I am trying to write a program to solve for pipe diameter for a pump system I've designed. I've done this on paper and understand the mechanics of the equations. I would appreciate any guidance.
EDIT: I have updated the code with some suggestions from users, still seeing quick divergence. The guesses in there are way too high. If I figure this out I will update it to working.
MODULE Sec
CONTAINS
SUBROUTINE Secant(fx,xold,xnew,xolder)
IMPLICIT NONE
INTEGER,PARAMETER::DP=selected_real_kind(15)
REAL(DP), PARAMETER:: gamma=62.4
REAL(DP)::z,phead,hf,L,Q,mu,rho,rough,eff,pump,nu,ppow,fric,pres,xnew,xold,xolder,D
INTEGER::I,maxit
INTERFACE
omitted
END INTERFACE
Q=0.0353196
Pres=-3600.0
z=-10.0
L=50.0
mu=0.0000273
rho=1.940
nu=0.5
rough=0.000005
ppow=412.50
xold=1.0
xolder=0.90
D=11.0
phead = (pres/gamma)
pump = (nu*ppow)/(gamma*Q)
hf = phead + z + pump
maxit=10
I = 1
DO
xnew=xold-((fx(xold,L,Q,hf,rho,mu,rough)*(xold-xolder))/ &
(fx(xold,L,Q,hf,rho,mu,rough)-fx(xolder,L,Q,hf,rho,mu,rough)))
xolder = xold
xold = xnew
I=I+1
WRITE(*,*) "Diameter = ", xnew
IF (ABS(fx(xnew,L,Q,hf,rho,mu,rough)) <= 1.0d-10) THEN
EXIT
END IF
IF (I >= maxit) THEN
EXIT
END IF
END DO
RETURN
END SUBROUTINE Secant
END MODULE Sec
PROGRAM Pipes
USE Sec
IMPLICIT NONE
INTEGER,PARAMETER::DP=selected_real_kind(15)
REAL(DP)::xold,xolder,xnew
INTERFACE
omitted
END INTERFACE
CALL Secant(f,xold,xnew,xolder)
END PROGRAM Pipes
FUNCTION f(D,L,Q,hf,rho,mu,rough)
IMPLICIT NONE
INTEGER,PARAMETER::DP=selected_real_kind(15)
REAL(DP), PARAMETER::pi=3.14159265d0, g=9.81d0
REAL(DP), INTENT(IN)::L,Q,rough,rho,mu,hf,D
REAL(DP)::f, fric, reynold, coef
fric=(hf/((L/D)*(((4.0*Q)/(pi*D**2))/2*g)))
reynold=((rho*(4.0*Q/pi*D**2)*D)/mu)
coef=(rough/(3.7d0*D))
f=(1/SQRT(fric))+2.0d0*log10(coef+(2.51d0/(reynold*SQRT(fric))))
END FUNCTION
You very clearly declare the function in the interface (and the implementation) as
FUNCTION f(L,D,Q,hf,rho,mu,rough)
IMPLICIT NONE
INTEGER,PARAMETER::DP=selected_real_kind(15)
REAL(DP), PARAMETER::pi=3.14159265, g=9.81
REAL(DP), INTENT(IN)::L,Q,rough,rho,mu,hf,D
REAL(DP)::fx
END FUNCTION
So you need to pass 7 arguments to it. And none of them are optional.
But when you call it, you call it as
xnew=xold-fx(xold)*((xolder-xold)/(fx(xolder)-fx(xold))
supplying a single argument to it. When you try to compile it with gfortran for example, the compiler will complain for not getting any argument for D (the second dummy argument), because it stops with the first error.
It seems that the initial values for xold and xolder are too far from the solution. If we change them as
xold = 3.0d-5
xolder = 9.0d-5
and changing the threshold for convergence more tightly as
IF (ABS(fx(xnew,L,Q,hf,rho,mu,rough)) <= 1.0d-10) THEN
then we get
...
Diameter = 7.8306011049894322E-005
Diameter = 7.4533171406818087E-005
Diameter = 7.2580746283970710E-005
Diameter = 7.2653611474296094E-005
Diameter = 7.2652684750264582E-005
Diameter = 7.2652684291155581E-005
Here, we note that the function f(x) is defined as
FUNCTION f(D,L,Q,hf,rho,mu,rough)
...
f = (1/(hf/((L/D)*((4*Q)/pi*D)))) !! (1)
+ 2.0 * log( (rough/(3.7*D)) + (2.51/(((rho*((4*Q)/pi*D))/mu) !! (2)
* (hf/((L/D)*((4*Q)/pi*D))))) !! (3)
)
END FUNCTION
where terms in Lines (1) and (3) are both constant, while terms in Line (2) are some constants over D. So, we see that f(D) = c1 - 2.0 * log( D / c2 ), so we can obtain the solution analytically as D = c2 * exp(c1/2.0) = 7.26526809959e-5, which agrees well with the numerical solution above. To get a rough idea of where the solution is, it is useful to plot f(D) as a function of D, e.g. using Gnuplot.
But I am afraid that the expression for f(D) itself (given in the Fortran code) might include some typo due to many parentheses. To avoid such issues, it is always useful to first arrange the expression for f(D) as simplest as possible before making a program.
(One TIP is to extract constant factors outside and pre-calculate them.)
Also, for debugging purposes it is sometimes useful to check the consistency of physical dimensions and physical units of various terms. Indeed, if the magnitude of the obtained solution is too large or too small, there might be some problem of conversion factors for physical units, for example.
Related
I use Fortran 90 via Force 2.0, with a 64bits pc under windows 10.
I believe it may be a bug since my classmates use a very similar code and it works for them.
This is my code :
program integ
implicit none
real :: a_x , b_x , integ_1d, c
a_x = 0
b_x = 1
c = integ_1d(a_x,b_x)
write(*,*)c
pause
end program integ
real function integ_1d (a_x , b_x)
real :: x, f_x, pas
real :: inte, a_x, b_x
integer :: i
integer , parameter :: npas=100
pas=(b_x-a_x )/ npas
inte =0.E0
do i=0,npas-1
x=a_x+( i*pas )
inte=inte+ f_x
end do
integ_1d=inte*pas
end function integ_1d
real function f_x(x)
real :: x
f_x = x*x
end function f_x
It compiles without any issues but always gives me different values, around 10^-38. example :
1.75483065E-38
PAUSE
To resume execution, type go. Other input will terminate the job.
or
1.16708418E-38
PAUSE
To resume execution, type go. Other input will terminate the job.
with the exact same code, compiled on the same computer with the same fortran version.
Thank you for your time.
I understand Monte carlo simulation is for estimating area by plotting random points and calculating the ration between the points outside the curve and inside the curve.
I have well calculated the value of pi assuming radius of curve to be unity.
Here is the code
program pi
implicit none
integer :: count, n, i
real :: r, x, y
count = 0
n=500
CALL RANDOM_SEED
DO i = 1, n
CALL RANDOM_NUMBER(x)
CALL RANDOM_NUMBER(y)
IF (x*x + y*Y <1.0) count = count + 1
END DO
r = 4 * REAL(count)/n
print *, r
end program pi
But to find integration , Textbook says to apply same idea. But I'm lost on How to write a code if I want to find the integration of
f(x)=sqrt(1+x**2) over a = 1 and b = 5
Before when radius was one, I did assume point falling inside by condition x*2+y**2 but How can I solve above one?
Any help is extremely helpful
I will write the code first and then explain:
Program integral
implicit none
real f
integer, parameter:: a=1, b=5, Nmc=10000000 !a the lower bound, b the upper bound, Nmc the size of the sampling (the higher, the more accurate the result)
real:: x, SUM=0
do i=1,Nmc !Starting MC sampling
call RANDOM_NUMBER(x) !generating random number x in range [0,1]
x=a+x*(b-a) !converting x to be in range [a,b]
SUM=SUM+f(x) !summing all values of f(x). EDIT: SUM is also an instrinsic function in Fortran so don't call your variable this, I named it so, to illustrate its purpose
enddo
print*, (b-a)*(SUM/Nmc) !final result of your integral
end program integral
function f(x) !defining your function
implicit none
real, intent(in):: x
real:: f
f=sqrt(1+x**2)
end function f
So what's happening:
The integral can be written as
. where:
(this g(x) is a uniform probability distribution of the variable x in [a,b]). And we can write the integral as:
where .
So, finally, we get that the integral should be:
So, all you have to do is generate a random number in the range [a,b] and then calcualte the value of your function for this x. Then do this lots of times (Nmc times), and calculate the sum. Then just divide with Nmc, to find the average and then multiply with (b-a). And this is what the code does.
There's lots of stuff on the internet for this. here's one example that visualizes it pretty nice
EDIT: Second way, that is the same as the Pi method:
Nin=0 !Number of points inside the function (under the curve)
do i=1,Nmc
call random_number(x)
call random_number(y)
x=a+x*(b-a)
y=f_min+y(f_max-f_min)
if (f(x)<y) Nin=Nin+1
enddo
print*, (f_max-f_min)*(b-a)*(real(Nin)/Nmc)
All of this, you could then enclose it in an outer do loop summing the (f_max-f_min)(b-a)(real(Nin)/Nmc) and in the end printing its average.
For this example, what you do is essentially creating an enclosing box from a to b (x dimension) and from f_min to f_max (y dimension) and then doing a sampling of points inside this area and counting the points that are in the function (Nin).Obviously you will have to know the minimum (f_min) and maximum (f_max) value of your function in the range [a,b]. Alternatively you could use arbitrarily low/high values for your f_min f_max but then you will be wasting a lot of points and your error will be bigger.
Rather than using three consecutive scalar IF statements I would like to use a single IF statement with a vector argument, if this is possible. I can't figure out how.
The reason for wanting this is to test it for speed. My code can run for days calling this section billions of times. Even a little speed up can make a large difference.
Here is the working code with three IF statements for a dummy scenario.
program main
!==============================================
! Define variables
!==============================================
real, dimension(10,3) :: r ! 10 atoms each with x,y,z coordinates
real, dimension(3) :: rij ! x,y,z vector of difference between two atoms
real :: Box_Length ! length of simulation box
real :: time, timer_start, timer_end
integer :: timer
!=======================================================
! Begin Program body
!=======================================================
Box_Length = 1.0 ! based on a box of length = 1 since coords are randomly generated between 0 and 1
!=================================
! Generate random atom coordinates
!=================================
r = 0.0
CALL RANDOM_NUMBER (r)
!=================================
! Begin algorithm
!=================================
call cpu_time(timer_start)
do timer = 1,30000
do i = 1,size(r)
do j = 1, size(r)
if(i == j) cycle
rij(:) = abs(r(i,:) - r(j,:))
!==============================
! Apply mirror image convention
!==============================
if(rij(1) > Box_Length - rij(1) ) rij(1) = rij(1) - Box_Length
if(rij(2) > Box_Length - rij(2) ) rij(2) = rij(2) - Box_Length
if(rij(3) > Box_Length - rij(3) ) rij(3) = rij(3) - Box_Length
!*******************************************************************************
! Question: Can I make it into a single if statement i.e. *
! *
! if(rij(:) > Box_Length(:) - rij(:) ) rij(:) = rij(:) - Box_Length(:) *
! *
! Where Box_Length is now a vector and only the coordinate that triggers *
! the if statement is modified. Meaning that if { rij(2) > Box_Length - rij(2) } *
! only rij(2) is modified, not all three. *
! I have tried making Box_Length a vector, but that failed. *
!*******************************************************************************
! insert rest of algorithm
enddo ! j-loop
enddo ! i loop
enddo ! timer loop
call cpu_time(timer_end)
time = timer_end - timer_start
print*, 'Time taken was: ', time
end program main
Thanks for any help on turning this into a vectorized IF statement. Also, I flip back and forth between column and row vectors. Currently column vectors are working faster for me. This IS NOT a question about column versus row vectors. I do my own timing and use the faster method. I simply can't get a working vector method to try timing against.
"if(rij(:) > Box_Length(:) - rij(:) ) rij(:) = rij(:) - Box_Length(:)"
can be
where (rij > Box_Length - rij) rij = rij - Box_Length
Not that it will not make it faster than an explicit DO loop, it is just a shorter way to write it. It can even make it slower, because temporary array may be used or the compiler may have hard time to vectorize it - in the SIMD vectorization sense.
I advise against using word "vectorization" to speak about the shorthand array notation in Fortran. In Fortran vectorization normally means using of the SIMD CPU instructions. The compiler call that vectorization. Your notion of vectorization comes from Python but is not used in Fortran an is misleading to other readers.
Also read https://software.intel.com/en-us/blogs/2008/03/31/doctor-it-hurts-when-i-do-this to see why you should use just rij and not rij(:).
TLDR: It is possible to write it on one line, but in Fortran array notation is NOT the way to make program faster. Often it has an opposite effect.
I am trying to write a program to solve for pipe diameter for a pump system I've designed. I've done this on paper and understand the mechanics of the equations. I would appreciate any guidance.
EDIT: I have updated the code with some suggestions from users, still seeing quick divergence. The guesses in there are way too high. If I figure this out I will update it to working.
MODULE Sec
CONTAINS
SUBROUTINE Secant(fx,xold,xnew,xolder)
IMPLICIT NONE
INTEGER,PARAMETER::DP=selected_real_kind(15)
REAL(DP), PARAMETER:: gamma=62.4
REAL(DP)::z,phead,hf,L,Q,mu,rho,rough,eff,pump,nu,ppow,fric,pres,xnew,xold,xolder,D
INTEGER::I,maxit
INTERFACE
omitted
END INTERFACE
Q=0.0353196
Pres=-3600.0
z=-10.0
L=50.0
mu=0.0000273
rho=1.940
nu=0.5
rough=0.000005
ppow=412.50
xold=1.0
xolder=0.90
D=11.0
phead = (pres/gamma)
pump = (nu*ppow)/(gamma*Q)
hf = phead + z + pump
maxit=10
I = 1
DO
xnew=xold-((fx(xold,L,Q,hf,rho,mu,rough)*(xold-xolder))/ &
(fx(xold,L,Q,hf,rho,mu,rough)-fx(xolder,L,Q,hf,rho,mu,rough)))
xolder = xold
xold = xnew
I=I+1
WRITE(*,*) "Diameter = ", xnew
IF (ABS(fx(xnew,L,Q,hf,rho,mu,rough)) <= 1.0d-10) THEN
EXIT
END IF
IF (I >= maxit) THEN
EXIT
END IF
END DO
RETURN
END SUBROUTINE Secant
END MODULE Sec
PROGRAM Pipes
USE Sec
IMPLICIT NONE
INTEGER,PARAMETER::DP=selected_real_kind(15)
REAL(DP)::xold,xolder,xnew
INTERFACE
omitted
END INTERFACE
CALL Secant(f,xold,xnew,xolder)
END PROGRAM Pipes
FUNCTION f(D,L,Q,hf,rho,mu,rough)
IMPLICIT NONE
INTEGER,PARAMETER::DP=selected_real_kind(15)
REAL(DP), PARAMETER::pi=3.14159265d0, g=9.81d0
REAL(DP), INTENT(IN)::L,Q,rough,rho,mu,hf,D
REAL(DP)::f, fric, reynold, coef
fric=(hf/((L/D)*(((4.0*Q)/(pi*D**2))/2*g)))
reynold=((rho*(4.0*Q/pi*D**2)*D)/mu)
coef=(rough/(3.7d0*D))
f=(1/SQRT(fric))+2.0d0*log10(coef+(2.51d0/(reynold*SQRT(fric))))
END FUNCTION
You very clearly declare the function in the interface (and the implementation) as
FUNCTION f(L,D,Q,hf,rho,mu,rough)
IMPLICIT NONE
INTEGER,PARAMETER::DP=selected_real_kind(15)
REAL(DP), PARAMETER::pi=3.14159265, g=9.81
REAL(DP), INTENT(IN)::L,Q,rough,rho,mu,hf,D
REAL(DP)::fx
END FUNCTION
So you need to pass 7 arguments to it. And none of them are optional.
But when you call it, you call it as
xnew=xold-fx(xold)*((xolder-xold)/(fx(xolder)-fx(xold))
supplying a single argument to it. When you try to compile it with gfortran for example, the compiler will complain for not getting any argument for D (the second dummy argument), because it stops with the first error.
It seems that the initial values for xold and xolder are too far from the solution. If we change them as
xold = 3.0d-5
xolder = 9.0d-5
and changing the threshold for convergence more tightly as
IF (ABS(fx(xnew,L,Q,hf,rho,mu,rough)) <= 1.0d-10) THEN
then we get
...
Diameter = 7.8306011049894322E-005
Diameter = 7.4533171406818087E-005
Diameter = 7.2580746283970710E-005
Diameter = 7.2653611474296094E-005
Diameter = 7.2652684750264582E-005
Diameter = 7.2652684291155581E-005
Here, we note that the function f(x) is defined as
FUNCTION f(D,L,Q,hf,rho,mu,rough)
...
f = (1/(hf/((L/D)*((4*Q)/pi*D)))) !! (1)
+ 2.0 * log( (rough/(3.7*D)) + (2.51/(((rho*((4*Q)/pi*D))/mu) !! (2)
* (hf/((L/D)*((4*Q)/pi*D))))) !! (3)
)
END FUNCTION
where terms in Lines (1) and (3) are both constant, while terms in Line (2) are some constants over D. So, we see that f(D) = c1 - 2.0 * log( D / c2 ), so we can obtain the solution analytically as D = c2 * exp(c1/2.0) = 7.26526809959e-5, which agrees well with the numerical solution above. To get a rough idea of where the solution is, it is useful to plot f(D) as a function of D, e.g. using Gnuplot.
But I am afraid that the expression for f(D) itself (given in the Fortran code) might include some typo due to many parentheses. To avoid such issues, it is always useful to first arrange the expression for f(D) as simplest as possible before making a program.
(One TIP is to extract constant factors outside and pre-calculate them.)
Also, for debugging purposes it is sometimes useful to check the consistency of physical dimensions and physical units of various terms. Indeed, if the magnitude of the obtained solution is too large or too small, there might be some problem of conversion factors for physical units, for example.
I'm relatively new to Fortran and I have an assignment to find quadrature weights and points where the points are the zeros of the nth legendre polynomial (found using Newton's method); I made functions to find the value of Pn(x) and P'n(x) to sub into Newton's method.
However when actually using the functions in my quadrature subroutine it comes back with:
Coursework2a.f90:44.3:
x = x - P(n,x)/dP(n,x)
1
Error: Unclassifiable statement at (1)
Does anybody know any reasons why this statement could be classed as unclassifiable?
subroutine Quadrature(n)
implicit none
integer, parameter :: dpr = selected_real_kind(15) !Double precision
real(dpr) :: P, dP, x, x_new, error = 1, tolerance = 1.0E-6, Pi = 3.141592 !Define Variables
integer, intent(in) :: n
integer :: i
!Next, find n roots. Start with first guess then iterate until error is greater than some tolerance.
do i = 1,n
x = -cos(((2.0*real(i)-1.0)/2.0*real(n))*Pi)
do while (error > tolerance)
x_new = x
x = x - P(n,x)/dP(n,x)
error = abs(x_new-x)
end do
print *, x
end do
end subroutine Quadrature
The line
x = -cos(((2.0*real(i)-1.0)/2.0*real(n))*Pi)
is likely missing a set of brackets around the denominator. As it is, the line divides (2.0*real(i)-1.0) by 2.0, then multiplies the whole thing by real(n). This may be why you get the same root for each loop.
real function p(n,x)
real::n,x
p=2*x**3 !or put in the function given to you.
end function
real function dp(n,x)
real::n,x
dp=6*x**2 !you mean derivative of polynomial p, I guess.
end function
Define function like this separately outside the main program. Inside the main program declare the functions like:
real,external::p, dp