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Monte Carlo simulation of a heat exchanger

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Something not often covered in school is the fact that measurements aren't a single number. I have lots of data from many different types of instruments and assure you that the values are rarely distributed normally or even symmetrically. If you don't consider uncertainty (both random and systematic) you are taking on risk. At a billion dollar power plant or manufacturing facility this can be financially devastating. One of the simplest examples is a heat exchanger. The flows and temperatures are only certain to with limits. You should familiarize yourself with uncertainty and confidence intervals. One way of illustrating this is with Monte Carlo, as in the attached spreadsheet. For this simple example, which assumes the measurements are all normally-distributed, the Monte Carlo results fall right on top of the theoretical ones with only 65,535 cases.



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