Is there a formal name for a concept or principle regarding the unexpected consequences of an incident due to the scale of the event? I could probably word that better but, for example, 9-11 conspiracy theorists rely on figures suggesting the fire in the twin towers could not have been hot enough to damage the steel substructure enough to collapse. But we have no comparable event to relate this attack to. Taking into account whatever structural damage would have occurred as well as the wind that might have fueled the fire, increasing temperatures, there just seems that there could be numerous factors on a large scale that are easy to miss, mistake, and/or miscalculate. I was also thinking the same could be true in the global warming controversy. There's a practically infinite set of circumstances involved and we're simply not capable of accounting for all of them.

global warming isn't a controversy

I didn't say it was. I said the "global warming controversy".

There is a name for this sort of thing: It's known as being an idiot.

That's nice. However, I would like to know if there is a more definitive, established, principle to use to refute conspiracy theorists.

http://en.wikipedia.org/wiki/Unintended_consequences

Windfall, blowback, Murphy's Law...

Yeah, but that doesn't seem to specifically refer to physical science.

Oh I'm not too sure about that. There is a big difference really between a conspiracy theorist and someone who has actual scientific evidence, though.

Yeah but if you look at the 9/11 attacks scientists on one side of the conspiracy will claim that the towers couldn't have fallen like that for various reasons. That the Pentagon couldn't have been struck by an airplane for various reasons. Scientists on an opposing side will make their case as well. They all use science to base their opinions. I'm assuming that there is scientifically accepted acknowledgment that, basically, when numerous incalculable circumstance are involved the opinion is, essentially, incomplete. My wording could be off but that is why I'm asking if such a principle or concept exists. I'm going to be surprised and disappointed if one doesn't.

As I've thought about this I'm thinking the better way to ask is if there is an established concept or principle that describes a situation where the data is either incomplete or too excessive in volume to accurately predict an outcome?

9/11 is not an example of an 'incomplete opinion'. It's an example of idiots selectively ignoring facts because they hate George Bush.

Thank you for expanding on my point.

Despite the examples you chose, I think the concept you're trying to name is just a simple "insufficient data"

'complexity'

I chose those examples because they seem to be two instances where scientists of differing opinions all rigidly believe they are correct. There must be some concept within science that acknowledges the unpredictable nature of events where we cannot fully understand the cumulative effects of a large number of factors.

Language doesn't always have to be pretentious to be meaningful. Scientists can use common words, too.

Also, the scientists who disagree tend to be disagreeing with things that are NOT IN THEIR FIELD.

I would trust a apprentice carpinter in their first year more than an Expert in Bacteriology when it comes to buildings and structural integrity.

This, or just "too many variables."

9/11 conspiracy theories are not a good example. They're the result of one person making an unscientific statement ("only controlled demolitions look like this, ever") or a true but misleading scientific statement ("steel doesn't melt before X degrees") and several more people who are incapable of intelligently evaluating the original statement just running with it.

Actually, Wookie, this is the exact definition of Chaos Theory, a name which sounds cool and EXTREME, but actually refers to a simple phenomenon: When an equation has too many variables working together in too many complex ways, then attempts to predict the outcome of the equation become less and less accurate. Just missing or misinterpreting a tiny amount of data could have tremendous repercussions in the long run.

One popular metaphor is the "butterfly effect", where a perfect model of the world is created in a computer program that accounts for the movements of every individual creature, the temperatures of every object, the density of every pocket of air, and every single other thing in the world save for a single butterfly in china. This model is used to predict the weather a week from the day it's turned on, and produces almost exact results, any tiny fluctuations either ignored or assumed to be the result of minor misinterpretation of data. The same model, still missing the butterfly, is cranked ahead a week and produces very very accurate results, but the margin of error grows. The incorrect readings are again considered the result of human error in application, or perhaps a minor error due to some computer glitch. This repeats again and again for years, until decades later it's predicting mostly sunny weather in Houston, while hurricanes ravage the gulf coast.

The same thing applies to real world concerns like this. Every scientist has their own interpretation of the data, enhanced and limited by their disciplines. Every layman looks at the data and is overwhelmed, clinging to the big important things like the temperature of burning jet fuel or the wind speed that morning while ignoring or misunderstanding less obvious data like the pattern of the blast or the dissemination of burning debris. Where one model would predict a standing building, another would predict a falling building, simply because some data was overlooked or misinterpreted. Tiny differences in understanding and observation, the unique compression artifacts of a video image or the slight miscalibration of a thermal sensor, all could lead two experts to entirely different conclusions, due to chaos theory.

-And if you scaled 9/11 up to cover the entire planet and replaced the towers with polar ice caps, then you have global warming, which has the same sort of thing at work.

The problem with conspiracy theories, in terms of logic, is that they usually start with a conclusion and then find premises that suit them. What that means is:



Which is an invalid statement, obviously.

Also, regards fire:

http://www.civ.ed.ac.uk/research/fire/public_html/Cardington/main.pdf

Full scale fire tests of a building (admittedly there is the difference of scale, but the mathematics behind steel behaviour in fire is well established) done in the hangar at Cardington, which is so large it's where they filmed all of "The Narrows" in Batman Begins. It's a hangar designed to house Zeppelins if you're interested.

On the 9-11 tangent the findings as I understand them goes like this:

1. Fire gets hot, like ULTRAMAN'S LASER EYES hot.
2. Steel beams which ordinarily provide buckling restraint to the columns lose the ability to do so due to event described in point 1.
3. Steel columns now have effective lengths (http://en.wikipedia.org/wiki/Buckling - in particular look at the first photograph) greater than their intended design
4. Columns fail, initiating a "pack of cards" collapse similar in principle (but not origin) to that of the collapse at Ronan Point (http://en.wikipedia.org/wiki/Ronan_point). In the business we would typically call it a "progressive collapse". Some might call it "disproportionate collapse", but in the case of WTC I'd say that the collapse was, sadly, proportionate to the cause.

As for your scale question, dunno. I know about steel buildings in fire though.

The first things that came to my mind are Gödel's incompleteness theorems

There's two interesting phenomena regarding the macro results of random events, chaos theory and emergence. Weather systems are chaotic in that it's basically impossible to predict what's going to happen beyond a certain threshold (3-4) days. Emergence is basically the opposite, even though the state of a system could be completely random, the interactions of the various parts (which could be probabilistic themselves) can give rise to a very predictable result. A good example is the Greenberg-Hastings cellular automata, even with a completely random starting state, it'll nearly always form a recognisable pattern within a handful of generations, and will nearly always end up following identical repetitious states after a number more.

With regards to global warming, the individual causes and events may be largely unpredictable and random, but the end result might well be completely predictable. I'm no climate change scientist so I can't speculate further. But the main lesson (and one that evolution has taught us time and again) is that random events don't always have chaotic outcomes.