Pulse Motors: Using the SNOT to Demonstrate a "True Experiment"
A true experiment is a system where a researcher varies an Independend Variable and observes its effect on a Dependent Variable, holding other factors constant. The true experiment is performed to test a well-formulated, potentially falsifiable hypothesis that is derived from some over-arching theory.
Here I use the mysterious SNOT (simple non-overunity toy, which has appeared in a couple of previous alt.snakeoil light-hearted spoofs) to demonstrate something that we very rarely see in the “free energy – overunity” research field: a true experiment.
The over-arching theory in this case is something like this: Even though magnetic fields are supposed to be conservative, there may be some arrangement of magnets, ramps, gates, shields, etc. that makes it possible to create a self-running, looping system that somehow replaces enough of the inevitable energy losses to keep on running without outside supply of power from conventional sources. This is the SMOT theory. (Simple Magnetic Overunity Toy).
People have been trying to “prove” this theory since permanent magnets in the form of lodestones were discovered many hundreds or even thousands of years ago. Mostly they try to do this by building apparatus, stacking things onto it, and spinning or elevating or cocking magnets or weights by hand, and mostly they draw conclusions based on subjective impressions of performance, without making any comparisons to a “baseline” or control condition, without a clear hypothesis, without operationalization of constructs, without instrumental data, and without even the most elementary use of statistics. In short, they don’t do real true experiments.
One hypothesis that falls out from the SMOT theory is this: If a proper arrangement of magnets, ramps, etc is produced, then it will have an effect on the average looping speed of the apparatus. A “null” hypothesis to be tested is the inverse of this: If I arrange magnets (ramps, etc) in a looping system, then there will be no effect on the speed of the loop.
These simple, clearly stated “IF-THEN” statements are proper experimental hypotheses, and here I illustrate one method by which such statements can be tested objectively to see if there is any support for them, or if they can be falsified. Properly speaking, one tests the “null” hypothesis, and if it fails to be supported, the positive hypothesis can be considered to be supported.
So let’s test this null: If I have a system that loops with a known input of energy, and I use the speed of the loop as the Dependent Variable that will tell me something about the performance, then an additional magnet placed near the loop will not affect the speed of the looping.
So to test this, I obviously need a few things. The first being a system that does in fact loop along stably, under external power. The SNOT pulse motor was developed with this in mind.
Next I need a precise and accurate way to measure the Dependent Variable, in this case the time it takes to make a complete loop. The Philips PM6676 Frequency Counter’s “period” function provides more than enough precision and accuracy to provide the data we need.
Finally, I need to be able to switch from the Control baseline condition (no external magnets) to the Experimental condition without otherwise perturbing the system and I need to hold other “third variables” constant or account for them.
And, post-experiment, I need some objective way to evaluate the data from the system, in order to be able to draw some conclusion as to whether or not the “null” hypothesis under test has been supported, or not. Elementary descriptive and inferential statistics serve this function.
So I set up, do some runs, record some figures, take the means and standard deviations and draw a tentative conclusion.
The stats from the trials and the schematic for the electronics module are at the very end of the video, so please don’t go away until you’ve seen them. And please don’t go away mad.
Any true experiment is bound to do several things. It can point the way to further research by allowing the researcher to generate new hypotheses to test. (I mention a few of them in the video, like the weight of the magnet warping the board, etc.) It can result in soundly falsifying the null, thus lending strong support to the “positive” hypothesis. Or it can confirm the null, which is bad for the theory that generated the original hypothesis in the first place.
A true experiment is like a filter that lets FACTS through and filters out the BS from claims of overunity performance.
