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Helsinki University of Technology. Laboratory of Applied Thermodynamics.

Teknillinen korkeakoulu. Sovelletun termodynamiikan laboratorio.

Espoo 2001, FINLAND

NUMERICAL AND EXPERIMENTAL STUDIES ON ROOM AIR FLOW

Report 132

Juhaveikko Ala-Juusela Jorma Heikkinen Kim Hagstrom

VTT Building Technology Halton Group Ltd.

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Helsinki University of Technology. Laboratory of Applied Thermodynamics.

Teknillinen korkeakoulu. Sovelletun termodynamiikan laboratorio.

Espoo 2001, FINLAND

NUMERICAL AND EXPERIMENTAL STUDIES ON ROOM AIR FLOW

Report 132

Juhaveikko Ala-Juusela Jorma Heikkinen Kim Hagstrom

VTT Building Technology Halton Group Ltd.

Helsinki University of Technology

Department of Mechanical Engineering

Laboratory of Applied Thermodynamics

Teknillinen korkeakoulu

Konetekniikan osasto

Sovelletun termodynamiikan laboratorio

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Distribution:

Helsinki University of Technology

Laboratory of Applied Thermodynamics

FIN-002015 HUT

Tel. +358-9-451 3581

Fax. +358-9-455 3724

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ABSTRACT

In this study the air flow in a small scale industrial hall is simulated numerically usingtwo different computing codes, the commercial flow solver with a high-Reynolds numberturbulence model and a university code with a low-Reynolds number turbulence model.The results are compared with measurements. Two different air supply arrangements withgrille or nozzle types of air terminal devices are studied, both with isothermal and non-isothermal boundary conditions.

The air flow patterns are very complicated since heat and momentum sources are dis-tributed. The supply air devices cannot be described in detail without the computationalgrid becoming impractically large. Therefore, an integral part of a CFD simulation is tosimplify the actual flow situation without losing essential features of the flow.

The air velocities with the high-Reynolds number code were consistently higher thanthe measured ones, and, therefore, one could say that these results were on the safe sideconsidering the draught risk. The low-Reynolds number simulations predicted too lowvelocities in some cases. In some parts of the room even the qualitative air flow pattern

was different in the two simulations, most notably in the regions where the buoyancy forcesand the inertia forces of the supply air jet are of the same magnitude and the supply air jetis deflecting near the solid boundaries.

It turned out to be difficult to make accurate comparisons with the measurementsbecause the comfort oriented, omnidirectional air speed measurements were not directlycomparable with the air velocity computed with the turbulence models. One possibilityis to use an artificial, modified velocity for comparison instead of the actual velocity. Thismethod has been used in this study and it seems that especially in low speed areas thecorrespondence between the measured and calculated speeds is improved by using themodified velocity for comparison.

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CONTENTS

Nomenclature 3

1 Introduction 4

2 Numerical Method 5

2.1 FINFLO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5Flow Equations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5Turbulence Modelling . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

2.2 Pseudo-compressibility Method . . . . . . . . . . . . . . . . . . . . . . . 72.3 FLUENT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

3 Investigated cases 9

3.1 Equipment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9Room Ventilation Simulator . . . . . . . . . . . . . . . . . . . . . . . . . 9Experimental Room Layout . . . . . . . . . . . . . . . . . . . . . . . . . 9Measurement and Control Systems and Equipment . . . . . . . . . . . . 9Omnidirectional Thermistor Anemometer . . . . . . . . . . . . . . . . . . 9

3.2 Experimental Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . 10Air Supply Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10Air Change Rate and Cooling Load . . . . . . . . . . . . . . . . . . . . . 10

3.3 Characterisation of the Air Supply Devices . . . . . . . . . . . . . . . . . 11Velocity Decay and Temperature Coefficients . . . . . . . . . . . . . . . . 11

4 Boundary Conditions for CFD Simulations 13

4.1 Air Supply Device . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13Inlet Boundary Conditions of the Grille Case . . . . . . . . . . . . . . . . 13

Inlet Boundary Conditions of the Nozzle Case . . . . . . . . . . . . . . . 154.2 Thermal Boundary Conditions . . . . . . . . . . . . . . . . . . . . . . . . 154.3 Wall Boundary Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . 16

5 Computational Grid 17

5.1 FINFLO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175.2 FLUENT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

6 FINFLO Results 20

6.1 Isothermal Room with Grille Type of Air Supply Devices . . . . . . . . . . 20Convergence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20Description of the Flow Field . . . . . . . . . . . . . . . . . . . . . . . . 21Comparison with the Measurements . . . . . . . . . . . . . . . . . . . . . 22

6.2 Non-isothermal Room with Grille Type of Air Supply Devices . . . . . . . 22Convergence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22Description of the Flow Field . . . . . . . . . . . . . . . . . . . . . . . . 24Comparison with the Measurements . . . . . . . . . . . . . . . . . . . . . 28

6.3 Isothermal Room with Nozzle Type of Air Supply Devices . . . . . . . . . 28Convergence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28Description of the Flow Field . . . . . . . . . . . . . . . . . . . . . . . . 29Comparison with the Measurements . . . . . . . . . . . . . . . . . . . . . 31

6.4 Non-isothermal Room with Nozzle Type of Air Supply Devices . . . . . . 32Convergence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32Description of the Flow Field . . . . . . . . . . . . . . . . . . . . . . . . 33Comparison with the Measurements . . . . . . . . . . . . . . . . . . . . . 34

7 Fluent Results 35

7.1 Isothermal Room with Grille Type of Air Supply Devices . . . . . . . . . . 35Convergence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35Description of the Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

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Comparison with the Measurements . . . . . . . . . . . . . . . . . . . . 357.2 Non-isothermal Room with Grille Type of Air Supply Devices . . . . . . . 38

Convergence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38Description of the Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38Comparison with the Measurements . . . . . . . . . . . . . . . . . . . . . 38

7.3 Isothermal Room with Nozzle Type of Air Supply Devices . . . . . . . . . 41

Convergence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41Description of the Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41Comparison with the Measurements . . . . . . . . . . . . . . . . . . . . . 41

7.4 Non-isothermal Room with Nozzle Type of Air Supply Devices . . . . . . 44Convergence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44Description of the Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44Comparison with the Measurements . . . . . . . . . . . . . . . . . . . . . 44

8 Comparison of Global Results 48

Average Velocity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48Modified Average Velocity . . . . . . . . . . . . . . . . . . . . . . . . . . 48Corrected Average Velocity . . . . . . . . . . . . . . . . . . . . . . . . . . 49

Maximum Velocity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49Turbulence Intensity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49Temperature Deviation and Maximum Temperature Difference . . . . . . 50Heat Removal Efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

9 Conclusions 51

Bibliography 52

A The Velocity Graphs, FINFLO Results 53

B The Velocity Graphs, Fluent Results 60

C Modified Air Speed 66

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NOMENCLATURE

Jacobian matrix

in the -direction; cell face area

constant Courant number

pressure coefficient total internal energy flux vectors in the -, - and -directions Prandtl number source term vector Reynolds number vector of conservative variables speed of sound

specific heat at a constant pressure

specific heat at a constant volume

specific internal energy gravitational acceleration enthalpy turbulent kinetic energy

mass flow

pressure heat flux time

velocity components in the

-,

- and

-directions

friction velocity

velocity vector

dimensionless distance from the wall

artificial sound speed coefficient

Kroneckers delta dissipation of the kinetic energy of the turbulence dynamic viscosity kinematic viscosity scalar density shear stress

Superscripts

transposition left side

right side fluctuating component

Subscripts

turbulent -component normal component

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1 INTRODUCTION

One of the main purposes of room ventilation is to maintain an acceptable thermal com-fort, which means that the local values of temperature, air speed, turbulence and heat radi-ation must be governed. Computational Fluid Dynamics (CFD) is a promising method toquantitatively predict the room air motion and temperature distribution but it has not beenwidely used by ventilation engineers because special expertise, hardware and software arerequired. The accuracy of simulations is generally found to be sufficient for ventilationdesign purposes. The experience from past international comparisons [1, 2] suggests thatthe measured and computed results obtained by different research groups are fairly similarif the flow problem, including the boundary conditions, is well defined.

There are still modelling difficulties because the air flow pattern is usually very com-plicated since heat and momentum sources are distributed and usually time dependent.The supply air devices cannot be described in detail and, therefore, an integral part of aCFD simulation is to simplify the actual flow situation without losing essential features ofthe flow. This problem is also present in this study, where the supply air grille is a com-

plicated device and needs to be simplified. Another flow detail treated in the present studyis the wall boundary layer, which is often simplified by using the so-called wall functionseven if they are known to be deficient in describing the real flow and especially the heattransfer on the walls.

In this report the simulations using the commercial Fluent code [3] and wall func-tions represent the usual practice in ventilation design, whereas the simulations with theuniversity code FINFLO [4] represent a more scientific approach without using the wallfunctions. To be able to abandon the wall functions one must use a low-Reynolds numberturbulence model which in this case was the Chiens -model [5]. One must notethat it would also be possible to perform low-Reynolds number simulations down to thewall using the Fluent program, but this option was not used in the present study.

There is a lack of reliable room air flow measurement results, especially concerning

industrial halls. The small scale (3:10) measurements performed in connection with thisstudy made it possible to compare the simulations with a realistic flow in an industrial hall.However, it turned out to be difficult to make accurate comparisons because the comfortoriented, omnidirectional air speed measurements are not directly comparable with theair velocity computed with the turbulence models. One possibility is not to compare theactual velocities but to use artificial, modified velocities for comparison. This method hasbeen used in this study to show that especially in low speed areas the direct comparisonof measured and calculated speeds is not appropriate. Every time the modification is usedon velocity, it is clearly stated in a text.

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2 NUMERICAL METHOD

2.1 FINFLO

The next subsections describing the physical equations and their numerical solution methodare a modified version of documentation by Siikonen [6] and [4].

Flow Equations

The Reynolds-averaged Navier-Stokes equations, and the equations for the kinetic energy

and dissipation

of turbulence, and the scalar

transport equation can be writtenin the following form

(2.1)

where the unknows are

. The inviscid fluxes are

(2.2)

where is the density, the velocity vector by using cartesian components is

, is the pressure, is the turbulent kinetic energy and its dissipation, is any scalar,and the total internal energy

is defined as

(2.3)

where is the internal energy. The viscous fluxes are

(2.4)

Here the stress tensor,

, includes laminar and turbulent components. The fluid is

assumed to be Newtonian and therefore, the laminar stresses are modeled by using Stokeshypothesis. The Reynolds stresses

are included in the stress tensor

.

(2.5)

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For the Reynolds stresses Boussinesqs approximation

(2.6)

is utilised, where

is a turbulent viscosity coefficient, which is calculated by using a

turbulence model, and

is Kroneckers delta. In the momentum and energy equations,the kinetic energy contribution

has been connected with pressure and appearsin the convective fluxes, whereas the diffusive part is connected with the viscous fluxes.Thus the viscous stresses contain laminar and turbulent parts. Respectively, the heat fluxcan be written

(2.7)

where is a molecular and

a turbulent thermal conductivity coefficient and is alaminar and

a turbulent Prandtl number, respectively, and

is a specific heat atconstant pressure. The diffusion of turbulence variables is modelled as

(2.8)

(2.9)

where

and

are turbulent Schmidts numbers of and , respectively. The pressureis calculated from an equation of state , which, for a perfect gas, is written

-

- (2.10)

where - is the ratio of specific heats

.The components of the source term are non-zero in buoyance terms and in turbu-

lence model equations. The buoyance terms are

(2.11)

where

is the reference density and is gravitational acceleration.In this study the third order upwind biased difference scheme was used to approximate

convective fluxes.

Turbulence Modelling

As mentioned, the turbulent stresses stemming from the Reynolds averaging of the mo-

mentum equation are modelled by using Boussinesqs approximation (2.6). The turbu-lent viscosity coefficient

is determined by using Chiens [5] low-Reynolds number model from the formula

(2.12)

where

is an empirical coefficient. The source term of Chiens model is

(2.13)

where is the normal distance from the wall, and the dimensionless distance

isdefined by

(2.14)

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Here

is friction velocity and

is friction on the wall, and the connection betweenthem is

. The unknown production of turbulent kinetic energy is modelledusing Boussinesqs approximation (2.6)

(2.15)

The turbulence model presented above contains empirical coefficients. They are givenby [4]

(2.16)

where the turbulence Reynoldss number is defined as

(2.17)

2.2 Pseudo-compressibility Method

In FINFLO the pseudo-compressibility method has been used for incompressible andnearly incompressible flows. Then the compressible code can be used. The pseudo-compressibility method was presented in 1967 by Chorin and it is presented in reference[7].

The mass continuity equation is used with compressible flows:

(2.18)

Density is solved from equation (2.18) and the pressure from the equation of the statefor an ideal gas . If the changes in density are small, the pressure is determinedwith a poor accuracy. The idea of the pseudo-compressibility method is to change theequation of continuity so that instead of density the pressure is solved and the density isdetermined by the pressure.

In the original pseudo-compressibility method the time derivative is added to the equa-tion of continuity.

(2.19)

where

is the coefficent from which the virtual speed of sound

isdetermined. The virtual speed of sound is thus smaller than the actual speed of sound.Then the pressure can be integrated with the velocities of the momentum equation. This

can be done to steady state flow, because in that case the time derivate is dropped out andthe incompressible flow equations becomes the solution. A time-accurate case is solved byadding the time derivate as a source term and pseudointegrating inside the time step [8].Then the virtual speed of sound does not depend on local flow velocity. By using a smallerspeed of sound than actual, the artificial compression is caused to the flow to achieve aconvergated result. In FINFLO there are differences from Chorins method; the density isstill a variable. The solution method of FINFLO is described in more detail in reference[9].

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2.3 FLUENT

The incompressible form of the commercial Fluent 4.47 computer code was used. Theflow equations themselves are very similar to the FINFLO equations presented above.Therefore only the differences are mentioned in this chapter.

The source terms for the formal unknowns

where is enthalpy, are

(2.20)

where the buoyancy production term

is

(2.21)

Boussinesqs model for the density is used, which treats density as a constant value inall the equations, except for the buoyancy source terms in the momentum and turbulenceequations, where it is calculated as

(2.22)

is temperature in Kelvins and the constant density is

= 1.2 kg/m .The high-Reynolds number model is used with st andard coefficients recommen-

ded by Launder and Spalding [10] that were also used in FINFLO simulations as the highReynolds number limit, see equation 2.16. On the walls, logarithmic wall functions [10]were applied.

A second-order upwind difference scheme was used to approximate all the convectivefluxes, including the turbulence variables.

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3 INVESTIGATED CASES

3.1 Equipment

Room Ventilation Simulator

The experiments were conducted in the room ventilation simulator at the University ofIllinois at Urbana-Champaign [11]. The room ventilation simulator consists of an ad-justable inner test room and an outer room for controlling the ambient environmentalconditions of the inner test room. During the experiments the inner test room was set at7.2 m

3.6 m

2.4 m to model a ventilated full scale room and the structures at 3:10

scale. An independent HVAC system provides a constantly conditioned supply air for theinner test room.

Experimental Room Layout

The experiments were made in an empty and obstructed room. In the obstructed room

the tests were made with and without a cooling load. The obstruction ratios were 30%of the room area and 30% of the room height. The obstructed room layout is shown inFigure 3.1.

Fig. 3.1: Experimental room layout.

The walls of the experimental room were insulated. The inner surface was madeof plywood that was painted black. Sheet metal boxes were used as obstructions in theexperiments. Light bulbs inside the obstructions were used to create the cooling load.The accuracy of power supply was

2%, depending on the network voltage. The actual

power usage and obstruction surface temperature was monitored during each experiment.

Measurement and Control Systems and Equipment

Supply and exhaust volume flow rates were controlled using transformers connected toeach fan. The volume flow rates of individual supply openings were adjusted using factory-made measurement and adjustment units (accuracy 5%) connected to the ductwork.Exhaust air flow was adjusted to keep the pressure difference zero between the inner andouter rooms. A temperature controller was utilized to keep the supply temperature at theset point during the test. A data acquisition system with T-type thermocouples was used tomonitor air temperatures in supply, exhaust, test room (10 points) and outer room.

Omnidirectional Thermistor Anemometer

The instrumentation for measuring air temperature and velocity was developed at the Hel-sinki University of Technology. It consists of an anemometer, omnidirectional thermistor

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probes, four rods and a measurement card in a PC-computer. The system is described indetail by Kovanen [12]. The anemometer is of a constant temperature type. The inaccur-acy of it is estimated to be

(0.03 + 0.03v) m/s, when the air velocity, v, is between 0.05

m/s and 1.0 m/s. The temperature of the probe during the velocity measurement is 55 C.The time constant of the system depends on the velocity region. With the step change0.0 - 0.1 m/s the time constant is 0.82 s, whereas with the step change 0.1 - 0.2 m/s the

time constant is 0.37 s. The probe (thermistor YSI 44002A) is designed so that the outputvoltage is almost independent of the direction of air movement: the inaccuracy is about

3 %.Altogether 30 thermistor probes were positioned in the occupied zone. The set up

was created in such a way that it was possible to change thermistor height from outsidethe test room without interfering with the measurements. During each test altogether90 measurements were made in thirty locations and at three different heights, 45 mm,330 mm and 520mm. The locations of the measurement points are shown in Figure 3.1.Sampling interval 0.2 s and integration time 60 s were used in these measurements. Theintegration time was chosen to minimise the duration of the test period. In this way theduration of one measuring cycle was two hours. The influence of the integration time wasstudied prior to actual measurements and no influence on the measurement results was

found when the integration time was reduced from 180 s to 60 s.

3.2 Experimental Procedure

The occupied zone velocity and temperature conditions were studied in the room withobstructions in isothermal and nonisothermal conditions. The occupied zone in the ex-periments reached up to 540 mm from the floor. The experiments were done in steadystate conditions.

Air Supply Methods

Two different air supply methods were studied in both physical and computational exper-iments :

1. Horizontal, concentrated, air supply with the occupied zone ventilated by reverseflow (from now on referred to as NOZZLE). The air was supplied from 2 nozzles hori-zontally from the left wall to the upper room level at 2.1 m height. The outlet diameter ofthe nozzles was 78 mm and the initial air velocity 10.7 m/s.

2. Horizontal air supply with the occupied zone ventilated directly by the jet (fromnow on referred to as GRILLE). The air was supplied from 3 grilles horizontally from thefront wall at 1.2 m height. The outlet size of the grille was 102 mm 114 mm and theinitial air velocity was 2.3m/s. The vertical vanes of the grille were adjusted at a 90 anglein order to create greater expansion of the jet in the horizontal direction. Positioning ofair supply inlets in the experimental room is shown in Figure 3.2.

Air Change Rate and Cooling Load

Used air flow rates, electric power supply to the heat source and measured temperaturedifference between supply and exhaust air are presented in Table 3.1 (Corresponding val-ues for full-scale room are 2 1/h and 50 W/m2).

Table 3.1: Used air flow rates, electric power supply of the heat source and measured temperature differencebetween supply and exhaust air.

SUPPLY CASE

METHOD [m /s] [kW] [ C] [ C]NOZZLE Isothermal 0.102 0 0.1

Nonisothermal 0.102 3 20.1 4.5GRILLE Isothermal 0.081 0 0.2

Nonisothermal 0.081 1.5 12.3 11

where

= air flow rate,

= electric power supply to the heat source,

= measuredtemperature difference between supply and exhaust air and

= supply air temperature.

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Fig. 3.2: Positioning of air supply inlets and outlets in the experimental room

3.3 Characterisation of the Air Supply Devices

The air supply devices were characterised by measuring velocity and temperature decayalong the jet axis and velocity profiles at one meter distance from the outlet. Jet measure-ments were made in the experimental room. Each diffuser was located in the middle ofthe short west wall at 0.3 m distance from the wall in the same way they were used during

experiments.A Tri-Sense Model #37000-00 instrument was used in the measurements . The air

velocity probe 37000-60 had an accuracy of 3% of the reading or 0.1m/s. The twotemperature sensors were J-type thermocouples with an accuracy of 0.4 C. Checkedconsistency between temperature sensors was 0.1 C.

Velocity Decay and Temperature Coefficients

Measured velocity decay (

) and temperature (

)coefficients for both supply air devices are presented in Table 3.2.

Table 3.2: Velocity decay (

) and temperature (

) coefficients of the supply air devices.

Supply Device

Nozzle 6.3 6.0Grille 2.1 2.0

Velocity profiles for nozzle and grille were measured using 10 m/s and 9 m/s initial

velocities, respectively. Profiles were measured at 1 m distance from the diffuser. Jetprofiles of nozzle followed exactly the theoretical Gauss error function curve. The grilletype used created a highly diverging jet with a 90 degree horizontal expansion angle. Thejet was expanded also in the vertical direction, but much less than horizontally. Jet profilesfor the grille are presented in Figure 3.3.

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Fig. 3.3: Measured horizontal and vertical velocity profiles for the jet at 1 meter distance from the grille. Thelines are data fitted polynomes.

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4 BOUNDARY CONDITIONS FOR CFD SIMULATIONS

4.1 Air Supply Device

Inlet Boundary Conditions of the Grille Case

Inlet boundary conditions were generated by calculating an empty room with a singlesupply air device. The results were compared with measured profiles at 1 m in front of thegrille and with the velocity decay coefficient

. The grille was modelled in CFD with

control volumes. In the vertical direction the uniform velocity distribution was used.The kinetic energy of turbulence and turbulent kinematic viscosity were adjusted in orderto get the correct profile and maximum velocities of the jet.

The air velocities near the grille were measured with a Laser-Doppler-Anemometer(LDA) in order to set the boundary conditions at the inlet. Figure 4.1 describes the meas-urement setup. The air flow through the grille was set to 27 l/s, which was also the flowrate in the experimental room. The angular speed of the fan was adjusted to maintaincorrect volume flow. The grille was installed at the end of the rectangular duct, which

was 2 m long. Velocity components were measured about 20 mm in front of the grillefrom 66 points over the center line and 15, 30 and 40 mm from the center line in both dir-ections, respectively. The flow was marked with vegetable oil. Small oil drops generatedwith compressed air were injected into the inlet of the fan.

30 Hz

Fan Electric

motor

Grill

Ventilationoutlet

Particle

generator

Compressedair

AC drive

Fig. 4.1: Measurement setup for the grille boundary conditions.

Aerometrics two-dimensional LDA was used in the measurements. Altogether 1000samples were t aken at each measurement point. This is a sufficient amount for velocitymeasurement. Figure 4.2 shows the air supply device, measured velocity vectors and velo-city vectors used as a boundary condition.

The velocities measured with the LDA were averaged in order to get a uniform dis-tribution in the vertical direction. From Figure 4.2 it can be seen that there are threeseparated jets coming out of the grille. The jet in the middle is very strong but narrow.In a FINFLO test calculation the jet in the middle caused two other jets to unite into amiddle jet. The measured profile (Fig. 3.3), however, shows that the real jet profile hastwo local maximums. In order to get a similar flow pattern in the calculation the average

value of the velocities was taken over the area of four rows of inlet cells in the middle.In isothermal CFD simulation the flow rate was 23.8 l/s, which was less than in the

measurements (27 l/s). The intensity of turbulence was 10 %, and the ratio betweenturbulent and physical viscosity was 100. In non-isothermal simulation the flow rate was27 l/s, which was also used in the measurements. The intensity of the turbulence was 20

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Fig. 4.2: Velocity vectors used as a boundary condition (top), velocity vectors measured with LDA (middle) andthe air supply device (bottom).

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% in the middle of the grille and 10 % in the two rows on both sides. The ratio betweenturbulent and physical viscosity was 100 in the middle and 10 000 on the sides.

It was found that these two boundary conditions produced almost similar jet profiles,see Figure 4.3. Therefore both boundary conditions were regarded as acceptable in thesimulations.

The profiles of the jet 1 m after the supply device are shown in Figure 4.3. The

velocity profile computed with the Fluent code in Figure 4.3 was obtained by fine tuningthe velocity and turbulence boundary conditions in order to get the correct velocity profile.These boundary conditions were also tested in FINFLO but they did not lead to similarresults. Finally it was agreed to use the boundary conditions described above in bothFINFLO and Fluent room air flow simulations. The same boundary conditions wereused in order to make the results comparable.

Fig. 4.3: Half of the velocity profiles of the calculated jet and measured profile.

Inlet Boundary Conditions of the Nozzle Case

The velocity profile in the round nozzle was modelled as a simple plug flow. The intensityof turbulence was 4 % and the ratio of turbulent and molecular viscosity was 100.

4.2 Thermal Boundary Conditions

The experimental room was thermally isolated from its surroundings to keep the conduc-tion heat flow from the room low. In addition the room was located inside another roomwhich was held at the same temperature as the test room. The room heat balance revealsthat some conduction or infiltration heat transfer has still taken place. The measuredcooling effect of the ventilation air flow was in the nozzle case 85 % of the total electricpower supply input and in the grille case 86 %.

The total heat flow from the rectangular obstructions on the floor was known fromthe experiments, see Table 3.1. But what was not known was the distribution betweenthe radiation and convection heat fluxes. Initial simulations using the discrete transferradiation model available in Fluent showed that the radiation part constitutes about 28%of the total heat flux from the obstacles. In these simulations the surface temperature ofthe obstacles was set to 30.2 C according to the measurements. The emissivity of theobstacles was 0.3 (galvanised steel sheet) and of the room walls 0.87 (plywood).

In the final simulations the constant heat flux boundary condition was used becausethis option was available in both computing codes. The radiation part was computed with

a simple spreadsheet model where the radiation heat flux from the obstacles was assumedto be 28 % of the total heat flux, based on earlier Fluent simulations. This radiation heatflux was distributed over the constant convective heat flux patches on the room walls usingthe view factor method and assuming no reflection. The heat fluxes on the patches areshown in Figures 4.4 and 4.5.

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7.38 7.38

3.98

3.98

2.26

4.18

5.12

1.96

3.61

4.83

1.85

3.49

4.66

2.20

2.35

3.47

1.53

3.34

3.473.47 0.72 m

0.84 m

0.84 m

Fig. 4.4: Heat fluxes (W/m ) on the boundary condition patches in the grille case. The heat flux on the ceilingwas 3.00 W/m and on the obstacles 64.86 W/m2.

9.97 9.97

5.38

5.38

3.05

5.65

6.92

2.64

4.88

6.52

2.50

4.72

6.30

2.97

3.18

4.69

2.07

4.51

4.694.69 0.72 m

0.84 m

0.84 m

Fig. 4.5: Heat fluxes (W/m ) on the boundary condition patches in the nozzle case. The heat flux on the ceilingwas 4.05 W/m and on the obstacles 95.12 W/m .

4.3 Wall Boundary Conditions

The basic difference between the two simulations was that in the Fluent simulations theconventional wall functions were used to describe the flow near the walls, whereas in theFINFLO simulations the computations were performed down to the wall. To be able to

abandon the wall functions one must use a very dense grid near the surfaces. This meansthat one must concentrate a large part of the computational cells near the boundaries. Thisprocedure has so far been regarded as too heavy for most practical ventilation simulations.

Because the geometry was symmetrical in all cases the symmetry boundary conditionwas utilised to reduce the number of computational cells.

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5 COMPUTATIONAL GRID

5.1 FINFLO

Both grids are build with several blocks in order to reduce the number of the grid cells.The space near the walls was covered with 200 mm thick blocks which are connected toothers with block faces at a angle to the wall. In that way the dense grid distributionneeded near the walls will not affect distribution along the walls.

In both cases the cell next to the wall was 0.5 mm. The dimensionless distance

defined in equation (2.14) was around 1 in all the walls. The number of grid points was1 394 112 in the grille case and 1 370 496 in the nozzle case.

Figure 5.1 shows the computational grid of the grilles case and Figure 5.2 the nozzlecase.

41

23

68

9

10

11

12

13

24

18

17

16

15

20 21

2223

25

x

y

z

Fig. 5.1: Computational grid and the calculation blocks of the room with grilles . Plane is the symmetryplane. Part of the blocks are removed to help visualisation.

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27

y

x

z

2829

26

24

1

24

3

5

6

8

9

10

11

13

14

15

16

17

18

Fig. 5.2: Computational grid and the calculation blocks of the room with nozzles. Plane

is the symmetryplane. Part of the blocks are removed to help visualisation.

5.2 FLUENT

A simple Cartesian grid was a natural choice because the computational domain is simple,see Figures 5.3 and 5.4. The disadvantage of the Cartesian grid is that the concentrationsof grid points near the supply air devices and near the walls create unnecessarily small gridspacing in other parts of the domain. The number of grid points was 585 200 in the grillecase and 575 824 in the nozzle case. The simulations were done first for coarser grids of

78 624 and 77 700 points to get an initial guess for the final doubled grid.To be able to use the logarithmic wall functions correctly the nondimensional distance

values near the walls should be more than about 30. This principle leads to very thicknear wall cells at low room air velocities. At a typical velocity of 0.1 m/s the cell thicknessneeds to be more than 120 mm [13]. This would mean poor resolution near the walls forother type of flows except fully developed boundary layers. Therefore the first cell distancewas chosen to be 20 mm leading to the , which is preferred for room heat transfercomputations in [14]. This arbitrary choice inherently includes an assumption that theaccurate wall friction computation is not crucial for the room air flow.

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Fig. 5.3: The Cartesian grid of the grille case used in Fluent. Only half of the room is shown because ofsymmetry.

Fig. 5.4: The Cartesian grid of the nozzle case used in Fluent. Only half of the room is shown because ofsymmetry.

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6 FINFLO RESULTS

6.1 Isothermal Room with Grille Type of Air Supply Devices

Convergence

The calculation converged within 12 000 calculation cycles. The calculation took 8 dayswith a Silicon Graphics Origin 2000 computer using two processors. The

-norm of themomentum and mass residuals (Fig. 6.1 and 6.2) was already converged within 2 000cycles. The kinetic energy of turbulence (Fig. 6.3) was not fully converged within 12 000cycles and from the curve it can be seen that it would take nearly 30 000 cycles before itwould be fully converged.

Fig. 6.1: L

-norm of the mass residual.

Fig. 6.2: L

-norm of the momentum residual in

-direction.

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Fig. 6.3: Convergence of the turbulent kinetic energy.

Description of the Flow Field

The supply air devices are located in the front wall at the half room height. The twooutlets are on the roof above the obstructions (Fig. 3.2). The supply air spreads stronglynear the grille. That is obvious considering the setting of the grille blades. The supplyair flow has two local maximum velocities until the flow impinges on the back wall anabout the height of the grilles. The flow returns above and below the original jet back tothe front wall. The places where the jets impinges on area where the jet from the grille ismixing with the return flow.

Fig. 6.4: Momentum on the symmetry plane and 5 cm from the floor and the back wall, isothermal.

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Fig. 6.5: Momentum magnitude at 1.2 m from the floor.

Comparison with the Measurements

The results are compared with the measurements in Appendix A, Figs. A.1-A.5. Themeasured velocities on both sides of the symmetry plane are shown in the figures. In thefirst three figures the measurements and computations are compared in the direction ofthe jet in the return flow. In the two other graphs (Figs. A.4 and A.5) the results are

plotted normal to the jets. Calculation underpredicts the velocity near the front and backwall and over-predicts in the middle of the room. The velocities in the room are extremelylow, which means that the accuracy of the velocity measurement is low. Therefore theresults are considered to be acceptable.

6.2 Non-isothermal Room with Grille Type of Air Supply Devices

Convergence

The convergence of the simulation is very slow. The number of iteration cycles neededwas 38 000. The average temperature in the room rose slowly due to the slow air speed.On the second grid level 100 000 cycles were needed before the heat balance was found.The L

-norm of the mass residual (Fig. 6.6) and the L

-norm of -direction momentum

(Fig. 6.7) still oscillate with a quite big amplitude. The average temperature (Fig. 6.8)and the total mass (Fig. 6.9) converge well. Change is just decreasing oscillations at theend. The difference between the in- and outcoming mass fluxes is 1.1 %. The kineticenergy of turbulence (Fig. 6.10) converged faster than the other monitored quantities andwas fully converged after about 30 000 cycles.

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Fig. 6.6: L

-norm of mass residual .

Fig. 6.7: L

-norm of the

-wise momentum residual

Fig. 6.8: Convergence of the spatial average temperature.

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Fig. 6.9: Convergence of the total mass.

Fig. 6.10: Convergence of the total turbulent kinetic energy.


This case is the same as the previous one except that there is heat flux from surfaces. Thesupply air is colder and thus denser than air in the room. The gravity bends the flowtowards the floor so that the jet impinges on the floor instead of the back wall. The area

where the flow hits the floor is about 1.5 m from the front wall. The jet is landing partlyon the obstructions. The bending of the jets and spreading into two maximum values canbe seen in Figure 6.11, where the momentum isosurfaces

are shown.Velocity vectors in the symmetry plane and planes 5 cm from the back wall and the floorare shown in Figure 6.12. The corresponding momentum distribution is shown in Figure6.13. After inpinging on the floor, part of the jet flows to the back wall and part of it returnsto the front wall. The flow that returns to the front wall flows, in the case of the middlejet, between the wall and obstruction and engages with the flow caused by the other inlet.In the case of the other jet the flow goes up from the corner of the room. Figure 6.14shows the temperature distribution in the room. The temperature level is 1 K lower thanin the measurements but otherwise quite similar. The turbulent kinetic energy (Fig. 6.15)is largest in the upper parts of the room. From Figure 6.16 the deflection and spreadingof the jet as well as flows driven by the heat sources can be seen.

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Fig. 6.11: The momentum isosurface

of the grilles case.

Fig. 6.12: Velocity vectors at a distance of 5 cm from the walls and on the symmetry plane.

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Fig. 6.13: Momentum at a distance of 5 cm from the walls and on the symmetry plane.

Fig. 6.14: Temperature at a distance of 5 cm from the walls and on the symmetry plane.

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Fig. 6.15: Ratio of turbulent and molecular viscocity at a distance of 5 cm from the walls and on the symmetryplane.

Fig. 6.16: Momentum on the plane 1 m from the floor

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A comparison with the measured velocities is shown in Appendix A (Figs. A.6-A.10). In thefirst three figures the measurements and computations are compared along the returningjet stream and in the last two normal to the jet. Calculation predicts the flow field betterthan in the isothermal case. At some points calculation predicts flow field well. As a wholethe calculations predict the flowfield quite well. The agreement is good near the front and

back wall.

6.3 Isothermal Room with Nozzle Type of Air Supply Devices

Convergence

The L

-norm of the mass residual (Fig. 6.17) is well converged in 8000 cycles and theL

-norm of the -wise momentum residual (Fig. 6.18) is still going slightly down. Thetotal mass (Fig. 6.19) seems to be climbing but the real change is small. The kineticenergy of turbulence (Fig. 6.20) is fully converged. The changes in convergence historiesare so small that if time had been allowed for convergence of all the values the benefitwould probably have been small compared with the time used. A Silicon Graphics Origin2000 computer was used in the calculation. The calculation time using two processors

was about the same as in the isothermal grille case.

Fig. 6.17: L

-norm of density residual.

Fig. 6.18: L

-norm of the -wise momentum residual.

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Fig. 6.19: Convergence of the total mass.



The supply air nozzles are on the left wall (see Fig. 3.2) and the outlets are located on theceiling above the obstruction in the middle of the room. The air flows from the nozzleto the opposite wall and then turns down and returns along space between wall and theobstructions. The stagnation point can be seen from velocity vectors in Figure 6.21. Themomentum distribution is shown in Figure 6.22. The jet is attached slightly to the ceiling.Between the obstructions the flow velocity is slow, mostly turbulent fluctuation. A wholeroom circulation is formed over the obstructions. The maximum velocity of 0.445 m/s inthe occupied zone is about 0.2 m from the floor and about 1.8 m from the left wall and0.07 m from the front wall. The location is slightly away from the measurement points, sothe calculated maximum velocity in chapter 8 is significantly lower. Turbulent viscosityvalues (Fig. 6.23) are largest inside the circulation mentioned above.

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Fig. 6.21: Velocity vectors at a distance of 5 cm from surfaces and on the symmetry plane, isothermal case.

Fig. 6.22: Momentun isosurfaces in planes at a distance of 5 cm from the walls and on the symmetry plane andplanes between the obstructions, isothermal case.

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Fig. 6.23: Ratio of turbulent viscosity and viscosity isosurface, isothermal case.


The results are compared with the measurements in Appendix A (Figs. A.11-A.16). Inthe first three figures the measurements and computations are compared in lines from theleft to the right wall. In the first figure the velocity is well predicted. The velocities areslightly higher near the front wall and lower near the back wall. Between the obstructions

(Figs. A.12 and A.13) the prediction of the velocity is poor. In the last three figures themeasured and computed velocities are modified to correspond to each other, as explainedin Appendix C. The turbulent intensity is high between the obstructions and the modifiedvelocities predict velocities more accurately (Figs. A.15 and A.16).

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6.4 Non-isothermal Room with Nozzle Type of Air Supply Devices

Convergence

The L

-norm of the mass residual is well converged after 10 000 cycles and the L

-normof the -wise momentum residual is converged after 15 000 cycles. The kinetic energy ofturbulence is fully converged. The Cray T3E supercomputer at the Center for Scientific

Computing (CSC) was used in this calculation. Using 32 processors the total time usedfor the calculation was about 5 days.

Fig. 6.24: L

-norm of mass residual.

Fig. 6.25: L

-norm of the

-wise momentum residual.


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Velocity vectors on a symmetry plane and on the planes at a distance of 5 cm from theback wall and the floor are shown in Figure 6.27. The momentum distribution is shownin Figure 6.28. The air from the nozzle flows almost directly to the opposite wall. Nearthe right wall the flow bends slightly downwards and towards the front wall. Then the airflows both along the corridor formed by the front wall and obstructions and between the

last two obstructions. The flow velocities between the obstructions are slightly higher thanin the isothermal case. The maximum velocity in the occupied zone is 0.514 m/s. It islocated 3 m from the left wall, 0.1 m from the front wall and 5 cm from the wall. As inthe isothermal case the maximum velocity is significantly higher than the one taken fromthe measurement point in Chapter 8. The temperature (Fig. 6.29) is lowest in the jet andnear the right wall.


Fig. 6.28: Momentun isosurfaces in planes at a distance of 5 cm from the walls and on the symmetry plane andplanes between the obstructions.

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Fig. 6.29: Temperature planes.


The results are compared to the measurements in Appendix A (Figs. A.17-A.19). In thiscase all the figures are along the jet direction. The first figure (Fig. A.17) is from thecorridor between the front wall and obstructions. The velocity is well predicted. Thevelocities are slightly higher near the front wall and lower near the back wall than the

measurements. Between the obstructions the agreement with the measured velocities ispoor (Figs. A.18 and A.19).

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7 FLUENT RESULTS

7.1 Isothermal Room with Grille Type of Air Supply Devices

Convergence

The Fluent manual states that a solution is generally well converged when the normalisedresiduals are of the order of . The residuals for the last 1000 iterations are shownin Figure 7.1. In addition to the residual check the flow field was also examined duringthe iteration to make sure that it remained constant.

- Dissipation

- W Velocity

- V Velocity

- U Velocity

- Pressure

500040003000200010000

1.000E+00

1.000E-01

1.000E-02

1.000E-03

1.000E-04

Iterations

- Turb Energy

Fig. 7.1: Normalized residuals showing the convergence history during the last 1000 iterations.

Description of the Flow

The qualitative flow field is quite similar to the flow field obtained by the FINFLO codebut there are small differences. The vector plot in Figure 7.2 shows that the supply air jetscreate two stagnation regions on the opposite wall, whereas in the FINFLO simulationsthree stagnation regions can be discerned (Fig. ??). It seems like the two jets combine intoa bigger jet (see also Figure 7.4). This may cause small differences in the return flow nearthe floor where the maximum velocities are found to be closer to the obstacles (Figure7.3) than in the FINFLO simulations (Figure 6.4).


The comparison with the measurements is shown in Appendix B. The first three figuresshow the velocities in the return flow between the obstacles and the last two figures nearthe front and back walls. The computed velocities are generally higher than the measuredones. The velocities in the plane at 0.9 m from to the side wall (Figure B.3) are smallerthan in the other two planes. This has apparently something to do with the way the jetscombine before they hit the back wall, because in the FINFLO simulations the results(Figures A.1- A.3) in the three measuring planes seem to be similar and, therefore, theflows of the three branches of the supply air jets are independent of each other. Themeasurements seem to support slightly smaller velocities in the back flow near the sidewall.

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3.37E-05

2.43E-04

4.53E-04

6.63E-04

8.73E-04

1.08E-03

1.29E-031.50E-03

1.71E-03

1.92E-03

2.13E-03

2.34E-03

2.55E-03

2.76E-03

2.97E-03

3.18E-03

3.39E-03

3.60E-03

3.81E-03

4.02E-03

4.23E-03

4.44E-03

4.65E-03

4.86E-03

5.07E-03

5.28E-03

5.49E-03

5.70E-03

5.91E-03

6.12E-03


1.00E-01

2.00E-01

3.00E-01

4.00E-01

5.00E-01

6.00E-01

7.00E-01

8.00E-01

9.00E-01

1.00E+00

Fig. 7.3: Velocity magnitude at a distance of 5 cm from the walls and on the symmetry plane. The velocity rangeis from 0.1 m/s to 1.0 m/s with an interval of 0.1 m/s.

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1.00E-01

2.00E-01

3.00E-01

4.00E-01

5.00E-01

6.00E-01

7.00E-01

8.00E-01

9.00E-01

1.00E+00

Fig. 7.4: Velocity magnitude at a distance of 1.2 m from the floor.

1

10

50

100

200

400

600

Fig. 7.5: Effective viscosity divided by molecular viscosity at a distance of 5 cm from the walls and on thesymmetry plane. The range is from 1 to 600 with variable intervals.

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7.2 Non-isothermal Room with Grille Type of Air Supply Devices

Convergence

The residuals for the last 1000 iterations are shown in Figure 7.6. The flow field was alsochecked during the iteration. Also the extract air temperature was monitored to make surethat the heat balance was achieved.

Enthalpy

Turb Energy

W Velocity

V Velocity

U Velocity

Pressure

40003000200010000

1.000E+00

1.000E-01

1.000E-02

1.000E-03

1.000E-04

1.000E-05

1.000E-06

Iterations

Dissipation



The cold supply air jet deflects downwards because of buoyancy and hits the floor nearthe middle of the room (see Figure 7.7), further away than in the FINFLO simulations. Alarge part of the supply air jet seems to drop between the obstacles and only a minor parton the upper surface of the obstacles. This makes the flow quite different from the flowfield obtained in the FINFLO simulations.


The comparison with the measured velocities is shown in Appendix B, Figures B6-B10.The simulated velocities in the first three Figures B.6- B.8 look very much the same. Allthese three planes are in the same position relative to the supply air jet. It seems that theflow of the different branches of the jet behave quite independently. This does not happenin the FINFLO simulations, where all three planes have different results. It is interesting

to note that the same phenomenon was found also in the isothermal simulations, but nowthe computing codes have changed places with each other in this respect.

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2.82E+02

2.82E+02

2.83E+02

2.83E+02

2.84E+02

2.84E+02

2.85E+022.86E+02

2.86E+02

2.87E+02

2.87E+02

2.88E+02

2.89E+02

2.89E+02

2.90E+02

2.90E+02

2.91E+02

2.92E+02

2.92E+02

2.93E+02

2.93E+02

2.94E+02

2.95E+02

2.95E+02

2.96E+02

2.96E+02

2.97E+02

2.97E+02

2.98E+02

2.99E+02


1.00E-01

2.00E-01

3.00E-01

4.00E-01

5.00E-01

6.00E-01

7.00E-01

8.00E-01

9.00E-01

1.00E+00

Fig. 7.8: Velocity magnitude at a distance of 5 cm from the walls and on the symmetry plane. The velocity rangeis from 0.1 m/s to 1.0 m/s with an interval of 0.1 m/s.

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2.92E+02

2.93E+02

2.94E+02

2.95E+02

2.96E+02

2.97E+02

Fig. 7.9: Temperature at a distance of 5 cm from the walls and on the symmetry plane. The temperature rangeis from 292 to 297 K with an interval of 11 K.

1

10

50

100

200

400

600

Fig. 7.10: Effective viscosity divided by molecular viscosity at a distance of 5 cm from the walls and on thesymmetry plane. The range is from 1 to 600 with variable intervals.

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7.3 Isothermal Room with Nozzle Type of Air Supply Devices

Convergence

The residuals for the last 1000 iterations are shown in Figure 7.11. The pressure residualsettles finally to at higher level of than desirable, but the flow pattern did not showany sign of changes.

Dissipation

W Velocity

V Velocity

U Velocity

Pressure

2000150010005000

1.000E+00

1.000E-01

1.000E-02

1.000E-03

1.000E-04

1.000E-05

Iterations

Turb Energy



The qualitative flow field (Figure 7.12) is quite similar to that in the FINFLO simulations(Figure 6.21). The supply air jet hits the right wall and deflects from the stagnation pointto the rest of the room. The main stream of the back flow can be found near the front walljust above the floor. The flow between the obstacles remains slow.


The comparison with the measured velocities is shown in appendix B, Figures B11-B13.The velocity in the main flow near the front wall is slightly overpredicted except near theright wall, where the measured velocities are higher than the simulated ones.

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4.81E-05

1.31E-03

2.57E-03

3.83E-03

5.09E-03

6.35E-03

7.61E-038.87E-03

1.01E-02

1.14E-02

1.26E-02

1.39E-02

1.52E-02

1.64E-02

1.77E-02

1.89E-02

2.02E-02

2.15E-02

2.27E-02

2.40E-02

2.52E-02

2.65E-02

2.78E-02

2.90E-02

3.03E-02

3.15E-02

3.28E-02

3.41E-02

3.53E-02

3.66E-02


1.00E-01

2.00E-01

3.00E-01

4.00E-01

5.00E-01

6.00E-01

7.00E-01

8.00E-01

9.00E-01

1.00E+00

Fig. 7.13: Velocity magnitude at a distance of 5 cm from the walls and on the symmetry plane. The velocityrange is from 0.1 m/s to 1.0 m/s with an interval of 0.1 m/s.

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1.00E-01

2.00E-01

3.00E-01

4.00E-01

5.00E-01

6.00E-01

7.00E-01

8.00E-01

9.00E-01

1.00E+00

Fig. 7.14: Velocity magnitude on planes between the obstructions. The velocity range is from 0.1 m/s to 1.0 m/swith an interval of 0.1 m/s.

1.80E-05

4.52E-03

9.01E-03

1.35E-02

1.80E-02

2.25E-02

2.70E-02

3.15E-02

3.60E-02

Fig. 7.15: Effective viscosity divided by molecular viscosity on planes between the obstructions. The range is

from 1 to 600 with variable intervals.

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7.4 Non-isothermal Room with Nozzle Type of Air Supply Devices

Convergence

The residuals for the last 1000 iterations are shown in Figure 7.16. The flow field was alsochecked during the iteration. Also the extract air temperature was monitored to make surethat the heat balance was achieved.

Enthalpy

Turb Energy

W Velocity

V Velocity

U Velocity

Pressure

6000400020000

1.000E+00

1.000E-01

1.000E-02

1.000E-03

1.000E-04

1.000E-05

1.000E-06

Iterations

Dissipation



The main difference compared with the isothermal case is that the jet is not hitting theright wall but is deflected towards the symmetry plane between the last two obstacles (Fig.7.17). It seems like the warm convective air flow from the rightmost obstacle hits theceiling and it is strong enough to turn the supply air jet leftwards. The behaviour of thetail of the jet is very different from the FINFLO simulations, where the jet hits the backwall in the right corner (Figure 6.27). The difference between the two simulations can beunderstood by the sensitive and unstable nature of the flow in the later stages of the jet,where buoyancy forces and inertia forces are of the same magnitude.


The measured velocities in Appendix B, Figures B14-B16, do not differ much from thevelocities of the isothermal case. The simulated velocities are again in the same range

but the simulated velocities have their maximum in the left part of the room whereas themeasured velocities are highest in the right part of the room.

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5.13E-05

1.41E-03

2.77E-03

4.12E-03

5.48E-03

6.84E-03

8.20E-039.56E-03

1.09E-02

1.23E-02

1.36E-02

1.50E-02

1.63E-02

1.77E-02

1.91E-02

2.04E-02

2.18E-02

2.31E-02

2.45E-02

2.58E-02

2.72E-02

2.86E-02

2.99E-02

3.13E-02

3.26E-02

3.40E-02

3.54E-02

3.67E-02

3.81E-02

3.94E-02

Fig. 7.17: Velocity vectors at 5 cm from the walls and on the symmetry plane.

1.00E-01

2.00E-01

3.00E-01

4.00E-01

5.00E-01

6.00E-01

7.00E-01

8.00E-01

9.00E-01

1.00E+00

Fig. 7.18: Velocity magnitude at 5 cm from the walls and on the symmetry plane. The velocity range is from 0.1m/, to 1.0 m/s, with an interval of 0.1 m/s.

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1.00E-01

2.00E-01

3.00E-01

4.00E-01

5.00E-01

6.00E-01

7.00E-01

8.00E-01

9.00E-01

1.00E+00

Fig. 7.19: Velocity magnitude on planes between the obstructions. The velocity range is from 0.1 m/s to 1.0 m/s,with an interval of 0.1 m/s.

2.97E+02

2.98E+02

2.99E+02

3.00E+02

3.01E+02

3.02E+02

Fig. 7.20: Temperature at a distance of 5 cm from the walls and on the symmetry plane. The temperature rangeis from 297 to 302 K, with an interval of 1 K.

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2.97E+02

2.98E+02

2.99E+02

3.00E+02

3.01E+02

3.02E+02

Fig. 7.21: Temperature on planes between the obstructions. The temperature range is from 297 to 302 K, withan interval of 1 K.

1

50

100

200

5000

1000

2000

Fig. 7.22: Effective viscosity divided by molecular viscosity on planes between the obstructions. The range is

from 1 to 600 with variable intervals.

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8 COMPARISON OF GLOBAL RESULTS

In this section the comparison between measurements and different computational meth-ods is made based on global parameters within the occupied zone. The computationalresults are taken only from the measurement locations. The parameters used are the aver-age, maximum and minimum velocities, the turbulence intensity, the spatial temperaturestandard deviation, the maximum temperature difference and the heat removal efficiencydefined as

(8.1)

where

,

and

are the air average temperatures at the exhaust, supply and occupiedzone. An additional comparison is made using modified average velocities. The modifiedvelocity is an attempt to make measurement and numerical results comparable by com-pensating for the different treatment of the turbulence in the methods. This problem isaddressed by Koskela et al. [15] and the equations of the approach used here are explainedin Appendix C. In a recent paper [16] they suggested a correction for the computed velo-

cities to make them comparable with the omnidirectional results.

Average Velocity

Grilles: The results from the different simulations were close to each other in an iso-thermal situation. The FINFLO results were equal to the measured results also in a non-isothermal situation, but Fluent gave twice the measured velocity level.Nozzles: The Fluent results were close to the measured results, but now FINFLO gavemuch lower velocities both in isothermal and non-isothermal situations.

Table 8.1: Comparison of global results, occupied zone average velocity, [m/s]

Grille NozzleMethod Empty Isothermal Nonisoth. Isothermal Nonisoth.Measured 0.042 0.032 0.070 0.242 0.282FINFLO 0.059 0.053 0.076 0.101 0.141FLUENT 0.046 0.137 0.276 0.274

Modified Average Velocity

The modification according to Appendix C increased the computational values more thanthe measured values. However, an important feature was that it increased the FINFLOresults for the nozzles, which were out of the class, close to the level of the other methods.

Thus it seems that, at least for computational results, the modified velocity gives a morerealistic picture of the total kinetic energy level within the room.

Table 8.2: Comparison of global results, modified occupied zone average velocity, [m/s]


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Corrected Average Velocity

The empirical corrected velocities suggested by Koskela et al. [16] for the numericalresults were 4 to 6 percent lower than the theoretical modified velocities. As the measuredomnidirectional velocities are not modified in this method the relationship between themeasured and the calculated average velocities is the same as with modified velocities.

Also the conclusions are the same.

Table 8.3: Comparison of global results, corrected occupied zone average velocity, [m/s]


Maximum Velocity

The maximum velocities followed the same trend as the average velocities. Fluent overes-timated velocities, while FINFLO gave lower velocities than the measured ones.Grilles: In the isothermal situation the FINFLO results agreed with the measurementsin an empty room, but in the obstructed room both computational methods gave slightlyhigher maximum velocities than were measured. In the nonisothermal situation the FIN-FLO maximum velocity was smaller than measured, but Fluent gave a higher maximumvelocity.Nozzles: The Fluent results were close, within 10-18 %, to the measurement results, butFINFLO gave much lower velocities especially in isothermal but also in nonisothermalsituations.

Table 8.4: Comparison of global results, occupied zone maximum velocity, [m/s]


Turbulence Intensity

The comparison of turbulence intensities from different methods is shown in Table 8.6.

However, one must keep in mind that the comparison of the turbulence intensities fromthe measurements and computations is artificial, because their physical meaning is dif-ferent [15]. Thus, the numerical turbulence values cannot be used for example for thecalculation of comfort conditions. The extremely high turbulence values in the FIN-FLO results shows that most of the total kinetic energy in the computation was generatedthrough the turbulence and not the mean flow.

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Table 8.5: Comparison of global results, occupied zone average turbulence intensity, [%]

Grille NozzleMethod Empty Isothermal Nonisoth. Isothermal Nonisoth.

Measured 96 82 74 35 38FINFLO 99 61 136 914 539FLUENT 106 73 81 68

Temperature Deviation and Maximum Temperature Difference

The results of spatial temperature st andard deviations from different methods are shown inTable 8.6. With grilles all the methods gave almost similar values, while with the nozzlesthe computational methods gave higher temperature nonuniformity than the measure-ments.

Table 8.6: Comparison of global results, an occupied zone spatial temperature standard deviation, [

]

Grille NozzleMethod Empty Isothermal Nonisoth. Isothermal Nonisoth.Measured 0.253 0.245 0.376 0.195 0.439FINFLO 0.521 0.964FLUENT 0.455 0.735

The maximum temperature differences from different methods were closer to eachother than one could have expected from the standard deviations. Only the FINFLOresults for the nozzles differ clearly from the others. The maximum temperature differencevalues are presented in Table 8.7.

Table 8.7: Comparison of global results, occupied zone maximum temperature difference, [

]

Grille NozzleMethod Empty Isothermal Nonisoth. Isothermal Nonisoth.Measured 1.160 0.940 1.580 0.860 2.250FINFLO 1.650 3.446FLUENT 1.590 2.510

Heat Removal Efficiency

The efficiency values from different methods were close to each other. However, thenumerical methods gave lower efficiencies with both air distribution methods than thosemeasured.

Table 8.8: Comparison of global results, heat removal efficiency

Grille NozzleMethod Nonisoth. Nonisoth.Measured 1.170 1.020FINFLO 1.133 0.944FLUENT 1.077 0.925

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9 CONCLUSIONS

Air velocity and temperature measurements in a small scale industrial hall were comparedwith the simulations that were performed using two different computing codes. The simu-lations using the commercial Fluent code with a high-Reynolds number model andwall functions represent the usual practise among ventilation design, whereas the simu-lations with the university code FINFLO represent a more scientific approach withoutusing the wall functions. The latter practise necessitates a low-Reynolds number turbu-lence model as well as a much finer computing mesh near the walls to capture the actualwall boundary layers. In the high-Reynolds number model simulations the first cell heightwas selected to be out of the actual operating range of the turbulence model in order toget better resolution near the heating elements. Two different air supply arrangementswith grille or nozzle types of air terminal devices were studied, both with isothermal andnonisothermal boundary conditions.

The flow boundary conditions were difficult to set accurately at the supply air grillebecause it was not possible to describe the small details of the grille in the computational

geometry. Therefore, the flow in front of the grille was separately measured using Laser-Doppler anemometry. Still it was necessary to simplify the measured flow field to beable to use it as a boundary condition in the simulations. The turbulence quantities weremanipulated in order to adjust the jet profile similar to the measurements. The supplyair terminal boundary conditions remain one of the main difficulties in the room air flowsimulations. Local grid refinement near the supply air device is perhaps necessary.

The measured thermal boundary conditions were much better known than in typicaldesign simulations. Still there was about 15 % uncertainty of the total room heat balancebecause of leakage or heat conduction in the test room. The radiation heat transfer wasevaluated before the simulations by using a simple spreadsheet calculation procedure andequivalent convection heat flux was set as a boundary condition. Symmetry was utilised inthe simulations but the measurements showed that flow was not fully symmetric in reality.

The measured temperature distribution was generally well predicted but there werebigger differences in the air velocity. The two simulation methods gave different quantit-ative results. Better results were achieved either with the low-Reynolds number code orwith the high Reynolds number code, depending on the case. The air velocities with thehigh Reynolds number code were consistently higher than the measured ones and there-fore these results were on the safe side considering the draught risk. The low-Reynoldsnumber simulations predicted too low velocities in some of the cases.

In some parts of the room even the qualitative air flow pattern was different in the twosimulations, most notably in the regions where the buoyancy forces and the inertia forcesof the supply air jet are of the same magnitude and the supply air jet is deflecting nearthe solid boundaries. In those parts of the flow the low-Reynolds number model seemsto perform better, probably because the natural convection boundary layer flow is betterresolved.

It turned out to be difficult to make accurate comparisons with the measurementsbecause the comfort oriented, omnidirectional air speed measurements were not directlycomparable with the air velocity computed with the turbulence models. One possibilityis to use an artificial, modified velocity for comparison instead of the actual velocity. Thismethod has been used in this study and it seems that especially in low speed areas thecorrespondence between the measured and calculated speeds becomes better by usingmodified velocity for comparison.

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BIBLIOGRAPHY

[1] Lemaire, A. D. (Ed.), Room Air and Contaminant Flow, Evaluation of Computa-tional Methods. Subtask-1 Summary Report of the IEA Annex 20: AirFlow Patternswithin Buildings., TNO, Delft, 1993. ISBN 9067432989.

[2] Heiselberg, P., Murakami, S., and Roulet, C.-A., IEA Annex 26: Energy efficientventilation of large enclosures, Ventilation of large spaces in buildings, analysis andprediction techniques, Aalborg University, Aalborg, 1998. ISSN 13957953 R9803.

[3] Fluent Incorporated, Lebanon, NH 03766, USA, FLUENT 4.4 Users Guide, 1997.

[4] FINFLO User Manual version 2.2, 1997.

[5] Chien, K.-Y., Predictions of Channel and Boundary-Layer Flows with a Low-Reynolds-Number Turbulence Model, AIAA Journal, Vol. 20, Jan 1982, pp. 3338.

[6] Siikonen, T., An Application of Roes Flux-Difference Splitting for the Tur-bulence Model, International Journal for Numerical Methods in Fluids, Vol. 21,No. 11, 1995, pp. 10171039.

[7] Hirsch, C., Computational Methods for Inviscid and Viscous Flows, Vol. 2 ofNumer-ical Computation of Internal and External Flows. Chichester: John Wiley & SonsLtd, 1990. ISBN 0471923516.

[8] Siikonen, T., Laskennallisen virtausmekaniikan ja lammonsiirron jatko-opintojakso, Teknillinen korkeakoulu, Sovelletun termodynamiikan laboratorio,Espoo, 1998.

[9] Rahman, M. and Rautaheimo, P., A Modification for an Explicit Algebraic StressModel, Helsinki University of Technology, Laboratory of Applied Thermodynamics,

1998. ISBN 9512240211.

[10] Launder, B. E. and Spalding, B., The numerical computation of turbulent flows,Computer methods in applied mechanics and engineering, Vol. 3, 1974, pp. 269289.

[11] Wu, G., Christianson, L., Zhang, J., and Riskowski, G., Adjustable DimensionRoom Ventilation Simulator for Room Air and Air Contaminant Distribution Mod-eling, in Proceedings of Indoor Air 90 Conference, 1990.

[12] Kovanen, K., Suuntariippumaton termistorianemometri, Masters thesis, Helsinginyliopisto, 1986.

[13] Heikkinen, J., Numerical prediction of room air flows (In Finnish). VTT ResearchReports 705., Technical Research Centre of Finland, Espoo, 1990.

[14] Chen, Q., Comparison of different k-e models for indoor air computations, Nu-merical heat transfer, Vol. Part B, No. 28, 1995, pp. 728734.

[15] Koskela, H., Niemela, R., Hautalampi, T., Heikkinen, J., and Collineau, S., Useof ultrasonic anemometer for characterising room air flows, in Proceedings of theIndoor Air Conference, (Nagoya, Japan), pp. 845850, July 1996.

[16] Koskela, H., Heikkinen, J., Niemela, R., and Hautalampi, T., Turbulence correc-tion for thermal comfort calculation, Building and Environment, Vol 36, 2001, pp.247-255.

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A THE VELOCITY GRAPHS, FINFLO RESULTS

Fig. A.1: Velocity in a plane 3.3 m from the right wall of the isothermal room with the grilles.



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Fig. A.4: Velocity in a plane 0.3 m from the front wall of the isothermal room with the grilles.

Fig. A.5: Velocity in a plane 0.3 m from the back wall of the isothermal room with the grilles.

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Fig. A.6: Velocity in a plane 3.3 m from the right wall of the room with the grilles.



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Fig. A.9: Velocity in a plane 0.3 m from the front wall of the room with the grilles.

Fig. A.10: Velocity in a plane 0.3 m from the back wall of the room with the grilles.

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0,00

0,05

0,10

0,15

0,20

0,25

0,30

0,35

0,40

0,45

0,0 1,0 2,0 3,0 4,0 5,0 6,0 7,0

distance from the left wall, m

airspe

ed,m/s

h = 0.05 m

h = 0.33 m

h = 0.51 m

h = 0.05 mh = 0.33 m

h = 0.51 m

Fig. A.11: Velocity in a plane 0.3 m from the front wall of the isothermal room with the nozzles.

0,00

0,05

0,10

0,15

0,20

0,25

0,30

0,35

0,0 1,0 2,0 3,0 4,0 5,0 6,0 7,0


airspeed,m/s

h = 0.05 m

h = 0.33 m

h = 0.51 m

h = 0.05 m

h = 0.33 m

h = 0.51 m


0,00

0,05

0,10

0,15

0,20

0,25

0,30

0,35

0,40

0,0 1,0 2,0 3,0 4,0 5,0 6,0 7,0


airsp

eed,m/s

h = 0.05 m

h = 0.33 m

h = 0.51 m

h = 0.05 m

h = 0.33 m

h = 0.51 m


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0,00

0,05

0,10

0,15

0,20

0,25

0,30

0,35

0,40

0,45

0,0 1,0 2,0 3,0 4,0 5,0 6,0 7,0


modifiedairspeed,m/s

h = 0.05 m

h = 0.33 m

h = 0.51 m

h = 0.05 mh = 0.33 m

h = 0.51 m

Fig. A.14: Modified velocity plane 0.3 m from the front wall of the isothermal room with the nozzles.

0,00

0,05

0,10

0,15

0,20

0,25

0,30

0,35

0,0 1,0 2,0 3,0 4,0 5,0 6,0 7,0



h = 0.05 m

h = 0.33 m

h = 0.51 m

h = 0.05 m

h = 0.33 m

h = 0.51 m

Fig. A.15: Modified velocity in a plane 1.05 m from the front wall of the isothermal room with the nozzles.

0,00

0,05

0,10

0,15

0,20

0,25

0,30

0,35

0,40

0,0 1,0 2,0 3,0 4,0 5,0 6,0 7,0



h = 0.05 m

h = 0.33 m

h = 0.51 m

h = 0.05 m

h = 0.33 m

h = 0.51 m

Fig. A.16: Modified velocity in a plane 1.8 m from the front wall of the isothermal room with the nozzles.

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Fig. A.17: Velocity in a plane 0.3 m from the front wall of the room with the nozzles.



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B THE VELOCITY GRAPHS, FLUENT RESULTS

0,00

0,02

0,04

0,06

0,08

0,10

0,12

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5

distance from the front wall, m

airspeed,m/s

h = 0.05 m

h = 0.33 m

h = 0.51 m

h = 0.05 m

h = 0.33 m

h = 0.51 m

Fig. B.1: Velocity in a plane 3.3 m from the right wall of the isothermal room with the grilles.

0,00

0,02

0,04

0,06

0,08

0,10

0,12

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


ai

rspeed,m/s

h = 0.05 m

h = 0.33 m

h = 0.51 m

h = 0.05 m

h = 0.33 m

h = 0.51 m


0,00

0,02

0,04

0,06

0,08

0,10

0,12

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


airspeed,m/s

h = 0.05 m

h = 0.33 m

h = 0.51 m

h = 0.05 m

h = 0.33 m

h = 0.51 m


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0,00

0,01

0,02

0,03

0,04

0,05

0,06

0,07

0,08

0,09

0,10

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


airspeed,m/s

h = 0.05 m

h = 0.33 mh = 0.51 m

h = 0.05 m

h = 0.33 m

h = 0.51 m

Fig. B.4: Velocity in a plane 0.3 m from the front wall of the isothermal room with the grilles.

0,00

0,01

0,02

0,03

0,04

0,05

0,06

0,07

0,08

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


airspeed,m/s

h = 0.05 m

h = 0.33 m

h = 0.51 m

h = 0.05 m

h = 0.33 m

h = 0.51 m

Fig. B.5: Velocity in a plane 0.3 m from the back wall of the isothermal room with the grilles.

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0,00

0,05

0,10

0,15

0,20

0,25

0,30

0,35

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


airsp

eed,m/s

h = 0.05 m

h = 0.33 m

h = 0.51 m

h = 0.05 m

h = 0.33 m

h = 0.51 m

Fig. B.6: Velocity in a plane 3.3 m from the right wall of the non-isothermal room with the grilles.

0,00

0,05

0,10

0,15

0,20

0,25

0,30

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


airspeed,m/s

h = 0.05 m

h = 0.33 m

h = 0.51 m

h = 0.05 m

h = 0.33 m

h = 0.51 m


0,00

0,05

0,10

0,15

0,20

0,25

0,30

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


airs

peed,m/s

h = 0.05 m

h = 0.33 m

h = 0.51 m

h = 0.05 m

h = 0.33 m

h = 0.51 m


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0,00

0,05

0,10

0,15

0,20

0,25

0,30

0,35

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


airspeed,m/s

h = 0.05 m

h = 0.33 m

h = 0.51 m

h = 0.05 m

h = 0.33 m

h = 0.51 m

Fig. B.9: Velocity in a plane 0.3 m from the front wall of the non-isothermal room with the grilles.

0,00

0,05

0,10

0,15

0,20

0,25

0,30

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5


airspeed,m/s

h = 0.05 m

h = 0.33 m

h = 0.51 m

h = 0.05 m

h = 0.33 m

h = 0.51 m

Fig. B.10: Velocity in a plane 0.3 m from the back wall of the non-isothermal room with the grilles.

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0,00

0,10

0,20

0,30

0,40

0,50

0,60

0,70

0,0 1,0 2,0 3,0 4,0 5,0 6,0 7,0

y, m

airspeed,m/s

h = 0.05 m

h = 0.33 m

h = 0.51 m

h = 0.05 m

h = 0.33 m

h = 0.51 m

Fig. B.11: Velocity in a plane 0.3 m from the front wall of the isothermal room with the nozzles.

0,00

0,10

0,20

0,30

0,40

0,50

0,60

0,0 1,0 2,0 3,0 4,0 5,0 6,0 7,0

y, m

airspeed,m/s

h = 0.05 m

h = 0.33 m

h = 0.51 m

h = 0.05 m

h = 0.33 m

h = 0.51 m


0,00

0,10

0,20

0,30

0,40

0,50

0,60

0,0 1,0 2,0 3,0 4,0 5,0 6,0 7,0

y, m

airspeed,m/s

h = 0.05 m

h = 0.33 m

h = 0.51 m

h = 0.05 m

h = 0.33 m

h = 0.51 m


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0,00

0,10

0,20

0,30

0,40

0,50

0,60

0,70

0,0 1,0 2,0 3,0 4,0 5,0 6,0 7,0


airspeed,m

/s

h = 0.05 m

h = 0.33 m

h = 0.51 m

h = 0.05 m

h = 0.33 m

h = 0.51 m

Fig. B.14: Velocity in a plane 0.3 m from the front wall of the non-isothermal room with the nozzles.

0,00

0,10

0,20

0,30

0,40

0,50

0,60

0,0 1,0 2,0 3,0 4,0 5,0 6,0 7,0


airspeed,m/s

h = 0.05 m

h = 0.33 m

h = 0.51 m

h = 0.05 m

h = 0.33 m

h = 0.51 m

Fig. B.15: Velocity in a plane 1.05 m from the front wall of the non-isothermal room with the nozzles.

0,00

0,10

0,20

0,30

0,40

0,50

0,60

0,0 1,0 2,0 3,0 4,0 5,0 6,0 7,0


airspeed,m/s

h = 0.05 m

h = 0.33 m

h = 0.51 m

h = 0.05 m

h = 0.33 m

h = 0.51 m

Fig. B.16: Velocity in a plane

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