Applied Computational Fluid Dynamics by Hyoung Woo Oh - HTML preview

PLEASE NOTE: This is an HTML preview only and some elements such as links or page numbers may be incorrect.
Download the book in PDF, ePub, Kindle for a complete version.

L

length of the rotor of the centrifuge, m

n

revolutions per minute, rpm

p

pressure, Pa (N m-2)

pc permeability,

m2

rbowl

bowl radius, m

rweir

weir radius, m

rboundary layer

radius of boundary layer, m

130

Applied Computational Fluid Dynamics

Si

sink term, N m-3

t

time, s

u

velocity in x direction, m s-1

v

velocity in y direction, m s-1

vax

axial velocity, m s-1

v velocity,

m

s-1

w

velocity in z direction, m s-1

x

particle diameter, m

xcell

cell length, m

y+

characteristic width of viscous sublayer, dimensionless

Greek letters

α

volume fraction, dimensionless

δ

thickness of the axial boundary layer, mm

δn

normal overlap, m

δt

tangential overlap, m

ε

turbulent kinetic energy dissipation rate, m2 s-3

εs sediment

porosity,

dimensionless

µ

dynamic viscosity, kg m-1 s-1

µt

turbulent viscosity, kg m-1 s-1

density, kg m-3

s

solids density, kg m-3



density difference between liquid and solid, kg m-3

τt

turbulent stress tensor, Pa (N m-2)

τw

wall shear stress, Pa (N m-2)

i Poissons

ratio,

dimensionless

specific turbulent kinetic energy dissipation rate, s-1

Indices

fluctuating component of a variable

q

phase

Abbreviations

LES

large-eddy simulation

RBR

rigid body rotation

RSM

Reynolds Stress Model

VOF

Volume of Fluid

St

Stokes number

10. Acknowledgments

We acknowledge support by Deutsche Forschungsgemeinschaft and Open Access

Publishing Fund of Karlsruhe Institute of Technology.

11. References

Anderson, N. G., Waters, D. A., Nunley, C. E., Gibson, R. F., Schilling, R. M., Denny, E. C., Cline, G. B., Babelay, E. F. & Perardi, T. E. (1969). K-Series Centrifuges I.

Computational Fluid Dynamics (CFD) and

Discrete Element Method (DEM) Applied to Centrifuges

131

Development of the K-II continuous-sample-flow-with-banding centrifuge system

for vaccine purification. Analytical Biochemistry, 32, 3, 460-494

ANSYS. (2006). Chapter 23.3.2 Volume Fraction Equation, In: User's Guide Ansys Fluent 6.3

ANSYS. (2009). Chapter 4.12.2 Standard Wall Functions, In: Theory Guide Ansys Fluent 12.0

ANSYS. (2009). Chapter 18.4.1 Discretization of the Momentum Equation, In: Theory Guide

Ansys Fluent 12. ,

ANSYS. (2009). Chapter 23. Modeling Discrete Phase, In: User's Guide Ansys Fluent 12.0

Asaf, Z., Rubinstein, D. & Shmulevich, I. (2007). Determination of discrete element model parameters required for soil tillage. Soil & Tillage Research, 92, 1-2, 227-242

Bass, E. (1959). Strömungen im Fliehkraftfeld I. Periodica Polytechics chem. Ingenieurwes, 3, 321-340

Bass, E. (1959). Strömungen im Fliehkraftfeld II - Absetzsicherheit von Röhrenzentrifugen.

Periodica Polytechics chem. Ingenieurwes, 4, 41-61

Bass, E. (1962). Strömungs- und Absetzvorgänge in Röhrenzentrifugen. 249-264

Brantley, J. N., Willis, D. D., Breillatt, J. P., Gibson, R. F., Patrick, L. C. & Anderson, N. G.

(1970). K-series centrifuges : IV. Measurement and control of temperature.

Analytical Biochemistry, 36, 2, 434-442

Brennan, M. S., M., N. & Holtham, P. N. (2007). Multiphase modelling of hydrocyclones –

prediction of cut-size. Minerals Engineering, 20, 395-406

Bürger, R. & Wendland, W. L. (2001). Sedimentation and suspension flows: Historical

perspective and some recent developments. Journal of Engineering Mathematics, 41,

2-3, 101-116

Buscall, R. (1990). The sedimentation of concentrated colloidal suspensions. Colloids and Surfaces Papers Presented at the Society of Chemical Industry Meeting, 43, 1, 33-53

Buscall, R., Mills, P. D. A., Stewart, R. F., Sutton, D., White, L. R. & Yates, G. E. (1987). The rheology of strongly-flocculated suspensions. Journal of Non-Newtonian Fluid

Mechanics, 24, 2, 183-202

Chu, K. W., Wang, B., Yu, A. B. & Vince, A. (2009). CFD-DEM modelling of multiphase flow in dense medium cyclones. Powder Technology, 193, 3, 235-247

Chu, K. W. & Yu, A. B. (2008). Numerical simulation of complex particle-fluid flows. Powder Technology, 179, 3, 104-114

Cundall, P. A. & Strack, O. D. L. (1979). Discrete Numerical-Model for Granular Assemblies.

Geotechnique, 29, 1, 47-65

Di Renzo, A. & Di Maio, F. P. (2005). An improved integral non-linear model for the contact of particles in distinct element simulations. Chemical Engineering Science, 60, 5, 1303-1312

Glinka, U. (1983). Die Strömung in Überlaufzentrifugen - Neue Ergebnisse mit einem

elektrolytischen Markierungsverfahren. Verfahrenstechnik, 17, 5, 315-318

Golovko, Y. D. (1969). Liquid Lag in Tubular Centrifuge Rotors. Khimicheskoe i Neftyanoe Mashinostroenie, 6, 13-14

Gondret, P., Lance, M. & Petit, L. (2002). Bouncing motion of spherical particles in fluids.

Physics of Fluids, 14, 2, 643-652

Gösele, W. (1968). Schichtströmung in Röhrenzentrifugen. Chemie IngenieurTechnik, 40, 13, 657-659

132

Applied Computational Fluid Dynamics

Gösele, W. (1974). Strömungen in Überlauf-Zentrifugen und ihr Einfluß auf die

Sedimentation. Chemie Ingenieur Technik, 46, 2, 67

Hartl, J. & Ooi, J. Y. (2008). Experiments and simulations of direct shear tests: porosity, contact friction and bulk friction. Granular Matter, 10, 4, 263-271

Hirt, C. W. & Nichols, B. D. (1981). Volume of Fluid (VOF) method for the dynamics of free boundaries. Journal of Computational Physics, 39, 1, 201-225

Horanyi, R. & Nemeth, J. (1971). Theoretical Investigation of Clarification Process in a Tube Centrifuge. Acta Chimica Academiae Scientarium Hungaricae, 69, 1, 59-75

Kelecy, F. J. (2008). Coupling momentum and continuity increases robustness. ANSYS

Advantage, 2, 2, 49-51

Kynch, G. J. (1952). A theory of sedimentation. Transactions of the Faraday Society, 48, 2, 166-176

Landman, K. A. & White, L. R. (1994). Solid/liquid separation of flocculated suspensions.

Advances in Colloid and Interface Science, 51, 175-246

Launder, B. E., Reece, G. J. & Rodi, W. (1975). Progress in development of a Reynolds-Stress turbulence closure. Journal of Fluid Mechanics, 68, APR15, 537-566

Launder, B. E. & Spalding, D. B. (1974). The numerical computation of turbulent flows.

Computer Methods in Applied Mechanics and Engineering, 3, 2, 269-289

Leung, W. (1998). Industrial Centrifugation Technology, McGraw.Hill, New York

Li, Y., Zhang, J. P. & Fan, L. S. (1999). Numerical simulation of gas-liquid-solid fluidization systems using a combined CFD-VOF-DPM method: bubble wake behavior.

Chemical Engineering Science, 54, 21, 5101-5107

Li, Y. J., Xu, Y. & Thornton, C. (2005). A comparison of discrete element simulations and experiments for 'sandpiles' composed of spherical particles. Powder Technology, 160, 3, 219-228

Lun, C. K. K. & Savage, S. B. (1987). A simple kinetic theory for granular flow of rough, inelastic, spherical particles. Journal of Applied Mechanics-Transactions of the Asme, 54, 1, 47-53

Mainza, A., Narasimha, M., Powell, M. S., Holtham, P. N. & Brennan, M. (2006). Study of

flow behaviour in a three-product cyclone using computational fluid dynamics.

Minerals Engineering, 19, 10, 1048-1058

Mindlin, R. D. (1949). Compliance of elastic bodies in contact. Journal of Applied Mechanics-Transactions of the Asme, 16, 3, 259-268

Mousavian, S. M. & Najafi, A. F. (2009). Numerical simulations of gas-liquid-solid flows in a hydrocyclone separator. Archive of Applied Mechanics, 79, 5, 395-409

Ni, L. A., Yu, A. B., Lu, G. Q. & Howes, T. (2006). Simulation of the cake formation and growth in cake filtration. Minerals Engineering, 19, 10, 1084-1097

Nowakowski, A. F., Cullivan, J. C., Williams, R. A. & Dyakowski, T. (2004). Application of CFD to modelling of the flow in hydrocyclones. Is this a realizable option or still a

research challange? Minerals Engineering, 17, 661-669

Perardi, T. E. & Anderson, N. G. (1970). K-series centrifuges : III. Effect of core taper on particle capture efficiency. Analytical Biochemistry, 34, 1, 112-122

Perardi, T. E., Leffler, R. A. A. & Anderson, N. G. (1969). K-series centrifuges II. Performance of the K-II rotor. Analytical Biochemistry, 32, 3, 495-511

Computational Fluid Dynamics (CFD) and

Discrete Element Method (DEM) Applied to Centrifuges

133

Reuter, H. (1967). Sedimentation in der Überlaufzentrifuge. Chemie-Ing. Tech. , 39, 9, 548-553

Romani Fernandez, X. & Nirschl, H. (2009). Multiphase CFD Simulation of a Solid Bowl

Centrifuge. Chemical Engineering & Technology, 32, 5, 719-725

Saunders, E. (1948). Nomograph for Particle Size Determination with the Sharples

Supercentrifuge. Analytical Chemistry, 20, 4, 379-381

Schaeflinger, U. & Stibi, H. (1991). Centrifugal separation of a mixture in a rotating bucket II.

Chemical Engineering Science, 46, 8, 2143-2152

Schaeflinger, U., Stibi, H. (1991). Centrifugal separation of a mixture in a rotating bucket. The American Society of Mechanical Engineers, 118, 173-182

Schütz, S., Piesche, M., Gorbach, G., Schilling, M., Seyfert, C., Kopf, P., Deuschle, T., Sautter, N., Popp, E. & Warth, T. (2007). CFD in der mechanischen Trenntechnik. Chemie

Ingenieur Technik, 79, II, 1777-1796

Sokolow, W. J. (1971). Moderne Industriezentrifugen, VEB Verlag Berlin, Leipzig

Spelter, L. E., Schirner, J. and Nirschl, H., (2011). A novel approach for determining the flow patterns in centrifuges by means of Laser-Doppler-Anemometry. Chemical

Engineering Science, In Press, Corrected Proof

Spelter, L. E. & Nirschl, H. (2010). Classification of Fine Particles in High-Speed Centrifuges.

Chemical Engineering & Technology, 33, 8, 1276-1282

Spelter, L. E., Steiwand, A. & Nirschl, H. (2010). Processing of dispersions containing fine particles or biological products in tubular bowl centrifuges. Chemical Engineering

Science, 65, 14, 4173-4181

Stahl, S., Spelter, L. E. & Nirschl, H. (2008). Investigations on the Separation Efficiency of Tubular Bowl Centrifuges. Chemical Engineering & Technology, 31, 11, 1577-1583

Stahl, W. H. (2004). Industrie-Zentrifugen, DrM Press, Männedorf

Stevens, A. B. & Hrenya, C. M. (2005). Comparison of soft-sphere models to

measurements of collision properties during normal impacts. Powder Technology,

154, 2-3, 99-109

Taylor, A. R. (1946). Concentration of the Rabbit Papilloma Virus with the Sharples

Supercentrifuge. Journal of Biological Chemistry, 163, 1, 283-287

Trawinski, H. (1959). Die äquivalente Klärfläche von Zentrifugen. Chemiker Zeitung

Chemische Apperatur, 83, 18, 606-612

van Wachem, B. G. M. & Almstedt, A. E. (2003). Methods for multiphase computational

fluid dynamics. Chemical Engineering Journal, 96, 1-3, 81-98

Wang, B. & Yu, A. B. (2006). Numerical study of particle–fluid flow in hydrocyclones with different body dimensions. Minerals Engineering, 19, 1022-1033

Wardle, K. E., Allen, T. R. & Swaney, R. (2006). Computational Fluid Dynamics (CFD) Study of the Flow in an Annular Centrifugal Contactor. Separation Science and Technology,

41, 2225-2244

Wilcox, D. C. (1988). Reassessment of the scale-determining equation for advanced

turbulence models. Aiaa Journal, 26, 11, 1299-1310

Yakhot, V. & Orszag, S. A. (1986). Renormalization-group analysis of turbulence. Physical Review Letters, 57, 14, 1722-1724

Zubkov, V. A. & Golovko, Y. D. (1968). Liquid Flow in the Extraction Head of a Tubular-

Centrifuge Rotor. Khimicheskoe i Neftyanoe Mashinostroenie, 12, 18-19

134

Applied Computational Fluid Dynamics

Zubkov, V. A. & Golovko, Y. D. (1969). Flow of Liquid in Rotor Outlet of a Tubular

Centrifuge. International Chemical Engineering, 9, 3, 403-406

7

CFD and Thermography Techniques

Applied in Cooling Systems Designs

Samuel Santos Borges and Cassiano Antunes Cezario

Research and Technological Innovation Department, WEG

Brazil

1. Introduction

The focus of this work consists in optimizing the water flow inside a water cooled electric

motor frame, aiming at the maximization of the power/frame size ratio, the minimization of

pressure drop and the avoidance of hot spots. For the development of this work

computational fluid dynamics (CFD) and thermography techniques were used.

For many years water cooled electric motors have been used by industry, especially in

specific applications that require features that can not be provided by conventional fan

cooled motors. Among theses features are a better power/frame size relation, low noise

levels, enclose applications, among others.

Cooling by means of water circulation is frequently used in large motors, typically frame

sizes above IEC 315. A justification for this practice not to be widely used in smaller motors is its higher cost compared to air cooling systems. However, provided that it presents some

technical and/or economical viability, water cooling can also be used in smaller frame sizes.

The technological progress have resulted in the development of new tools that facilitate the study of this motor type, such as the computational fluid dynamics and the thermography

techniques, which consist, respectively, in the use of numeric models applied to fluid

mechanics and the obtaining of the motor surface temperature distribution.

2. Benefits and drawbacks

The following advantages and disadvantages of this kind of motor can be mentioned, in

comparison with air cooled motors.

2.1 Advantages

Greater power/frame size ratio;

Lower noise level;

Higher efficiency;

The outside waste deposit on the frame does not damage the motor cooling;

No problems with waste deposit on the external fan blade;

It can be used in totally enclosure environment;

The heat removed from the motor is not directly dissipated into the environment;

Possibility of using the same cooling fluid of the load and/or machine where it is

installed;

136

Applied Computational Fluid Dynamics

Better resistance to local impact.

2.2 Disadvantages

Higher manufacturing cost;

Auxiliary system to provide water;

Need to control the water chemical composition;

Risk of corrosion inside of the water circuit;

Risk of fouling in the water circuit;

Risk of leaks;

More precautions on maintenance.

3. Fundamental concepts

3.1 Cooling system

The cooling systems are apparatus usually comprised of several components that interact to

keep the temperature of machines and systems in general controlled in order not to exceed

the limits imposed by quality, safety, performance and/or efficiency. For instance, systems

such as internal combustion engines, turbines, compressors, bearings, electric machines,

electronic structures, electrical conductors, chemical and welding processes, among many

others, can be mentioned as some examples of systems comprising thermal restrictions.

Consequently, the cooling systems are very important to industries and should therefore be

designed to keep a good performance and reliability.

The more commonly used coolants are gases and liquids. Among them, due to their wide

occurrence, low cost and practicality, air and water are customarily employed. They can be

used in many different ways: in direct or indirect contact with the systems, by means of one or more fluid combinations, separated or mixed. And they can be forcedly or naturally moved,

by physical mechanisms respectively known as forced convection and natural convection.

3.2 Heat transfer

Heat transfer concerns the exchange of thermal energy from one region of higher

temperature to another of lower temperature in one or more means. This exchange occurs

by mechanisms as conduction, convection, radiation and phase-change.

3.2.1 Conduction

The conduction occurs due to interactions between the particles of fluids. Thermal

insulation, tanks, plates and ducts walls, fins, and others are examples of devices that

exchange heat by conduction. It is described by Fourier’s Law and the following equation:

T

q  

k

kA

(1)

n

Where,

qk: Heat flux of conduction;

K: Thermal conductivity;

A: Heat transfer area;

T

 : Temperature gradient;

n: Direction.

CFD and Thermography Techniques Applied in Cooling Systems Designs

137

3.2.2 Convection

The convection is the heat transfer between a solid surface and a moving fluid. This

phenomenon can be natural, induced by density difference (low fluid velocity), or forced,

customarily supplied by fans or pumps (high fluid velocity).

q h (

A T T)

h

s

(2)

Where,

qh: Heat flux of convection;

h: Convection coefficient;

A: Heat transfer area;

Ts: Surface temperature;

T∞: Fluid temperature.

3.2.3 Radiation

The thermal radiation is provided by electromagnetic waves emission. The classic example

of this phenomenon is the heat transfer between sun and earth. It is given by Stefan-

Boltzmann Law.

4

4

q   (

1

T

2

T )

r

(3)

Where,

qr: Heat flux of radiation;

ε: Emissivity;

σ: Stefan-Boltzmann constant;

T1, T2: Surface temperatures.

3.2.4 Phase – Change

It is boiling, condensation, freezing and melting. These processes are given by following

equations.

Q  .

m H

 (4)

Where,

Q: Amount of heat;

m: Mass;

ΔH: Specific latent heat.

3.2.5 Heat transfer in conduits

In the heat transfer in the fluid flowing in a conduit, the temperature is neither uniform in the fluid flow direction nor in the heat flux direction. Therefore, the bulk temperature is

assumed as reference temperature. The use of a temperature reference allows to execute the

heat balance in steady state. In this case, the transferred heat per time unit is a direct

measure of the bulk temperature difference between two conduit sections. That is,

q   .

m c .

p

b

T (5)

138

Applied Computational Fluid Dynamics

Where,

q: Amount of heat per time unit;

m : Mass flow rate;

cp: Specific heat of fluid;

ΔTb: Bulk temperature difference of fluid among two conduit sections.

3.3 Fluid dynamics

3.3.1 Mass flow rate

The mass flow rate is given by the mass of fluid which passes through a surface per time

unit and can be calculated from the following equation:

m  . .

v A (6)

Where,

m : Mass flow rate;

ρ: Fluid density;

v: Mean velocity in the section;

A: Area of conduit section.

3.3.2 Pressure drop

The pressure drop in pipes may be occasioned by means of:

Localized drops (valves, curves, and others);

Friction;

Difference of piping height.

The pressure drop is obtained as a function of Reynolds number, which depends on the

flu