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You can solve the Colebrook equation by iteration using the ]. An example is provided in C# here.<ref></ref> You can solve the Colebrook equation by iteration using the ]. An example is provided in C# here.<ref></ref>

The Easy and True equation can be solved with the Colebrook-White Equation. It is not an "Approximation", it is a true solution. There are two numbers. Rr and Re to enter in to the Colebrook-White equation. The solution will be the f. The Colebrook-White equation is 1/sqrt(f)=-2*Log(Rr/3.7+2.51/(Re*sqrt(f)))

To compute the equation, just change the 1/sqrt(f) to an X, and the right section is 2.51/(Re*sqrt(f)) can be correctly entered as 2.51/Re*1/sqrt(f) then to use the X it will be 2.51/Re+X And the Easy and True solution will be X=-2*Log(Rr/3.7+2.51/Rr+X)

So in Excel, just enter a guess number in a cell, (maybe 1 to 10, might be closer) and below the guess number, enter the equation =-2*Log(Rr/3.7+2.51/Rr+X) but for the X just point the Excel to the guess number, and format the equation to 15 digits. Then copy the equation to below to about 20 cells below, and the X will be changed to the previous cell. And the loops will stop changing to 15 digits. If bottom cells are not the same, just copy the bottom cell to some more loops, but 20 cells in usually more then needed. You can change the top guess number to a closer number like the bottom solution.

Then below the bottom cell enter =1/X/X, where the X's are just pointed to the previous number. This will be the correct solution to f. If you use the f to compute 1/Sqrt(f) and the -2*Log(Rr/3.7+2.51/(Re*sqrt(f))) you will see both computations are to the X. (This is a right computation not an approximation)

Then you can compute some of the approximation to find the f, and the best approximation will be the Goudar–Sonnad equation that is mostly the correct approximation. Most of the time it is right to the 15 digits, but the "e/D" is the "Rr" in the made equation.

Now if you want more than 15 digits, you can compute the think at this web site.... keisan.casio.com/exec/system/1380521258. They learned my solution was right and not an approximation in the the year 2013. The USA does not what to publish my free correct solution, because the it would stop the selling of approximations.


===Expanded forms=== ===Expanded forms===

Revision as of 19:25, 25 June 2015

In fluid dynamics, the Darcy friction factor formulae are equations – based on experimental data and theory – for the Darcy friction factor. The Darcy friction factor is a dimensionless quantity used in the Darcy–Weisbach equation, for the description of friction losses in pipe flow as well as open channel flow. It is also known as the Darcy–Weisbach friction factor or Moody friction factor and is four times larger than the Fanning friction factor.

Flow regime

Which friction factor formula may be applicable depends upon the type of flow that exists:

  • Laminar flow
  • Transition between laminar and turbulent flow
  • Fully turbulent flow in smooth conduits
  • Fully turbulent flow in rough conduits
  • Free surface flow.

Laminar flow

The Darcy friction factor for laminar flow in a circular pipe (Reynolds number less than 2320) is given by the following formula:

f = 64 R e {\displaystyle f={\frac {64}{\mathrm {Re} }}}

where:

  • f {\displaystyle f} is the Darcy friction factor
  • R e {\displaystyle \mathrm {Re} } is the Reynolds number.

Transition flow

Transition (neither fully laminar nor fully turbulent) flow occurs in the range of Reynolds numbers between 2300 and 4000. The value of the Darcy friction factor is subject to large uncertainties in this flow regime.

Turbulent flow in smooth conduits

The Blasius correlation is the simplest equation for computing the Darcy friction factor. Because the Blasius correlation has no term for pipe roughness, it is valid only to smooth pipes. However, the Blasius correlation is sometimes used in rough pipes because of its simplicity. The Blasius correlation is valid up to the Reynolds number 100000.

Turbulent flow in rough conduits

The Darcy friction factor for fully turbulent flow (Reynolds number greater than 4000) in rough conduits is given by the Colebrook equation.

Free surface flow

The last formula in the Colebrook equation section of this article is for free surface flow. The approximations elsewhere in this article are not applicable for this type of flow.

Choosing a formula

Before choosing a formula it is worth knowing that in the paper on the Moody chart, Moody stated the accuracy is about ±5% for smooth pipes and ±10% for rough pipes. If more than one formula is applicable in the flow regime under consideration, the choice of formula may be influenced by one or more of the following:

  • Required precision
  • Speed of computation required
  • Available computational technology:
    • calculator (minimize keystrokes)
    • spreadsheet (single-cell formula)
    • programming/scripting language (subroutine).

Compact forms

The Colebrook equation is an implicit equation that combines experimental results of studies of turbulent flow in smooth and rough pipes. It was developed in 1939 by C. F. Colebrook. The 1937 paper by C. F. Colebrook and C. M. White is often erroneously cited as the source of the equation. This is partly because Colebrook in a footnote (from his 1939 paper) acknowledges his debt to White for suggesting the mathematical method by which the smooth and rough pipe correlations could be combined. The equation is used to iteratively solve for the Darcy–Weisbach friction factor f. This equation is also known as the Colebrook–White equation.

For conduits that are flowing completely full of fluid at Reynolds numbers greater than 4000, it is defined as:

1 f = 2 log 10 ( ε 3.7 D h + 2.51 R e f ) {\displaystyle {\frac {1}{\sqrt {f}}}=-2\log _{10}\left({\frac {\varepsilon }{3.7D_{\mathrm {h} }}}+{\frac {2.51}{\mathrm {Re} {\sqrt {f}}}}\right)}
or
1 f = 2 log 10 ( ε 14.8 R h + 2.51 R e f ) {\displaystyle {\frac {1}{\sqrt {f}}}=-2\log _{10}\left({\frac {\varepsilon }{14.8R_{\mathrm {h} }}}+{\frac {2.51}{\mathrm {Re} {\sqrt {f}}}}\right)}

where:

  • f {\displaystyle f} is the Darcy friction factor
  • Roughness height, ε {\displaystyle \varepsilon } (m, ft)
  • Hydraulic diameter, D h {\displaystyle D_{\mathrm {h} }} (m, ft) – For fluid-filled, circular conduits, D h {\displaystyle D_{\mathrm {h} }} = D = inside diameter
  • Hydraulic radius, R h {\displaystyle R_{\mathrm {h} }} (m, ft) – For fluid-filled, circular conduits, R h {\displaystyle R_{\mathrm {h} }} = D/4 = (inside diameter)/4
  • R e {\displaystyle \mathrm {Re} } is the Reynolds number
  • How to check the f {\displaystyle f}  ? Compute both sides of the Colebrook-White equation with the f {\displaystyle f} and if both sides are the same then the f {\displaystyle f} was good.

Note: Some sources use a constant of 3.71 in the denominator for the roughness term in the first equation above.

Solving

The Colebrook equation is usually solved numerically due to its implicit nature. Recently, the Lambert W function has been employed to obtain explicit reformulation of the Colebrook equation.

You can solve the Colebrook equation by iteration using the Newton–Raphson method. An example is provided in C# here.

The Easy and True equation can be solved with the Colebrook-White Equation. It is not an "Approximation", it is a true solution. There are two numbers. Rr and Re to enter in to the Colebrook-White equation. The solution will be the f. The Colebrook-White equation is 1/sqrt(f)=-2*Log(Rr/3.7+2.51/(Re*sqrt(f)))

To compute the equation, just change the 1/sqrt(f) to an X, and the right section is 2.51/(Re*sqrt(f)) can be correctly entered as 2.51/Re*1/sqrt(f) then to use the X it will be 2.51/Re+X And the Easy and True solution will be X=-2*Log(Rr/3.7+2.51/Rr+X)

So in Excel, just enter a guess number in a cell, (maybe 1 to 10, might be closer) and below the guess number, enter the equation =-2*Log(Rr/3.7+2.51/Rr+X) but for the X just point the Excel to the guess number, and format the equation to 15 digits. Then copy the equation to below to about 20 cells below, and the X will be changed to the previous cell. And the loops will stop changing to 15 digits. If bottom cells are not the same, just copy the bottom cell to some more loops, but 20 cells in usually more then needed. You can change the top guess number to a closer number like the bottom solution.

Then below the bottom cell enter =1/X/X, where the X's are just pointed to the previous number. This will be the correct solution to f. If you use the f to compute 1/Sqrt(f) and the -2*Log(Rr/3.7+2.51/(Re*sqrt(f))) you will see both computations are to the X. (This is a right computation not an approximation)

Then you can compute some of the approximation to find the f, and the best approximation will be the Goudar–Sonnad equation that is mostly the correct approximation. Most of the time it is right to the 15 digits, but the "e/D" is the "Rr" in the made equation.

Now if you want more than 15 digits, you can compute the think at this web site.... keisan.casio.com/exec/system/1380521258. They learned my solution was right and not an approximation in the the year 2013. The USA does not what to publish my free correct solution, because the it would stop the selling of approximations.

Expanded forms

Additional, mathematically equivalent forms of the Colebrook equation are:

1 f = 1.7384 2 log 10 ( 2 ε D h + 18.574 R e f ) {\displaystyle {\frac {1}{\sqrt {f}}}=1.7384\ldots -2\log _{10}\left({\frac {2\varepsilon }{D_{\mathrm {h} }}}+{\frac {18.574}{\mathrm {Re} {\sqrt {f}}}}\right)}
where:
1.7384... = 2 log (2 × 3.7) = 2 log (7.4)
18.574 = 2.51 × 3.7 × 2

and

1 f = 1.1364 + 2 log 10 ( D h / ε ) 2 log 10 ( 1 + 9.287 R e ( ε / D h ) f ) {\displaystyle {\frac {1}{\sqrt {f}}}=1.1364\ldots +2\log _{10}(D_{\mathrm {h} }/\varepsilon )-2\log _{10}\left(1+{\frac {9.287}{\mathrm {Re} (\varepsilon /D_{\mathrm {h} }){\sqrt {f}}}}\right)}
or
1 f = 1.1364 2 log 10 ( ε D h + 9.287 R e f ) {\displaystyle {\frac {1}{\sqrt {f}}}=1.1364\ldots -2\log _{10}\left({\frac {\varepsilon }{D_{\mathrm {h} }}}+{\frac {9.287}{\mathrm {Re} {\sqrt {f}}}}\right)}
where:
1.1364... = 1.7384... − 2 log (2) = 2 log (7.4) − 2 log (2) = 2 log (3.7)
9.287 = 18.574 / 2 = 2.51 × 3.7.

The additional equivalent forms above assume that the constants 3.7 and 2.51 in the formula at the top of this section are exact. The constants are probably values which were rounded by Colebrook during his curve fitting; but they are effectively treated as exact when comparing (to several decimal places) results from explicit formulae (such as those found elsewhere in this article) to the friction factor computed via Colebrook's implicit equation.

Equations similar to the additional forms above (with the constants rounded to fewer decimal places, or perhaps shifted slightly to minimize overall rounding errors) may be found in various references. It may be helpful to note that they are essentially the same equation.

Free surface flow

Another form of the Colebrook-White equation exists for free surfaces. Such a condition may exist in a pipe that is flowing partially full of fluid. For free surface flow:

1 f = 2 log 10 ( ε 12 R h + 2.51 R e f ) . {\displaystyle {\frac {1}{\sqrt {f}}}=-2\log _{10}\left({\frac {\varepsilon }{12R_{\mathrm {h} }}}+{\frac {2.51}{\mathrm {Re} {\sqrt {f}}}}\right).}

Approximations of the Colebrook equation

Haaland equation

The Haaland equation was proposed by Norwegian Institute of Technology professor Haaland in 1984. It is used to solve directly for the Darcy–Weisbach friction factor f for a full-flowing circular pipe. It is an approximation of the implicit Colebrook–White equation, but the discrepancy from experimental data is well within the accuracy of the data. It was developed by S. E. Haaland in 1983.

The Haaland equation is defined as:

1 f = 1.8 log 10 [ ( ε / D 3.7 ) 1.11 + 6.9 R e ] {\displaystyle {\frac {1}{\sqrt {f}}}=-1.8\log _{10}\left}

where:

Swamee–Jain equation

The Swamee–Jain equation is used to solve directly for the Darcy–Weisbach friction factor f for a full-flowing circular pipe. It is an approximation of the implicit Colebrook–White equation.

f = 0.25 [ log 10 ( ε 3.7 D + 5.74 R e 0.9 ) ] 2 {\displaystyle f=0.25\left^{-2}}

where f is a function of:

  • Roughness height, ε (m, ft)
  • Pipe diameter, D (m, ft)
  • Reynolds number, Re (unitless).

Serghides's solution

Serghides's solution is used to solve directly for the Darcy–Weisbach friction factor f for a full-flowing circular pipe. It is an approximation of the implicit Colebrook–White equation. It was derived using Steffensen's method.

The solution involves calculating three intermediate values and then substituting those values into a final equation.

A = 2 log 10 ( ε 3.7 D + 12 Re ) {\displaystyle A=-2\log _{10}\left({\varepsilon \over 3.7D}+{12 \over {\mbox{Re}}}\right)}
B = 2 log 10 ( ε 3.7 D + 2.51 A Re ) {\displaystyle B=-2\log _{10}\left({\varepsilon \over 3.7D}+{2.51A \over {\mbox{Re}}}\right)}
C = 2 log 10 ( ε 3.7 D + 2.51 B Re ) {\displaystyle C=-2\log _{10}\left({\varepsilon \over 3.7D}+{2.51B \over {\mbox{Re}}}\right)}
1 f = ( A ( B A ) 2 C 2 B + A ) {\displaystyle {\frac {1}{\sqrt {f}}}=\left(A-{\frac {(B-A)^{2}}{C-2B+A}}\right)}

where f is a function of:

The equation was found to match the Colebrook–White equation within 0.0023% for a test set with a 70-point matrix consisting of ten relative roughness values (in the range 0.00004 to 0.05) by seven Reynolds numbers (2500 to 10).

Goudar–Sonnad equation

Goudar equation is the most accurate approximation to solve directly for the Darcy–Weisbach friction factor f for a full-flowing circular pipe. It is an approximation of the implicit Colebrook–White equation. Equation has the following form

a = 2 ln ( 10 ) {\displaystyle a={2 \over \ln(10)}}
b = ε / D 3.7 {\displaystyle b={\varepsilon /D \over 3.7}}
d = ln ( 10 ) R e 5.02 {\displaystyle d={\ln(10)Re \over 5.02}}
s = b d + ln ( d ) {\displaystyle s={bd+\ln(d)}}
q = s s / ( s + 1 ) {\displaystyle q={{s}^{s/(s+1)}}}
g = b d + ln d q {\displaystyle g={bd+\ln {d \over q}}}
z = ln q g {\displaystyle z={\ln {q \over g}}}
D L A = z g g + 1 {\displaystyle D_{LA}=z{g \over {g+1}}}
D C F A = D L A ( 1 + z / 2 ( g + 1 ) 2 + ( z / 3 ) ( 2 g 1 ) ) {\displaystyle D_{CFA}=D_{LA}\left(1+{\frac {z/2}{(g+1)^{2}+(z/3)(2g-1)}}\right)}
1 f = a [ ln ( d q ) + D C F A ] {\displaystyle {\frac {1}{\sqrt {f}}}={a\left}}

where f is a function of:

Brkić solution

Brkić shows one approximation of the Colebrook equation based on the Lambert W-function

S = l n R e 1.816 l n 1.1 R e l n ( 1 + 1.1 R e ) {\displaystyle S=ln{\frac {Re}{\mathrm {1.816ln{\frac {1.1Re}{\mathrm {ln(1+1.1Re)} }}} }}}
1 f = 2 log 10 ( ε / D 3.71 + 2.18 S Re ) {\displaystyle {\frac {1}{\sqrt {f}}}=-2\log _{10}\left({\varepsilon /D \over 3.71}+{2.18S \over {\mbox{Re}}}\right)}

where Darcy friction factor f is a function of:

The equation was found to match the Colebrook–White equation within 3.15%.

Blasius correlations

Early approximations by Paul Richard Heinrich Blasius in terms of the Moody friction factor are given in one article of 1913:

f = .316 R e 1 4 {\displaystyle f=.316\mathrm {Re} ^{-{1 \over 4}}} .

Johann Nikuradse in 1932 proposed that this corresponds to a power law correlation for the fluid velocity profile.

Mishra and Gupta in 1979 proposed a correction for curved or helically coiled tubes, taking into account the equivalent curve radius, Rc:

f = 0.316 R e 1 4 + 0.0075 D 2 R c {\displaystyle f=0.316\mathrm {Re} ^{-{1 \over 4}}+0.0075{\sqrt {\frac {D}{2R_{c}}}}} ,

with,

R c = R [ 1 + ( H 2 π R ) 2 ] {\displaystyle R_{c}=R\left}

where f is a function of:

  • Pipe diameter, D (m, ft)
  • Curve radius, R (m, ft)
  • Helicoidal pitch, H (m, ft)
  • Reynolds number, Re (unitless)

valid for:

  • Retr < Re < 10
  • 6.7 < 2Rc/D < 346.0
  • 0 < H/D < 25.4

Table of Approximations

The following table lists historical approximations where:

Note that the Churchill equation (1977) is the only one that returns a correct value for friction factor in the laminar flow region (Reynolds number < 2300). All of the others are for transitional and turbulent flow only.

Table of Colebrook equation approximations
Equation Author Year Ref

λ = .0055 ( 1 + ( 2 × 10 4 ε D + 10 6 R e ) 1 3 ) {\displaystyle \lambda =.0055(1+(2\times 10^{4}\cdot {\frac {\varepsilon }{D}}+{\frac {10^{6}}{Re}})^{\frac {1}{3}})}

Moody 1947

λ = .094 ( ε D ) 0.225 + 0.53 ( ε D ) + 88 ( ε D ) 0.44 R e Ψ {\displaystyle \lambda =.094({\frac {\varepsilon }{D}})^{0.225}+0.53({\frac {\varepsilon }{D}})+88({\frac {\varepsilon }{D}})^{0.44}\cdot {Re}^{-{\Psi }}}

where
Ψ = 1.62 ( ε D ) 0.134 {\displaystyle \Psi =1.62({\frac {\varepsilon }{D}})^{0.134}}
Wood 1966

1 λ = 2 log ( ε 3.715 D + 15 R e ) {\displaystyle {\frac {1}{\sqrt {\lambda }}}=-2\log({\frac {\varepsilon }{3.715D}}+{\frac {15}{Re}})}

Eck 1973

1 λ = 2 log ( ε 3.7 D + 5.74 R e 0.9 ) {\displaystyle {\frac {1}{\sqrt {\lambda }}}=-2\log({\frac {\varepsilon }{3.7D}}+{\frac {5.74}{Re^{0.9}}})}

Jain and Swamee 1976

1 λ = 2 log ( ( ε 3.71 D ) + ( 7 R e ) 0.9 ) {\displaystyle {\frac {1}{\sqrt {\lambda }}}=-2\log(({\frac {\varepsilon }{3.71D}})+({\frac {7}{Re}})^{0.9})}

Churchill 1973

1 λ = 2 log ( ( ε 3.715 D ) + ( 6.943 R e ) 0.9 ) ) {\displaystyle {\frac {1}{\sqrt {\lambda }}}=-2\log(({\frac {\varepsilon }{3.715D}})+({\frac {6.943}{Re}})^{0.9}))}

Jain 1976

λ = 8 [ ( 8 R e ) 12 + 1 ( Θ 1 + Θ 2 ) 1.5 ) ] 1 12 {\displaystyle \lambda =8^{\frac {1}{12}}}

where
Θ 1 = [ 2.457 ln [ ( 7 R e ) 0.9 + 0.27 ε D ] ] 16 {\displaystyle \Theta _{1}=]^{16}}
Θ 2 = ( 37530 R e ) 16 {\displaystyle \Theta _{2}=({\frac {37530}{Re}})^{16}}
Churchill 1977

1 λ = 2 log [ ε 3.7065 D 5.0452 R e log ( 1 2.8257 ( ε D ) 1.1098 + 5.8506 R e 0.8981 ) ] {\displaystyle {\frac {1}{\sqrt {\lambda }}}=-2\log}

Chen 1979

1 λ = 1.8 log [ R e 0.135 R e ( ε D ) + 6.5 ] {\displaystyle {\frac {1}{\sqrt {\lambda }}}=1.8\log}

Round 1980

1 λ = 2 log ( ε 3.7 D + 5.158 l o g ( R e 7 ) R e ( 1 + R e 0.52 29 ( ε D ) 0.7 ) ) {\displaystyle {\frac {1}{\sqrt {\lambda }}}=-2\log \left({\frac {\varepsilon }{3.7D}}+{\frac {5.158log({\frac {Re}{7}})}{Re\left(1+{\frac {Re^{0.52}}{29}}({\frac {\varepsilon }{D}})^{0.7}\right)}}\right)}

Barr 1981

1 λ = 2 log [ ε 3.7 D 5.02 R e log ( ε 3.7 D 5.02 R e log ( ε 3.7 D + 13 R e ) ) ] {\displaystyle {\frac {1}{\sqrt {\lambda }}}=-2\log}

or

1 λ = 2 log [ ε 3.7 D 5.02 R e log ( ε 3.7 D + 13 R e ) ] {\displaystyle {\frac {1}{\sqrt {\lambda }}}=-2\log}

Zigrang and Sylvester 1982

1 λ = 1.8 log [ ( ε 3.7 D ) 1.11 + 6.9 R e ] {\displaystyle {\frac {1}{\sqrt {\lambda }}}=-1.8\log \left}

Haaland 1983

λ = [ Ψ 1 ( Ψ 2 Ψ 1 ) 2 Ψ 3 2 Ψ 2 + Ψ 1 ] 2 {\displaystyle \lambda =^{-2}}

or

λ = [ 4.781 ( Ψ 1 4.781 ) 2 Ψ 2 2 Ψ 1 + 4.781 ] 2 {\displaystyle \lambda =^{-2}}

where
Ψ 1 = 2 log ( ε 3.7 D + 12 R e ) {\displaystyle \Psi _{1}=-2\log({\frac {\varepsilon }{3.7D}}+{\frac {12}{Re}})}
Ψ 2 = 2 log ( ε 3.7 D + 2.51 Ψ 1 R e ) {\displaystyle \Psi _{2}=-2\log({\frac {\varepsilon }{3.7D}}+{\frac {2.51\Psi _{1}}{Re}})}
Ψ 3 = 2 log ( ε 3.7 D + 2.51 Ψ 2 R e ) {\displaystyle \Psi _{3}=-2\log({\frac {\varepsilon }{3.7D}}+{\frac {2.51\Psi _{2}}{Re}})}
Serghides 1984

1 λ = 2 log ( ε 3.7 D + 95 R e 0.983 96.82 R e ) {\displaystyle {\frac {1}{\sqrt {\lambda }}}=-2\log({\frac {\varepsilon }{3.7D}}+{\frac {95}{Re^{0.983}}}-{\frac {96.82}{Re}})}

Manadilli 1997

1 λ = 2 log { ε 3.7065 D 5.0272 R e log [ ε 3.827 D 4.657 R e log ( ( ε 7.7918 D ) 0.9924 + ( 5.3326 208.815 + R e ) 0.9345 ) ] } {\displaystyle {\frac {1}{\sqrt {\lambda }}}=-2\log \lbrace {\frac {\varepsilon }{3.7065D}}-{\frac {5.0272}{Re}}\log\rbrace }

Monzon, Romeo, Royo 2002

1 λ = 0.8686 ln [ 0.4587 R e ( S 0.31 ) S ( S + 1 ) ] {\displaystyle {\frac {1}{\sqrt {\lambda }}}=0.8686\ln}

where:
S = 0.124 R e ε D + ln ( 0.4587 R e ) {\displaystyle S=0.124Re{\frac {\varepsilon }{D}}+\ln(0.4587Re)}
Goudar, Sonnad 2006

1 λ = 0.8686 ln [ 0.4587 R e ( S 0.31 ) S ( S + 0.9633 ) ] {\displaystyle {\frac {1}{\sqrt {\lambda }}}=0.8686\ln}

where:
S = 0.124 R e ε D + ln ( 0.4587 R e ) {\displaystyle S=0.124Re{\frac {\varepsilon }{D}}+\ln(0.4587Re)}
Vatankhah, Kouchakzadeh 2008

1 λ = α [ α + 2 log ( B R e ) 1 + 2.18 B ] {\displaystyle {\frac {1}{\sqrt {\lambda }}}=\alpha -}

where
α = ( 0.744 ln ( R e ) ) 1.41 ( 1 + 1.32 ε D ) {\displaystyle \alpha ={\frac {(0.744\ln(Re))-1.41}{(1+1.32{\sqrt {\frac {\varepsilon }{D}}})}}}
B = ε 3.7 D R e + 2.51 α {\displaystyle \mathrm {B} ={\frac {\varepsilon }{3.7D}}Re+2.51\alpha }
Buzzelli 2008

λ = 6.4 ( ln ( R e ) ln ( 1 + .01 R e ε D ( 1 + 10 ε D ) ) ) 2.4 {\displaystyle \lambda ={\frac {6.4}{(\ln(Re)-\ln(1+.01Re{\frac {\varepsilon }{D}}(1+10{\sqrt {\frac {\varepsilon }{D}}})))^{2.4}}}}

Avci, Kargoz 2009

λ = 0.2479 0.0000947 ( 7 log R e ) 4 ( log ( ε 3.615 D + 7.366 R e 0.9142 ) ) 2 {\displaystyle \lambda ={\frac {0.2479-0.0000947(7-\log Re)^{4}}{(\log({\frac {\varepsilon }{3.615D}}+{\frac {7.366}{Re^{0.9142}}}))^{2}}}}

Evangleids, Papaevangelou, Tzimopoulos 2010
  1. The Haaland equation was proposed by Norwegian Institute of Technology professor Haaland in 1984. It is used to solve directly for the Darcy–Weisbach friction factor f for a full-flowing circular pipe. It is an approximation of the implicit Colebrook–White equation, but the discrepancy from experimental data is well within the accuracy of the data. It was developed by S. E. Haaland in 1983.

References

  1. Manning, Francis S.; Thompson, Richard E. (1991). Oilfield Processing of Petroleum. Vol. 1: Natural Gas. PennWell Books. ISBN 0-87814-343-2., 420 pages. See page 293.
  2. Colebrook, C.F. (February 1939). "Turbulent flow in pipes, with particular reference to the transition region between smooth and rough pipe laws". Journal of the Institution of Civil Engineers. London.
  3. Colebrook, C. F. and White, C. M. (1937). "Experiments with Fluid Friction in Roughened Pipes". Proceedings of the Royal Society of London. Series A, Mathematical and Physical Sciences. 161 (906): 367–381. Bibcode:1937RSPSA.161..367C. doi:10.1098/rspa.1937.0150.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  4. VDI Heat Atlas second edition page 1058 (ISBN 978-3-540-77876-9)
  5. More, A. A. (2006). "Analytical solutions for the Colebrook and White equation and for pressure drop in ideal gas flow in pipes". Chemical Engineering Science. 61 (16): 5515–5519. doi:10.1016/j.ces.2006.04.003.
  6. Métodos Numéricos con C#
  7. ^ BS Massey Mechanics of Fluids 6th Ed ISBN 0-412-34280-4
  8. P.K. Swami, A.K. Jaine, Explicit equations for pipeflow problems, J Hydraulics Div, Proc ASCE (1976), pp. 657–664 May
  9. Serghides, T.K (1984). "Estimate friction factor accurately". Chemical Engineering Journal 91(5): 63–64.
  10. Goudar, C.T., Sonnad, J.R. (August 2008). "Comparison of the iterative approximations of the Colebrook–White equation". Hydrocarbon Processing Fluid Flow and Rotating Equipment Special Report(August 2008): 79–83.
  11. Brkić, Dejan (2011). "An Explicit Approximation of Colebrook's equation for fluid flow friction factor". Petroleum Science and Technology. 29 (15): 1596–1602. doi:10.1080/10916461003620453.
  12. Trinh, On the Blasius correlation for friction factors, p. 1
  13. Adrian Bejan, Allan D. Kraus, Heat transfer handbook, John Wiley & Sons, 2003
  14. Beograd, Dejan Brkić (March 2012). "Determining Friction Factors in Turbulent Pipe Flow". Chemical Engineering: 34–39.(subscription required)
  15. Churchill, S.W. (November 7, 1977). "Friction-factor equation spans all fluid-flow regimes". Chemical Engineering: 91–92.

Further reading

  • Colebrook, C.F. (February 1939). "Turbulent flow in pipes, with particular reference to the transition region between smooth and rough pipe laws". Journal of the Institution of Civil Engineers. London. doi:10.1680/ijoti.1939.13150.
    For the section which includes the free-surface form of the equation – "Computer Applications in Hydraulic Engineering" (5th ed.). Haestad Press. 2002. {{cite journal}}: Cite journal requires |journal= (help), p. 16.
  • Haaland, SE (1983). "Simple and Explicit Formulas for the Friction Factor in Turbulent Flow". Journal of Fluids Engineering. 105 (1). ASME: 89–90. doi:10.1115/1.3240948.
  • Swamee, P.K.; Jain, A.K. (1976). "Explicit equations for pipe-flow problems". Journal of the Hydraulics Division. 102 (5). ASCE: 657–664.
  • Serghides, T.K (1984). "Estimate friction factor accurately". Chemical Engineering. 91 (5): 63–64. – Serghides' solution is also mentioned here.
  • Moody, L.F. (1944). "Friction Factors for Pipe Flow". Transactions of the ASME. 66 (8): 671–684.
  • Brkić, Dejan (2011). "Review of explicit approximations to the Colebrook relation for flow friction". Journal of Petroleum Science and Engineering. 77 (1): 34–48. doi:10.1016/j.petrol.2011.02.006.
  • Brkić, Dejan (2011). "W solutions of the CW equation for flow friction". Applied Mathematics Letters. 24 (8): 1379–1383. doi:10.1016/j.aml.2011.03.014.

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