Oil data reduction

AO1958 · Jan 28, 2012

Dear All,

I am trying to find an equation to fit the data of oil viscosity properties.

As I suppose many of you know, the main problem is due to the large excursion of values in function of temperature.
I have found this interesting post thread391-287467.

I have then tried to utilize the equation

viscosity = A*exp(B/T),

without great success, since I can't fit the properties to this equation, nor the formula of the attempt to realize a logarithmic interpolation - kind of the spreadsheet in the quoted thread - seems to work, since I am having large deviations (even 700%) in the intermediate points.

Please, I would like to understand if, according to your experience, these equations fit to every oil, or only to some oils, or if you could recommend me some different solutions to utilize.

Thanks

electricpete · Jan 28, 2012

Attached is a spreadsheet that will build an ASTM D341 curve of viscosity vs temperature based on two data points (viscosity at two temperatures).

The tabs of interest will be the first (leftmost) 6 tabs. The last (rightmost) 4 tabs relate to interpretting viscosity index.... not your question.

Referring to the task of th first 6 tabs, I have cut/pasted an my explanation of how it works:

electricpete said:
Tab CurvePlotInput and CurvePlot
from ASTM D341:
log (log(v + 0.7)) = A - B log T <eq1>
where v is kinematic viscosity in cSt, T is temperature in K, log is base 10 log,
and A and B are unknown constants which can be solved from two data points (v1,T1), (v2,T2).
SOLVE FOR A AND B USING THE TWO DATA POINTS AS FOLLOWS:
Plug the data from the first ppoint v1,T1 into eq1:
log (log(v1 + 0.7)) = A - B log T1 <eq2>
solve eq2 for A
A = log(log(v1+0.7)) + B*log(T1) <eq3>
plug the data from the second point v2,T2 int eq1
log (log(v2 + 0.7)) = A - B log T2 <eq4>
substitute into eq4 the value A from eq3
log (log(v2 + 0.7)) = [log(log(v1+0.7)) + B*log(T1)] - B log T2 <eq5>
solve eq5 for B
B = {log (log(v2 + 0.7)) - log(log(v1+0.7)) } / (logT1-logT2) <eq6>
solve equation 4 for A
A = log (log(v2 + 0.7)) + B log T2 <eq7>
solve eq 1 for v
v = 10^(10^(A-B*LOG(T)))-0.7 <eq8>
equation 8 using values of A from eq7 and B from eq6 give us v as a function of T.

There have been some threads before that jmw initiated on a similar subject, going into considerable detail.

=====================================
(2B)+(2B)' ?

PaoloPemi · Jan 29, 2012

if you have experimental data (as viscosity at different temperatures) and need to find a suitable correlation (for data regression) a simple way to proceed is to test different correlations and verify which provides the best fitting, you should be able to do that even with Excel (with data regression for multiple parameters utility), I prefer to use the procedure in Prode Properties ( for download see

http://www.prode.com

) , this permits to calculate the parameters for several predefined correlations including all those included in DIPPR

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Oil data reduction

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