spectral signatures we get back from the optical spectrometer.
The SAFIRE experiment is based on Monte's announces of the electric Sun model
of charged plasma affecting the matter of a different electrical potential.
So, we introduce electrical power in the form of voltage and current
than chamber pressure and plasma gas types.
And when these factors are introduced into the experiment,
then we measure these responses:
Plasma voltage and current; Chamber pressure; Plasma gas types;
Light spectra; Langmuir probes voltages; Temperature;
Video capture; Photography.
Here is a picture of phase one of SAFIRE
showing the array of many instruments we are using to acquire data.
As each instrument is acquiring data
we also recorded video of each instrument computer monitor.
This is the mass spectroscopy,
this is a screen of voltage current and pressure gauge,
this is a screen of the light spectra.
And we also conduct synchronize video recording
of the changes in the SAFIRE chamber in real time,
this then consolidate all the video feeds into one master video,
as a video recording of each experiment.
This is the grand tour of the video, it helps our team very effectively recognize
the points of interest that happened during the experiment.
Let us investigate how data acquisition devices work.
You have seen some of the results, now let's take a look at the vorish under the root.
There is an analog-to-digital converter at the heart of each data acquisition device.
The controller connects the data acquisition device and collects the digital data.
The computer communicates with the controller,
reach the controller's data and stores the data.
The data acquisition path follows from the data acquisition device
through the controller into the computer where all the data is stored.
A data transformation engine takes all the data from the experiment
and transforms the data into comprehensive graphical overlays
and this is to help the SAFIRE team to analyze the data
looking for causes of the effects the observer of the time.
Here we have thousands of data points of the plasma current,
now be overly the voltage,
and high pressure measurements,
and high vacuum pressure measurements and these are just a few,
there are thousands and thousands of data points.
But what we see is that in this region, for example,
after the pressure drop in the chamber, there is a huge spike in voltage and current.
The data transformation engine allows us
to zoom into these regions with extremely high resolution
and we see that both, the voltage and current,
are discharging out in this region of the graph.
What we discovered was quite profound, that during a short time
SAFIRE had an intense plasma discharge that measured over 2 million watts.
What is so profound is that we limited the input power to only 1800 watts.
The transformation engine allows us to zoom in
and examine in extremely high detail these points of interests.
It is these kind of information that helps us determine
what factors need to be used in the design of experiments
that Dr. Paul Anderson will present now.
Thank you.
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