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Building and Environment 68 (2013) 225e238

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Building and Environment

journal homepage: www.elsevier .com/locate/bui ldenv

Characterization of non-isothermal flows typical of builtenvironments in a laboratory scale model. Part I e Experimentswith 3D PIV

Nuno Serra, Viriato Semiao*

Mechanical Engineering Department, Instituto Superior Tecnico, Universidade Tecnica de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal

a r t i c l e i n f o

Article history:Received 6 January 2013Received in revised form30 May 2013Accepted 2 June 2013

Keywords:3D PIVDisplacementMixingNon-isothermal flowsBuilt environment

* Corresponding author. Tel.: þ351 21 8417726; faxE-mail address: ViriatoSemiao@ist.utl.pt (V. Semia

0360-1323/$ e see front matter � 2013 Elsevier Ltd.http://dx.doi.org/10.1016/j.buildenv.2013.06.007

a b s t r a c t

Built environments are major energy consumers worldwide and their efficiency is recognized as a keyfactor for the sustainable development of modern societies. Consequently, pressure has been put onresearchers and engineers to make recourse to all available tools to improve such efficiency. A contri-bution to this goal is the gathering of experimental data viewing a comprehensive understanding of theinvolved transport phenomena. The present work addresses this issue by presenting a set of experi-mental data acquired with the 3D PIV technique and a set of profile thermocouples, which allow char-acterizing the velocity and temperature fields in a laboratory model (scale 1:30) of an office room, with athermal resistance mimicking an occupant. An improved version of the moving average methodology isused to eliminate spurious vectors from the experimental data. Two ventilation strategies (mixing anddisplacement) are tested. Results for mixing show that the high momentum of the inlet flow promotes ahomogeneous temperature field due to a large recirculation zone formed downstream the buoyantplume above the heat source. This plume constitutes however an aerodynamic barrier hindering themixing process in the zone below the inlet grille (upstream the plume). Displacement results evidencethe existence of a short-circuit flow between the inlet and outlet grilles. This undesirable phenomenongenerates recirculation zones that promote a homogeneous temperature field, and not the aimed ther-mally stratified one. This may provoke discomfort to the occupant. The present data set is of capitalimportance to validate CFD results in built environment flows.

� 2013 Elsevier Ltd. All rights reserved.

1. Introduction

Energy is presently one of the major issues of the politicalagenda worldwide due to the marked increase of its price and itsimpact on the economies of most countries [1]. In convergencewith this, the growing awareness of the public opinion on the needto preserve the environment and the direct relation between en-ergy consumption and pollutant emissions evidence the crucialimportance to find ways to reduce the rapidly growing energyconsumption.

About 1/3 of the world’s consumption of primary energy fromfossil fuels (i.e. 4123 Mtoe) originates from building services [2,3],with the inherent CO2 emissions. In fact, the building sector, i.e.residential and commercial buildings, is the greatest energy con-sumer and CO2 emitter in the EU, being responsible for about 40% of

: þ351 21 8475545.o).

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the total energy consumption (i.e. 700 Mtoe). This has made ofenergy efficiency in buildings a key factor for the sustainabledevelopment of modern societies [4].

HVAC (heating, ventilation and air conditioning) and lighting arethe major energy consumers in buildings. Hence, it is vital that theenergy performance of built environments is well understood andoptimized [2], in order to guarantee that such environments becomeincreasingly healthy and comfortablewith less energy consumptionand, consequently, with a reduced impact on the environment. Thatis why pressure has been put on scientists and engineers to makerecourse to all available tools to achieve such goal.

Computational fluid dynamics (CFD), which has been widelyused since the late 1990s [3,5e9], has proved to be a powerful toolfor such purpose, as it has the potential to predict accurately allrelevant dynamic parameters that control the performance of builtenvironments in terms of energy and comfort. Notwithstanding,CFD is built up with physical and numerical models that requirecomprehensive validation against experimental data acquired atlaboratory scale for such purpose, so that it can then be applied to

N. Serra, V. Semiao / Building and Environment 68 (2013) 225e238226

real life built environments. Yet, there is a surprising dearth of suchvalidation data [10], particularly for the entire volume of indoor air,three-dimensional and non-isothermal flows.

In transport phenomena research, including those occurring inbuilt environments, scale models have been often used at labora-tory studies to reduce the inherent cost and time associated withthe use of full-scale systems [10]. Such an approach enhances themanual operability of the experiments, allowing simultaneously fora more detailed spatial interrogation and a smaller number ofextraneous variables [5]. This approach is also used in the presentwork, where air flow data are obtained inside a laboratorial scalemodel mimicking an office room (scale 1:30).

From the experimental point of view, one of the best establishedand widely used techniques to characterize flow kinematics is theparticle image velocimetry (PIV). However, to the present authors’knowledge, no work has reported the use of 3D PIV together withthermocouples to characterize experimentally and in detail for theentire room volume the thermal kinematics of three-dimensionalnon-isothermal flows in built environments as done herein. Infact, most of the works on this subject in the literature may begrouped in three main categories: (i) kinematic characterization ofisothermal flows with 2D PIV [10e17]; (ii) kinematic character-ization of isothermal flows with 3D PIV [18,19]; (iii) kinematiccharacterization of non-isothermal flows with 2D PIV and ther-mocouples [20,21].

Posner et al. [10] performed detailed LDA (laser Doppleranemometry) and 2D PIV measurements in an isothermal flowinside a scale model of a room (scale 1:10) to evaluate the potentialof different turbulence models. The authors concluded that theRNG keε [22] model behaved better than the standard keε modelfor their case. Bosbach et al. [12] investigated an isothermal air flowinside an airplane cabin by comparing numerical results obtainedwith different turbulence models against data acquired experi-mentally with 2D PIV. This study revealed that reliable predictionsof the simulated flows require low Reynolds number turbulencemodels. Van-Hoof et al. [16,17] studied different transitional jetflows in a reduced scale water-filled model. The other works using2D PIV reported flow measurements in very limited regions of theentire volume flow: Ji and Lee [13] characterized the air flow insidethe module of an automotive HVAC; Cao et al. [14,15] characterizedthe mean and instantaneous jet flow fields in the near-injectionregion.

The works using 3D PIV in isothermal flows also reported flowmeasurements in limited regions of the entire flow: Meslem et al.[18] characterized an innovative concept for optimized air diffusionusing the experimental data to validate CFD predictions; Meslemet al. [19] used 3D PIV measurements to assess the predictingcapability of three turbulence models in twin jet flows in the near-region of a lobed diffuser.

Kühn et al. [20] combined the 2D PIV technique with K-typethermocouples to characterize the non-isothermal flow field in afull-scale mock-up passenger aircraft cabin for two different airinlet configurations. Kamiji et al. [21] used 2D PIV combined withthermocouples to characterize the effect of turbulence on air flow-mixture inside an HVAC unit. However, since actual flows in builtenvironments are inherently three-dimensional, the use of the 2DPIV technique that ignores the out-of-plane velocity componentmay be of limited interest.

It should be mentioned that a reduced number of works usedPIV combined with other techniques with purposes different fromthose of the present work, but nonetheless related to them. Pous-sou et al. [23] combined the 2D PIV with the Planar Laser-InducedFluorescence (PLIF) techniques to study the effects of a movinghuman body on both the isothermal flow and the contaminanttransport inside an aircraft cabin in a scale water-based model

(scale 1:10). Sanjuan et al. [24] used 3D PIV and thermographytechniques to characterize the non-isothermal flow in open jointventilated façades to validate numerical predictions. Karadenizet al. [25] and Kumlutas et al. [26] applied meshed infrared ther-mography and stereo-PIV to study the three-dimensional flowstructures and to visualize the temperature profiles in the rectan-gular jet in the outflow of a split air conditioner unit.

In the present work the 3D PIV technique is used together withk-type thermocouples to characterize in detail and for the entireroom volume the three-dimensional velocity and temperaturefields of non-isothermal flows inside a built environment model(scale 1:30) with two different ventilation strategies: mixing anddisplacement. Moreover, an improved velocity vector validationmethod for the 3D PIV technique is proposed and validated.

The experimental data acquired in the scale model and pre-sented herein constitute a useful set to assess the accuracy of nu-merical and physical models as will be done in Part II of this work.Then, once validated, those models can be applied to real scale airconditioning flows, viewing the optimization of energy re-quirements and comfort conditions. Moreover, the data obtainedfor the two experimental strategies allow one to understand thephysical mechanisms associated with each strategy, which makesoptimization a task that can be done more systematically.

2. Experimental

2.1. Experimental setup

Fig. 1 displays a scheme of the experimental setup. As it can beseen, it comprises the scale model of an office room designed andbuilt up specifically for this work; the smoke seedingmachine, usedto produce flow tracer particles for the PIV technique; the fan topromote air flow into the room model; the laser emitting system(laser head and body hardware); the trigger controller to syn-chronize the cameras operation with the laser pulses; the two CCDcameras with the Scheimpflug adapter, with their horizontal axesmaking a 15� angle; the PC; and the temperature measuring system(probe and surface thermocouples with the data logger).

The scale model room is depicted in detail in Fig. 2 and has in-ternal dimensions of 0.2 � 0.1 � 0.12 m3 (length �width � height).It is entirely made of 3 mm thickness plexiglass, and has twodifferent configurations, mixing as sketched in Fig. 2(a) anddisplacement as shown in Fig. 2(b).

An electrical resistance of 1000 U is used as a heat source tomimic the heat released from an occupant in the room.

2.1.1. The PIV systemThe three-dimensional flow inside the scale model room was

measured with the 3D PIV technique mentioned above. For that,the air flowwas seededwith smoke particles with sizes in the range0.25e6 mm, using a smoke generator machine (ROSCO 1700), andtheir motion inside the model was captured by two CCD cameras(Dantec HiSense camera, 1024 � 1280 pixels2). The tracer particleswere illuminated by a light sheet (of 2.5 mm thickness) producedby a water-cooled double-pulse Nd:YAG laser system (NEW WAVESOLO III 50 with an energy of mJ/pulse). An external trigger pro-cessing unit synchronizes the operation of the cameras and thelaser and coordinates the data traffic between the CCD cameras andthe computer e see Fig. 1.

The angular stereoscopic PIV used herein is a calibration-basedsystem with the reconstruction being based on calibration co-efficients obtained before recording the data flow field. The cali-bration process determines the yez image-to-object plane spacemapping and the x, y and z calibration coefficients, and it was doneherein following the methodology described by Soloff et al. [27].

Fig. 1. Scheme of the experimental setup.

N. Serra, V. Semiao / Building and Environment 68 (2013) 225e238 227

In contrast to the 2D PIV calibration, this approach does notrequire the knowledge of the system geometry at any stage duringreconstruction as the calibration data is acquired at three differentx-locations (see Fig.1), holding the calibration target shown in Fig. 3at the object plane, slightly behind (but parallel to) it, and in front ofit. The distances between the calibration planes were comparableto the light sheet thickness.

2.1.2. The thermocouplesSince the temperature distribution has a significant effect on

both the flow kinematics and occupants’ thermal comfort, the

Fig. 2. Layout of the scale model of an office room. (a) Mixing ventilation configura-tion; (b) displacement ventilation configuration.

average air temperature fields were also acquired at different po-sitions in the scale model, covering the entire physical domain. Forthat purpose five parallel profile probes were used. Each probeconsists of six small diameter calibrated K-type thermocouples(OMEGA pp6-36-k-u-12-6 pnt profile probe 3/1600 dia � 12 cmlg;precision �1.1 �C) placed inside a single outer sheath suited forprofiling the temperature at various points along a single axis in thez-direction (see Fig. 4). The entire set of thermocouples was posi-tioned with a spatial resolution of 20 � 16.7 � 24 mm3; in eachposition the temperature was recorded at a rate of 1/2 Hz andaveraged over a time period of 10 min. This resulted in a totalmeasurement time of approximately 90 min for each temperaturefield. The average ambient temperature in the mock-up was atsteady state. Simultaneously, five surface K-type thermocouples(precision �1.1 �C) were placed at the model walls and at theelectrical resistance to measure their temperatures.

Both the profile and the surface thermocouples were connectedas single-ended inputs to a 32 channel data logger (OMEGAOM-SQ2040-2F16; accuracy �0.1% of full scale).

Fig. 3. Calibration target for the 3D PIV system.

Fig. 4. Layout of the inner temperature measuring system: five parallel profile probeswith six thermocouples each. Traverse distance in the y-direction is 20 mm.

N. Serra, V. Semiao / Building and Environment 68 (2013) 225e238228

A hot wire anemometer (AIRFLOW TA3; with an estimateduncertainty of 0.024m/s with a confidence interval above 95%) wasused to measure the inflow velocity.

2.2. Experimental procedures and post processing of data

For each ventilation strategy,mixing anddisplacement, 40 three-dimensional vector fields were measured with the laser light sheetin YZ planes (see Fig. 4), the distance betweenplanes being constantand with a value of Dx ¼ 2.5 mm. A special platform was manufac-tured and used to move the model room along the x-direction,keeping the relative position of the laser and CCD cameras fixed.

Subsequently, the temperatures at the walls and at 9 XZ planeswere measured (recall that in each plane there are 5 probes with 6vertical sites for temperature acquisition totalizing 270 measuringlocations). Thedistancesbetweenmeasured temperatureswerekeptconstant (Dz¼ 24mm;Dy¼ 20mm andDx¼ 16.7mm)e see Fig. 4.

The pulsed laser beams were directed towards the scale modelthrough the plexiglass walls after being shaped into a light sheet bya cylindrical lens. With the first laser pulse, the particles inside thelight sheet are illuminated, and their scattered light is recorded bythe CCD cameras. After a very short delay (a few milliseconds), theparticles are illuminated again by a second laser pulse, and a secondframe of the particles is recorded (double frame mode) by eachcamera.

Fast Fourier transform (FFT) cross-correlation was used tointerrogate each pair of images, which were sectioned into smallinterrogation areas (IA), definedbyagridwith cells of 16�16pixels2

corresponding to an area of 2.045 � 2.045 mm2. Each IA yielded asingle velocity vector.

The two frames of each pair were separated by time intervals of5 ms and 1.2 ms, respectively for displacement and mixture, inorder to ensure a displacement of the particles smaller than 25% ofthe IA characteristic length [28]. Seventy pairs of frames, resultingin seventy vector maps, were obtained and treated by the post-processing validation method described below.

All the previously described steps were performed separatelyfor each CCD camera. Then, the two vector fields (one of eachcamera) were combined through the calibration coefficients pre-viously obtained yielding a three-dimensional vector field.

2.2.1. Methodology to identify spurious vectorsThe instantaneous nature of the acquisition process of the PIV

technique, where all the spatial information is processed simulta-neously, embodies a certain probability to produce invalid data,

rising from several error sources and resulting in velocity vectorsphysically unrealistic [29e31].

It is inherent to the nature of such spurious vectors to be randomin direction and magnitude, with values above a pixel, beingtherefore easily detected. The major factors responsible for theirappearance are the insufficient number of particles present in theIA and the presence of strong velocity gradients [32].

To overcome this flaw, PIV data are usually subject to a post-interrogation image processing to identify the spurious vectorsand, subsequently, eliminate them from the data set or replacethem by surrogate ones physically supported [33].

Although the visual inspection of PIV measured data might beused to eliminate spurious velocity vectors, this would be a tedioustask and, more important, a quite subjective, non-reproducible andnot optimal approach. Hence, a robust and optimally efficientautomatic procedure is required. The three best established andlargely tested validation procedures are the moving average [29],the median test [30] and its modified version [31].

The median test [30] and its modified version [31] use a medianestimate of the velocity and a normalized median test that sanc-tions, in all cases, a single detection threshold fairly independent ofthe (local) level of the velocity variations. However, these methods(as well as the moving average one) require a priori testing of themeasured results in order to attain the best fitted constants thatmake valid vectors acceptable, and the spurious ones rejected. Thismeans that each process interrogation would require its own(optimal) detection level for the identification of spurious data, andin most cases the detection level depends both on the flow char-acteristics and on a wide range of suggested detection factors(Høst-Madsen and McCluskey [29] suggested a very broad detec-tion factor range between 0.01 and 0.1 when using the movingaverage validation). This would make the process to attain the bestfitted detection factor somehow subjective and iterative. Because ofthat, an improved version of the moving average, based on localmass conservation is proposed herein, and is described below.

In an actual velocity field of an incompressible flow, and basedon local mass conservation, it is acceptable to assume that the ve-locity variations are small in a close vicinity of a tested vector andevery value above an imposed limit is spurious. This means that thevelocity variation relatively to a reference value must be below athreshold, as expressed by Eq. (1).

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiU02 þ V 02 þW 02

p���MVn

��� � εlimit (1)

In Eq. (1) U0 ¼ U � Un, V 0 ¼ V � Vn and W 0 ¼ W �Wn; and,Un, Vn and Wn are the weighted averages of the velocity compo-nents of the adjacent vectors. These values are defined as:

Unðx; y; zÞ ¼ 1MNL

XxþM�12

i¼ x�M�12

XyþL�12

j¼ y�L�12

XzþN�12

k¼ z�N�12

Uði; j; kÞaði; j; kÞ (2.a)

Vnðx; y; zÞ ¼ 1MNL

XxþM�12

i¼ x�M�12

XyþL�12

j¼ y�L�12

XzþN�12

k¼ z�N�12

Vði; j; kÞaði; j; kÞ (2.b)

Wnðx; y; zÞ ¼ 1MNL

XxþM�12

i¼ x�M�12

XyþL�12

j¼ y�L�12

XzþN�12

k¼ z�N�12

Wði; j; kÞaði; j; kÞ

(2.c)

N. Serra, V. Semiao / Building and Environment 68 (2013) 225e238 229

In the previous equations a is a normalized weighting factordefined as:

aðx; y; zÞ ¼ cðx; y; zÞPxþM�12

i¼ x�M�12

PyþL�12

j¼ y�L�12

PzþN�12

k¼ z�N�12cði; j; kÞ

(3)

with c taking the value 1 for vectors adjacent to the tested vector inthe coordinate directions; 1=

ffiffiffi2

pfor vectors located in the near-

diagonals of the tested vector; and 0 for the vectors located in thefar-diagonals of the tested vector.

The previously referred values are the relative distances be-tween testing vectors: 1 for the vectors in IAs perpendicular to thetested vector; and 1=

ffiffiffi2

pfor vectors in IAs located in the nearest

diagonals positions. Although statistically one might expectimproved results when using a denser set of data, experience evi-denced that the vectors in the far diagonal should be ignored asthey made the testing vector to deviate from expected values,increasing the value of εlimit.

Fig. 5. Comparison of different post-processing techniques for the velocity field in the mixintest validation; (c) 3D moving average validation; (d) improved 3D moving average validat

In turn,���MVn

��� is the testing vector magnitude described as:

���MVn

���ðx; y; zÞ ¼ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiU2n�x; y; z

�þ V2n�x; y; z

�þW2n�x; y; z

�q(4)

Note that, M, L and N, are the number of neighbour vectorsconsidered in the x, y and z-directions, respectively. In the presentstudy the optimal value for M, L and N is 3 (M ¼ L ¼ N ¼ 3).

The previously described procedure was applied to several CFDbuilt environment test cases with varying inlet turbulence in-tensities in order to establish the best fitted detection factor (εlimitin Eq. (1)) for this kind of flows. It was observed that in all cases 99%of the data set obeyed to Eq. (1) with εlimit ¼ 0.15.

Another interesting observation was that, as expected from thestrong mixing character of high turbulence intensity flows (i.e. aninlet flow turbulence intensity above 5%), their test revealed that98% of the data set obeyed to Eq. (1) with εlimit ¼ 0.1. Moreover, 96%of data set of the near-laminar test case (i.e. for the inlet flow withturbulence intensity below 1%) satisfies the previously referredthreshold (0.1) for εlimit.

g ventilation strategy at an XZ plane (Y ¼ 0.1 m). (a) 2D post-processing; (b) 3D medianion (εlimit ¼ 0.15).

Fig. 6. Comparison of different post-processing techniques for the velocity field in the displacement ventilation strategy at an XZ plane (Y ¼ 0.1 m). (a) 2D post-processing; (b) 3Dmedian test validation; (c) 3D moving average validation; (d) improved 3D moving average validation (εlimit ¼ 0.15).

Fig. 7. Scheme of the Scheimpflug angular displacement system [38].

N. Serra, V. Semiao / Building and Environment 68 (2013) 225e238230

It should be mentioned that the uniform grid size used inthe CFD calculations for the laboratory scale model roomwas 1.7 � 1.7 � 1.7 mm3, which compares with the2.045 � 2.045 � 2.5 mm3 of the volume containing each experi-mental vector obtained with the 3D PIV procedure.

Moreover, in this improved version of the moving averageprocedure each spurious vector is replaced by the vector compo-nents defined by Eq. (2.aec).

To test the efficiency and accuracy of the proposed validationmethod, the measured velocity fields were post-processed using it,and the results were compared with those obtained with threeother post-processing strategies: a 2D strategy, the median test andthe moving average validation, the outcome being presented inFigs. 5 and 6 as an illustrative example.

Fig. 5(a) and 6(a) show the velocity vector results for the mixingand displacement test cases at the XZ middle plane (Y ¼ 0.1 m),after performing two of the 2D post-processing methods of theDynamic Studio software from DANTEC (peak height and movingaverage validation). The 3D post-processing procedures were alsoapplied and the velocity vector results are presented in Fig. 5(b) and

6(b) for the median test validation; Fig. 5(c) and 6(c) for the movingaverage validation, and Fig. 5(d) and 6(d) for the method proposedherein (with εlimit ¼ 0.15).

It is noticeable from the analysis of the previous figures that themethod proposed herein and the moving average validation one

N. Serra, V. Semiao / Building and Environment 68 (2013) 225e238 231

perform similarly well for both the mixing and the displacementventilation strategies, resulting in homogeneous vector fields.

On the other hand, the median test validation performed worsethan the two previous ones and closer to the 2D post-processingtechnique for both ventilation strategies e compare Fig. 5 (a) to(b) and 6(a) to (b).

It should be mentioned that the implementation of the movingaverage validation test required iterations in order to attain the bestfitted detection correlation factor. This trial-and-error processcontrasts with the method proposed herein as, for the latter, the15% upper limit of the detection factor may be applied to a verywide multitude of inner flows in built environments.

2.3. Error analysis

Arroyo and Greated [34], Prasad et al. [35] and Lawson and Wu[36] presented error analyses for the PIV translation system,whereas Lawson and Wu [36] and Zang and Prasad [37] presentederror analyses for the angular displacement system, the latterincluding the Scheimpflug condition for the angular displacementarrangement. It was concluded from the experimental results thatthe Scheimpflug stereocamera PIV system can provide accuracies

Fig. 8. Experimental velocity vectors acquired with the 3D PIV technique for the mixing sX ¼ 0.0667 m.

comparable, or even higher, than the translation stereocamerasystem. From the standard methods of error analysis, the un-certainties in the calculated displacements can be related to theuncertainties in the geometric parameters of the stereocamera thatare displayed in Fig. 7 [38].

Assuming that each of the intervening variables is uncorrelatedwith the others and distributed normallywith a standard deviation,s, and thatperfect image registration is performedby theacquisitionsystem, the uncertainties of the displacements are defined as [38]:

hsDxDx

i2¼

�s2DY1

þ s2DY2

�� d0MnSDx

2þhsSS

i2þ�sMn

Mn

2þ�sd0

d0

2(5.a)

sDyDy

� 2¼ sDY1

y� S2

� �MnSDy

" #2þ sDY2

yþ S2

� �MnSDy

" #2þ sMn

Mn

� 2

þ sSS

DxDy

yd0

� 2þ sy

d0

DxDy

� 2(5.b)

trategy at four YZ planes. (a) X ¼ 0.0167 m; (b) X ¼ 0.0334 m; (c) X ¼ 0.050 m; (d)

Fig. 9. Experimental velocity vectors acquired with the 3D PIV technique for the mixing strategy at two XZ planes: (a) Y ¼ 0.060 m; (b) ¼ 0.100 m.

N. Serra, V. Semiao / Building and Environment 68 (2013) 225e238232

sDzDz

h i2¼ s2DY1

þ s2DY2

� � zM SDz

� 2þ s2DZ1 þ s2DZ2

� � 12M Dz

� 2

n n

þ sMn

Mn1þ Dx

Dzd0

�� 2þ sS

SDxDz

zd0

� 2þ 12

szd0

DxDz

� 2(5.c)

In the previous equations Dx, Dy and Dz are the true particledisplacement components, DXi, DYi and DZi the apparent dis-placements measured by the cameras, Mn the nominal magnifica-tion, d0 the nominal object distance, di the corresponding imagedistance and S the distance between the cameraelens axes.

Fig. 10. Experimental Reynolds stress profiles acquired with the 3D PIV technique forthe mixing strategy at the station located at X ¼ 0.05 m; Y ¼ 0.10 m.

Among the uncertainties listed above, sDY1, sDY2

, sDZ1 and sDZ2arise exclusively from the interrogation process of the PIV imagesand include random and bias errors [35]. The remaining un-certainties, sy, sz, sS, sMn and sd0 are due to errors in themeasuringof the various distances of the stereocamera system.

If one wants to evaluate the errors emerging onlyfrom the PIV interrogation process, and assuming sDY1

¼ sDY2¼

sDZ1 ¼ sDZ2 ¼ sDY , Eq. (5.aec) become:

sDxzffiffiffi2

p �d0MnS

sDY (6.a)

sDyz1ffiffiffi2

p�1Mn

sDY ðfor y ¼ 0Þ (6.b)

sDzz1ffiffiffi2

p�1Mn

sDY ðfor z ¼ 0Þ (6.c)

Moreover sDx=sDz ¼ sDx=sDy ¼ 2d0=S ¼ 1=tan q, which is therelative error of the out-of-plane (perpendicular do the laser sheet)to the in-plane (laser sheet plane) components of displacement.

The analysis of Zang and Prasad [37] showed that theScheimpflug angular displacement system also exhibits an identicalvariation for the out-of-plane error with q.

The absolute value of the in-plane error in a 3D PIV is smaller (bya factor of 1=

ffiffiffi2

p) than that of the corresponding value for a 2D

system, because two cameras in the 3D system contribute equallyto the final result. The stereo arrangement also removes theperspective error, which can be quite sizable in single camera 2DPIV [36].

3. Results and discussion

The measuring techniques previously described were applied tocharacterize the flow kinematics and temperature distribution ofthe built environment inside the laboratory scale model previouslydescribed.

Fig. 11. Experimental velocity vectors acquired with the 3D PIV technique for the displacement strategy at two YZ planes: (a) X ¼ 0.0334 m; (b) X ¼ 0.050 m.

Fig. 12. Experimental velocity vectors acquired with the 3D PIV technique for the displacement strategy at three XZ planes: (a) Y ¼ 0.020 m; (b) Y ¼ 0.060 m; (c) Y ¼ 0.100 m.

N. Serra, V. Semiao / Building and Environment 68 (2013) 225e238 233

Fig. 13. Experimental velocity components profiles acquired with the 3D PIV technique for the displacement strategy as a function of Z located at X ¼ 0.05 m; Y ¼ 0.02 m, for: (a) U e

velocity; (b) V e velocity; (c) W e velocity.

N. Serra, V. Semiao / Building and Environment 68 (2013) 225e238234

3.1. Flow field

Herein, the experimentally measured velocities for the studiedventilation strategies (mixing and displacement) are presented andthe main flow characteristics are discussed.

The maximum random uncertainties of the experimental local-average velocities are the following ones, for a 0.1 pixel rms noiselevel of the PIV data [31]:

- for displacement, �0.006745 m/s (relative error to the inletvelocity of 8.9%), and �0.001807 m/s (relative error to the inletvelocity of 2.4%), for out-of-plane and in-plane errors,respectively;

- for mixing, �0.028104 m/s, (relative error to the inlet velocityof 8.0%), and �0.007531 m/s (relative error to the inlet velocityof 2.2%) for out-of-plane and in-plane errors, respectively.

Fig. 14. Experimental Reynolds stress profiles acquired with the 3D PIV technique forthe displacement strategy at the station located at X ¼ 0.05 m; Y ¼ 0.10 m.

3.1.1. The mixing strategyFig. 8 shows the experimental velocity vectors for the mixing

ventilation strategy, at four different YZ vertical planes: (a)X¼ 0.0167m; (b) X¼ 0.0334m; (c) X¼ 0.05 m (the middle plane ofthe room); and (d) X ¼ 0.0667.

The large and strong recirculation zone that is discernible on theroom right-hand side (above the outlet grille) in all displayed

Fig. 15. Experimental temperature profiles acquired with the thermocouples set as a function of Z for the mixing strategy at different positions. (a) X ¼ 0.05 m; Y ¼ 0.02 m; (b)X ¼ 0.05 m; Y ¼ 0.06 m; (c) X ¼ 0.05 m; Y ¼ 0.10 m; (d) X ¼ 0.05 m; Y ¼ 0.14 m.

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planes pushes the plume, which emerges from the heat source(located at Y¼ 0.1 m), to the room inlet side (on the left in Fig. 8), asis particularly evident in Fig. 8(b, c). This constitutes the maincharacteristic of this type of ventilation strategy: a very high mo-mentum of the inlet flow that induces a shear layer with highdiffusive transport, dominating particularly the entire right-handside flow field and promoting there a high mixing efficiency.

However, another main characteristic that can be observed inthis figures is the strong influence of the plume on the mainflow field, by creating an aerodynamic barrier that prevents thepreviously referred recirculation flow to extend to the entireroom, as becomes evident by observing the left hand side flowfield in Fig. 8(aed). This flow pattern may be a hindrance for themixing strategy and may generate a lack of comfort below theinlet grille.

Fig. 9 displays the experimental velocity vectors at two constantXZ planes: (a) Y ¼ 0.060 m and (b) Y¼ 0.100 m (the middle plane ofthe room). As can be seen, the previously described recirculationstructure is not evident at these planes. Moreover, there is not aclear flow path, which indicates a pattern of the large zone recir-culating predominantly around an axis parallel to the x-direction. Inopposition, the plume exhibits a clear 3D structure with a clearimpact on the flow that is evident in these planes also: the plumebuoyancy-driven flow is the dominant structure, creating, as

noticeable in Fig. 9(a,b), two counter-rotating recirculation flowstructures on the top of the room.

Fig. 10 shows the experimental vertical profiles (as a function ofZ) of the turbulent Reynolds stresses (normal stresses, u0u0, v0v0,w0w0; and shear stresses, u0v0, u0w0, v0w0) in the middle of the room(X ¼ 0.05 m and Y ¼ 0.10 m) and above the heat source.

As can be seen from that figure all the Reynolds normal stressesexhibit a very similar pattern: (i) they have quite large valuesimmediately downstream the heat source (small Z values) indi-cating that turbulence is being produced due to RayleigheBénardinstabilities, typical of buoyant flows with large temperature gra-dients (as will be seen below when discussing Fig. 15); (ii) for Zvalues between 0.025 and 0.1 m they decay considerably until theyreach a plateau, indicating that the turbulent kinetic energy pro-duction is stable therein and responsible for the thermal plumeconical shape growth e see Figs. 8(c) and 9(b); (iii) close to theroom ceiling (large Z values) they increase significantly denotingthe influence of the very high momentum inlet jet.

The Reynolds shear stresses exhibit a large gradient value at lowZ values making the thermal plume to enlarge in size in that region.After that, those gradients become negligible, with the Reynoldsshear stresses attaining a plateau with a value close to zero. Thismeans that the thermal plume enlargement in this region isensured by the normal stresses.

Fig. 16. Experimental temperature profiles acquired with the thermocouples set as a function of Z for the displacement strategy at different positions. (a) X ¼ 0.05 m; Y ¼ 0.02 m; (b)X ¼ 0.05 m; Y ¼ 0.06 m; (c) X ¼ 0.05 m; Y ¼ 0.14 m; (d) X ¼ 0.05 m; Y ¼ 0.10 m.

N. Serra, V. Semiao / Building and Environment 68 (2013) 225e238236

3.1.2. The displacement strategyFig.11 displays the experimentally measured velocity vectors for

the displacement ventilation strategy at two YZ planes, X ¼ 0.0334and X ¼ 0.050 m (the middle plane of the room).

Due to the difference between the inlet air temperature andthat inside the room, a marked buoyant driven flow is formedimmediately downstream the inlet grille e see Fig. 11. This buoyantflowcreates a short-circuit phenomenon of the airflowbetween theinlet and the outlet grilles, and two large counter-rotating recircu-lation structures in both sides of the room. These large recirculationzones separate two dominating buoyant flows: the previouslyreferred inletflowasdisplayed in Fig.11(a); and theplumeabove theheat source (aRayleigheBénard instability) asdisplayed in Fig.11(b),which is deflected towards the outlet by the inlet flow.

As seen before, the mixing ventilation strategy is designed toguarantee uniform conditions in the entire built environmentthrough a mixing process based on the large momentum and tur-bulent inlet flow, and making the flow practically independent ofthe air density differences. Differently, the displacement ventilationstrategy depends strongly on buoyancy-driven flows, failing itsobjective when the density differences are not favorable: this is thecase of the above-described flow that promotes a typical mixingflow and not a stratified built environment as expected, which mayproduce lack of comfort for the occupant.

Fig. 12 shows the experimental velocity vectors at three XZplanes, Y ¼ 0.020 m, Y ¼ 0.060 m and Y ¼ 0.100 m, for the

displacement strategy. These velocity vectors reveal the influenceof the two referred buoyant structures. In fact, in Fig. 12(a) themarked inlet upwards flow mentioned before is observable at themiddle of the plane, whereas Fig. 12(b) evidences the confluencezone of the two previously referred buoyant flows, the inlet and theplume, denoting the verticality and high momentum content of theflow in the studied region that may be uncomfortable for theoccupant. Another interesting flow feature captured by Fig. 12(c) isthe fast enlargement of the plume, originated by the mixing tur-bulent wake flow above the heat source that is due to the note-worthy buoyant forces in presence.

Fig. 13 depicts the three velocity components profiles, as afunction of Z, at positions X ¼ 0.05 m and Y ¼ 0.020 m. Theseprofiles evidence the inherently three-dimensional character of theflow field in this region of the room, exhibiting the effect of twoconcomitant influences: one exerted until the middle height of theroom, inducing relatively large values of the three velocity com-ponents, and a strong flow instability caused its buoyant turbulentmomentum; the other exerted at the confluence of the previouslydescribed large recirculating structure above the inlet.

Fig. 14 shows the experimental vertical profiles (as a function ofZ) of the turbulent Reynolds stresses above the heat source in themiddle of the room (X ¼ 0.05 m and Y ¼ 0.10 m).

That figure evidences a very similar pattern of all the Reynoldsnormal stresses: (i) they have quite large values immediatelydownstream the heat source (small Z values), indicating that

N. Serra, V. Semiao / Building and Environment 68 (2013) 225e238 237

turbulence is being produced due to RayleigheBénard instabilities,which is typical of buoyant flows with large temperature gradients(as will be seen belowwhen discussing Fig. 16); (ii) they decay afterthat to smaller values; (iii) for Z values above 0.075 they increasesharply due to the interaction of the inlet flow with the thermalplume previously discussed when analysing Fig. 11(b).

The Reynolds shear stresses exhibit a slight gradient at low Zvalues making the thermal plume to enlarge in size in that region.After that, those gradients vanish, with the Reynolds shear stressesattaining a plateau with a value close to zero. Exception to thisbehaviour is the u0v0 that exhibits non zero growing values as aresult of the above-mentioned interaction of the inlet flowwith thethermal plume.

3.2. Temperature field

The experimental temperature values, measured with a �1.1 �Cprecision, and their relation with the flow kinematics for the twoventilations strategies are presented and discussed below.

3.2.1. The mixing strategyFig. 15 shows the temperature profiles as a function of Z, for the

mixing strategy, at four different positions: X ¼ 0.05 m, Y ¼ 0.02 m;X ¼ 0.05 m, Y ¼ 0.06 m; X ¼ 0.05 m, Y ¼ 0.10 m; X ¼ 0.05 m,Y ¼ 0.14 m. This figure evidences the main characteristic of themixing ventilation strategy: the homogeneity of the temperaturefield. In fact, the mixing ventilation strategy is designed to guar-antee uniform conditions in the entire air-conditioned space. Bymixing the fresh air with the one existing inside the room thepollutants are diluted and a uniform temperature field is created[9]. Suchmixing results from the insufflation of a highly convective/diffusive flow into the room, taking advantage of both the turbu-lence intensity and high momentum of such flow. This enhancesthe flow transport and mixing ability to promote uniform enthalpyand temperature fields, as illustrated in Fig. 15(a, b, d).

The exception to this behaviour is the temperature profile dis-played in Fig. 15(c), located in the wake above the heat source,where a marked temperature gradient is observable. This temper-ature gradient is actually the driving force of the plume buoyantflow e see Fig. 8(c).

3.2.2. The displacement strategyIn displacement ventilation fresh air is insufflated close to the

floor through a grille located at a sidewall. Displacement design isbased on air density gradients: fresh air, cooler than the room air,flows close to the floor until it comes across a heat source, usuallythe occupant, being then heated up, which causes a buoyant flowsurrounding it. This ascending buoyant flow carries the fresh airupwards and creates a clean and fresh environment at the occupantvicinity.

However, due to the low momentum and near-laminar inletflow, this ventilation strategy is very sensitive to adverse inflowtemperature gradients. In opposition to the mixing strategy, whichrelies on the high momentum and turbulence intensity of the inletflow, displacement relies on the inner flow kinematics. In fact, thisstrategy supports its ventilation and climatization efficiencies on anegative temperature gradient at the inlet.

However, when the inlet flow has not the required momentumit may cause, in extreme situations, a short-circuit phenomenon ofthe fresh air flow between the inlet and the outlet grilles, as seenbefore. Such an unexpected behaviour is evidenced in Fig. 16 thatshows the temperature profiles as a function of Z for different po-sitions. The short-circuit phenomenon between the inlet and outletyields the fairly homogeneous vertical temperature profiles e

Fig. 16(aec) e rather than the expected and desirable thermal

stratification as discussed above. The exception is the profile shownin Fig. 16(d), corresponding to the temperature measurements inthe heat source wake, where thermal gradients typical of buoyantflows are present.

4. Conclusions

In the present work the 3D PIV technique was used in associa-tion with a set of thermocouples to characterize the transportphenomena (momentum and energy) inside a built environment,mimicked by those occurring inside a laboratory scale model (scale1:30). A thermal resistance was placed in the middle of the modelfloor to simulate an occupant.

An improved version of the moving average post-processingprocedure, proposed herein to eliminate spurious vectorsinherent to the PIV technique, proved to be accurate with theadvantage of not requiring an iterative process for factors tuning.

Two ventilation strategies (mixing and displacement) werestudied and compared.

Besides the present data set being of crucial importance tovalidate CFD predictions (as will be done in part II of this work), thefollowing conclusions can be withdrawn:

- Themixing strategy accomplishes its objective ensuring a quiteuniform temperature field inside the room, as a consequence ofthe very large inlet flow momentum. The turbulent inlet jetinduces the appearance of a large recirculation zone down-stream the turbulent buoyant plume emerging above the heatsource, promoting this way a turbulent convective/diffusivemixing and a quite homogeneous temperature field in thatregion.

- The buoyant plume existing in the mixing strategy works as anaerodynamic barrier to the mixing process.

- The present displacement strategy fails its purpose as, ratherthan promoting a stratified built environment in the occupantregion, it behaves closer to the mixing strategy by producing afairly homogeneous field temperature. This is a consequence ofas undesired short-circuit phenomenon that occurs betweenthe inlet and outlet flows.

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