Fitting Data to a Prescribed Equation
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I have an equation of the following form
Nu=A*(0.75+0.013*ALFA)*(RE)^(m)*0.711^(1/3)
Where ALFA and RE are a set of prescribed values
ALFA=0 5 10 15 20 25 Re= 200000 300000 400000 500000
Nu is a set of values obtained from simulations
I know that my equation should look like the one previously shown, I would like to solve for the coefficients A and m so my prescribed values validate the equation
Any help please?
7 Kommentare
dpb
am 22 Okt. 2017
How do you expect to use the resulting correlation; as function which variables?
You use nonliner fitting; convert the measured data to values of the correlation at the points for which you have the values at those points for which you have the data.
You may have issues of correlation/estimation depending on the locations of those points; you've not given that much info; try it and find out what happens...
As for which tools to use for the fitting, depends on which toolboxes you have; there are routines in either the Curve Fitting or the Statistics TBs or you can use the fminsearch routine in base product having neither of the above....
Abdallah Samad
am 22 Okt. 2017
Kaushik Lakshminarasimhan
am 22 Okt. 2017
Do the entries in the table correspond to values of Nu?
Abdallah Samad
am 23 Okt. 2017
dpb
am 23 Okt. 2017
Also, please clarify the equation -- is the power term at the end
RE^[m*Pr^1/3]
or
(RE^m)*Pr^1/3
or yet some other grouping? My initial fitting with the first isn't promising at all...
Abdallah Samad
am 23 Okt. 2017
Antworten (1)
Nicolas Schmit
am 23 Okt. 2017
Bearbeitet: Nicolas Schmit
am 23 Okt. 2017
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