Errors prove accuracy of short-circuit calculator
ArCad's short circuit calculator can now handle input data tolerances and tracks error propagation.
ArCad's short circuit calculator can now handle input data tolerances and tracks error propagation.
The company has implemented a parameter of tolerances to its service, which has an effect on final results within the analysis.
Many other procedures do not take into account room for error, which can distort final values.
In an ideal world, it would be possible to eliminate tolerances so that values can be precise without any assumptions.
But the term "error" in science and engineering does not mean a mistake.
Rather it means inevitable uncertainty that happens because empirical measurements cannot be perfectly corrected.
All measurements in practice and even in principle have some error associated with them; no measured quantity can be determined with infinite precision and zero deviation.
Without proper error analysis, no valid scientific conclusions can be drawn.
In fact, wrong results can happen if error analysis is ignored.
By including room for error, calculations can consider all tolerances - both plus and minus.
Another factor to consider is reducing or extending values to their most significant digit.
This allows answers to be more accurate, and reveals the hazard levels to be more precise.
In other words, the calculator validation procedure, input data analysis and algorithm for capacity calculations ensure that the results do not claim to be more precise than can be justified by the input data accuracy.
Typical commercial software packages have more interfaces and graphics content, which make them more appealing and expensive.
ArcAd's online tool is user friendly and is offered at a reasonable price.
It also comes accompanied with calculation examples showing the procedure in action.
The ArcAd online short circuit calculator carefully handles input data tolerances and tracks error propagation through massive computations associated with short circuit analyses.
The following are some of the rules for approximate calculations adopted by the calculator.
When quantities are being added or subtracted, the number of decimal places (not significant digits) in the answer should be the same as the least number of decimal places in any of the numbers being added or subtracted.
In calculations involving multiplication and division, the number of significant digits in an answer should equal the least number of significant digits in any one of the numbers being multiplied or divided.
When finding the square root of a number, the result has the same accuracy as the number.
When performing multiple-step calculations, keep one more significant digit than required by rules above in intermediate results.
This digit is dropped off the final result.
In this manner, phenomenon known as "round-off error" is effectively avoided.
And if one of the original factors has more significant digits than the other, round the more accurate number to one more significant digit than appears in the less accurate number.
The extra digit protects the answer from the effects of multiple rounding.
In conventional error propagation theory, errors always increase when quantities are added, subtracted, multiplied, divided or operated in any other fashion.
That is that the errors always combine in the worst possible way.
The calculator hard coded error propagation rules take into consideration the fact that the error in one variable happens to cancel out some of the error in the other variable and so, on the average, the total error will be less than the sum of the errors in its parts.
It can be proved that the results calculated using the rules above contain significant digits only.
ArCad strongly believes that if the resulting fault current margin error cannot be quantified, it is not engineering - it is only guesswork.
As far as the company is aware, none of the available competing products performs proper error analysis.
It wouldn't be a problem if most accurate system equipment data were available.
Experience shows that by far most real world studies are built on approximate and therefore more or less accurate input data.
The concept of precision is very important indeed and can impact results in surprising ways.
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