Thursday, February 5, 2009

CFD Integrity

Quantifying uncertainty in simulation predictions is something at which most modelling communities fall short, and the Computational Fluid Dynamics community is no exception. There is plenty published on uncertainty estimation, but the state of the practice lags the state of the art considerably in this area.

It does not help matters that it is very hard and expensive to do a thorough job of quantifying the uncertainty of the result of a complex calculation. If it takes a week to get one data point, doing a Monte Carlo sensitivity analysis is probably out of the question, and differentiating your code could take years. It also doesn't help that many of the decision makers who are the consumers of the CFD product don't really want to hear how uncertain the results are, often they want pretty pictures and a warm fuzzy feeling (colorful fluid dynamics is great for marketing too).

I highly recommend the article on quantifying uncertainty by P.J. Roache. It is well written, and it is a special treat to read a CFD paper with a sentence like,

Clearly, we are not interested in such worthless semantics and effete philosophizing, but in practical definitions, applied in the context of engineering and science accuracy.

Roache is addressing the hand wringing made popular in the "soft" academic communities about the ability to define "truth".

Other than being a good basic engineering practice, making sure users of your results are well aware of the uncertainty is a matter of integrity too. There's an obligation that comes with expertise. Boole's words on the subject still ring true. More recently Feynman said much the same thing about integrity as an expert advising others:

I'm talking about a specific, extra type of integrity that is not lying, but bending over backwards to show how you are maybe wrong, that you ought to have when acting as a scientist. And this is our responsibility as scientists, certainly to other scientists, and I think to laymen.

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