not sure how to answer this question, class has no matlab book and is only 40 min a week.

In petroleum industries, it is common that the molecular weight of an oil fraction is unknown and thus must be estimated by using a correlation. A correction that is widely used is developed by Riazi and Daubert, which is also referred to as the API (American Petroleum Institute) method. The correlation can be applied to hydrocarbons with molecular weight ranging from 70-700, which is nearly equivalent to boiling point range of 300-850K, and the API gravity range of 14.4-93. This molecular weight (M) correlation is givenas a function of the average boiling point (Tb) and the specific gravity at 60 °F (SG) of the oil fraction of interest as follows:

M=42.965*exp(2.097x10^-4 *Tb-7.78712SG+2.08476x10^-3 *TbxSG)Tb^1.26007SG^4.98308

where Tb is in K and SG is related to the API gravity (API) SG=141.5/(API+131.5)

a) Estimate the molecular weight of an oil fraction that has an average boiling point of 344.7 °C and an API gravity of 50.

b) Plot on the same graph M vs. Tb(400≤Tb≤600K) with API gravity=20, 40, and 60.

i'm pretty sure i figured out part a) but not sure how to get the different API on to the same graph

[dpb]

To add to an existing plot use

hold on  % doc hold for details...

[Joshua Pingleton]

MikeG your my hero bro for asking this question on the internet. Go Pokes!!!

Answer 1

[KSSV]

SGfun = @(API) 141.5/(API+131.5) ;
Mfun = @(Tb,SG) 42.965*exp(2.097*10^-4*Tb-7.78712*SG+2.08476*10^-3 *Tb*SG)*Tb^1.26007*SG^4.98308 ;

Tb = 344.7+273 ;
API = 50 ;
%%a
SG = SGfun(API) ;
M = Mfun(Tb,SG) 

%%b
figure
hold on

Tb = 400:600 ;
API = [20, 40,60] ;

for i = 1:length(API)
    SG = SGfun(API(i)) ;
    for j = 1:length(Tb)
        M(j) = Mfun(Tb(j),SG) ;
    end
    plot(M,Tb)
end
legend('API=20','API=40','API=60')

[Joshua Pingleton]

KSSV, Thank you so much man!!! I also had the same question.

[Jan]

Run time does not matter here. But I like to mention that it is much cheaper to use the constant 2.097e-4 instead of the multiplication and very expensive power operation 2.097*10^-4.