哈尔滨工程大学数值分析大作业2014-附fortran程序

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FORTRAN程序设计大作业

FORTRAN程序设计大作业

上海师范大学FORTRAN 大作业题目:核检钢筋砼矩形截面梁的安全性能及求算施工托架在荷载作用下的各杆轴力专业土木工程(中英合作)学号姓名120445055王璐祎120445056张双指导老师郭剑虹完成日期2014年11月一.问题描述1:现核检一钢筋混凝土矩形截面梁,已知该混凝土保护层为25mm(二a类环境),宽度为b,高度为h,所能承受弯矩设计值M=160kN·m,采用C20级混凝土,HRB400级钢筋,箍筋直径为8mm,截面配筋如下图1-1所示,请核查该核矩形截面的安全性。

图1-1附表1:混凝土强度设计值(N/mm2)附表2 普通钢筋强度设计值(N/mm2)二.程序代码1:PROGRAM EXAMIMPLICIT NONEINTEGER B,HREAL FY,AS,H0,X,A1,FC(8),FT(8),CB,M,PMIN,P READ *,B,HA1=1.0FC=(/7.2,9.6,11.9,14.3,16.7,19.1,21.1,23.1/) FT=(/0.91,1.10,1.27,1.43,1.57,1.71,1.80,1.89/)AS=1256FY=360CB=0.518H0=H-25-8-10PMIN=0.45*FT(8)/FYP=AS/(B*H)DO WHILE (P<PMIN)选择语句当P<PMIN时DO WHILE (P<0.002)选择语句当P<0.002时PRINT *,"FAIL"输出 FAILEND DO结束选择语句X=FY*AS/(A1*FC(8)*B)那么X=FY乘以AS除以(A1乘以FC(8)乘以B)IF(X<(CB*H)) THEN选择语句当X小于CB乘以H时M=FY*AS*(H0-X/2)END IF结束选择语句IF (M>160) THEN选择语句当M大于160时PRINT *,"PASS"输出“PASS”ELSE否则PRINT *,"FAIL"输出"FAIL"END IF结束选择WRITE(*,10)FC10 FORMAT(1X,2X4)PAUSEEND结束三.问题描述2:下所示为一施工托架的计算简图。

哈尔滨工程大学传热学大作业数值计算matlab程序内容

哈尔滨工程大学传热学大作业数值计算matlab程序内容

传热学作业数值计算1 程序内容: 数值计算matlab程序内容:>> tw1=10; % 赋初值赋初值 tw2=20; c=1.5; p2=20; p1=c*p2; L2=40; L1=c*L2; deltaX=L2/p2; a=p2+1; b=p1+1; =ones(a,b)*5; m1=ones(a,b); m1(a,2:b-1)=zeros(1,b-2); m1(2:a,1)=zeros(a-1,1); m1(2:a,b)=zeros(a-1,1); m1(1,:)=ones(1,b)*2; k=0; max1=1.0; tn= ; while(max1>1e-6) max1=0; k=k+1; for i=1:1:a for j=1:1:b m=m1(i,j); n= (i,j); switch m case 0 tn(i,j)=tw1; case 1 tn(i,j)=0.25*(tn(i,j+1)+tn(i,j-1)+tn(i+1,j)+tn(i-1,j)); case 2 tn(i,j)=tw1+tw2*sin(pi*(j-1)/(b-1)); end er=abs(tn(i,j)-n); if er>max1 max1=er; end end end =tn; end k max1 t2=ones(a,b); %求解析温度场求解析温度场for i=a:-1:1 for j=1:1:b y=deltaX*(a-i); x=deltaX*(j-1); t2(i,j)=tw1+tw2*sin(pi*x/L1)*(sinh(pi*y/L1))/(sinh(pi*L2/L1)); end end t2 迭代次数k =706 数值解温度场 数值解每次迭代的最大误差max1 =9.8531e-07 解析温度场 t2 解析温度场取第11行的解析解和数值解的点行的解析解和数值解的点行的解析解的直线,散点为其数值解的点 曲线为第11行的解析解的直线,散点为其数值解的点解析解 第11行的误差=[数值解(11行) –解析解(11行)]/解析解数值温度场图像数值温度场图像 解析温度场图像解析温度场图像数值解与解析解的误差数值解与解析解的误差数值计算matlab 程序内容:程序内容: >> tw1=10; tw2=20; c=1.5; p2=20; p1=c*p2; L2=20; deltaX=L2/p2; L1=c*L2; a=p2+1; b=p1+1; =ones(a,b)*5; m1=ones(a,b); m1(a,2:b-1)=zeros(1,b-2); m1(2:a,1)=zeros(a-1,1); m1(2:a,b)=zeros(a-1,1); m1(1,:)=ones(1,b)*2; k=0; max1=1.0; tn= ; while(max1>1e-6) max1=0; k=k+1; for i=1:1:a for j=1:1:b m=m1(i,j); n= (i,j); switch m case 0 tn(i,j)=tw1; case 1 tn(i,j)=0.25*(tn(i,j+1)+tn(i,j-1)+tn(i+1,j)+tn(i-1,j)); case 2 tn(i,j)=tw2; end er=abs(tn(i,j)-n); if er>max1 max1=er; end end end =tn; end k max1 tx=ones(a,b); for i=1:1:a for j=1:1:b y=(a-i)*deltaX; x=(j-1)*deltaX; m=sym('m'); g=(((-1)^(m+1)+1)/m)*sin(m*pi*x/L1)*sinh(m*pi*y/L1)/sinh(m*pi*L2/L1); h=symsum(g,m,1,100); tx(i,j)=2*h*(tw2-tw1)/pi+tw1; end end tx 迭代次数k = 695 数值解温度场 数值解每次迭代的最大误差max1 =9.8243e-07 解析温度场 tx = 解析温度场行的解析解和数值解的点取第11行的解析解和数值解的点行的解析解的直线,散点为其数值解的点 曲线为第11行的解析解的直线,散点为其数值解的点解析解 第11行的误差=[数值解(11行) –解析解(11行)]/解析解图像: 数值温度场 图像图像 :解析温度场tx图像:数值解与解析解的误差数值解与解析解的误差程序内容: 数值计算matlab程序内容:>> t0=90; =10; L=10; c=0.25; p2=20; p1=p2/c; B=c*L; d=0.5*B; h=10; a=p2+1; b=p1+1; deltaX=B/p2; lambda=160; Bi=h*deltaX/lambda; =ones(a,b)*10; m1=ones(a,b)*3; m1(2:a-1,1)=zeros(a-2,1); m1(a,2:b-1)=ones(1,b-2); m1(1,2:b-1)=ones(1,b-2)*6; m1(2:a-1,b)=ones(a-2,1)*2; m1(1,b)=ones(1,1)*4; m1(a,b)=ones(1,1)*5; m1(1,1)=7; m1(a,1)=8; tn= ; max1=1.0; k=0; while ( max1>1e-6) k=k+1; max1=0; for i=1:1:a for j=1:1:b m=m1(i,j); n=tn(i,j); switch m case 0 tn(i,j)=t0; case 1 tn(i,j)=(2*tn(i-1,j)+tn(i,j-1)+tn(i,j+1)-4* )/(4+2*Bi)+ ; case 2 tn(i,j)=(2*tn(i,j-1)+tn(i-1,j)+tn(i+1,j)-4* )/(4+2*Bi)+ ; case 3 tn(i,j)=0.25*(tn(i,j-1)+tn(i,j+1)+tn(i-1,j)+tn(i+1,j)); case 4 tn(i,j)=(tn(i,j-1)+tn(i+1,j)-2* )/(2*Bi+2)+ ; case 5 tn(i,j)=(tn(i,j-1)+tn(i-1,j)-2* )/(2*Bi+2)+ ; case 6 tn(i,j)=(2*tn(i+1,j)+tn(i,j-1)+tn(i,j+1)-4* )/(4+2*Bi)+ ; case 7 tn(i,j)=t0; case 8 tn(i,j)=t0; end er=abs(tn(i,j)-n); if er>max1 max1=er; end end end =tn; end k ta=ones(a,b); Bi1=h*d/lambda; sbi=sqrt(Bi1); for i=1:1:a for j=1:1:b if i>(a+1)/2 y=-(i-(a+1)/2)*deltaX; else y=((a+1)/2-i)*deltaX; end x=deltaX*(j-1); ta(i,j)=(cosh(sbi*(L-x)/d)+sbi*sinh(sbi*(L-x)/d))*(t0- )/(cosh(sbi*L/d)+sbi*sinh(sbi*L/d))+ ; end end ta 迭代次数k =1461 数值解温度场 解析温度场 ta 解析温度场行的解析解和数值解的点取第11行的解析解和数值解的点曲线为第11行的解析解的直线,散点为其数值解的点行的解析解的直线,散点为其数值解的点解析解 第11行的误差=[数值解(11行) –解析解(11行)]/解析解图像如下图像如下数值温度场图像数值温度场图像 解析温度场图像解析温度场图像数值解与解析解的误差数值解与解析解的误差程序内容:数值计算matlab程序内容:>> tw=10; L2=15; c=0.75; L1=L2/c; p2=24 ; p1=p2/c; deltaX=2*L2/p2; a=p2+1; b=p1+1; lambda=16; qv0=24; =ones(a,b)*5; m1=ones(a,b); m1(1,:)=zeros(1,b); m1(2:a,b)=zeros(a-1,1); m1(2:a,1)=zeros(a-1,1); m1(a,2:b-1)=zeros(1,b-2); tn= ; max1=1.0; k=0; while(max1>1e-6) max1=0; k=k+1; for i=1:1:a for j=1:1:b m=m1(i,j); n=tn(i,j); switch m case 0 tn(i,j)=tw; case 1 tn(i,j)=0.25*(tn(i-1,j)+tn(i+1,j)+tn(i,j-1)+tn(i,j+1)+qv0*(deltaX^2)/lambda); end er=abs(tn(i,j)-n); if er>max1 max1=er; end end end =tn; end k; tx=ones(a,b); for i=1:1:a for j=1:1:b if i>(a+1)/2 y=-(i-(a+1)/2)*deltaX; else y=((a+1)/2-i)*deltaX; end if j>(b+1)/2 x=(j-(b+1)/2)*deltaX; else x=-((b+1)/2-j)*deltaX; end m=sym('m'); xi=(2*m-1)*pi/2; g=((-1)^m)/(xi^3)*(cosh(xi*y/L1)/cosh(xi*L2/L1))*cos(xi*x/L1); h=symsum(g,m,1,100); tx(i,j)=2*qv0*L1^2/lambda*h+qv0*(L1^2-x^2)/(2*lambda)+tw; end end tx 数值温度场 解析温度场tx 取第13行的解析解和数值解的点行的解析解和数值解的点行的解析解的直线,散点为其数值解的点曲线为第13行的解析解的直线,散点为其数值解的点解析解 第13行的误差=[数值解(13行) –解析解(13行)]/解析解数值温度场图像数值温度场图像 解析温度场图像解析温度场图像数值解与解析解的误差数值解与解析解的误差。

北航数值分析报告大作业第三题(fortran)

北航数值分析报告大作业第三题(fortran)

“数值分析“计算实习大作业第三题——SY1415215孔维鹏一、计算说明1、将x i=0.08i,y j=0.5+0.05j分别代入方程组(A.3)得到关于t,u,v,w的的方程组,调用离散牛顿迭代子函数求出与x i,y j对应的t i,u j。

2、调用分片二次代数插值子函数在点(t i,u j)处插值得到z(x i,y j)=f(x i,y j),得到数表(x i,y j,f(x i,y j))。

3、对于k=1,2,3,4⋯,分别调用最小二乘拟合子函数计算系数矩阵c rs及误差σ,直到满足精度,即求得最小的k值及系数矩阵c rs。

4、将x i∗=0.1i,y j∗=0.5+0.2j分别代入方程组(A.3)得到关于t∗,u∗,v∗,w∗的的方程组,调用离散牛顿迭代子函数求出与x i∗,y j∗对应的t i∗,u j∗,调用分片二次代数插值子函数在点(t i∗,u j∗)处插值得到z∗(x i∗,y j∗)=f(x i∗,y j∗);调用步骤3中求得的系数矩阵c rs求得p(x i∗,y j∗),打印数表(x i∗,y j∗,f(x i∗,y j∗),p(x i∗,y j∗))。

二、源程序(FORTRAN)PROGRAM SY1415215DIMENSION X(11),Y(21),T(6),U(6),Z(6,6),UX(11,21),TY(11,21),FXY(11,21),C(6,6) DIMENSION X1(8),Y1(5),FXY1(8,5),PXY1(8,5),UX1(8,5),TY1(8,5)REAL(8) X,Y,T,U,Z,FXY,UX,TY,C,E,X1,Y1,FXY1,PXY1,UX1,TY1OPEN (1,FILE='第三题计算结果.TXT')DO I=1,11X(I)=0.08*(I-1)ENDDODO I=1,21Y(I)=0.5+0.05*(I-1)ENDDO!*****求解非线性方程组,得到z=f(t,u)的函数*******DO I=1,11DO J=1,21CALL DISNEWTON_NONLINEAR(X(I),Y(J),UX(I,J),TY(I,J)) ENDDOENDDO!*************分片二次插值得到z=f(x,y)***********DO I=1,11DO J=1,21CALL INTERPOLATION(UX(I,J),TY(I,J),FXY(I,J))ENDDOENDDOWRITE (1,"('数表(x,y,f(x,y)):')")WRITE (1,"(3X,'X',7X,'Y',10X,'F(X,Y)')")DO I=1,11DO J=1,21WRITE(1,'(1X,F5.2,2X,F5.3,2X,E20.13)') X(I),Y(J),FXY(I,J) ENDDOWRITE (1,"('')")ENDDO!***********最小二乘拟合得到P(x,y)**************N=11M=21WRITE (1,'(" ","K和σ分别为:")')DO K=1,20CALL LSFITTING(X,Y,FXY,C,N,M,K,K,E)WRITE (1,'(I3,2X,E20.13)') K-1,EIF(E<10E-7) EXITENDDOWRITE(1,'(" ")')WRITE(1,'("系数矩阵Crs(按行)为:")')DO I=1,KDO J=1,KWRITE (1,'(E20.13,2X,\)') C(I,J)ENDDOWRITE (1,"('')")WRITE (*,"('')")ENDDODO I=1,8X1(I)=0.1*IENDDODO J=1,5Y1(J)=0.5+0.2*JENDDODO I=1,8DO J=1,5CALL DISNEWTON_NONLINEAR(X1(I),Y1(J),UX1(I,J),TY1(I,J))ENDDOENDDODO I=1,8DO J=1,5CALL INTERPOLATION(UX1(I,J),TY1(I,J),FXY1(I,J))ENDDOENDDOPXY1=0DO I=1,8DO J=1,5DO II=1,KDO JJ=1,KPXY1(I,J)=PXY1(I,J)+C(II,JJ)*(X1(I)**(II-1))*(Y1(J)**(JJ-1)) ENDDOENDDOENDDOENDDOWRITE(1,'(" ")')WRITE(1,'("数表(x,y,f(x,y),p(x,y)):")')WRITE(1,"(2X,'X',6X,'Y',12X,'F(X,Y)',14X,'P(X,Y)')")DO I=1,8DO J=1,5WRITE(1,'(F5.3,2X,F5.3,2X,E20.13,2X,E20.13)') X1(I),Y1(J),FXY1(I,J),PXY1(I,J) ENDDOWRITE (1,"('')")ENDDOCLOSE (1)END!***********用离散牛顿法求解非线性方程组****************SUBROUTINE DISNEWTON_NONLINEAR(X1,Y1,U,T)PARAMETER (N=4)REAL EPS !EPS为迭代精度,M为最大迭代次数DIMENSION X(N),H(N),Y(N),JA(N,N),E(N),XK(N)REAL(8) JA,X,H,Y,E,XK,U,T,V,W,X1,Y1,E1,E2F1(T,U,V,W)=0.5*COS(T)+U+V+W-X1-2.67F2(T,U,V,W)=T+0.5*SIN(U)+V+W-Y1-1.07F3(T,U,V,W)=0.5*T+U+COS(V)+W-X1-3.74F4(T,U,V,W)=T+0.5*U+V+SIN(W)-Y1-0.79EPS=10E-12M=100X=1.0DO K=1,MH=1!计算Y=F(x)Y(1)=F1(X(1),X(2),X(3),X(4))Y(2)=F2(X(1),X(2),X(3),X(4))Y(3)=F3(X(1),X(2),X(3),X(4))Y(4)=F4(X(1),X(2),X(3),X(4))!计算JA(N,N)E=0.0DO I=1,NDO J=1,NDO JJ=1,NIF(JJ==J) THENE(JJ)=X(JJ)+H(JJ)ELSEE(JJ)=X(JJ)ENDIFENDDOIF(I==1) THENJA(I,J)=(F1(E(1),E(2),E(3),E(4))-F1(X(1),X(2),X(3),X(4)))/H(J) ELSEIF(I==2) THENJA(I,J)=(F2(E(1),E(2),E(3),E(4))-F2(X(1),X(2),X(3),X(4)))/H(J) ELSEIF(I==3) THENJA(I,J)=(F3(E(1),E(2),E(3),E(4))-F3(X(1),X(2),X(3),X(4)))/H(J) ELSEIF(I==4) THENJA(I,J)=(F4(E(1),E(2),E(3),E(4))-F4(X(1),X(2),X(3),X(4)))/H(J) ENDIFENDDOENDDO!求解线性方程组CALL GAUSS(JA,XK,-Y,N)!判断精度CALL NORM(XK,N,E1)CALL NORM(X,N,E2)IF(E1/E2<=EPS) THENT=X(1)U=X(2)EXITELSEDO I=1,NX(I)=X(I)+XK(I)ENDDOENDIFENDDORETURNEND!**********列主元高斯消去法求解线性方程组********* SUBROUTINE GAUSS(A,X,B,N)DIMENSION A(N,N),B(N),X(N),T(N,N),TB(N)REAL M(N,N)REAL(8) A,B,X,T!消元过程DO K=1,N-1TA=A(K,K)TL=KDO L=K+1,NIF ((A(L,K)>TA).OR.(A(L,K)==TA)) THENTA=A(L,K)TL=LDO J=K,NT(K,J)=A(K,J)A(K,J)=A(TL,J)A(TL,J)=T(K,J)ENDDOTB(K)=B(K)B(K)=B(TL)B(TL)=TB(K)ENDIFENDDODO I=K+1,NM(I,K)=A(I,K)/A(K,K)A(I,K)=0DO J=K+1,NA(I,J)=A(I,J)-M(I,K)*A(K,J)ENDDOB(I)=B(I)-M(I,K)*B(K)ENDDOENDDO!回代过程X(N)=B(N)/A(N,N)DO K=N-1,1,-1S=0.0DO J=K+1,NS=S+A(K,J)*X(J)ENDDOX(K)=(B(K)-S)/A(K,K)ENDDORETURNEND!***********求向量的无穷数************ SUBROUTINE NORM(X,N,A)DIMENSION X(N)REAL(8) X,AA=ABS(X(1))DO I=2,NIF(ABS(X(I))>ABS(X(I-1))) THENA=ABS(X(I))ENDIFENDDORETURNEND!**************分片二次代数插值************** SUBROUTINE INTERPOLATION(U,V,W) PARAMETER (N=6,M=6)DIMENSION X(N),Y(M),Z(M,N),LK(3),LR(3)REAL(8) X,Y,Z,H,TREAL(8) U,V,W,LK,LR !U,V分别为插值点处的坐标,W为插值结果INTEGER R!**********************数据赋值********************** DATA Y/0.0,0.2,0.4,0.6,0.8,1.0/DATA X/0.0,0.4,0.8,1.2,1.6,2.0/DATA Z/-0.5,-0.42,-0.18,0.22,0.78,1.5,&&-0.34,-0.5,-0.5,-0.34,-0.02,0.46,&&0.14,-0.26,-0.5,-0.58,-0.5,-0.26,&&0.94,0.3,-0.18,-0.5,-0.66,-0.66,&&2.06,1.18,0.46,-0.1,-0.5,-0.74,&&3.5,2.38,1.42,0.62,-0.02,-0.5/H=0.4T=0.2!******************计算K,R*************************IF(U<=X(2)+H/2) THENK=2ELSEIF(U>X(N-1)-H/2) THENK=N-1ELSEDO I=3,N-2IF((U>X(I)-H/2).AND.(U<=X(I)+H/2)) THENK=IENDIFENDDOENDIFIF(V<=Y(2)+T/2) THENR=2ELSEIF(V>Y(M-1)-T/2) THENR=M-1ELSEDO J=3,M-2IF((V>Y(J)-T/2).AND.(V<=Y(J)+T/2)) THENR=JENDIFENDDOENDIFI=KJ=RLK(1)=(U-X(I))*(U-X(I+1))/(X(I-1)-X(I))/(X(I-1)-X(I+1))LK(2)=(U-X(I-1))*(U-X(I+1))/(X(I)-X(I-1))/(X(I)-X(I+1)) LK(3)=(U-X(I))*(U-X(I-1))/(X(I+1)-X(I))/(X(I+1)-X(I-1)) LR(1)=(V-Y(J))*(V-Y(J+1))/(Y(J-1)-Y(J))/(Y(J-1)-Y(J+1)) LR(2)=(V-Y(J-1))*(V-Y(J+1))/(Y(J)-Y(J-1))/(Y(J)-Y(J+1)) LR(3)=(V-Y(J))*(V-Y(J-1))/(Y(J+1)-Y(J))/(Y(J+1)-Y(J-1))W=0DO K=1,3DO R=1,3W=W+LK(K)*LR(R)*Z(J+R-2,I+K-2)ENDDOENDDORETURNEND!*******************最小二乘拟合子函数************** SUBROUTINE LSFITTING(X,Y,Z,A,N,M,P,Q,DT1)INTEGER P,QDIMENSION X(N),Y(M),Z(N,M),A(P,Q)DIMENSION APX(20),APY(20),BX(20),BY(20),U(20,20),V(20,M) DIMENSION T(20),T1(20),T2(20)REAL(8) X,Y,Z,A,DT1DO I=1,PDO J=1,QA(I,J)=0.0ENDDOENDDOIF(P>N) P=NIF(P>20) P=20IF(Q>M) Q=MIF(Q>20) Q=20XX=0YY=0D1=NAPX(1)=0.0DO I=1,NAPX(1)=APX(1)+X(I)ENDDOAPX(1)=APX(1)/D1DO J=1,MV(1,J)=0.0DO I=1,NV(1,J)=V(1,J)+Z(I,J)ENDDOV(1,J)=V(1,J)/D1ENDDOIF(P>1) THEND2=0.0APX(2)=0.0DO I=1,NG=X(I)-APX(1)D2=D2+G*GAPX(2)=APX(2)+(X(I)-XX)*G*G ENDDOAPX(2)=APX(2)/D2BX(2)=D2/D1DO J=1,MV(2,J)=0.0DO I=1,NG=X(I)-APX(1)V(2,J)=V(2,J)+Z(I,J)*GENDDOV(2,J)=V(2,J)/D2ENDDOD1=D2ENDIFDO K=3,PD2=0.0APX(K)=0.0DO J=1,MV(K,J)=0.0ENDDODO I=1,NG1=1.0G2=X(I)-APX(1)DO J=3,KG=(X(I)-APX(J-1))*G2-BX(J-1)*G1 G1=G2G2=GENDDOD2=D2+G*GAPX(K)=APX(K)+X(I)*G*GDO J=1,MV(K,J)=V(K,J)+Z(I,J)*GENDDOENDDODO J=1,MV(K,J)=V(K,J)/D2ENDDOAPX(K)=APX(K)/D2BX(K)=D2/D1D1=D2ENDDOD1=MAPY(1)=0.0DO I=1,MAPY(1)=APY(1)+Y(I)ENDDOAPY(1)=APY(1)/D1DO J=1,PU(J,1)=0.0DO I=1,MU(J,1)=U(J,1)+V(J,I) ENDDOU(J,1)=U(J,1)/D1ENDDOIF(Q>1)THEND2=0.0APY(2)=0.0DO I=1,MG=Y(I)-APY(1)D2=D2+G*GAPY(2)=APY(2)+(Y(I))*G*G ENDDOAPY(2)=APY(2)/D2BY(2)=D2/D1DO J=1,PU(J,2)=0.0DO I=1,MG=Y(I)-APY(1)U(J,2)=U(J,2)+V(J,I)*GENDDOU(J,2)=U(J,2)/D2ENDDOD1=D2ENDIFDO K=3,QD2=0.0APY(K)=0.0DO J=1,PU(J,K)=0.0ENDDODO I=1,MG1=1.0G2=Y(I)-APY(1)DO J=3,KG=(Y(I)-APY(J-1))*G2-BY(J-1)*G1 G1=G2G2=GENDDOD2=D2+G*GAPY(K)=APY(K)+Y(I)*G*GDO J=1,PU(J,K)=U(J,K)+V(J,I)*GENDDOENDDODO J=1,PU(J,K)=U(J,K)/D2ENDDOAPY(K)=APY(K)/D2BY(K)=D2/D1D1=D2ENDDOV(1,1)=1.0V(2,1)=-APY(1)V(2,2)=1.0DO I=1,PDO J=1,QA(I,J)=0.0ENDDOENDDODO I=3,QV(I,I)=V(I-1,I-1)V(I,I-1)=-APY(I-1)*V(I-1,I-1)+V(I-1,I-2)IF(I>=4) THENDO K=I-2,2,-1V(I,K)=-APY(I-1)*V(I-1,K)+V(I-1,K-1)-BY(I-1)*V(I-2,K) ENDDOENDIFV(I,1)=-APY(I-1)*V(I-1,1)-BY(I-1)*V(I-2,1)ENDDODO I=1,PIF(I==1) THENT(1)=1.0T1(1)=1.0ELSEIF(I==2) THENT(1)=-APX(1)T(2)=1.0T2(1)=T(1)T2(2)=T(2)ELSET(I)=T2(I-1)T(I-1)=-APX(I-1)*T2(I-1)+T2(I-2)IF(I>=4) THENDO K=I-2,2,-1T(K)=-APX(I-1)*T2(K)+T2(K-1)-BX(I-1)*T1(K)ENDDOENDIFT(1)=-APX(I-1)*T2(1)-BX(I-1)*T1(1)T2(I)=T(I)DO K=I-1,1,-1T1(K)=T2(K)T2(K)=T(K)ENDDOENDIFDO J=1,QDO K=I,1,-1DO L=J,1,-1A(K,L)=A(K,L)+U(I,J)*T(K)*V(J,L)ENDDOENDDOENDDOENDDODT1=0.0DO I=1,NX1=X(I)DO J=1,MY1=Y(J)X2=1.0DD=0.0DO K=1,PG=A(K,Q)DO KK=Q-1,1,-1G=G*Y1+A(K,KK)ENDDOG=G*X2DD=DD+GX2=X2*X1ENDDODT=DD-Z(I,J)DT1=DT1+DT*DTENDDOENDDORETURNEND三、计算结果数表(x,y,f(x,y)):X Y UX TY F(X,Y) 0.00 0.500 1.345 0.243 0.17E+000.00 0.550 1.322 0.269 0.66E+000.00 0.600 1.299 0.295 0.35E+000.00 0.650 1.277 0.322 0.94E+000.00 0.700 1.255 0.350 0.30E-020.00 0.750 1.235 0.377 -0.87E-010.00 0.800 1.215 0.406 -0.58E+000.00 0.850 1.196 0.434 -0.72E+000.00 0.900 1.177 0.463 -0.54E+000.00 0.950 1.159 0.492 -0.86E+000.00 1.050 1.125 0.550 -0.74E+00 0.00 1.100 1.109 0.580 -0.06E+00 0.00 1.150 1.093 0.609 -0.00E+00 0.00 1.200 1.079 0.639 -0.18E+00 0.00 1.250 1.064 0.669 -0.52E+00 0.00 1.300 1.050 0.699 -0.19E+00 0.00 1.350 1.037 0.729 -0.48E+00 0.00 1.400 1.024 0.759 -0.68E+00 0.00 1.450 1.011 0.790 -0.52E+00 0.00 1.500 1.000 0.820 -0.29E+000.08 0.500 1.415 0.228 0.67E+00 0.08 0.550 1.391 0.253 0.08E+00 0.08 0.600 1.368 0.279 0.02E+00 0.08 0.650 1.346 0.306 0.47E+00 0.08 0.700 1.325 0.333 0.57E+00 0.08 0.750 1.304 0.360 0.48E-01 0.08 0.800 1.284 0.388 -0.73E-01 0.08 0.850 1.265 0.416 -0.16E+00 0.08 0.900 1.246 0.444 -0.29E+00 0.08 0.950 1.229 0.473 -0.36E+00 0.08 1.000 1.211 0.502 -0.08E+00 0.08 1.050 1.194 0.531 -0.29E+00 0.08 1.100 1.178 0.560 -0.78E+00 0.08 1.150 1.163 0.589 -0.93E+00 0.08 1.200 1.148 0.619 -0.44E+00 0.08 1.250 1.133 0.649 -0.92E+00 0.08 1.300 1.119 0.679 -0.71E+000.08 1.400 1.093 0.739 -0.37E+00 0.08 1.450 1.080 0.769 -0.83E+00 0.08 1.500 1.068 0.799 -0.92E+000.16 0.500 1.483 0.214 0.31E+00 0.16 0.550 1.460 0.239 0.64E+00 0.16 0.600 1.437 0.264 0.91E+00 0.16 0.650 1.414 0.290 0.06E+00 0.16 0.700 1.393 0.316 0.70E+00 0.16 0.750 1.372 0.343 0.59E+00 0.16 0.800 1.352 0.370 0.12E+00 0.16 0.850 1.333 0.398 0.77E-02 0.16 0.900 1.315 0.426 -0.83E-01 0.16 0.950 1.297 0.454 -0.58E+00 0.16 1.000 1.279 0.483 -0.20E+00 0.16 1.050 1.262 0.512 -0.11E+00 0.16 1.100 1.246 0.541 -0.74E+00 0.16 1.150 1.231 0.570 -0.09E+00 0.16 1.200 1.216 0.600 -0.59E+00 0.16 1.250 1.201 0.629 -0.66E+00 0.16 1.300 1.187 0.659 -0.71E+00 0.16 1.350 1.174 0.689 -0.32E+00 0.16 1.400 1.161 0.718 -0.56E+00 0.16 1.450 1.148 0.748 -0.31E+00 0.16 1.500 1.136 0.778 -0.75E+000.24 0.500 1.551 0.201 0.66E+01 0.24 0.550 1.527 0.225 0.03E+000.24 0.650 1.482 0.275 0.64E+00 0.24 0.700 1.460 0.301 0.47E+00 0.24 0.750 1.439 0.327 0.34E+00 0.24 0.800 1.419 0.354 0.24E+00 0.24 0.850 1.400 0.381 0.69E+00 0.24 0.900 1.381 0.409 0.04E-01 0.24 0.950 1.363 0.437 -0.42E-01 0.24 1.000 1.346 0.465 -0.06E+00 0.24 1.050 1.329 0.494 -0.59E+00 0.24 1.100 1.313 0.523 -0.83E+00 0.24 1.150 1.297 0.552 -0.15E+00 0.24 1.200 1.282 0.581 -0.19E+00 0.24 1.250 1.267 0.610 -0.84E+00 0.24 1.300 1.253 0.640 -0.66E+00 0.24 1.350 1.240 0.669 -0.30E+00 0.24 1.400 1.227 0.699 -0.86E+00 0.24 1.450 1.214 0.729 -0.84E+00 0.24 1.500 1.202 0.759 -0.77E+000.32 0.500 1.617 0.188 0.28E+01 0.32 0.550 1.593 0.212 0.49E+01 0.32 0.600 1.570 0.236 0.68E+00 0.32 0.650 1.547 0.261 0.75E+00 0.32 0.700 1.526 0.286 0.60E+00 0.32 0.750 1.505 0.312 0.77E+00 0.32 0.800 1.485 0.339 0.05E+00 0.32 0.850 1.466 0.365 0.99E+00 0.32 0.900 1.447 0.393 0.27E+000.32 1.000 1.411 0.448 -0.01E-02 0.32 1.050 1.395 0.477 -0.41E-01 0.32 1.100 1.378 0.505 -0.18E+00 0.32 1.150 1.363 0.534 -0.25E+00 0.32 1.200 1.347 0.563 -0.29E+00 0.32 1.250 1.333 0.592 -0.90E+00 0.32 1.300 1.319 0.621 -0.00E+00 0.32 1.350 1.305 0.650 -0.40E+00 0.32 1.400 1.292 0.680 -0.54E+00 0.32 1.450 1.279 0.710 -0.79E+00 0.32 1.500 1.267 0.739 -0.91E+000.40 0.500 1.681 0.177 0.91E+01 0.40 0.550 1.658 0.199 0.00E+01 0.40 0.600 1.634 0.223 0.83E+01 0.40 0.650 1.612 0.247 0.02E+01 0.40 0.700 1.591 0.272 0.94E+00 0.40 0.750 1.570 0.298 0.49E+00 0.40 0.800 1.550 0.324 0.94E+00 0.40 0.850 1.530 0.350 0.40E+00 0.40 0.900 1.512 0.377 0.33E+00 0.40 0.950 1.493 0.405 0.99E+00 0.40 1.000 1.476 0.432 0.68E+00 0.40 1.050 1.459 0.460 0.08E-01 0.40 1.100 1.443 0.488 -0.84E-01 0.40 1.150 1.427 0.517 -0.98E+00 0.40 1.200 1.412 0.545 -0.27E+00 0.40 1.250 1.397 0.574 -0.06E+000.40 1.350 1.369 0.632 -0.66E+00 0.40 1.400 1.356 0.662 -0.37E+00 0.40 1.450 1.343 0.691 -0.43E+00 0.40 1.500 1.331 0.721 -0.12E+000.48 0.500 1.745 0.166 0.69E+01 0.48 0.550 1.721 0.188 0.02E+01 0.48 0.600 1.698 0.211 0.74E+01 0.48 0.650 1.676 0.235 0.40E+01 0.48 0.700 1.654 0.259 0.23E+01 0.48 0.750 1.634 0.284 0.56E+00 0.48 0.800 1.613 0.310 0.28E+00 0.48 0.850 1.594 0.336 0.49E+00 0.48 0.900 1.575 0.363 0.31E+00 0.48 0.950 1.557 0.390 0.66E+00 0.48 1.000 1.539 0.417 0.30E+00 0.48 1.050 1.522 0.444 0.34E+00 0.48 1.100 1.506 0.472 0.07E-01 0.48 1.150 1.490 0.500 -0.62E-01 0.48 1.200 1.475 0.529 -0.45E+00 0.48 1.250 1.460 0.557 -0.86E+00 0.48 1.300 1.446 0.586 -0.39E+00 0.48 1.350 1.432 0.615 -0.22E+00 0.48 1.400 1.419 0.644 -0.67E+00 0.48 1.450 1.406 0.674 -0.55E+00 0.48 1.500 1.394 0.703 -0.14E+000.56 0.500 1.808 0.156 0.48E+010.56 0.600 1.761 0.200 0.10E+01 0.56 0.650 1.739 0.223 0.68E+01 0.56 0.700 1.717 0.247 0.94E+01 0.56 0.750 1.696 0.272 0.33E+01 0.56 0.800 1.676 0.297 0.11E+00 0.56 0.850 1.657 0.323 0.63E+00 0.56 0.900 1.638 0.349 0.97E+00 0.56 0.950 1.620 0.375 0.52E+00 0.56 1.000 1.602 0.402 0.56E+00 0.56 1.050 1.585 0.429 0.47E+00 0.56 1.100 1.568 0.457 0.20E+00 0.56 1.150 1.552 0.485 0.13E+00 0.56 1.200 1.537 0.513 0.09E-01 0.56 1.250 1.522 0.541 -0.47E-01 0.56 1.300 1.508 0.570 -0.99E+00 0.56 1.350 1.494 0.599 -0.82E+00 0.56 1.400 1.481 0.627 -0.26E+00 0.56 1.450 1.468 0.657 -0.71E+00 0.56 1.500 1.455 0.686 -0.98E+000.64 0.500 1.870 0.147 0.74E+01 0.64 0.550 1.846 0.168 0.10E+01 0.64 0.600 1.823 0.190 0.54E+01 0.64 0.650 1.801 0.213 0.42E+01 0.64 0.700 1.779 0.236 0.56E+01 0.64 0.750 1.758 0.260 0.03E+01 0.64 0.800 1.738 0.285 0.42E+01 0.64 0.850 1.718 0.310 0.41E+010.64 0.950 1.681 0.362 0.36E+00 0.64 1.000 1.664 0.388 0.18E+00 0.64 1.050 1.646 0.415 0.28E+00 0.64 1.100 1.630 0.443 0.07E+00 0.64 1.150 1.614 0.470 0.66E+00 0.64 1.200 1.598 0.498 0.09E+00 0.64 1.250 1.584 0.526 0.50E-01 0.64 1.300 1.569 0.554 -0.88E-01 0.64 1.350 1.555 0.583 -0.76E+00 0.64 1.400 1.542 0.611 -0.66E+00 0.64 1.450 1.529 0.640 -0.33E+00 0.64 1.500 1.516 0.669 -0.56E+000.72 0.500 1.931 0.139 0.94E+01 0.72 0.550 1.907 0.159 0.84E+01 0.72 0.600 1.884 0.181 0.36E+01 0.72 0.650 1.862 0.203 0.40E+01 0.72 0.700 1.840 0.226 0.47E+01 0.72 0.750 1.819 0.249 0.56E+01 0.72 0.800 1.799 0.273 0.19E+01 0.72 0.850 1.779 0.298 0.37E+01 0.72 0.900 1.760 0.323 0.86E+01 0.72 0.950 1.742 0.349 0.76E+00 0.72 1.000 1.724 0.375 0.24E+00 0.72 1.050 1.707 0.402 0.55E+00 0.72 1.100 1.691 0.429 0.97E+00 0.72 1.150 1.675 0.456 0.27E+00 0.72 1.200 1.659 0.484 0.31E+000.72 1.250 1.644 0.511 0.51E+00 0.72 1.300 1.630 0.539 0.49E+00 0.72 1.350 1.616 0.568 0.72E-02 0.72 1.400 1.602 0.596 -0.69E-01 0.72 1.450 1.589 0.625 -0.67E+00 0.72 1.500 1.576 0.653 -0.20E+000.80 0.500 1.992 0.131 0.31E+01 0.80 0.550 1.968 0.151 0.44E+01 0.80 0.600 1.945 0.172 0.41E+01 0.80 0.650 1.922 0.193 0.45E+01 0.80 0.700 1.900 0.216 0.00E+01 0.80 0.750 1.879 0.239 0.10E+01 0.80 0.800 1.859 0.263 0.16E+01 0.80 0.850 1.840 0.287 0.52E+01 0.80 0.900 1.821 0.312 0.02E+01 0.80 0.950 1.802 0.337 0.38E+01 0.80 1.000 1.784 0.363 0.89E+01 0.80 1.050 1.767 0.389 0.28E+00 0.80 1.100 1.751 0.416 0.09E+00 0.80 1.150 1.734 0.443 0.23E+00 0.80 1.200 1.719 0.470 0.93E+00 0.80 1.250 1.704 0.498 0.15E+00 0.80 1.300 1.689 0.525 0.86E+00 0.80 1.350 1.675 0.553 0.64E+00 0.80 1.400 1.662 0.582 0.74E-01 0.80 1.450 1.649 0.610 -0.37E-01 0.80 1.500 1.636 0.638 -0.81E+00K和σ分别为:0 0.93E+031 0.61E+012 0.92E-023 0.53E-034 0.16E-055 0.77E-07系数矩阵Crs(按行)为:0.00E+01 -0.83E+01 0.56E+00 0.97E+00 -0.03E+00 0.70E-010.91E+01 -0.99E+00 -0.96E+01 0.17E+01 -0.66E+00 0.10E-010.77E+00 0.42E+01 -0.10E+00 -0.81E+00 0.81E+00 -0.62E-01-0.25E+00 -0.21E+00 0.97E+00 -0.18E+00 0.49E+00 -0.63E-010.34E+00 -0.56E+00 0.69E-01 0.51E+00 -0.77E-01 0.27E-01-0.94E-01 0.94E+00 -0.58E+00 0.69E-01 -0.50E-01 0.53E-02数表(x,y,f(x,y),p(x,y)):X Y F(X,Y) P(X,Y)0.100 0.700 0.58E+00 0.05E+000.100 1.100 -0.66E+00 -0.26E+00 0.100 1.300 -0.68E+00 -0.31E+00 0.100 1.500 -0.52E+00 -0.49E+000.200 0.700 0.54E+00 0.19E+00 0.200 0.900 -0.63E-01 -0.65E-01 0.200 1.100 -0.90E+00 -0.90E+00 0.200 1.300 -0.84E+00 -0.90E+00 0.200 1.500 -0.03E+00 -0.04E+000.300 0.700 0.82E+00 0.09E+00 0.300 0.900 0.48E+00 0.11E+00 0.300 1.100 -0.63E+00 -0.88E+00 0.300 1.300 -0.72E+00 -0.96E+00 0.300 1.500 -0.34E+00 -0.84E+000.400 0.700 0.79E+00 0.89E+00 0.400 0.900 0.56E+00 0.63E+00 0.400 1.100 -0.83E-01 -0.04E-01 0.400 1.300 -0.72E+00 -0.71E+00 0.400 1.500 -0.85E+00 -0.07E+000.500 0.700 0.56E+01 0.92E+01 0.500 0.900 0.51E+00 0.23E+00 0.500 1.100 0.59E+00 0.27E+00 0.500 1.300 -0.53E+00 -0.11E+00 0.500 1.500 -0.67E+00 -0.33E+000.600 0.900 0.14E+00 0.75E+00 0.600 1.100 0.19E+00 0.32E+00 0.600 1.300 -0.70E-01 -0.82E-01 0.600 1.500 -0.08E+00 -0.75E+000.700 0.700 0.89E+01 0.29E+01 0.700 0.900 0.91E+01 0.11E+01 0.700 1.100 0.60E+00 0.97E+00 0.700 1.300 0.22E-01 0.06E-01 0.700 1.500 -0.53E+00 -0.80E+000.800 0.700 0.09E+01 0.06E+01 0.800 0.900 0.32E+01 0.50E+01 0.800 1.100 0.03E+00 0.79E+00 0.800 1.300 0.25E+00 0.50E+00 0.800 1.500 -0.14E+00 -0.28E+00。

数值分析大作业四

数值分析大作业四

《数值分析》大作业四一、算法设计方案:复化梯形积分法,选取步长为1/500=0.002,迭代误差控制在E ≤1.0e-10①复化梯形积分法:11()[()()2()]2n bak hf x dx f a f b f a kh -=⎰≈+++∑,截断误差为:322()''()''(),[,]1212T b a b a R f h f a b n ηηη--=-=-∈其中。

复化Simpson 积分法,选取步长为1/50=0.02,迭代误差控制在E ≤1.0e-10②Simpson 积分法:121211()[()()4()2()]3m m bi i a i i hf x dx f a f b f x f x --==≈+++∑∑⎰, 截断误差为:4(4)(),[,]180s b a R h f a b ηη-=-∈。

③Guass积分法选用Gauss-Legendre 求积公式:111()()ni i i f x dx A f x -=≈∑⎰截断误差为:R= ()()n 2n 422n!2×(2[2!]2n 1f n n ⨯(2)η())+ η∈(1,1)。

选择9个节点:-0.9681602395,-0.8360311073,-0.6133714327,-0.3242534234,0,0.3242534234,0.6133714327,0.8360311073,0.9681602395, 对应的求积系数依次为:0.0812743884,0.1806481607,0.2606106964,0.3123470770,0.3302393550,0.3123470770,0.2606106964,0.1806481607,0.0812743884。

二、程序源代码:#include<stdio.h>#include<math.h>#include<stdlib.h>#define E 1.0e-10/****定义函数g和K*****/double g(double a){double b;b=exp(4*a)+(exp(a+4)-exp(-a-4))/(a+4);return b;}double K(double a,double b){double c;c=exp(a*b);return c;}/******复化梯形法******/void Tixing( ){double u[1001],x[1001],h,c[1001],e;int i,j,k;FILE *fp;fp=fopen("f:/result0. xls ","w");h=1.0/1500;for(i=0;i<3001;i++){x[i]=i*h-1;u[i]=g(x[i]);}for(k=0;k<100;k++){e=0;for(i=0;i<1001;i++){for(j=1,c[i]=0;j<N-1;j++)c[i]+=K(x[i],x[j])*u[j];u[i]=g(x[i])-h*c[i]-h/2*(K(x[i],x[0])*u[0]+K(x[i],x[N-1])*u[N-1]);e+=h*(exp(4*x[i])-u[i])*(exp(4*x[i])-u[i]);}if(e<=E) break;}for(i=0;i<1001;i++)fprintf(fp,"%.12lf,%.12lf\n",x[i],u[i]);fclose(fp);}/******复化Simpson法******/void simpson( ){double u[101],x[101],h,c[101],d[101],e;int i,j,k;FILE *fp;fp=fopen("f:/result1.xls","w");h=1.0/50;for(i=0;i<101;i++){x[i]=i*h-1;u[i]=g(x[i]);}for(k=0;k<50;k++){e=0;for(i=0;i<101;i++){for(j=1,c[i]=0,d[i]=0;j<51;j++){c[i]+=K(x[i],x[2*j-1])*u[2*j-1];if(j<50)d[i]+=K(x[i],x[2*j])*u[2*j];}u[i]=g(x[i])-4*h/3*c[i]-2*h/3*d[i]-h/3*(K(x[i],x[0])*u[0]+K(x[i],x[M-1])*u[M-1]);e+=h*(exp(4*x[i])-u[i])*(exp(4*x[i])-u[i]);}if(e<=E) break;}for(i=0;i<101;i++)fprintf(fp,"%.12lf,%.12lf\n",x[i],u[i]);fclose(fp);}/******Gauss积分法******/void gauss( ){double x[9]={-0.9681602395,-0.8360311073,-0.6133714327,-0.3242534234,0,\0.3242534234,0.6133714327,0.8360311073,0.9681602395},A[9]={0.0812743884,0.1806481607,0.2606106964,0.3123470770,0.3302393550,\0.3123470770,0.2606106964,0.1806481607,0.0812743884},u[9],c[9],e;int i,j,k;FILE *fp;fp=fopen("f:/result2. xls ","w");for(i=0;i<9;i++)u[i]=g(x[i]);for(k=0;k<50;k++){e=0;for(i=0;i<9;i++){for(j=0,c[i]=0;j<9;j++)c[i]+=A[j]*K(x[i],x[j])*u[j];u[i]=g(x[i])-c[i];e+=A[i]*(exp(4*x[i])-u[i])*(exp(4*x[i])-u[i]);}if(e<=E) break;}for(i=0;i<9;i++)fprintf(fp,"%.12lf,%.12lf\n",x[i],u[i]);fclose(fp);}/******主函数******/main(){Tixing ( );Simpson( );Gauss( );return 0;}三、运算结果复化梯形数据-10.018323-0.920.02523-0.9980.018471-0.9180.025433-0.9960.018619-0.9160.025637-0.9940.018768-0.9140.025843-0.9920.018919-0.9120.026051-0.990.019071-0.910.02626-0.9880.019224-0.9080.026471-0.9860.019378-0.9060.026683-0.9840.019534-0.9040.026897-0.9820.019691-0.9020.027113-0.980.019849-0.90.027331-0.9780.020008-0.8980.02755-0.9760.020169-0.8960.027772-0.9740.020331-0.8940.027995-0.9720.020494-0.8920.028219-0.970.020658-0.890.028446-0.9680.020824-0.8880.028674-0.9660.020992-0.8860.028905-0.9640.02116-0.8840.029137-0.9620.02133-0.8820.029371-0.960.021501-0.880.029607-0.9580.021674-0.8780.029844-0.9560.021848-0.8760.030084-0.9540.022023-0.8740.030326-0.9520.0222-0.8720.030569-0.950.022378-0.870.030815-0.9480.022558-0.8680.031062-0.9460.022739-0.8660.031311-0.9440.022922-0.8640.031563-0.9420.023106-0.8620.031816-0.940.023291-0.860.032072-0.9380.023478-0.8580.032329-0.9360.023667-0.8560.032589-0.9340.023857-0.8540.032851-0.9320.024048-0.8520.033114-0.930.024241-0.850.03338-0.9280.024436-0.8480.033648-0.9260.024632-0.8460.033918-0.9240.02483-0.8440.034191-0.9220.025029-0.8420.034465-0.840.034742-0.760.047841-0.8380.035021-0.7580.048225-0.8360.035302-0.7560.048613 -0.8340.035586-0.7540.049003 -0.8320.035872-0.7520.049396 -0.830.03616-0.750.049793 -0.8280.03645-0.7480.050193 -0.8260.036743-0.7460.050596 -0.8240.037038-0.7440.051002 -0.8220.037335-0.7420.051412 -0.820.037635-0.740.051825 -0.8180.037937-0.7380.052241 -0.8160.038242-0.7360.052661 -0.8140.038549-0.7340.053084 -0.8120.038858-0.7320.05351 -0.810.039171-0.730.05394 -0.8080.039485-0.7280.054373 -0.8060.039802-0.7260.054809 -0.8040.040122-0.7240.05525 -0.8020.040444-0.7220.055693 -0.80.040769-0.720.056141 -0.7980.041096-0.7180.056591 -0.7960.041426-0.7160.057046 -0.7940.041759-0.7140.057504 -0.7920.042094-0.7120.057966 -0.790.042432-0.710.058431 -0.7880.042773-0.7080.058901 -0.7860.043116-0.7060.059374 -0.7840.043463-0.7040.05985 -0.7820.043812-0.7020.060331 -0.780.044164-0.70.060816 -0.7780.044518-0.6980.061304 -0.7760.044876-0.6960.061796 -0.7740.045236-0.6940.062293 -0.7720.045599-0.6920.062793 -0.770.045966-0.690.063297 -0.7680.046335-0.6880.063805 -0.7660.046707-0.6860.064318 -0.7640.047082-0.6840.064834 -0.7620.04746-0.6820.065355-0.680.06588-0.60.090722 -0.6780.066409-0.5980.091451-0.6760.066942-0.5960.092185 -0.6740.06748-0.5940.092926 -0.6720.068022-0.5920.093672 -0.670.068568-0.590.094424 -0.6680.069119-0.5880.095183 -0.6660.069674-0.5860.095947 -0.6640.070234-0.5840.096718 -0.6620.070798-0.5820.097494 -0.660.071366-0.580.098277 -0.6580.071939-0.5780.099067 -0.6560.072517-0.5760.099862 -0.6540.0731-0.5740.100664 -0.6520.073687-0.5720.101473 -0.650.074278-0.570.102288 -0.6480.074875-0.5680.103109 -0.6460.075476-0.5660.103937 -0.6440.076082-0.5640.104772 -0.6420.076694-0.5620.105614 -0.640.077309-0.560.106462 -0.6380.07793-0.5580.107317 -0.6360.078556-0.5560.108179 -0.6340.079187-0.5540.109048 -0.6320.079823-0.5520.109924 -0.630.080464-0.550.110806 -0.6280.08111-0.5480.111696 -0.6260.081762-0.5460.112593 -0.6240.082418-0.5440.113498 -0.6220.08308-0.5420.114409 -0.620.083748-0.540.115328 -0.6180.08442-0.5380.116254 -0.6160.085098-0.5360.117188 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-0.0180.9305170.062 1.281442 -0.0160.9379910.064 1.291735 -0.0140.9455250.066 1.30211 -0.0120.953120.068 1.312569 -0.010.9607750.07 1.323112 -0.0080.9684930.072 1.333739 -0.0060.9762720.074 1.344452 -0.0040.9841130.076 1.355251 -0.0020.9920180.078 1.366136 00.9999860.08 1.377109 0.002 1.0080180.082 1.38817 0.004 1.0161140.084 1.39932 0.006 1.0242760.086 1.41056 0.008 1.0325030.088 1.4218890.09 1.433310.17 1.973853 0.092 1.4448230.172 1.9897080.094 1.4564280.174 2.005689 0.096 1.4681260.176 2.021799 0.098 1.4799180.178 2.038039 0.1 1.4918050.18 2.054408 0.102 1.5037870.182 2.07091 0.104 1.5158660.184 2.087543 0.106 1.5280410.186 2.104311 0.108 1.5403150.188 2.121213 0.11 1.5526870.19 2.138251 0.112 1.5651580.192 2.155425 0.114 1.577730.194 2.172738 0.116 1.5904020.196 2.19019 0.118 1.6031760.198 2.207781 0.12 1.6160530.2 2.225515 0.122 1.6290340.202 2.24339 0.124 1.6421180.204 2.261409 0.126 1.6553080.206 2.279573 0.128 1.6686040.208 2.297883 0.13 1.6820060.21 2.31634 0.132 1.6955160.212 2.334945 0.134 1.7091350.214 2.3537 0.136 1.7228630.216 2.372605 0.138 1.7367010.218 2.391662 0.14 1.750650.22 2.410872 0.142 1.7647120.222 2.430236 0.144 1.7788860.224 2.449756 0.146 1.7931740.226 2.469433 0.148 1.8075770.228 2.489268 0.15 1.8220960.23 2.509262 0.152 1.8367310.232 2.529417 0.154 1.8514840.234 2.549733 0.156 1.8663550.236 2.570213 0.158 1.8813460.238 2.590857 0.16 1.8964570.24 2.611667 0.162 1.911690.242 2.632645 0.164 1.9270450.244 2.65379 0.166 1.9425230.246 2.675106 0.168 1.9581260.248 2.6965930.25 2.7182520.33 3.743385 0.252 2.7400850.332 3.7734530.254 2.7620940.334 3.803761 0.256 2.7842790.336 3.834314 0.258 2.8066430.338 3.865111 0.26 2.8291860.34 3.896156 0.262 2.8519110.342 3.927451 0.264 2.8748180.344 3.958996 0.266 2.8979090.346 3.990796 0.268 2.9211850.348 4.02285 0.27 2.9446480.35 4.055162 0.272 2.96830.352 4.087734 0.274 2.9921420.354 4.120567 0.276 3.0161750.356 4.153664 0.278 3.0404010.358 4.187026 0.28 3.0648220.36 4.220657 0.282 3.0894390.362 4.254558 0.284 3.1142540.364 4.288731 0.286 3.1392680.366 4.323179 0.288 3.1644830.368 4.357903 0.29 3.18990.37 4.392906 0.292 3.2155220.372 4.42819 0.294 3.2413490.374 4.463758 0.296 3.2673840.376 4.499612 0.298 3.2936280.378 4.535753 0.3 3.3200830.38 4.572185 0.302 3.346750.382 4.608909 0.304 3.3736320.384 4.645928 0.306 3.4007290.386 4.683245 0.308 3.4280440.388 4.720861 0.31 3.4555790.39 4.75878 0.312 3.4833350.392 4.797003 0.314 3.5113130.394 4.835533 0.316 3.5395160.396 4.874373 0.318 3.5679460.398 4.913524 0.32 3.5966040.4 4.95299 0.322 3.6254930.402 4.992773 0.324 3.6546130.404 5.032876 0.326 3.6839670.406 5.0733 0.328 3.7135570.408 5.114050.41 5.1551260.497.099276 0.412 5.1965330.4927.1562980.414 5.2382720.4947.213778 0.416 5.2803460.4967.27172 0.418 5.3227590.4987.330127 0.42 5.3655120.57.389004 0.422 5.4086080.5027.448353 0.424 5.4520510.5047.508179 0.426 5.4958420.5067.568486 0.428 5.5399850.5087.629277 0.43 5.5844830.517.690556 0.432 5.6293380.5127.752327 0.434 5.6745540.5147.814595 0.436 5.7201330.5167.877362 0.438 5.7660770.5187.940634 0.44 5.8123910.528.004414 0.442 5.8590770.5228.068707 0.444 5.9061380.5248.133516 0.446 5.9535770.5268.198845 0.448 6.0013960.5288.264699 0.45 6.04960.538.331082 0.452 6.0981910.5328.397998 0.454 6.1471730.5348.465452 0.456 6.1965480.5368.533447 0.458 6.2463190.5388.601989 0.46 6.296490.548.671081 0.462 6.3470640.5428.740728 0.464 6.3980450.5448.810935 0.466 6.4494340.5468.881705 0.468 6.5012370.5488.953044 0.47 6.5534560.559.024956 0.472 6.6060940.5529.097445 0.474 6.6591550.5549.170517 0.476 6.7126420.5569.244175 0.478 6.7665580.5589.318426 0.48 6.8209080.569.393272 0.482 6.8756950.5629.46872 0.484 6.9309210.5649.544774 0.486 6.9865910.5669.621439 0.4887.0427080.5689.6987190.579.776620.6513.46367 0.5729.8551470.65213.571810.5749.9343050.65413.68082 0.57610.01410.65613.79071 0.57810.094530.65813.90147 0.5810.175610.6614.01313 0.58210.257340.66214.12569 0.58410.339730.66414.23915 0.58610.422780.66614.35352 0.58810.50650.66814.46881 0.5910.590890.6714.58502 0.59210.675960.67214.70217 0.59410.761710.67414.82026 0.59610.848150.67614.9393 0.59810.935280.67815.05929 0.611.023110.6815.18025 0.60211.111650.68215.30218 0.60411.20090.68415.42509 0.60611.290870.68615.54898 0.60811.381560.68815.67387 0.6111.472980.6915.79977 0.61211.565130.69215.92667 0.61411.658020.69416.0546 0.61611.751660.69616.18355 0.61811.846050.69816.31354 0.6211.94120.716.44457 0.62212.037110.70216.57665 0.62412.133790.70416.7098 0.62612.231250.70616.84401 0.62812.32950.70816.97931 0.6312.428530.7117.11569 0.63212.528360.71217.25316 0.63412.628990.71417.39174 0.63612.730420.71617.53143 0.63812.832680.71817.67225 0.6412.935750.7217.81419 0.64213.039650.72217.95728 0.64413.144390.72418.10151 0.64613.249960.72618.24691 0.64813.356390.72818.393470.7318.541210.8125.53363 0.73218.690130.81225.738720.73418.840250.81425.94545 0.73618.991580.81626.15385 0.73819.144120.81826.36392 0.7419.297890.8226.57568 0.74219.452890.82226.78914 0.74419.609140.82427.00431 0.74619.766640.82627.22121 0.74819.925410.82827.43985 0.7520.085450.8327.66025 0.75220.246780.83227.88242 0.75420.409410.83428.10638 0.75620.573340.83628.33213 0.75820.738580.83828.5597 0.7620.905160.8428.78909 0.76221.073070.84229.02033 0.76421.242330.84429.25342 0.76621.412950.84629.48839 0.76821.584940.84829.72524 0.7721.758310.8529.964 0.77221.933080.85230.20467 0.77422.109250.85430.44728 0.77622.286830.85630.69184 0.77822.465840.85830.93836 0.7822.646290.8631.18686 0.78222.828190.86231.43735 0.78423.011550.86431.68986 0.78623.196380.86631.9444 0.78823.382690.86832.20098 0.7923.570510.8732.45962 0.79223.759830.87232.72034 0.79423.950670.87432.98315 0.79624.143040.87633.24807 0.79824.336960.87833.51513 0.824.532440.8833.78432 0.80224.729490.88234.05568 0.80424.928110.88434.32922 0.80625.128340.88634.60496 0.80825.330170.88834.882910.8935.163090.94643.99154 0.89235.445520.94844.344880.89435.730220.9544.701070.89636.017210.95245.060110.89836.306510.95445.422040.936.598120.95645.786870.90236.892080.95846.154630.90437.188410.9646.525350.90637.487110.96246.899050.90837.788210.96447.275750.9138.091730.96647.655470.91238.397680.96848.038240.91438.70610.9748.424090.91639.016990.97248.813040.91839.330380.97449.205110.9239.646280.97649.600330.92239.964720.97849.998720.92440.285720.9850.400320.92640.60930.98250.805140.92840.935480.98451.213210.9341.264280.98651.624560.93241.595720.98852.039210.93441.929820.9952.45720.93642.26660.99252.878540.93842.606090.99453.303270.9442.948310.99653.73140.94243.293270.99854.162980.94443.64101154.59802复化Simpson数据:-1 0.018319929 -0.34 0.256658088 0.32 3.596641805 -0.98 0.0198445 -0.32 0.278035042 0.34 3.896195298-0.96 0.021494322 -0.3 0.301192133 0.36 4.220697765-0.94 0.023283225 -0.28 0.326278124 0.38 4.572227037-0.92 0.025220379 -0.26 0.353453177 0.4 4.95303418-0.9 0.027320224 -0.24 0.382891765 0.42 5.365557596-0.88 0.029594431 -0.22 0.41478194 0.44 5.812438891-0.86 0.032059069 -0.16 0.527292277 0.54 8.671138204-0.84 0.034728638 -0.14 0.571209036 0.56 9.39333156-0.82 0.037621263 -0.12 0.61878367 0.58 10.17567433-0.8 0.040754615 -0.1 0.670320427 0.6 11.02317608-0.78 0.044149394 -0.08 0.726149698 0.62 11.94126383-0.76 0.047826844 -0.06 0.78662861 0.64 12.93581634-0.74 0.051810827 -0.04 0.85214479 0.66 14.01320231-0.72 0.056126648 -0.02 0.92311742 0.68 15.1803205-0.7 0.060802006 0 1.0000013 0.7 16.44464467 -0.68 0.065866854 0.02 1.083288424 0.72 17.81427057 -0.66 0.071353499 0.04 1.173512427 0.74 19.29796874 -0.64 0.077297255 0.06 1.271250748 0.76 20.90523965 -0.62 0.083735917 0.08 1.377129533 0.78 22.64637562 -0.6 0.090711017 0.1 1.491826493 0.8 24.53252554 -0.58 0.098266855 0.12 1.616076341 0.82 26.57576756 -0.56 0.106452202 0.14 1.750674449 0.84 28.78918506 -0.54 0.11531904 0.16 1.896482943 0.86 31.18695183 -0.52 0.12492459 0.18 2.054435268 0.88 33.78442141 -0.5 0.135329888 0.2 2.225543071 0.9 36.59822683 -0.48 0.14660204 0.22 2.410901825 0.92 39.64638571 -0.46 0.158812728 0.24 2.611698647 0.94 42.94841704 -0.44 0.17204064 0.26 2.829219145 0.96 46.52546475 -0.42 0.18636997 0.28 3.064856356 0.98 50.40043451 -0.4 0.201892977 0.3 3.320119013 1 54.59813904 -0.38 0.218708553 0.46 6.296539601-0.36 0.236924875 0.48 6.820959636-0.2 0.449328351 0.5 7.389057081-0.18 0.486751777 0.52 8.0044696750102030405060四、讨论①在满足相同精度要求的情况下复化梯形积分法比复化Simpson 积分法计算所需节点数多,计算量大。

北航数值分析大作业第二题(fortran)

北航数值分析大作业第二题(fortran)

!计算A(r+1) DO I=1,N DO J=1,N A(I,J)=A(I,J)-W(I)*U(J)-U(I)*P(J) ENDDO ENDDO ENDIF ENDDO RETURN END
!***************符号函数子程序*****************! FUNCTION SGN(X) REAL(8) X IF(X>0) THEN SGN=1 ELSE IF(X<0) THEN SGN=-1 ELSE IF(X==0) THEN SGN=0 ENDIF END
DIMENSION A(N,N),A1(N,N),A2(N,N),C(2,N),Q(N,N),R(N,N),CR(N),CM(N)!C为存储特征值的数 组,1为实部,为虚部 REAL(8) A,A1,A2,C,Q,R,CM E=1E-12 L=1000 !精度水平 !迭代最大次数
OPEN(1,FILE='数值分析大作业第二题计算结果.TXT') DO I=1,N DO J=1,N IF(I==J) THEN A(I,J)=1.52*COS(I+1.2*J) ELSE A(I,J)=SIN(0.5*I+0.2*J) ENDIF ENDDO ENDDO A1=A WRITE(*,"('矩阵A为:')") WRITE(1,"('矩阵A为:')") DO I=1,N DO J=1,N WRITE(*,"(2X,E20.13,2X,\)") A(I,J) WRITE(1,"(2X,E20.13,2X,\)") A(I,J) ENDDO WRITE(*,"(' ')") WRITE(1,"(' ')") ENDDO !使用矩阵的拟上三角化的算法将矩阵A化为拟上三角矩阵A(n-1) CALL HESSENBERG(A,N) WRITE(*,"('拟上三角化后矩阵A(n-1)为:')") WRITE(1,"('拟上三角化后矩阵A(n-1)为:')") DO I=1,N DO J=1,N WRITE(*,"(2X,E20.13,2X,\)") A(I,J) WRITE(1,"(2X,E20.13,2X,\)") A(I,J) ENDDO WRITE(*,"('')") WRITE(1,"('')") ENDDO !计算对矩阵A(n-1)实行QR方法迭代结束后所得矩阵 A2=A CALL QRD(A2,N,Q,R)

哈工大数值分析实验报告

哈工大数值分析实验报告


实验报告一:非线性方程求解.................................................................................... 1
摘要、前言、数学原理 ............................................................................................. 1 Python 程序设计 ........................................................................................................ 2 结果分析和讨论 ......................................................................................................... 6 结论 ........................................................................................................................... 12 摘要、前言、数学原理 ........................................................................................... 13 Python 程序设计 ...................................................................................................... 14 结果分析和讨论 ....................................................................................................... 16 结论 ........................................................................................................................... 17 摘要、前言、数学原理 ........................................................................................... 18 Python 程序设计 ...................................................................................................... 19 结果分析和讨论 ..................................................................................................... 26 结论 ........................................................................................................................... 30 摘要、前言、数学原理 ........................................................................................... 31 Python 程序设计 ...................................................................................................... 32 结果分析和讨论 ....................................................................................................... 33 结论 ........................................................................................................................... 35

数值分析实验题和程序报告

数值分析实验题和程序报告

数值分析实验题和程序实验2.1多项式插值的振荡现象问题提出:考虑在一个固定的区间上用插值逼近一个函数。

显然Lagrange插值中使用的节点越多,插值多项式的次数就越高。

我们自然关心插值多项的次数增加时,L n(x)是否也更加靠近被逼近的函数。

Runge 给出的一个例子是极著名并富有启发性的。

设区间[-1, 1]上函数1f (x) 21+25 x实验内容:考虑区间[-1,1]的一个等距划分,分点为2iXj=-1 •, i =0,1, 2,…,nn则拉格朗日插值多项式为1l i(x)21 25 x i其中,h (x), i = 0,1, 2,…,n是n次Lagrange插值基函数。

实验要求:(1)选择不断增大的分点数目n =2, 3,… 画出原函数f (x)及插值多项式函数L n(x)在[-1,1]上的图像,比较并分析实验结果。

(2)选择其他的函数,例如定义在区间[-5,5]上的函数xh(x) = ---------- , g(x) =arctan x1 +x重复上述的实验,看其结果如何。

1、实验MATLAB 程序function charpt2_1%输入:函数式选择,插值节点数%输出:拟合函数及原函数的图形promps={'选择实验函数,若选f(x),输入f,若选h(x),输入h,若选g(x),输入g:'};result=inputdlg(promps, 'charpt2_1',1,{ 'f'});Nb_f=char(result);if (Nb_f~= 'f' & Nb_f~= 'h' & Nb_f~= 'g')errordlg( '实验函数选择错误!'); return ;endresult=inputdlg({ '请输入第一幅图插值节点数N>=2:'},'charpt2_1',1,{ '2'}); Nd0=str2num(char(result));if (Nd0<2)errordlg( '节点数输入错误!'); return ;endresult=inputdlg({ '请输入两幅图间插值节点数差值D:'}, 'charpt2_1',1,{ '1'}); D=str2num(char(result));switch Nb_fcase'f'f=inline( '1./(1+25*x.A2)' );a=-1;b=1;case'h'f=inline( 'x./(1+x.A4)' );a=-5;b=5;case'g'f=inline( 'atan(x)');a=-5;b=5;endfor i=1:6Nd=Nd0+(i-1).*D;x0=linspace(a,b,Nd+1); y0=feval(f,x0);x=a:0.01:b;y=Lagrange(x0,y0,x);subplot(2,3,i);plot(x0,y0, '*');hold on;fplot(f,[a,b], 'k');hold on;plot(x,y, 'b--');s1='x (节点数N='; s2=num2str(Nd);s3=')'; s=[s1 s2 s3]; xlabel(s);ylabel( 'y=f(x) - and y=Ln(x)--' ); end%Lagra nge插值函数function y=Lagrange(x0,y0,x) n=length(x0);m=length(x);for i=1:m z=x(i); s=0.0;for k=1:np=1.0;for j=1:n if (j~=k) p=p*(z-x0(j))/(x0(k)-x0(j));end end s=s+p*y0(k);end y(i)=s;end2、实验结果对于函数f(x),当选择的分点数冃不断增大时,得到的拟合插值多项 式函数图形如图1-1和图1-2所示。

北航数值分析大作业一.docx

北航数值分析大作业一.docx

数值分析—计算实习作业一学院:机械工程学院专业:材料加工工程姓名:暴一品学号:SY12071342012-10-29一、算法设计方案观察矩阵A ,结构为带状,且与主对角线相邻的两个带的值b 和c 都是常数。

从而可以用带原点平移的幂法或反幂法计算λ1和λ501。

所以算法的设计方案如下:1.求按模最大的特征值,并记为max_eigenvalue ,算法如下所示⎪⎪⎪⎪⎩⎪⎪⎪⎪⎨⎧=======------≤≤-),2,1()sgn(),,(/max ),,()(1)()(11)1(11)1(1)1()0()0(10ΛΛΛk h h h h Ay u h u y h h h h u k r k r k Tk nk k kk r k k k j nj k rTn β任取非零向量2.平移矩阵得到A ’=A-max_eigenvalueI ,再次用幂法,这次求出的A ’的按模大的特征值pymax_eigenvalue 就是与步骤1求出的特征值相差最大的特征值。

即两者一个为最大的特征值,另一个为最小的特征值。

3.根据max_eigenvalue 和pymax_eigenvalue 的正负性,直接确定λ1,和λ501。

4.对原矩阵A 用反幂法,求出其按模最小的特征值,记为s_eigenvalue ,此即λs 。

⎪⎪⎪⎪⎩⎪⎪⎪⎪⎨⎧=====∈--------),2,1(/111111110Λk u y y Au u y u u R u k T k k k k k k k k Tk k n βηη任取非零向量在反幂法的求解过程中,每迭代一次都要求满足解线性方程组Auk=yk-1。

本题中矩阵A 上半带宽为2,下半带宽也为2 。

故选择采用三角分解法求解方程组:先将原矩阵改写成5行501列的矩阵C (不存储A 的0元素) A 的带内元素aij=c 中的元素ci-j+3。

再对C 矩阵做LU 分解。

对于k=1,2,…,n ,执行∑---=+-+-+-+--=1)2,2,1max(,3,3,3,3:k j k t jj t t t k j j k j j k ccc c [j=k,k+1,…,min(k+2,n)]kk s k r i t k k t t t i k k i k k i c ccc c ,31),,1max(,3,3,3,3/)(:∑---=+-+-+-+--=[i=k+1,k+2,…,min(k+2,n);k<n]求解Lx=b ,Uuk=x (数组b 先是存放原方程组右端向量yk-1,后来存放中间向量x )∑--=+--=1),1max(,3:i r i t tt t i i i bcb b (i=2,3,…,n )nn kn c b u ,3/:=in i i t kt tt i i ki c u cb u ,3),2min(1,3/)(:∑++=+--= (i=n-1,n-2, (1)5.对k=1,2,……39执行:先根据题中给出的公式算出μk ,再将矩阵平移A ”=A-μk ,对矩阵A ”运用反幂法(线性方程组的解法同上),就可以求出与μk 最接近的特征值λik ,保存在数组py_eigenvalue 中。

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B班大作业要求:1. 使用统一封皮;2. 上交大作业内容包含:一摘要二数学原理三程序设计(必须对输入变量、输出变量进行说明;编程无语言要求,但程序要求通过)四结果分析和讨论五完成题目的体会与收获3. 提交大作业的时间:本学期最后一次课,或考前答疑;过期不计入成绩;4. 提交方式:打印版一份;或手写大作业,但必须使用A4纸。

5. 撰写的程序需打印出来作为附录。

课程设计课程名称:设计题目:学号:姓名:完成时间:题目一:非线性方程求根 一 摘要非线性方程的解析解通常很难给出,因此非线性方程的数值解就尤为重要。

本实验通过使用常用的求解方法二分法和Newton 法及改进的Newton 法处理几个题目,分析并总结不同方法处理问题的优缺点。

观察迭代次数,收敛速度及初值选取对迭代的影响。

用Newton 法计算下列方程(1) 310x x --= , 初值分别为01x =,00.45x =,00.65x =;(2) 32943892940x x x +-+= 其三个根分别为1,3,98-。

当选择初值02x =时给出结果并分析现象,当6510ε-=⨯,迭代停止。

二 数学原理对于方程f(x)=0,如果f(x)是线性函数,则它的求根是很容易的。

牛顿迭代法实质上是一种线性化方法,其基本思想是将非线性方程f(x)=0逐步归结为某种线性方程来求解。

设已知方程f(x)=0有近似根x k (假定k f'(x )0≠) ,将函数f(x)在点x k 进行泰勒展开,有k k k f(x)f(x )+f'(x )(x-x )+≈⋅⋅⋅于是方程f(x)=0可近似的表示为k k k f(x )+f'(x )(x-x )=0这是个线性方程,记其根为x k+1,则x k+1的计算公式为k+1k ()x =x -'()k k f x f x ,k=0,1,2,… 这就是牛顿迭代法或简称牛顿法。

三 程序设计(本程序由Fortran 语言编制)(1)对于310x x --=,按照上述数学原理,编制的程序如下program newton implicit nonereal :: x(0:50),fx(0:50),f1x(0:50)!分别为自变量x ,函数f(x)和一阶导数f1(x) integer :: kwrite(*,*) "x(0)="read(*,*) x(0) !输入变量:初始值x(0)open(10,file='1.txt') do k=1,50,1fx(k)=x(k-1)**3-x(k-1)-1 f1x(k)=3*x(k-1)**2-1x(k)=x(k-1)-fx(k)/f1x(k) !牛顿法write(*,'(I3,1x,f11.6)') k,x(k) !输出变量:迭代次数k 及x 的值 write(10,'(I3,1x,f11.6)') k,x(k)if(abs(x(k)-x(k-1))<1e-6) exit !终止迭代条件 end do stop end(2)对于32943892940x x x +-+=,按照上述数学原理,编制的程序如下program newton implicit nonereal :: x(0:50),fx(0:50),f1x(0:50)!分别为自变量x ,函数f(x)和一阶导数f1(x) integer :: kwrite(*,*) "x(0)="read(*,*) x(0) !输入变量:初始值x(0)open(10,file='1.txt') do k=1,50,1fx(k)=x(k-1)**3+94*x(k-1)**2-389*x(k-1)+294 f1x(k)=3*x(k-1)**2+188*x(k-1)-389x(k)=x(k-1)-fx(k)/f1x(k) !牛顿法write(*,'(I3,1x,f11.6)') k,x(k) !输出变量:迭代次数k 及x 的值 write(10,'(I3,1x,f11.6)') k,x(k)if(abs(x(k)-x(k-1))<5e-6) exit !终止迭代条件 end do stop end四 结果分析和讨论(1)对于方程310x x --=,当初值分别为01x =,00.45x =,00.65x =时,所得结果如下结果分析与讨论:从计算结果可以看到,当取的初始值不同时,虽然均得到了近似解x *=1.324718,但收敛速度明显不同。

当初始值x 0充分接近于方程的单根时,可保证迭代序列快速收敛。

在本例中,初始值1、0.65和0.45距方程的单根越来越远,故收敛速度越来越慢。

(2)对于方程32943892940x x x +-+=,当初始值x 0=2时计算结果如下结果分析与讨论:牛顿法有明显的几何解释,方程f(x)=0的根x*可解释为曲线y=f(x)与x轴的交点的横坐标。

设x k是根x*的某个近似值,过曲线y=f(x)上横坐标为x k的点P k引曲线y=f(x)的切线,并将该切线与x轴的交点坐标x k+1作为x*的新的近似值。

在本例中,当初始值x0=2时,在这个点的切线方程与x轴的交点恰为方程的一个根x=-98,故迭代了两次就得到了结果。

五完成题目的体会与收获对于牛顿法,当初始值x0充分接近于方程的单根时,可保证迭代序列快速收敛。

当方程有不止一个根时,所得结果与初始值的选取有关。

题目二:线性方程组求解一摘要对于实际的工程问题,很多问题归结为线性方程组的求解。

本实验通过实际题目掌握求解线性方程组的数值解法,直接法或间接法。

有一平面机构如图所示,该机构共有13条梁(图中标号的线段)由8个铰接点(图中标号的圈)联结在一起。

上述结构的1号铰接点完全固定,8号铰接点竖立方向固定,并在2号、5号和6号铰接点,分别有如图所示的10吨、15吨和20吨的负载,在静平衡的条件下,任何一个铰接点上水平和竖立方向受力都是平衡的,以此计算每个梁的受力情况。

101520令2/1=α,假设f 为各个梁上的受力,例如对8号铰接点有01213=+f f α对5号铰接点,则有10965f f f f +=+αα15975=++f f f αα针对各个铰接点,列出方程并求出各个梁上的受力。

二 数学原理 高斯列主元消去法:⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎣⎡=⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎣⎡⋅⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎣⎡n n nn n n n n b b b x x x a a a a a a a a a 2121212222111211方法说明(以4阶为例):第1步消元——在增广矩阵(A ,b )第一列中找到绝对值最大的元素,将其所在行与第一行交换,再对(A ,b )做初等行变换使原方程组转化为如下形式:⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎣⎡=⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎣⎡⋅⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎣⎡*******0***0***0****4321x x x x第2步消元——在增广矩阵(A ,b )中的第二列中(从第二行开始)找到绝对值最大的元素,将其所在行与第二行交换,再对(A ,b )做初等行变换使原方程组转化为:⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎣⎡=⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎣⎡⋅⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎣⎡******00**00***0****4321x x x x第3步消元——在增广矩阵(A ,b )中的第三列中(从第三行开始)找到绝对值最大的元素,将其所在行与第二行交换,再对(A ,b )做初等行变换使原方程组转化为:⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎣⎡=⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎣⎡⋅⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎣⎡*****000**00***0****4321x x x x按x 4→ x 3→ x 2→ x 1 的顺序回代求解出方程组的解。

针对各个铰接点列方程: 对2号铰接点有260f f -= 310f =对3号铰接点有1450f f f αα--=1350f f f αα++=对4号铰接点有480f f -=70f =对5号铰接点有569100f f f f αα+--=579150f f f αα++-=对6号铰接点有10130f f -= 1120f =对7号铰接点有89120f f f αα+-=911120f f f αα++=对8号铰接点有12130f f α+=三 程序设计(本程序由Fortran 语言编制)program main implicit noneinteger,parameter :: n=13 !输入量:系数阵的维数 real :: js(n)dimension :: a(n,n),b(n),x(n) double precision a,b,xreal,parameter :: m=0.7071 !m 代表α=1/integer :: i,j logical ldata((a(i,j),j=1,13),i=1,13) / m,0.,1.,0.,m,0.,0.,0.,0.,0.,0.,0.,0., & !输入量:方程的系数阵 0.,1.,0.,0.,0.,-1.,0.,0.,0.,0.,0.,0.,0., &0.,0.,1.,0.,0.,0.,0.,0.,0.,0.,0.,0.,0., &0.,0.,0.,1.,0.,0.,0.,-1.,0.,0.,0.,0.,0., &m,0.,0.,-1.,-m,0.,0.,0.,0.,0.,0.,0.,0., &0.,0.,0.,0.,m,1.,0.,0.,-m,-1.,0.,0.,0.,&0.,0.,0.,0.,0.,0.,1.,0.,0.,0.,0.,0.,0.,&0.,0.,0.,0.,0.,0.,0.,1.,m,0.,0.,-m,0.,& 0.,0.,0.,0.,m,0.,1.,0.,m,0.,0.,0.,0.,& 0.,0.,0.,0.,0.,0.,0.,0.,0.,1.,0.,0.,-1.,&0.,0.,0.,0.,0.,0.,0.,0.,0.,0.,1.,0.,0.,&0.,0.,0.,0.,0.,0.,0.,0.,m,0.,1.,m,0.,&0.,0.,0.,0.,0.,0.,0.,0.,0.,0.,0.,m,1. /b=0. !输入量:方程的右边项b(3)=10.b(9)=15.b(11)=20.write(*,"(13(13(f5.2,1x),/))") ((a(i,j),j=1,13),i=1,13) !输出矩阵call agaus(a,b,n,x,l,js)if (l/=0) thenwrite(*,"(3(5f8.2,/))") x(:) !输出结果end ifstopendsubroutine agaus(a,b,n,x,l,js)dimension a(n,n),x(n),b(n),js(n)double precision a,b,x,tl=1 !逻辑变量do k=1,n-1d=0.0do i=k,ndo j=k,nif (abs(a(i,j))>d) thend=abs(a(i,j))js(k)=jis=iend ifend doend do !把行绝对值最大的元素换到主元位置if (d+1.0==1.0) thenl=0else !最大元素为0无解if(js(k)/=k) thendo i=1,nt=a(i,k)a(i,k)=a(i,js(k))a(i,js(k))=tend do !最大元素不在K行,K行end ifif(is/=k) thendo j=k,nt=a(k,j)a(k,j)=a(is,j)a(is,j)=t !交换到K列end dot=b(k)b(k)=b(is)b(is)=tend if !最大元素在主对角线上end if !消去if (l==0) thenwrite(*,100)returnend ifdo j=k+1,na(k,j)=a(k,j)/a(k,k)end dob(k)=b(k)/a(k,k) !求三角矩阵do i=k+1,ndo j=k+1,na(i,j)=a(i,j)-a(i,k)*a(k,j)end dob(i)=b(i)-a(i,k)*b(k)end doend doif (abs(a(n,n))+1.0==1.0) thenl=0write(*,100)returnend ifx(n)=b(n)/a(n,n)do i=n-1,1,-1t=0.0do j=i+1,nt=t+a(i,j)*x(j)end dox(i)=b(i)-tend do100 format(1x,'fail')js(n)=ndo k=n,1,-1if (js(k)/=k) thent=x(k)x(k)=x(js(k))x(js(k))=tend ifend doreturnend四结果分析和讨论由程序计算的各个杆的受力如下:结果分析与讨论:列方程时假定各杆均受拉力,得到的结果有负值,说明力与假设方向相反。

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