Prodigy; a rebuttal for some such "twiddle twaddle" as that Hp2g article describes...note the bolded part(s).
All boils down to -"dont know why it works and dont care. Just care that it works." This read was given to me on another forum as suggested reading. Again just the bold parts here have revelance to the "Impossibe" argument regarding mpg claims.
Momentum, Kinetic Energy, and Arrow Penetration
(And What They Mean for the Bowhunter)
By
Dr. Ed Ashby
Excerpt from:
Prologue
"To understand the relationship between an arrow’s kinetic energy, its momentum, and their implications towards the ability of a hunting arrow to penetrate tissues, one must rely on the laws of physics. This discussion cannot be made totally uncomplicated. The following is an attempt to impart a fundamental understanding of the applicable principles of physics, as simply as I can, and relate them to the results from actual field data.
Before delving into the deep abyss of the physics involved in arrow penetration, it is appropriate to first take a few moments to discuss the field data, and the logic behind why it is collected in the manner that it is.
Judging from questions I receive, this appears to be a very misunderstood aspect of the study of terminal ballistics. It is, in many aspects, more akin to forensic medicine than to laboratory science. The aficionado of the many forensic medical shows, now so popular on television, will recognize the methodology. One starts with a real event, something known to have occurred, and then uses pure science to determine and explain the “how and why’ of the incident.
Penetration data collected from real shots, into real tissues, is not a static measurement. Outcomes differ from shot to shot, as the uniformity of tissues encountered change. In the real world it is impossible to control all the variables, and one does not wish to do so. Those variables do exist. They will be encountered.
The scholar of abstract science will cite that this testing methodology includes too many variables, but it is precisely because of the multitude of variables that it is necessary. When dealing with infinitely complex variables, only ‘outcome driven’ information analysis, from a multiplicity of data, provides usable results. This is why the medical community commonly uses ‘outcome driven’ studies.
A commonplace example of these differing test approaches occurred with the development of automobile air bags. Engineers did enormous static testing with crash dummies, controlling all variables, before air bags were introduced.
After the introduction of air bags into production automobiles, studies showed that significant numbers of adult humans were being injured, and sometimes killed, by air bags during their deployment. An even larger number of children were being injured or killed. Static testing had indicated the deployment force would be safe. The ‘reality’ outcome was not as the static testing had predicted.
Outcome studies of air bag performance, in real automobile crashes, with real people on board, pinpointed the incidences where both serious and fatal damage was caused to humans by the air bag. It delineated the tendencies; when the events were likely to occur.
The static test standard was a male, of 160 pounds weight, seated normally within the car. Observed injuries and deaths occurred when occupant size was below the ‘average size’ that had been used in the static studies to determine the safe force levels exerted upon the various parts of the body during air bag deployment AND when the occupant was located closer to the air bag at time of deployment than the ‘static testing standard’ (as with persons using a cushion or pillow behind their back while driving or riding).
The frequency of occurrence of these events was tracked in the outcome studies, and found to have a significant prevalence. Then researchers turned to the pure sciences to find the explanations for the events, which had now been shown to occur in the real world. Force of impact, in relation to both occupant size and position at time of impact, was the culprit.
The force of air bag deployment was simply too violent for human tissues, under particular sets of circumstances, which did occur in the real world application of the air bags. The force of air bag deployment was modified. Outcome analysis of air bag deployment force continues today, and the regulations and guidelines are still being modified, based upon outcome driven studies.
The above example pinpoints the major differences in methodology between the measurements of pure laboratory science and the outcome driven method of deriving conclusions. In laboratory science, one starts with pure measurements and tries to predict future events. Outcome driven studies start with events known to occur; then looks for the scientific explanations of how and why it occurred.
Outcome driven studies factor in the probability of occurrence when a large number of independently acting variables are randomly introduced into the observed results. Another way of saying this is that outcome driven studies include the Murphy Factor; to find out what can happen; when it is likely to happen; and how often it actually happens.
Another major difference between laboratory science and outcome driven studies is that outcome driven results have an ‘acceptability level’. Their validity does not have to meet any level of ‘engineering credibility’; (but)the ability to be repeated at will, each and every time."
Bottom line is - Nothing ole Rob says changes the results.
P
AI
