Please assist to resolve a updated requirement in multi-variables (inbuilt for function); it only undergo once update among the ten expected outputs, see line 7 and 60
    8 vues (au cours des 30 derniers jours)
  
       Afficher commentaires plus anciens
    
The SANAI2 function need only  (Qy0(1:34,1) input and D (to be updated accordingly as for function) and L (non updated). The Output be in DD (table) to assist observation analytical results etc. However all variables of DD in rows not changing as my expectation as 1st row to 10th row, seen executed output tables and other relevant information, below; included not solution not found (10 times). Please assist to resolve the code problem. Thanks once again.
FUNCTION AND FOR ... WITH D=[ ] ....
function [Qy, DD, FUN] = SANAI2(Qy0)                                           
        tic,                                                                                                                    % matL=abs(matr);   [NodLp,pQ]=size(matr); 
        NodLp=41;  LP=5;   data1=4;     pQ=35; data2=data1+1+1;  Nod3=NodLp-data1-LP;   p=pQ-1;  JJ=data1+Nod3+1;    HLD=0;
                                       ee=0.04;          vs=1.00001*10^-6;                                                       %format shortEng,            % L=matr(1,1:end-1);     D=matr(2,1:end-1);  
            D=[];          DD=zeros(10,p);         %
    for n=1:10
        L = [100	1350	900	1150	1450	450	850	850	800	950	1200	3500	800	500	550	2730	1750	800	400	2200	1500	500	2650	1230	1300	850	300	750	1500	2000	1600	150	860	950];
        D = [0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610
          ];
        Dia = [0.305	0.406	0.508	0.609	0.762	1.016	1.905]; szDia=size(Dia,2);
% Qy0(1:34,1)=5.53;
FUN=@(Qy)[(1.*Qy(3).*abs(Qy(3)*8.*L(1,3)*1./(9.81*3.14.^2.*D(1,3).^5).*(0.25.*(log10(ee./(3.7.*D(1,3))+2.51*3.14*vs.*D(1,3)./(4.*Qy(3)).*(0.25.*(log10(ee./(3.7.*D(1,3))+2.51*3.14*vs.*D(1,3)./(4.*Qy(3)).*(0.25.*(log10(ee./(3.7.*D(1,3))+2.51*3.14*vs.*D(1,3)./(4.*Qy(3)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(4).*abs(Qy(4)*8.*L(1,4)*1./(9.81*3.14.^2.*D(1,4).^5).*(0.25.*(log10(ee./(3.7.*D(1,4))+2.51*3.14*vs.*D(1,4)./(4.*Qy(4)).*(0.25.*(log10(ee./(3.7.*D(1,4))+2.51*3.14*vs.*D(1,4)./(4.*Qy(4)).*(0.25.*(log10(ee./(3.7.*D(1,4))+2.51*3.14*vs.*D(1,4)./(4.*Qy(4)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(5).*abs(Qy(5)*8.*L(1,5)*1./(9.81*3.14.^2.*D(1,5).^5).*(0.25.*(log10(ee./(3.7.*D(1,5))+2.51*3.14*vs.*D(1,5)./(4.*Qy(5)).*(0.25.*(log10(ee./(3.7.*D(1,5))+2.51*3.14*vs.*D(1,5)./(4.*Qy(5)).*(0.25.*(log10(ee./(3.7.*D(1,5))+2.51*3.14*vs.*D(1,5)./(4.*Qy(5)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(6).*abs(Qy(6)*8.*L(1,6)*1./(9.81*3.14.^2.*D(1,6).^5).*(0.25.*(log10(ee./(3.7.*D(1,6))+2.51*3.14*vs.*D(1,6)./(4.*Qy(6)).*(0.25.*(log10(ee./(3.7.*D(1,6))+2.51*3.14*vs.*D(1,6)./(4.*Qy(6)).*(0.25.*(log10(ee./(3.7.*D(1,6))+2.51*3.14*vs.*D(1,6)./(4.*Qy(6)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(7).*abs(Qy(7)*8.*L(1,7)*1./(9.81*3.14.^2.*D(1,7).^5).*(0.25.*(log10(ee./(3.7.*D(1,7))+2.51*3.14*vs.*D(1,7)./(4.*Qy(7)).*(0.25.*(log10(ee./(3.7.*D(1,7))+2.51*3.14*vs.*D(1,7)./(4.*Qy(7)).*(0.25.*(log10(ee./(3.7.*D(1,7))+2.51*3.14*vs.*D(1,7)./(4.*Qy(7)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(8).*abs(Qy(8)*8.*L(1,8)*1./(9.81*3.14.^2.*D(1,8).^5).*(0.25.*(log10(ee./(3.7.*D(1,8))+2.51*3.14*vs.*D(1,8)./(4.*Qy(8)).*(0.25.*(log10(ee./(3.7.*D(1,8))+2.51*3.14*vs.*D(1,8)./(4.*Qy(8)).*(0.25.*(log10(ee./(3.7.*D(1,8))+2.51*3.14*vs.*D(1,8)./(4.*Qy(8)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(9).*abs(Qy(9)*8.*L(1,9)*1./(9.81*3.14.^2.*D(1,9).^5).*(0.25.*(log10(ee./(3.7.*D(1,9))+2.51*3.14*vs.*D(1,9)./(4.*Qy(9)).*(0.25.*(log10(ee./(3.7.*D(1,9))+2.51*3.14*vs.*D(1,9)./(4.*Qy(9)).*(0.25.*(log10(ee./(3.7.*D(1,9))+2.51*3.14*vs.*D(1,9)./(4.*Qy(9)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(13).*abs(Qy(13)*8.*L(1,13)*1./(9.81*3.14.^2.*D(1,13).^5).*(0.25.*(log10(ee./(3.7.*D(1,13))+2.51*3.14*vs.*D(1,13)./(4.*Qy(13)).*(0.25.*(log10(ee./(3.7.*D(1,13))+2.51*3.14*vs.*D(1,13)./(4.*Qy(13)).*(0.25.*(log10(ee./(3.7.*D(1,13))+2.51*3.14*vs.*D(1,13)./(4.*Qy(13)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(14).*abs(Qy(14)*8.*L(1,14)*1./(9.81*3.14.^2.*D(1,14).^5).*(0.25.*(log10(ee./(3.7.*D(1,14))+2.51*3.14*vs.*D(1,14)./(4.*Qy(14)).*(0.25.*(log10(ee./(3.7.*D(1,14))+2.51*3.14*vs.*D(1,14)./(4.*Qy(14)).*(0.25.*(log10(ee./(3.7.*D(1,14))+2.51*3.14*vs.*D(1,14)./(4.*Qy(14)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(15).*abs(Qy(15)*8.*L(1,15)*1./(9.81*3.14.^2.*D(1,15).^5).*(0.25.*(log10(ee./(3.7.*D(1,15))+2.51*3.14*vs.*D(1,15)./(4.*Qy(15)).*(0.25.*(log10(ee./(3.7.*D(1,15))+2.51*3.14*vs.*D(1,15)./(4.*Qy(15)).*(0.25.*(log10(ee./(3.7.*D(1,15))+2.51*3.14*vs.*D(1,15)./(4.*Qy(15)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(16).*abs(Qy(16)*8.*L(1,16)*1./(9.81*3.14.^2.*D(1,16).^5).*(0.25.*(log10(ee./(3.7.*D(1,16))+2.51*3.14*vs.*D(1,16)./(4.*Qy(16)).*(0.25.*(log10(ee./(3.7.*D(1,16))+2.51*3.14*vs.*D(1,16)./(4.*Qy(16)).*(0.25.*(log10(ee./(3.7.*D(1,16))+2.51*3.14*vs.*D(1,16)./(4.*Qy(16)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(17).*abs(Qy(17)*8.*L(1,17)*1./(9.81*3.14.^2.*D(1,17).^5).*(0.25.*(log10(ee./(3.7.*D(1,17))+2.51*3.14*vs.*D(1,17)./(4.*Qy(17)).*(0.25.*(log10(ee./(3.7.*D(1,17))+2.51*3.14*vs.*D(1,17)./(4.*Qy(17)).*(0.25.*(log10(ee./(3.7.*D(1,17))+2.51*3.14*vs.*D(1,17)./(4.*Qy(17)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(18).*abs(Qy(18)*8.*L(1,18)*1./(9.81*3.14.^2.*D(1,18).^5).*(0.25.*(log10(ee./(3.7.*D(1,18))+2.51*3.14*vs.*D(1,18)./(4.*Qy(18)).*(0.25.*(log10(ee./(3.7.*D(1,18))+2.51*3.14*vs.*D(1,18)./(4.*Qy(18)).*(0.25.*(log10(ee./(3.7.*D(1,18))+2.51*3.14*vs.*D(1,18)./(4.*Qy(18)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(19).*abs(Qy(19)*8.*L(1,19)*1./(9.81*3.14.^2.*D(1,19).^5).*(0.25.*(log10(ee./(3.7.*D(1,19))+2.51*3.14*vs.*D(1,19)./(4.*Qy(19)).*(0.25.*(log10(ee./(3.7.*D(1,19))+2.51*3.14*vs.*D(1,19)./(4.*Qy(19)).*(0.25.*(log10(ee./(3.7.*D(1,19))+2.51*3.14*vs.*D(1,19)./(4.*Qy(19)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(0);...
     (1.*Qy(16).*abs(Qy(16)*8.*L(1,16)*1./(9.81*3.14.^2.*D(1,16).^5).*(0.25.*(log10(ee./(3.7.*D(1,16))+2.51*3.14*vs.*D(1,16)./(4.*Qy(16)).*(0.25.*(log10(ee./(3.7.*D(1,16))+2.51*3.14*vs.*D(1,16)./(4.*Qy(16)).*(0.25.*(log10(ee./(3.7.*D(1,16))+2.51*3.14*vs.*D(1,16)./(4.*Qy(16)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(17).*abs(Qy(17)*8.*L(1,17)*1./(9.81*3.14.^2.*D(1,17).^5).*(0.25.*(log10(ee./(3.7.*D(1,17))+2.51*3.14*vs.*D(1,17)./(4.*Qy(17)).*(0.25.*(log10(ee./(3.7.*D(1,17))+2.51*3.14*vs.*D(1,17)./(4.*Qy(17)).*(0.25.*(log10(ee./(3.7.*D(1,17))+2.51*3.14*vs.*D(1,17)./(4.*Qy(17)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(18).*abs(Qy(18)*8.*L(1,18)*1./(9.81*3.14.^2.*D(1,18).^5).*(0.25.*(log10(ee./(3.7.*D(1,18))+2.51*3.14*vs.*D(1,18)./(4.*Qy(18)).*(0.25.*(log10(ee./(3.7.*D(1,18))+2.51*3.14*vs.*D(1,18)./(4.*Qy(18)).*(0.25.*(log10(ee./(3.7.*D(1,18))+2.51*3.14*vs.*D(1,18)./(4.*Qy(18)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(19).*abs(Qy(19)*8.*L(1,19)*1./(9.81*3.14.^2.*D(1,19).^5).*(0.25.*(log10(ee./(3.7.*D(1,19))+2.51*3.14*vs.*D(1,19)./(4.*Qy(19)).*(0.25.*(log10(ee./(3.7.*D(1,19))+2.51*3.14*vs.*D(1,19)./(4.*Qy(19)).*(0.25.*(log10(ee./(3.7.*D(1,19))+2.51*3.14*vs.*D(1,19)./(4.*Qy(19)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(20).*abs(Qy(20)*8.*L(1,20)*1./(9.81*3.14.^2.*D(1,20).^5).*(0.25.*(log10(ee./(3.7.*D(1,20))+2.51*3.14*vs.*D(1,20)./(4.*Qy(20)).*(0.25.*(log10(ee./(3.7.*D(1,20))+2.51*3.14*vs.*D(1,20)./(4.*Qy(20)).*(0.25.*(log10(ee./(3.7.*D(1,20))+2.51*3.14*vs.*D(1,20)./(4.*Qy(20)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(23).*abs(Qy(23)*8.*L(1,23)*1./(9.81*3.14.^2.*D(1,23).^5).*(0.25.*(log10(ee./(3.7.*D(1,23))+2.51*3.14*vs.*D(1,23)./(4.*Qy(23)).*(0.25.*(log10(ee./(3.7.*D(1,23))+2.51*3.14*vs.*D(1,23)./(4.*Qy(23)).*(0.25.*(log10(ee./(3.7.*D(1,23))+2.51*3.14*vs.*D(1,23)./(4.*Qy(23)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(24).*abs(Qy(24)*8.*L(1,24)*1./(9.81*3.14.^2.*D(1,24).^5).*(0.25.*(log10(ee./(3.7.*D(1,24))+2.51*3.14*vs.*D(1,24)./(4.*Qy(24)).*(0.25.*(log10(ee./(3.7.*D(1,24))+2.51*3.14*vs.*D(1,24)./(4.*Qy(24)).*(0.25.*(log10(ee./(3.7.*D(1,24))+2.51*3.14*vs.*D(1,24)./(4.*Qy(24)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(25).*abs(Qy(25)*8.*L(1,25)*1./(9.81*3.14.^2.*D(1,25).^5).*(0.25.*(log10(ee./(3.7.*D(1,25))+2.51*3.14*vs.*D(1,25)./(4.*Qy(25)).*(0.25.*(log10(ee./(3.7.*D(1,25))+2.51*3.14*vs.*D(1,25)./(4.*Qy(25)).*(0.25.*(log10(ee./(3.7.*D(1,25))+2.51*3.14*vs.*D(1,25)./(4.*Qy(25)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(26).*abs(Qy(26)*8.*L(1,26)*1./(9.81*3.14.^2.*D(1,26).^5).*(0.25.*(log10(ee./(3.7.*D(1,26))+2.51*3.14*vs.*D(1,26)./(4.*Qy(26)).*(0.25.*(log10(ee./(3.7.*D(1,26))+2.51*3.14*vs.*D(1,26)./(4.*Qy(26)).*(0.25.*(log10(ee./(3.7.*D(1,26))+2.51*3.14*vs.*D(1,26)./(4.*Qy(26)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(27).*abs(Qy(27)*8.*L(1,27)*1./(9.81*3.14.^2.*D(1,27).^5).*(0.25.*(log10(ee./(3.7.*D(1,27))+2.51*3.14*vs.*D(1,27)./(4.*Qy(27)).*(0.25.*(log10(ee./(3.7.*D(1,27))+2.51*3.14*vs.*D(1,27)./(4.*Qy(27)).*(0.25.*(log10(ee./(3.7.*D(1,27))+2.51*3.14*vs.*D(1,27)./(4.*Qy(27)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(28).*abs(Qy(28)*8.*L(1,28)*1./(9.81*3.14.^2.*D(1,28).^5).*(0.25.*(log10(ee./(3.7.*D(1,28))+2.51*3.14*vs.*D(1,28)./(4.*Qy(28)).*(0.25.*(log10(ee./(3.7.*D(1,28))+2.51*3.14*vs.*D(1,28)./(4.*Qy(28)).*(0.25.*(log10(ee./(3.7.*D(1,28))+2.51*3.14*vs.*D(1,28)./(4.*Qy(28)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(0);...
     (1.*Qy(24).*abs(Qy(24)*8.*L(1,24)*1./(9.81*3.14.^2.*D(1,24).^5).*(0.25.*(log10(ee./(3.7.*D(1,24))+2.51*3.14*vs.*D(1,24)./(4.*Qy(24)).*(0.25.*(log10(ee./(3.7.*D(1,24))+2.51*3.14*vs.*D(1,24)./(4.*Qy(24)).*(0.25.*(log10(ee./(3.7.*D(1,24))+2.51*3.14*vs.*D(1,24)./(4.*Qy(24)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(25).*abs(Qy(25)*8.*L(1,25)*1./(9.81*3.14.^2.*D(1,25).^5).*(0.25.*(log10(ee./(3.7.*D(1,25))+2.51*3.14*vs.*D(1,25)./(4.*Qy(25)).*(0.25.*(log10(ee./(3.7.*D(1,25))+2.51*3.14*vs.*D(1,25)./(4.*Qy(25)).*(0.25.*(log10(ee./(3.7.*D(1,25))+2.51*3.14*vs.*D(1,25)./(4.*Qy(25)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(29).*abs(Qy(29)*8.*L(1,29)*1./(9.81*3.14.^2.*D(1,29).^5).*(0.25.*(log10(ee./(3.7.*D(1,29))+2.51*3.14*vs.*D(1,29)./(4.*Qy(29)).*(0.25.*(log10(ee./(3.7.*D(1,29))+2.51*3.14*vs.*D(1,29)./(4.*Qy(29)).*(0.25.*(log10(ee./(3.7.*D(1,29))+2.51*3.14*vs.*D(1,29)./(4.*Qy(29)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(30).*abs(Qy(30)*8.*L(1,30)*1./(9.81*3.14.^2.*D(1,30).^5).*(0.25.*(log10(ee./(3.7.*D(1,30))+2.51*3.14*vs.*D(1,30)./(4.*Qy(30)).*(0.25.*(log10(ee./(3.7.*D(1,30))+2.51*3.14*vs.*D(1,30)./(4.*Qy(30)).*(0.25.*(log10(ee./(3.7.*D(1,30))+2.51*3.14*vs.*D(1,30)./(4.*Qy(30)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(31).*abs(Qy(31)*8.*L(1,31)*1./(9.81*3.14.^2.*D(1,31).^5).*(0.25.*(log10(ee./(3.7.*D(1,31))+2.51*3.14*vs.*D(1,31)./(4.*Qy(31)).*(0.25.*(log10(ee./(3.7.*D(1,31))+2.51*3.14*vs.*D(1,31)./(4.*Qy(31)).*(0.25.*(log10(ee./(3.7.*D(1,31))+2.51*3.14*vs.*D(1,31)./(4.*Qy(31)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(32).*abs(Qy(32)*8.*L(1,32)*1./(9.81*3.14.^2.*D(1,32).^5).*(0.25.*(log10(ee./(3.7.*D(1,32))+2.51*3.14*vs.*D(1,32)./(4.*Qy(32)).*(0.25.*(log10(ee./(3.7.*D(1,32))+2.51*3.14*vs.*D(1,32)./(4.*Qy(32)).*(0.25.*(log10(ee./(3.7.*D(1,32))+2.51*3.14*vs.*D(1,32)./(4.*Qy(32)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(33).*abs(Qy(33)*8.*L(1,33)*1./(9.81*3.14.^2.*D(1,33).^5).*(0.25.*(log10(ee./(3.7.*D(1,33))+2.51*3.14*vs.*D(1,33)./(4.*Qy(33)).*(0.25.*(log10(ee./(3.7.*D(1,33))+2.51*3.14*vs.*D(1,33)./(4.*Qy(33)).*(0.25.*(log10(ee./(3.7.*D(1,33))+2.51*3.14*vs.*D(1,33)./(4.*Qy(33)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(34).*abs(Qy(34)*8.*L(1,34)*1./(9.81*3.14.^2.*D(1,34).^5).*(0.25.*(log10(ee./(3.7.*D(1,34))+2.51*3.14*vs.*D(1,34)./(4.*Qy(34)).*(0.25.*(log10(ee./(3.7.*D(1,34))+2.51*3.14*vs.*D(1,34)./(4.*Qy(34)).*(0.25.*(log10(ee./(3.7.*D(1,34))+2.51*3.14*vs.*D(1,34)./(4.*Qy(34)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(0);...
     (1.*Qy(1).*abs(Qy(1)*8.*L(1,1)*1./(9.81*3.14.^2.*D(1,1).^5).*(0.25.*(log10(ee./(3.7.*D(1,1))+2.51*3.14*vs.*D(1,1)./(4.*Qy(1)).*(0.25.*(log10(ee./(3.7.*D(1,1))+2.51*3.14*vs.*D(1,1)./(4.*Qy(1)).*(0.25.*(log10(ee./(3.7.*D(1,1))+2.51*3.14*vs.*D(1,1)./(4.*Qy(1)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(10).*abs(Qy(10)*8.*L(1,10)*1./(9.81*3.14.^2.*D(1,10).^5).*(0.25.*(log10(ee./(3.7.*D(1,10))+2.51*3.14*vs.*D(1,10)./(4.*Qy(10)).*(0.25.*(log10(ee./(3.7.*D(1,10))+2.51*3.14*vs.*D(1,10)./(4.*Qy(10)).*(0.25.*(log10(ee./(3.7.*D(1,10))+2.51*3.14*vs.*D(1,10)./(4.*Qy(10)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(11).*abs(Qy(11)*8.*L(1,11)*1./(9.81*3.14.^2.*D(1,11).^5).*(0.25.*(log10(ee./(3.7.*D(1,11))+2.51*3.14*vs.*D(1,11)./(4.*Qy(11)).*(0.25.*(log10(ee./(3.7.*D(1,11))+2.51*3.14*vs.*D(1,11)./(4.*Qy(11)).*(0.25.*(log10(ee./(3.7.*D(1,11))+2.51*3.14*vs.*D(1,11)./(4.*Qy(11)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(12).*abs(Qy(12)*8.*L(1,12)*1./(9.81*3.14.^2.*D(1,12).^5).*(0.25.*(log10(ee./(3.7.*D(1,12))+2.51*3.14*vs.*D(1,12)./(4.*Qy(12)).*(0.25.*(log10(ee./(3.7.*D(1,12))+2.51*3.14*vs.*D(1,12)./(4.*Qy(12)).*(0.25.*(log10(ee./(3.7.*D(1,12))+2.51*3.14*vs.*D(1,12)./(4.*Qy(12)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-4);...
     (1.*Qy(1).*abs(Qy(1)*8.*L(1,1)*1./(9.81*3.14.^2.*D(1,1).^5).*(0.25.*(log10(ee./(3.7.*D(1,1))+2.51*3.14*vs.*D(1,1)./(4.*Qy(1)).*(0.25.*(log10(ee./(3.7.*D(1,1))+2.51*3.14*vs.*D(1,1)./(4.*Qy(1)).*(0.25.*(log10(ee./(3.7.*D(1,1))+2.51*3.14*vs.*D(1,1)./(4.*Qy(1)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(21).*abs(Qy(21)*8.*L(1,21)*1./(9.81*3.14.^2.*D(1,21).^5).*(0.25.*(log10(ee./(3.7.*D(1,21))+2.51*3.14*vs.*D(1,21)./(4.*Qy(21)).*(0.25.*(log10(ee./(3.7.*D(1,21))+2.51*3.14*vs.*D(1,21)./(4.*Qy(21)).*(0.25.*(log10(ee./(3.7.*D(1,21))+2.51*3.14*vs.*D(1,21)./(4.*Qy(21)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(22).*abs(Qy(22)*8.*L(1,22)*1./(9.81*3.14.^2.*D(1,22).^5).*(0.25.*(log10(ee./(3.7.*D(1,22))+2.51*3.14*vs.*D(1,22)./(4.*Qy(22)).*(0.25.*(log10(ee./(3.7.*D(1,22))+2.51*3.14*vs.*D(1,22)./(4.*Qy(22)).*(0.25.*(log10(ee./(3.7.*D(1,22))+2.51*3.14*vs.*D(1,22)./(4.*Qy(22)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-4);...
     (1.*Qy(1))+(-1.*Qy(2))+(-2.472000e-01);...
     (1.*Qy(2))+(-1.*Qy(3))+(-1.*Qy(19))+(-1.*Qy(20))+(-2.361000e-01);...
     (1.*Qy(3))+(-1.*Qy(4))+(-3.610000e-02);...
     (1.*Qy(4))+(-1.*Qy(5))+(-2.014000e-01);...
     (1.*Qy(5))+(-1.*Qy(6))+(-2.792000e-01);...
     (1.*Qy(6))+(-1.*Qy(7))+(-3.750000e-01);...
     (1.*Qy(7))+(-1.*Qy(8))+(-1.528000e-01);...
     (1.*Qy(8))+(-1.*Qy(9))+(-1.458000e-01);...
     (1.*Qy(9))+(-1.*Qy(10))+(1.*Qy(13))+(-1.458000e-01);...
     (1.*Qy(10))+(-1.*Qy(11))+(-1.389000e-01);...
     (1.*Qy(11))+(-1.*Qy(12))+(-1.556000e-01);...
     (1.*Qy(12))+(-2.611000e-01);...
     (-1.*Qy(13))+(1.*Qy(14))+(-1.708000e-01);...
     (-1.*Qy(14))+(1.*Qy(15))+(-7.780000e-02);...
     (-1.*Qy(15))+(1.*Qy(16))+(-1.*Qy(28))+(-8.610000e-02);...
     (-1.*Qy(16))+(1.*Qy(17))+(-2.403000e-01);...
     (-1.*Qy(17))+(1.*Qy(18))+(-3.736000e-01);...
     (-1.*Qy(18))+(1.*Qy(19))+(-1.670000e-02);...
     (1.*Qy(20))+(-1.*Qy(21))+(-1.*Qy(23))+(-3.542000e-01);...
     (1.*Qy(21))+(-1.*Qy(22))+(-2.583000e-01);...
     (1.*Qy(22))+(-1.347000e-01);...
     (1.*Qy(23))+(-1.*Qy(24))+(-1.*Qy(29))+(-2.903000e-01);...
     (1.*Qy(24))+(-1.*Qy(25))+(-2.278000e-01);...
     (1.*Qy(25))+(1.*Qy(26))+(-4.720000e-02);...
     (-1.*Qy(26))+(1.*Qy(27))+(-2.500000e-01);...
     (-1.*Qy(27))+(1.*Qy(28))+(-1.028000e-01);...
     (1.*Qy(29))+(-1.*Qy(30))+(-8.060000e-02);...
     (1.*Qy(30))+(-1.*Qy(31))+(-1.000000e-01);...
     (1.*Qy(31))+(-1.*Qy(32))+(-1.000000e-01);...
     (1.*Qy(32))+(1.*Qy(33))+(-2.920000e-02);...
     (-1.*Qy(33))+(1.*Qy(34))+(-2.236000e-01)];
options = optimoptions('fsolve','Display','iter',MaxIterations=100000, MaxFunctionEvaluations=100000, Algorithm='levenberg-marquardt');            %  'levenberg-marquardt'
[Qy] = fsolve(FUN, Qy0, options); 
       for i=1:size(D,2)
                          vel=abs(4*Qy(i,1)./(3.14*D(1,i).^2));     [rn, cn]=find(Dia(1,1:szDia)<D(1,i),1,'first');    [rx, cx]=find(Dia(1,1:szDia)>D(1,i),1,'first');    % vel_mn=0.5*Dia(2,i);
            if isempty(rn)&&isempty(rx)                                                                                                             
            elseif vel<0.3 && ~isempty(rn);                                      D(1,i) = Dia(1,cn);  
            elseif vel>2.0 && ~isempty(rx);                                      D(1,i) = Dia(1,cx);           
            else (~isempty(rn)&&~isempty(rx))&&((vel<2&&vel>0.3));                  end   
      end
 DD(n,:) = D(:);   D = D;            %Qy=Qy,
 end
          DD,                         Li=L'; Di=D';         vel=abs(4*Qy(:,1)./(3.14.*(Di(:,1)).^2));   Re=abs(4.*Qy(:,1)./(3.14*vs.*Di(:,1))); 
                                                            fy11=-2*log10(ee./(3.7.*Di(:,1))+2.51*3.14*vs.*Di(:,1)./(4.*Qy(:,1)*0.0001.^0.5)); fy1=-2*log10(ee./(3.7.*Di(:,1))+2.51*3.14*vs.*Di(:,1)./(4.*Qy(:,1)).*fy11.^0.5); fy=-2*log10(ee./(3.7.*Di(:,1))+2.51*3.14*vs.*Di(:,1)./(4.*Qy(:,1)).*fy1.^0.5);  f=-2*log10(ee./(3.7.*Di(:,1))+2.51*3.14*vs.*Di(:,1)./(4.*Qy(:,1)).*fy.^0.5); ff=(1./f).^2;
                                                            n=7; Data1=zeros(p,n);   Data1(:,1)=Li(:,1); Data1(:,2)=Di(:,1);   Data1(:,3)=Qy(:,1);          Data1(:,4)=vel(:,1); Data1(:,5)=ff(:,1);  Data1(:,6)=Re(:,1);  Data1(:,7)=8./(9.81*3.14.^2).*Data1(:,5).*Data1(:,1).*(Data1(:,3)).^2./(Data1(:,2)).^5;
                                                            StrNum={'string','double','double','double','double','double','double','double'};               subTitl={'Pipes [x-z]', 'Length [m]', 'Diameter [m]', 'Flow rate [m3/s]', 'Velocity [m/s]', 'Friction, f', 'Reynold No.', 'Headlosses [m]'};	
                                                            tz=table('size', [p, 8], 'variabletypes',StrNum, 'variablenames', subTitl);                     Pipexz=["1P","2P","3P","4P","5P","6P","7P","8P","9P","10P","11P","12P","13P","14P","15P","16P","17P","18P","19P","20P","1P","2P","3P","4P","5P","6P","7P","8P","9P","10P","11P","12P","13P","14P"];
                                                            tz{:,1}=Pipexz';  tz{:,2:8} = Data1(:,1:7),                         toc,                                % tz{:,2:cCc+0} = Data1(:,1:cCc),                                                                                                         % MIDsrt=sortrows(tz,sn);  MIDfn=MIDsrt;  MIDfn(:,end)=[ ];     
end
EXECUTED OUTPUT
>>  Qy0(1:34,1)=5.53;sanai(Qy0)
                                        First-order                     Norm of 
 Iteration  Func-count   ||f(x)||^2      optimality       Lambda           step
     0          35      3.52488e+08        4.33e+07         0.01
     1          70      4.43873e+07        6.09e+06        0.001        23.7573
     2         105      3.05072e+06        8.03e+05       0.0001        9.30781
     3         140           186221        9.93e+04        1e-05        7.81348
     4         175          11176.6        1.25e+04        1e-06        3.95876
     5         210          843.678        1.43e+03        1e-07        1.91422
     6         250          489.147         3.1e+03         0.01        2.28327
     7         285          291.247        2.14e+03        0.001       0.813901
     8         320          76.6649        1.29e+03       0.0001       0.712558
     9         355          2.91388             144        1e-05       0.237979
    10         393          2.54221             182         0.01       0.269592
    11         429           1.9157            62.7          0.1       0.199454
    12         465         0.581441            3.11            1       0.086335
    13         500         0.537512           0.482          0.1      0.0227771
    14         536         0.537034           0.307            1      0.0117352
    15         571         0.536874           0.187          0.1     0.00848093
    16         607         0.536791          0.0923            1     0.00591641
    17         642         0.536744          0.0463          0.1     0.00465591
    18         677         0.536694           0.419         0.01      0.0180623
    19         714         0.536654         0.00912            1      0.0032493
    20         749         0.536652         0.00243          0.1     0.00105161
No solution found.
fsolve stopped because the problem appears regular as measured by the gradient,
but the vector of function values is not near zero as measured by the
value of the function tolerance.
<stopping criteria details>
                                        First-order                     Norm of 
 Iteration  Func-count   ||f(x)||^2      optimality       Lambda           step
     0          35      3.52488e+08        4.33e+07         0.01
     1          70      4.43873e+07        6.09e+06        0.001        23.7573
     2         105      3.05072e+06        8.03e+05       0.0001        9.30781
     3         140           186221        9.93e+04        1e-05        7.81348
     4         175          11176.6        1.25e+04        1e-06        3.95876
     5         210          843.678        1.43e+03        1e-07        1.91422
     6         250          489.147         3.1e+03         0.01        2.28327
     7         285          291.247        2.14e+03        0.001       0.813901
     8         320          76.6649        1.29e+03       0.0001       0.712558
     9         355          2.91388             144        1e-05       0.237979
    10         393          2.54221             182         0.01       0.269592
    11         429           1.9157            62.7          0.1       0.199454
    12         465         0.581441            3.11            1       0.086335
    13         500         0.537512           0.482          0.1      0.0227771
    14         536         0.537034           0.307            1      0.0117352
    15         571         0.536874           0.187          0.1     0.00848093
    16         607         0.536791          0.0923            1     0.00591641
    17         642         0.536744          0.0463          0.1     0.00465591
    18         677         0.536694           0.419         0.01      0.0180623
    19         714         0.536654         0.00912            1      0.0032493
    20         749         0.536652         0.00243          0.1     0.00105161
No solution found.
fsolve stopped because the problem appears regular as measured by the gradient,
but the vector of function values is not near zero as measured by the
value of the function tolerance.
<stopping criteria details>
                                        First-order                     Norm of 
 Iteration  Func-count   ||f(x)||^2      optimality       Lambda           step
     0          35      3.52488e+08        4.33e+07         0.01
     1          70      4.43873e+07        6.09e+06        0.001        23.7573
     2         105      3.05072e+06        8.03e+05       0.0001        9.30781
     3         140           186221        9.93e+04        1e-05        7.81348
     4         175          11176.6        1.25e+04        1e-06        3.95876
     5         210          843.678        1.43e+03        1e-07        1.91422
     6         250          489.147         3.1e+03         0.01        2.28327
     7         285          291.247        2.14e+03        0.001       0.813901
     8         320          76.6649        1.29e+03       0.0001       0.712558
     9         355          2.91388             144        1e-05       0.237979
    10         393          2.54221             182         0.01       0.269592
    11         429           1.9157            62.7          0.1       0.199454
    12         465         0.581441            3.11            1       0.086335
    13         500         0.537512           0.482          0.1      0.0227771
    14         536         0.537034           0.307            1      0.0117352
    15         571         0.536874           0.187          0.1     0.00848093
    16         607         0.536791          0.0923            1     0.00591641
    17         642         0.536744          0.0463          0.1     0.00465591
    18         677         0.536694           0.419         0.01      0.0180623
    19         714         0.536654         0.00912            1      0.0032493
    20         749         0.536652         0.00243          0.1     0.00105161
No solution found.
fsolve stopped because the problem appears regular as measured by the gradient,
but the vector of function values is not near zero as measured by the
value of the function tolerance.
<stopping criteria details>
                                        First-order                     Norm of 
 Iteration  Func-count   ||f(x)||^2      optimality       Lambda           step
     0          35      3.52488e+08        4.33e+07         0.01
     1          70      4.43873e+07        6.09e+06        0.001        23.7573
     2         105      3.05072e+06        8.03e+05       0.0001        9.30781
     3         140           186221        9.93e+04        1e-05        7.81348
     4         175          11176.6        1.25e+04        1e-06        3.95876
     5         210          843.678        1.43e+03        1e-07        1.91422
     6         250          489.147         3.1e+03         0.01        2.28327
     7         285          291.247        2.14e+03        0.001       0.813901
     8         320          76.6649        1.29e+03       0.0001       0.712558
     9         355          2.91388             144        1e-05       0.237979
    10         393          2.54221             182         0.01       0.269592
    11         429           1.9157            62.7          0.1       0.199454
    12         465         0.581441            3.11            1       0.086335
    13         500         0.537512           0.482          0.1      0.0227771
    14         536         0.537034           0.307            1      0.0117352
    15         571         0.536874           0.187          0.1     0.00848093
    16         607         0.536791          0.0923            1     0.00591641
    17         642         0.536744          0.0463          0.1     0.00465591
    18         677         0.536694           0.419         0.01      0.0180623
    19         714         0.536654         0.00912            1      0.0032493
    20         749         0.536652         0.00243          0.1     0.00105161
No solution found.
fsolve stopped because the problem appears regular as measured by the gradient,
but the vector of function values is not near zero as measured by the
value of the function tolerance.
<stopping criteria details>
                                        First-order                     Norm of 
 Iteration  Func-count   ||f(x)||^2      optimality       Lambda           step
     0          35      3.52488e+08        4.33e+07         0.01
     1          70      4.43873e+07        6.09e+06        0.001        23.7573
     2         105      3.05072e+06        8.03e+05       0.0001        9.30781
     3         140           186221        9.93e+04        1e-05        7.81348
     4         175          11176.6        1.25e+04        1e-06        3.95876
     5         210          843.678        1.43e+03        1e-07        1.91422
     6         250          489.147         3.1e+03         0.01        2.28327
     7         285          291.247        2.14e+03        0.001       0.813901
     8         320          76.6649        1.29e+03       0.0001       0.712558
     9         355          2.91388             144        1e-05       0.237979
    10         393          2.54221             182         0.01       0.269592
    11         429           1.9157            62.7          0.1       0.199454
    12         465         0.581441            3.11            1       0.086335
    13         500         0.537512           0.482          0.1      0.0227771
    14         536         0.537034           0.307            1      0.0117352
    15         571         0.536874           0.187          0.1     0.00848093
    16         607         0.536791          0.0923            1     0.00591641
    17         642         0.536744          0.0463          0.1     0.00465591
    18         677         0.536694           0.419         0.01      0.0180623
    19         714         0.536654         0.00912            1      0.0032493
    20         749         0.536652         0.00243          0.1     0.00105161
No solution found.
fsolve stopped because the problem appears regular as measured by the gradient,
but the vector of function values is not near zero as measured by the
value of the function tolerance.
<stopping criteria details>
                                        First-order                     Norm of 
 Iteration  Func-count   ||f(x)||^2      optimality       Lambda           step
     0          35      3.52488e+08        4.33e+07         0.01
     1          70      4.43873e+07        6.09e+06        0.001        23.7573
     2         105      3.05072e+06        8.03e+05       0.0001        9.30781
     3         140           186221        9.93e+04        1e-05        7.81348
     4         175          11176.6        1.25e+04        1e-06        3.95876
     5         210          843.678        1.43e+03        1e-07        1.91422
     6         250          489.147         3.1e+03         0.01        2.28327
     7         285          291.247        2.14e+03        0.001       0.813901
     8         320          76.6649        1.29e+03       0.0001       0.712558
     9         355          2.91388             144        1e-05       0.237979
    10         393          2.54221             182         0.01       0.269592
    11         429           1.9157            62.7          0.1       0.199454
    12         465         0.581441            3.11            1       0.086335
    13         500         0.537512           0.482          0.1      0.0227771
    14         536         0.537034           0.307            1      0.0117352
    15         571         0.536874           0.187          0.1     0.00848093
    16         607         0.536791          0.0923            1     0.00591641
    17         642         0.536744          0.0463          0.1     0.00465591
    18         677         0.536694           0.419         0.01      0.0180623
    19         714         0.536654         0.00912            1      0.0032493
    20         749         0.536652         0.00243          0.1     0.00105161
No solution found.
fsolve stopped because the problem appears regular as measured by the gradient,
but the vector of function values is not near zero as measured by the
value of the function tolerance.
<stopping criteria details>
                                        First-order                     Norm of 
 Iteration  Func-count   ||f(x)||^2      optimality       Lambda           step
     0          35      3.52488e+08        4.33e+07         0.01
     1          70      4.43873e+07        6.09e+06        0.001        23.7573
     2         105      3.05072e+06        8.03e+05       0.0001        9.30781
     3         140           186221        9.93e+04        1e-05        7.81348
     4         175          11176.6        1.25e+04        1e-06        3.95876
     5         210          843.678        1.43e+03        1e-07        1.91422
     6         250          489.147         3.1e+03         0.01        2.28327
     7         285          291.247        2.14e+03        0.001       0.813901
     8         320          76.6649        1.29e+03       0.0001       0.712558
     9         355          2.91388             144        1e-05       0.237979
    10         393          2.54221             182         0.01       0.269592
    11         429           1.9157            62.7          0.1       0.199454
    12         465         0.581441            3.11            1       0.086335
    13         500         0.537512           0.482          0.1      0.0227771
    14         536         0.537034           0.307            1      0.0117352
    15         571         0.536874           0.187          0.1     0.00848093
    16         607         0.536791          0.0923            1     0.00591641
    17         642         0.536744          0.0463          0.1     0.00465591
    18         677         0.536694           0.419         0.01      0.0180623
    19         714         0.536654         0.00912            1      0.0032493
    20         749         0.536652         0.00243          0.1     0.00105161
No solution found.
fsolve stopped because the problem appears regular as measured by the gradient,
but the vector of function values is not near zero as measured by the
value of the function tolerance.
<stopping criteria details>
                                        First-order                     Norm of 
 Iteration  Func-count   ||f(x)||^2      optimality       Lambda           step
     0          35      3.52488e+08        4.33e+07         0.01
     1          70      4.43873e+07        6.09e+06        0.001        23.7573
     2         105      3.05072e+06        8.03e+05       0.0001        9.30781
     3         140           186221        9.93e+04        1e-05        7.81348
     4         175          11176.6        1.25e+04        1e-06        3.95876
     5         210          843.678        1.43e+03        1e-07        1.91422
     6         250          489.147         3.1e+03         0.01        2.28327
     7         285          291.247        2.14e+03        0.001       0.813901
     8         320          76.6649        1.29e+03       0.0001       0.712558
     9         355          2.91388             144        1e-05       0.237979
    10         393          2.54221             182         0.01       0.269592
    11         429           1.9157            62.7          0.1       0.199454
    12         465         0.581441            3.11            1       0.086335
    13         500         0.537512           0.482          0.1      0.0227771
    14         536         0.537034           0.307            1      0.0117352
    15         571         0.536874           0.187          0.1     0.00848093
    16         607         0.536791          0.0923            1     0.00591641
    17         642         0.536744          0.0463          0.1     0.00465591
    18         677         0.536694           0.419         0.01      0.0180623
    19         714         0.536654         0.00912            1      0.0032493
    20         749         0.536652         0.00243          0.1     0.00105161
No solution found.
fsolve stopped because the problem appears regular as measured by the gradient,
but the vector of function values is not near zero as measured by the
value of the function tolerance.
<stopping criteria details>
                                        First-order                     Norm of 
 Iteration  Func-count   ||f(x)||^2      optimality       Lambda           step
     0          35      3.52488e+08        4.33e+07         0.01
     1          70      4.43873e+07        6.09e+06        0.001        23.7573
     2         105      3.05072e+06        8.03e+05       0.0001        9.30781
     3         140           186221        9.93e+04        1e-05        7.81348
     4         175          11176.6        1.25e+04        1e-06        3.95876
     5         210          843.678        1.43e+03        1e-07        1.91422
     6         250          489.147         3.1e+03         0.01        2.28327
     7         285          291.247        2.14e+03        0.001       0.813901
     8         320          76.6649        1.29e+03       0.0001       0.712558
     9         355          2.91388             144        1e-05       0.237979
    10         393          2.54221             182         0.01       0.269592
    11         429           1.9157            62.7          0.1       0.199454
    12         465         0.581441            3.11            1       0.086335
    13         500         0.537512           0.482          0.1      0.0227771
    14         536         0.537034           0.307            1      0.0117352
    15         571         0.536874           0.187          0.1     0.00848093
    16         607         0.536791          0.0923            1     0.00591641
    17         642         0.536744          0.0463          0.1     0.00465591
    18         677         0.536694           0.419         0.01      0.0180623
    19         714         0.536654         0.00912            1      0.0032493
    20         749         0.536652         0.00243          0.1     0.00105161
No solution found.
fsolve stopped because the problem appears regular as measured by the gradient,
but the vector of function values is not near zero as measured by the
value of the function tolerance.
<stopping criteria details>
                                        First-order                     Norm of 
 Iteration  Func-count   ||f(x)||^2      optimality       Lambda           step
     0          35      3.52488e+08        4.33e+07         0.01
     1          70      4.43873e+07        6.09e+06        0.001        23.7573
     2         105      3.05072e+06        8.03e+05       0.0001        9.30781
     3         140           186221        9.93e+04        1e-05        7.81348
     4         175          11176.6        1.25e+04        1e-06        3.95876
     5         210          843.678        1.43e+03        1e-07        1.91422
     6         250          489.147         3.1e+03         0.01        2.28327
     7         285          291.247        2.14e+03        0.001       0.813901
     8         320          76.6649        1.29e+03       0.0001       0.712558
     9         355          2.91388             144        1e-05       0.237979
    10         393          2.54221             182         0.01       0.269592
    11         429           1.9157            62.7          0.1       0.199454
    12         465         0.581441            3.11            1       0.086335
    13         500         0.537512           0.482          0.1      0.0227771
    14         536         0.537034           0.307            1      0.0117352
    15         571         0.536874           0.187          0.1     0.00848093
    16         607         0.536791          0.0923            1     0.00591641
    17         642         0.536744          0.0463          0.1     0.00465591
    18         677         0.536694           0.419         0.01      0.0180623
    19         714         0.536654         0.00912            1      0.0032493
    20         749         0.536652         0.00243          0.1     0.00105161
No solution found.
fsolve stopped because the problem appears regular as measured by the gradient,
but the vector of function values is not near zero as measured by the
value of the function tolerance.
<stopping criteria details>
DD =
  Columns 1 through 14
    0.7620    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100    0.3050    0.3050    0.3050    0.6100    0.6100
    0.7620    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100    0.3050    0.3050    0.3050    0.6100    0.6100
    0.7620    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100    0.3050    0.3050    0.3050    0.6100    0.6100
    0.7620    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100    0.3050    0.3050    0.3050    0.6100    0.6100
    0.7620    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100    0.3050    0.3050    0.3050    0.6100    0.6100
    0.7620    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100    0.3050    0.3050    0.3050    0.6100    0.6100
    0.7620    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100    0.3050    0.3050    0.3050    0.6100    0.6100
    0.7620    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100    0.3050    0.3050    0.3050    0.6100    0.6100
    0.7620    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100    0.3050    0.3050    0.3050    0.6100    0.6100
    0.7620    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100    0.3050    0.3050    0.3050    0.6100    0.6100
  Columns 15 through 28
    0.6100    0.3050    0.3050    0.6100    0.6100    0.3050    0.3050    0.3050    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100
    0.6100    0.3050    0.3050    0.6100    0.6100    0.3050    0.3050    0.3050    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100
    0.6100    0.3050    0.3050    0.6100    0.6100    0.3050    0.3050    0.3050    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100
    0.6100    0.3050    0.3050    0.6100    0.6100    0.3050    0.3050    0.3050    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100
    0.6100    0.3050    0.3050    0.6100    0.6100    0.3050    0.3050    0.3050    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100
    0.6100    0.3050    0.3050    0.6100    0.6100    0.3050    0.3050    0.3050    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100
    0.6100    0.3050    0.3050    0.6100    0.6100    0.3050    0.3050    0.3050    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100
    0.6100    0.3050    0.3050    0.6100    0.6100    0.3050    0.3050    0.3050    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100
    0.6100    0.3050    0.3050    0.6100    0.6100    0.3050    0.3050    0.3050    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100
    0.6100    0.3050    0.3050    0.6100    0.6100    0.3050    0.3050    0.3050    0.6100    0.6100    0.6100    0.6100    0.6100    0.6100
  Columns 29 through 34
    0.7620    0.7620    0.7620    0.7620    0.7620    0.7620
    0.7620    0.7620    0.7620    0.7620    0.7620    0.7620
    0.7620    0.7620    0.7620    0.7620    0.7620    0.7620
    0.7620    0.7620    0.7620    0.7620    0.7620    0.7620
    0.7620    0.7620    0.7620    0.7620    0.7620    0.7620
    0.7620    0.7620    0.7620    0.7620    0.7620    0.7620
    0.7620    0.7620    0.7620    0.7620    0.7620    0.7620
    0.7620    0.7620    0.7620    0.7620    0.7620    0.7620
    0.7620    0.7620    0.7620    0.7620    0.7620    0.7620
    0.7620    0.7620    0.7620    0.7620    0.7620    0.7620
tz =
  34×8 table
    Pipes [x-z]    Length [m]    Diameter [m]    Flow rate [m3/s]    Velocity [m/s]    Friction, f    Reynold No.    Headlosses [m]
    ___________    __________    ____________    ________________    ______________    ___________    ___________    ______________
       "1P"            100          0.762            0.69245             1.5192         0.073207      1.1576e+06         1.1301    
       "2P"           1350           0.61            0.56451             1.9326         0.081505      1.1789e+06         34.338    
       "3P"            900           0.61            0.26093            0.89329         0.081515       5.449e+05         4.8914    
       "4P"           1150           0.61            0.34484             1.1806          0.08151      7.2014e+05         10.916    
       "5P"           1450           0.61            0.26461             0.9059         0.081515       5.526e+05         8.1048    
         :             :              :                 :                  :                :              :               :       
       "10P"          2000          0.762             -0.904             1.9833         0.073189      1.5113e+06         38.512    
       "11P"          1600          0.762            -1.0621             2.3301          0.07319      1.7755e+06         42.528    
       "12P"           150          0.762            -1.3096             2.8732         0.073191      2.1893e+06          6.062    
       "13P"           860          0.762             1.4968             3.2838         0.073201      2.5022e+06         45.405    
       "14P"           950          0.762             1.8107             3.9726           0.0732      3.0271e+06         73.405    
	Display all 34 rows.
Elapsed time is 0.854046 seconds.
ans =
    0.6924
    0.5645
    0.2609
    0.3448
    0.2646
    0.1076
   -0.1452
   -0.1757
   -0.1988
    0.0163
    0.0168
    0.0217
    0.2380
    0.2849
    0.2382
   -0.0391
    0.0768
    0.3273
    0.2238
   -0.0371
    0.0467
   -0.0462
   -0.3201
    0.3550
    0.2484
   -0.3343
   -0.2131
   -0.2381
   -0.8605
   -0.9040
   -1.0621
   -1.3096
    1.4968
    1.8107
1 commentaire
  Alex Sha
      
 le 15 Mai 2024
				@Eng. FM You have 34 unknowns (Qy(1)-Qy(34)), but 36 equations, in this case, there is no exact solution usually.
Réponses (1)
  Eng. Fredius Magige
      
 le 16 Mai 2024
        Simply solved by this way ...
function [Qy, DD, FUN] = SANAI2(Qy0)                                           
        tic,                                                                                                                    % matL=abs(matr);   [NodLp,pQ]=size(matr); 
        NodLp=41;  LP=5;   data1=4;     pQ=35; data2=data1+1+1;  Nod3=NodLp-data1-LP;   p=pQ-1;  JJ=data1+Nod3+1;    HLD=0;
                                       ee=0.04;          vs=1.00001*10^-6;                                                       %format shortEng,            % L=matr(1,1:end-1);     D=matr(2,1:end-1);  
    D = [0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610	0.610];                   
    DD=zeros(10,p);
for n=1:10
        L = [100	1350	900	1150	1450	450	850	850	800	950	1200	3500	800	500	550	2730	1750	800	400	2200	1500	500	2650	1230	1300	850	300	750	1500	2000	1600	150	860	950];
        D = D;
        Dia = [0.305	0.406	0.508	0.609	0.762	1.016	1.905]; szDia=size(Dia,2);
% Qy0(1:34,1)=5.53;
FUN=@(Qy)[(1.*Qy(3).*abs(Qy(3)*8.*L(1,3)*1./(9.81*3.14.^2.*D(1,3).^5).*(0.25.*(log10(ee./(3.7.*D(1,3))+2.51*3.14*vs.*D(1,3)./(4.*Qy(3)).*(0.25.*(log10(ee./(3.7.*D(1,3))+2.51*3.14*vs.*D(1,3)./(4.*Qy(3)).*(0.25.*(log10(ee./(3.7.*D(1,3))+2.51*3.14*vs.*D(1,3)./(4.*Qy(3)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(4).*abs(Qy(4)*8.*L(1,4)*1./(9.81*3.14.^2.*D(1,4).^5).*(0.25.*(log10(ee./(3.7.*D(1,4))+2.51*3.14*vs.*D(1,4)./(4.*Qy(4)).*(0.25.*(log10(ee./(3.7.*D(1,4))+2.51*3.14*vs.*D(1,4)./(4.*Qy(4)).*(0.25.*(log10(ee./(3.7.*D(1,4))+2.51*3.14*vs.*D(1,4)./(4.*Qy(4)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(5).*abs(Qy(5)*8.*L(1,5)*1./(9.81*3.14.^2.*D(1,5).^5).*(0.25.*(log10(ee./(3.7.*D(1,5))+2.51*3.14*vs.*D(1,5)./(4.*Qy(5)).*(0.25.*(log10(ee./(3.7.*D(1,5))+2.51*3.14*vs.*D(1,5)./(4.*Qy(5)).*(0.25.*(log10(ee./(3.7.*D(1,5))+2.51*3.14*vs.*D(1,5)./(4.*Qy(5)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(6).*abs(Qy(6)*8.*L(1,6)*1./(9.81*3.14.^2.*D(1,6).^5).*(0.25.*(log10(ee./(3.7.*D(1,6))+2.51*3.14*vs.*D(1,6)./(4.*Qy(6)).*(0.25.*(log10(ee./(3.7.*D(1,6))+2.51*3.14*vs.*D(1,6)./(4.*Qy(6)).*(0.25.*(log10(ee./(3.7.*D(1,6))+2.51*3.14*vs.*D(1,6)./(4.*Qy(6)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(7).*abs(Qy(7)*8.*L(1,7)*1./(9.81*3.14.^2.*D(1,7).^5).*(0.25.*(log10(ee./(3.7.*D(1,7))+2.51*3.14*vs.*D(1,7)./(4.*Qy(7)).*(0.25.*(log10(ee./(3.7.*D(1,7))+2.51*3.14*vs.*D(1,7)./(4.*Qy(7)).*(0.25.*(log10(ee./(3.7.*D(1,7))+2.51*3.14*vs.*D(1,7)./(4.*Qy(7)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(8).*abs(Qy(8)*8.*L(1,8)*1./(9.81*3.14.^2.*D(1,8).^5).*(0.25.*(log10(ee./(3.7.*D(1,8))+2.51*3.14*vs.*D(1,8)./(4.*Qy(8)).*(0.25.*(log10(ee./(3.7.*D(1,8))+2.51*3.14*vs.*D(1,8)./(4.*Qy(8)).*(0.25.*(log10(ee./(3.7.*D(1,8))+2.51*3.14*vs.*D(1,8)./(4.*Qy(8)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(9).*abs(Qy(9)*8.*L(1,9)*1./(9.81*3.14.^2.*D(1,9).^5).*(0.25.*(log10(ee./(3.7.*D(1,9))+2.51*3.14*vs.*D(1,9)./(4.*Qy(9)).*(0.25.*(log10(ee./(3.7.*D(1,9))+2.51*3.14*vs.*D(1,9)./(4.*Qy(9)).*(0.25.*(log10(ee./(3.7.*D(1,9))+2.51*3.14*vs.*D(1,9)./(4.*Qy(9)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(13).*abs(Qy(13)*8.*L(1,13)*1./(9.81*3.14.^2.*D(1,13).^5).*(0.25.*(log10(ee./(3.7.*D(1,13))+2.51*3.14*vs.*D(1,13)./(4.*Qy(13)).*(0.25.*(log10(ee./(3.7.*D(1,13))+2.51*3.14*vs.*D(1,13)./(4.*Qy(13)).*(0.25.*(log10(ee./(3.7.*D(1,13))+2.51*3.14*vs.*D(1,13)./(4.*Qy(13)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(14).*abs(Qy(14)*8.*L(1,14)*1./(9.81*3.14.^2.*D(1,14).^5).*(0.25.*(log10(ee./(3.7.*D(1,14))+2.51*3.14*vs.*D(1,14)./(4.*Qy(14)).*(0.25.*(log10(ee./(3.7.*D(1,14))+2.51*3.14*vs.*D(1,14)./(4.*Qy(14)).*(0.25.*(log10(ee./(3.7.*D(1,14))+2.51*3.14*vs.*D(1,14)./(4.*Qy(14)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(15).*abs(Qy(15)*8.*L(1,15)*1./(9.81*3.14.^2.*D(1,15).^5).*(0.25.*(log10(ee./(3.7.*D(1,15))+2.51*3.14*vs.*D(1,15)./(4.*Qy(15)).*(0.25.*(log10(ee./(3.7.*D(1,15))+2.51*3.14*vs.*D(1,15)./(4.*Qy(15)).*(0.25.*(log10(ee./(3.7.*D(1,15))+2.51*3.14*vs.*D(1,15)./(4.*Qy(15)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(16).*abs(Qy(16)*8.*L(1,16)*1./(9.81*3.14.^2.*D(1,16).^5).*(0.25.*(log10(ee./(3.7.*D(1,16))+2.51*3.14*vs.*D(1,16)./(4.*Qy(16)).*(0.25.*(log10(ee./(3.7.*D(1,16))+2.51*3.14*vs.*D(1,16)./(4.*Qy(16)).*(0.25.*(log10(ee./(3.7.*D(1,16))+2.51*3.14*vs.*D(1,16)./(4.*Qy(16)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(17).*abs(Qy(17)*8.*L(1,17)*1./(9.81*3.14.^2.*D(1,17).^5).*(0.25.*(log10(ee./(3.7.*D(1,17))+2.51*3.14*vs.*D(1,17)./(4.*Qy(17)).*(0.25.*(log10(ee./(3.7.*D(1,17))+2.51*3.14*vs.*D(1,17)./(4.*Qy(17)).*(0.25.*(log10(ee./(3.7.*D(1,17))+2.51*3.14*vs.*D(1,17)./(4.*Qy(17)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(18).*abs(Qy(18)*8.*L(1,18)*1./(9.81*3.14.^2.*D(1,18).^5).*(0.25.*(log10(ee./(3.7.*D(1,18))+2.51*3.14*vs.*D(1,18)./(4.*Qy(18)).*(0.25.*(log10(ee./(3.7.*D(1,18))+2.51*3.14*vs.*D(1,18)./(4.*Qy(18)).*(0.25.*(log10(ee./(3.7.*D(1,18))+2.51*3.14*vs.*D(1,18)./(4.*Qy(18)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(19).*abs(Qy(19)*8.*L(1,19)*1./(9.81*3.14.^2.*D(1,19).^5).*(0.25.*(log10(ee./(3.7.*D(1,19))+2.51*3.14*vs.*D(1,19)./(4.*Qy(19)).*(0.25.*(log10(ee./(3.7.*D(1,19))+2.51*3.14*vs.*D(1,19)./(4.*Qy(19)).*(0.25.*(log10(ee./(3.7.*D(1,19))+2.51*3.14*vs.*D(1,19)./(4.*Qy(19)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(0);...
     (1.*Qy(16).*abs(Qy(16)*8.*L(1,16)*1./(9.81*3.14.^2.*D(1,16).^5).*(0.25.*(log10(ee./(3.7.*D(1,16))+2.51*3.14*vs.*D(1,16)./(4.*Qy(16)).*(0.25.*(log10(ee./(3.7.*D(1,16))+2.51*3.14*vs.*D(1,16)./(4.*Qy(16)).*(0.25.*(log10(ee./(3.7.*D(1,16))+2.51*3.14*vs.*D(1,16)./(4.*Qy(16)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(17).*abs(Qy(17)*8.*L(1,17)*1./(9.81*3.14.^2.*D(1,17).^5).*(0.25.*(log10(ee./(3.7.*D(1,17))+2.51*3.14*vs.*D(1,17)./(4.*Qy(17)).*(0.25.*(log10(ee./(3.7.*D(1,17))+2.51*3.14*vs.*D(1,17)./(4.*Qy(17)).*(0.25.*(log10(ee./(3.7.*D(1,17))+2.51*3.14*vs.*D(1,17)./(4.*Qy(17)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(18).*abs(Qy(18)*8.*L(1,18)*1./(9.81*3.14.^2.*D(1,18).^5).*(0.25.*(log10(ee./(3.7.*D(1,18))+2.51*3.14*vs.*D(1,18)./(4.*Qy(18)).*(0.25.*(log10(ee./(3.7.*D(1,18))+2.51*3.14*vs.*D(1,18)./(4.*Qy(18)).*(0.25.*(log10(ee./(3.7.*D(1,18))+2.51*3.14*vs.*D(1,18)./(4.*Qy(18)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(19).*abs(Qy(19)*8.*L(1,19)*1./(9.81*3.14.^2.*D(1,19).^5).*(0.25.*(log10(ee./(3.7.*D(1,19))+2.51*3.14*vs.*D(1,19)./(4.*Qy(19)).*(0.25.*(log10(ee./(3.7.*D(1,19))+2.51*3.14*vs.*D(1,19)./(4.*Qy(19)).*(0.25.*(log10(ee./(3.7.*D(1,19))+2.51*3.14*vs.*D(1,19)./(4.*Qy(19)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(20).*abs(Qy(20)*8.*L(1,20)*1./(9.81*3.14.^2.*D(1,20).^5).*(0.25.*(log10(ee./(3.7.*D(1,20))+2.51*3.14*vs.*D(1,20)./(4.*Qy(20)).*(0.25.*(log10(ee./(3.7.*D(1,20))+2.51*3.14*vs.*D(1,20)./(4.*Qy(20)).*(0.25.*(log10(ee./(3.7.*D(1,20))+2.51*3.14*vs.*D(1,20)./(4.*Qy(20)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(23).*abs(Qy(23)*8.*L(1,23)*1./(9.81*3.14.^2.*D(1,23).^5).*(0.25.*(log10(ee./(3.7.*D(1,23))+2.51*3.14*vs.*D(1,23)./(4.*Qy(23)).*(0.25.*(log10(ee./(3.7.*D(1,23))+2.51*3.14*vs.*D(1,23)./(4.*Qy(23)).*(0.25.*(log10(ee./(3.7.*D(1,23))+2.51*3.14*vs.*D(1,23)./(4.*Qy(23)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(24).*abs(Qy(24)*8.*L(1,24)*1./(9.81*3.14.^2.*D(1,24).^5).*(0.25.*(log10(ee./(3.7.*D(1,24))+2.51*3.14*vs.*D(1,24)./(4.*Qy(24)).*(0.25.*(log10(ee./(3.7.*D(1,24))+2.51*3.14*vs.*D(1,24)./(4.*Qy(24)).*(0.25.*(log10(ee./(3.7.*D(1,24))+2.51*3.14*vs.*D(1,24)./(4.*Qy(24)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(25).*abs(Qy(25)*8.*L(1,25)*1./(9.81*3.14.^2.*D(1,25).^5).*(0.25.*(log10(ee./(3.7.*D(1,25))+2.51*3.14*vs.*D(1,25)./(4.*Qy(25)).*(0.25.*(log10(ee./(3.7.*D(1,25))+2.51*3.14*vs.*D(1,25)./(4.*Qy(25)).*(0.25.*(log10(ee./(3.7.*D(1,25))+2.51*3.14*vs.*D(1,25)./(4.*Qy(25)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(26).*abs(Qy(26)*8.*L(1,26)*1./(9.81*3.14.^2.*D(1,26).^5).*(0.25.*(log10(ee./(3.7.*D(1,26))+2.51*3.14*vs.*D(1,26)./(4.*Qy(26)).*(0.25.*(log10(ee./(3.7.*D(1,26))+2.51*3.14*vs.*D(1,26)./(4.*Qy(26)).*(0.25.*(log10(ee./(3.7.*D(1,26))+2.51*3.14*vs.*D(1,26)./(4.*Qy(26)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(27).*abs(Qy(27)*8.*L(1,27)*1./(9.81*3.14.^2.*D(1,27).^5).*(0.25.*(log10(ee./(3.7.*D(1,27))+2.51*3.14*vs.*D(1,27)./(4.*Qy(27)).*(0.25.*(log10(ee./(3.7.*D(1,27))+2.51*3.14*vs.*D(1,27)./(4.*Qy(27)).*(0.25.*(log10(ee./(3.7.*D(1,27))+2.51*3.14*vs.*D(1,27)./(4.*Qy(27)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(28).*abs(Qy(28)*8.*L(1,28)*1./(9.81*3.14.^2.*D(1,28).^5).*(0.25.*(log10(ee./(3.7.*D(1,28))+2.51*3.14*vs.*D(1,28)./(4.*Qy(28)).*(0.25.*(log10(ee./(3.7.*D(1,28))+2.51*3.14*vs.*D(1,28)./(4.*Qy(28)).*(0.25.*(log10(ee./(3.7.*D(1,28))+2.51*3.14*vs.*D(1,28)./(4.*Qy(28)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(0);...
     (1.*Qy(24).*abs(Qy(24)*8.*L(1,24)*1./(9.81*3.14.^2.*D(1,24).^5).*(0.25.*(log10(ee./(3.7.*D(1,24))+2.51*3.14*vs.*D(1,24)./(4.*Qy(24)).*(0.25.*(log10(ee./(3.7.*D(1,24))+2.51*3.14*vs.*D(1,24)./(4.*Qy(24)).*(0.25.*(log10(ee./(3.7.*D(1,24))+2.51*3.14*vs.*D(1,24)./(4.*Qy(24)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(25).*abs(Qy(25)*8.*L(1,25)*1./(9.81*3.14.^2.*D(1,25).^5).*(0.25.*(log10(ee./(3.7.*D(1,25))+2.51*3.14*vs.*D(1,25)./(4.*Qy(25)).*(0.25.*(log10(ee./(3.7.*D(1,25))+2.51*3.14*vs.*D(1,25)./(4.*Qy(25)).*(0.25.*(log10(ee./(3.7.*D(1,25))+2.51*3.14*vs.*D(1,25)./(4.*Qy(25)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(29).*abs(Qy(29)*8.*L(1,29)*1./(9.81*3.14.^2.*D(1,29).^5).*(0.25.*(log10(ee./(3.7.*D(1,29))+2.51*3.14*vs.*D(1,29)./(4.*Qy(29)).*(0.25.*(log10(ee./(3.7.*D(1,29))+2.51*3.14*vs.*D(1,29)./(4.*Qy(29)).*(0.25.*(log10(ee./(3.7.*D(1,29))+2.51*3.14*vs.*D(1,29)./(4.*Qy(29)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(30).*abs(Qy(30)*8.*L(1,30)*1./(9.81*3.14.^2.*D(1,30).^5).*(0.25.*(log10(ee./(3.7.*D(1,30))+2.51*3.14*vs.*D(1,30)./(4.*Qy(30)).*(0.25.*(log10(ee./(3.7.*D(1,30))+2.51*3.14*vs.*D(1,30)./(4.*Qy(30)).*(0.25.*(log10(ee./(3.7.*D(1,30))+2.51*3.14*vs.*D(1,30)./(4.*Qy(30)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(31).*abs(Qy(31)*8.*L(1,31)*1./(9.81*3.14.^2.*D(1,31).^5).*(0.25.*(log10(ee./(3.7.*D(1,31))+2.51*3.14*vs.*D(1,31)./(4.*Qy(31)).*(0.25.*(log10(ee./(3.7.*D(1,31))+2.51*3.14*vs.*D(1,31)./(4.*Qy(31)).*(0.25.*(log10(ee./(3.7.*D(1,31))+2.51*3.14*vs.*D(1,31)./(4.*Qy(31)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(32).*abs(Qy(32)*8.*L(1,32)*1./(9.81*3.14.^2.*D(1,32).^5).*(0.25.*(log10(ee./(3.7.*D(1,32))+2.51*3.14*vs.*D(1,32)./(4.*Qy(32)).*(0.25.*(log10(ee./(3.7.*D(1,32))+2.51*3.14*vs.*D(1,32)./(4.*Qy(32)).*(0.25.*(log10(ee./(3.7.*D(1,32))+2.51*3.14*vs.*D(1,32)./(4.*Qy(32)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(33).*abs(Qy(33)*8.*L(1,33)*1./(9.81*3.14.^2.*D(1,33).^5).*(0.25.*(log10(ee./(3.7.*D(1,33))+2.51*3.14*vs.*D(1,33)./(4.*Qy(33)).*(0.25.*(log10(ee./(3.7.*D(1,33))+2.51*3.14*vs.*D(1,33)./(4.*Qy(33)).*(0.25.*(log10(ee./(3.7.*D(1,33))+2.51*3.14*vs.*D(1,33)./(4.*Qy(33)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-1.*Qy(34).*abs(Qy(34)*8.*L(1,34)*1./(9.81*3.14.^2.*D(1,34).^5).*(0.25.*(log10(ee./(3.7.*D(1,34))+2.51*3.14*vs.*D(1,34)./(4.*Qy(34)).*(0.25.*(log10(ee./(3.7.*D(1,34))+2.51*3.14*vs.*D(1,34)./(4.*Qy(34)).*(0.25.*(log10(ee./(3.7.*D(1,34))+2.51*3.14*vs.*D(1,34)./(4.*Qy(34)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(0);...
     (1.*Qy(1).*abs(Qy(1)*8.*L(1,1)*1./(9.81*3.14.^2.*D(1,1).^5).*(0.25.*(log10(ee./(3.7.*D(1,1))+2.51*3.14*vs.*D(1,1)./(4.*Qy(1)).*(0.25.*(log10(ee./(3.7.*D(1,1))+2.51*3.14*vs.*D(1,1)./(4.*Qy(1)).*(0.25.*(log10(ee./(3.7.*D(1,1))+2.51*3.14*vs.*D(1,1)./(4.*Qy(1)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(10).*abs(Qy(10)*8.*L(1,10)*1./(9.81*3.14.^2.*D(1,10).^5).*(0.25.*(log10(ee./(3.7.*D(1,10))+2.51*3.14*vs.*D(1,10)./(4.*Qy(10)).*(0.25.*(log10(ee./(3.7.*D(1,10))+2.51*3.14*vs.*D(1,10)./(4.*Qy(10)).*(0.25.*(log10(ee./(3.7.*D(1,10))+2.51*3.14*vs.*D(1,10)./(4.*Qy(10)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(11).*abs(Qy(11)*8.*L(1,11)*1./(9.81*3.14.^2.*D(1,11).^5).*(0.25.*(log10(ee./(3.7.*D(1,11))+2.51*3.14*vs.*D(1,11)./(4.*Qy(11)).*(0.25.*(log10(ee./(3.7.*D(1,11))+2.51*3.14*vs.*D(1,11)./(4.*Qy(11)).*(0.25.*(log10(ee./(3.7.*D(1,11))+2.51*3.14*vs.*D(1,11)./(4.*Qy(11)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(12).*abs(Qy(12)*8.*L(1,12)*1./(9.81*3.14.^2.*D(1,12).^5).*(0.25.*(log10(ee./(3.7.*D(1,12))+2.51*3.14*vs.*D(1,12)./(4.*Qy(12)).*(0.25.*(log10(ee./(3.7.*D(1,12))+2.51*3.14*vs.*D(1,12)./(4.*Qy(12)).*(0.25.*(log10(ee./(3.7.*D(1,12))+2.51*3.14*vs.*D(1,12)./(4.*Qy(12)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-4);...
     (1.*Qy(1).*abs(Qy(1)*8.*L(1,1)*1./(9.81*3.14.^2.*D(1,1).^5).*(0.25.*(log10(ee./(3.7.*D(1,1))+2.51*3.14*vs.*D(1,1)./(4.*Qy(1)).*(0.25.*(log10(ee./(3.7.*D(1,1))+2.51*3.14*vs.*D(1,1)./(4.*Qy(1)).*(0.25.*(log10(ee./(3.7.*D(1,1))+2.51*3.14*vs.*D(1,1)./(4.*Qy(1)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(21).*abs(Qy(21)*8.*L(1,21)*1./(9.81*3.14.^2.*D(1,21).^5).*(0.25.*(log10(ee./(3.7.*D(1,21))+2.51*3.14*vs.*D(1,21)./(4.*Qy(21)).*(0.25.*(log10(ee./(3.7.*D(1,21))+2.51*3.14*vs.*D(1,21)./(4.*Qy(21)).*(0.25.*(log10(ee./(3.7.*D(1,21))+2.51*3.14*vs.*D(1,21)./(4.*Qy(21)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(1.*Qy(22).*abs(Qy(22)*8.*L(1,22)*1./(9.81*3.14.^2.*D(1,22).^5).*(0.25.*(log10(ee./(3.7.*D(1,22))+2.51*3.14*vs.*D(1,22)./(4.*Qy(22)).*(0.25.*(log10(ee./(3.7.*D(1,22))+2.51*3.14*vs.*D(1,22)./(4.*Qy(22)).*(0.25.*(log10(ee./(3.7.*D(1,22))+2.51*3.14*vs.*D(1,22)./(4.*Qy(22)).*0.00001.^-0.5)).^-2).^-0.5)).^-2).^-0.5)).^-2)))+(-4);...
     (1.*Qy(1))+(-1.*Qy(2))+(-2.472000e-01);...
     (1.*Qy(2))+(-1.*Qy(3))+(-1.*Qy(19))+(-1.*Qy(20))+(-2.361000e-01);...
     (1.*Qy(3))+(-1.*Qy(4))+(-3.610000e-02);...
     (1.*Qy(4))+(-1.*Qy(5))+(-2.014000e-01);...
     (1.*Qy(5))+(-1.*Qy(6))+(-2.792000e-01);...
     (1.*Qy(6))+(-1.*Qy(7))+(-3.750000e-01);...
     (1.*Qy(7))+(-1.*Qy(8))+(-1.528000e-01);...
     (1.*Qy(8))+(-1.*Qy(9))+(-1.458000e-01);...
     (1.*Qy(9))+(-1.*Qy(10))+(1.*Qy(13))+(-1.458000e-01);...
     (1.*Qy(10))+(-1.*Qy(11))+(-1.389000e-01);...
     (1.*Qy(11))+(-1.*Qy(12))+(-1.556000e-01);...
     (1.*Qy(12))+(-2.611000e-01);...
     (-1.*Qy(13))+(1.*Qy(14))+(-1.708000e-01);...
     (-1.*Qy(14))+(1.*Qy(15))+(-7.780000e-02);...
     (-1.*Qy(15))+(1.*Qy(16))+(-1.*Qy(28))+(-8.610000e-02);...
     (-1.*Qy(16))+(1.*Qy(17))+(-2.403000e-01);...
     (-1.*Qy(17))+(1.*Qy(18))+(-3.736000e-01);...
     (-1.*Qy(18))+(1.*Qy(19))+(-1.670000e-02);...
     (1.*Qy(20))+(-1.*Qy(21))+(-1.*Qy(23))+(-3.542000e-01);...
     (1.*Qy(21))+(-1.*Qy(22))+(-2.583000e-01);...
     (1.*Qy(22))+(-1.347000e-01);...
     (1.*Qy(23))+(-1.*Qy(24))+(-1.*Qy(29))+(-2.903000e-01);...
     (1.*Qy(24))+(-1.*Qy(25))+(-2.278000e-01);...
     (1.*Qy(25))+(1.*Qy(26))+(-4.720000e-02);...
     (-1.*Qy(26))+(1.*Qy(27))+(-2.500000e-01);...
     (-1.*Qy(27))+(1.*Qy(28))+(-1.028000e-01);...
     (1.*Qy(29))+(-1.*Qy(30))+(-8.060000e-02);...
     (1.*Qy(30))+(-1.*Qy(31))+(-1.000000e-01);...
     (1.*Qy(31))+(-1.*Qy(32))+(-1.000000e-01);...
     (1.*Qy(32))+(1.*Qy(33))+(-2.920000e-02);...
     (-1.*Qy(33))+(1.*Qy(34))+(-2.236000e-01)];
options = optimoptions('fsolve','Display','iter',MaxIterations=100000, MaxFunctionEvaluations=100000, Algorithm='levenberg-marquardt');            %  'levenberg-marquardt'
[Qy] = fsolve(FUN, Qy0, options); 
       for i=1:size(D,2)
                          vel=abs(4*Qy(i,1)./(3.14*D(1,i).^2));     [rn, cn]=find(Dia(1,1:szDia)<D(1,i),1,'first');    [rx, cx]=find(Dia(1,1:szDia)>D(1,i),1,'first');    % vel_mn=0.5*Dia(2,i);
            if isempty(rn)&&isempty(rx)                                                                                                             
            elseif vel<0.3 && ~isempty(rn);                                      D(1,i) = Dia(1,cn);  
            elseif vel>2.0 && ~isempty(rx);                                      D(1,i) = Dia(1,cx);           
            else (~isempty(rn)&&~isempty(rx))&&((vel<2&&vel>0.3));                  end   
      end
 DD(n,:) = D(:);   D = D;            %Qy=Qy,
 end
          DD,                         Li=L'; Di=D';         vel=abs(4*Qy(:,1)./(3.14.*(Di(:,1)).^2));   Re=abs(4.*Qy(:,1)./(3.14*vs.*Di(:,1))); 
                                                            fy11=-2*log10(ee./(3.7.*Di(:,1))+2.51*3.14*vs.*Di(:,1)./(4.*Qy(:,1)*0.0001.^0.5)); fy1=-2*log10(ee./(3.7.*Di(:,1))+2.51*3.14*vs.*Di(:,1)./(4.*Qy(:,1)).*fy11.^0.5); fy=-2*log10(ee./(3.7.*Di(:,1))+2.51*3.14*vs.*Di(:,1)./(4.*Qy(:,1)).*fy1.^0.5);  f=-2*log10(ee./(3.7.*Di(:,1))+2.51*3.14*vs.*Di(:,1)./(4.*Qy(:,1)).*fy.^0.5); ff=(1./f).^2;
                                                            n=7; Data1=zeros(p,n);   Data1(:,1)=Li(:,1); Data1(:,2)=Di(:,1);   Data1(:,3)=Qy(:,1);          Data1(:,4)=vel(:,1); Data1(:,5)=ff(:,1);  Data1(:,6)=Re(:,1);  Data1(:,7)=8./(9.81*3.14.^2).*Data1(:,5).*Data1(:,1).*(Data1(:,3)).^2./(Data1(:,2)).^5;
                                                            StrNum={'string','double','double','double','double','double','double','double'};               subTitl={'Pipes [x-z]', 'Length [m]', 'Diameter [m]', 'Flow rate [m3/s]', 'Velocity [m/s]', 'Friction, f', 'Reynold No.', 'Headlosses [m]'};	
                                                            tz=table('size', [p, 8], 'variabletypes',StrNum, 'variablenames', subTitl);                     Pipexz=["1P","2P","3P","4P","5P","6P","7P","8P","9P","10P","11P","12P","13P","14P","15P","16P","17P","18P","19P","20P","1P","2P","3P","4P","5P","6P","7P","8P","9P","10P","11P","12P","13P","14P"];
                                                            tz{:,1}=Pipexz';  tz{:,2:8} = Data1(:,1:7),                         toc,                                % tz{:,2:cCc+0} = Data1(:,1:cCc),                                                                                                         % MIDsrt=sortrows(tz,sn);  MIDfn=MIDsrt;  MIDfn(:,end)=[ ];     
end
0 commentaires
Voir également
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!


