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Application of CFD-Techniques in Fluid Machinery

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Modelling Fluid Flow

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Abstract

The CFD-techniques being applied for the simulation of the operating behaviour and performance prediction as well as the design optimisation of fluid machinery are described and briefly discussed. Then, the developed CFD-codes are applied to predict the performances of axial and diagonal fans as well as of a centrifugal pump for which also the head drop due to cavitation has been simulated. Furthermore, the predicted performance curves are compared with measurements. Finally, the capability of the real-time design system is demonstrated with respect to the optimum design of the inlet and outlet blade angels as well as to the blade length of a centrifugal pump impeller.

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Abbreviations

b:

blade height

g:

acceleration due to gravity

i = βs1−β1:

incidence angle

k:

turbulent kinetic energy

m, n:

meridional coordinates

nq:

specific speed

p:

pressure

r, φ, z:

[m], [rad] cylindrical coordinates

rref:

reference radius

s:

developed arc length

sk:

tip clearance

t:

time

u:

circumferential velocity

D:

impeller diameter

H:

total head

NPSH:

Net Positive Suction Head

NPSHi:

incipient NPSH-value

NPSH3%:

NPSH-value for 3% head drop

Q:

flow rate

R:

radius of bubbles

T:

Temperature

V:

total cell volume

α:

vapour void fraction

β:

relative flow angle

βs:

blade angle

ε:

turbulent dissipation rate

Δφw:

wrapping angle

V:

hub to tip ratio, viscosity

ρ:

density

ω:

angular velocity

1,2:

Blade inlet, outlet

l :

liquid

t :

turbulent

th :

theoretical

va :

vapour

\({c_p} = \frac{{2(p - {p_{va}})}}{{\rho u_2^2}}\) :

pressure coefficient

\(\varphi = \frac{{8Q}}{{\pi {D^3}\omega }}\) :

flow coefficient

\({\varphi _v} = \frac{\varphi }{{1 - {v^2}}}\) :

axial flow coefficient

\({\varphi _r} = \frac{\varphi }{{(4\frac{{{b_2}}}{D})}}\) :

radial flow coefficient

\({\Psi _t} = \frac{{8gH}}{{{\omega ^2}{D^2}}}\) :

total flow coefficient

\(\lambda = \varphi \cdot {\Psi _t}\) :

power density

\({\eta _h} = \frac{H}{{{H_{th}}}}\) :

hydraulic efficiency

3D:

three dimensional

ANN:

Artificial Neural Networks

B-B:

Blade to Blade

DNS:

Direct Numerical Simulation

H-S:

Hub to Shroud

LES:

Large Eddy Simulation

NEL:

National Engineering Laboratory

RANS:

Reynold-averaged Navier-Stokes equations

RTD:

Real Time Design

TFA:

Fachgebiet Turbomaschinen und Antriebstechnik, Darmstadt University of Technology

TUBS:

Technical University of Braunschweig

URANS:

unsteady Reynolds-averaged Navier-Stokes equations

VDMA:

Verband Deutscher Maschinen und Anlagenbau e.V.

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Authors and Affiliations

  1. Institute of Fluid Mechanics Hydraulic Machinery Dept., Munich University of Technology, Boltzmannstr. 15, 85748, Garching, Germany

    R. Schilling

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  1. R. Schilling
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Editors and Affiliations

  1. Department of Fluid Mechanics, Budapest University of Technology and Economics, Bertalan Lajos u. 4-6, H-1111, Budapest, Hungary

    János Vad  & Tamás Lajos  & 

  2. Lehrstuhl für Fluidmechanik, Abteilung Hydraulische Maschinen, Technische Universität München, Boltzmannstr. 15, D-85748, Garching, Germany

    Rudolf Schilling

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Schilling, R. (2004). Application of CFD-Techniques in Fluid Machinery. In: Vad, J., Lajos, T., Schilling, R. (eds) Modelling Fluid Flow. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-08797-8_1

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  • DOI: https://doi.org/10.1007/978-3-662-08797-8_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-06034-2

  • Online ISBN: 978-3-662-08797-8

  • eBook Packages: Springer Book Archive

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