The influence of wind direction on natural ventilation: Application to a largesemi-enclosed stadium

T. van Hooff1,2, B. Blocken3.

1 PhD student, Building Physics and Systems, Eindhoven University of Technology, Eindhoven,The Netherlands, t.a.j.v.hooff@tue.nl

2 PhD student, Laboratory of Building Physics, Katholieke Universiteit Leuven, Leuven,Belgium

3 Associate Professor, Eindhoven University of Technology, Eindhoven, The Netherlands,b.j.e.blocken@tue.nl

ABSTRACT

Natural ventilation is a commonly applied way in building engineering to ensure a healthy andcomfortable indoor climate. In this paper CFD simulations of the natural ventilation of a largesemi-enclosed stadium in the Netherlands are described. Simulations are performed to assess theair exchange rate for a total of eight wind directions. The CFD model consists of both thecomplex stadium geometry and the urban environment in which the stadium is located. A gridsensitivity analysis is conducted, furthermore, validation of the CFD model is performed usingfull-scale 3D wind velocity measurements. Comparison of the calculated air exchange ratesshowed that the wind direction has a significant effect on the air exchange rate; differences up to100% were found for the air exchange rate, which can be explained by the position and size ofthe buildings upstream of the stadium.

INTRODUCTION

Natural ventilation is nowadays more and more applied in buildings to maintain a healthy andcomfortable indoor climate. The driving force for natural ventilation can be wind or buoyancy,but usually a combination of these forces is present. Wind speed and wind direction caninfluence the amount of natural ventilation to a large extent, but numerical studies of naturalventilation in which the wind conditions are varied are limited. A previous study concerning theinfluence of wind direction on the air exchange rate (ACH) was conducted by Horan and Finn[1] who examined the air exchange rate for four wind directions and found significantdifferences in ACH. Jiang and Chen [2] performed Large Eddy Simulations of fluctuating winddirections, but their study emphasized on short term small fluctuations of wind direction.In this paper the influence of wind direction on the air exchange rate of a large multifunctionalsports stadium during summer conditions is investigated using Computational Fluid Dynamics(CFD). Sports stadia are increasingly being used for other purposes, such as concerts,conferences and other activities. One of these multifunctional sports stadia, and subject of thisstudy, is the Amsterdam ‘ArenA’ stadium in the Netherlands. The ArenA is equipped with aretractable roof construction. When the roof is closed, ventilation can only occur throughrelatively small openings in the building envelope. No HVAC systems are present in the stadium,and therefore the air exchange rate depends on natural ventilation through the roof and openingsin the building envelope, being the only means to ensure indoor air quality and thermal comfort.A specific feature of this research is the combined and simultaneous simulation of the wind flowin the complex urban environment around the stadium with the air flow inside the stadium.

DESCRIPTION OF STADIUM AND SURROUNDINGS

SURROUNDINGS

The urban area considered in this study is part of the city of Amsterdam, which is located in thenorth-west of the Netherlands. The city of Amsterdam and its surroundings are located on veryflat terrain; height differences are limited to less than 6 m. The stadium is surrounded by mediumand high rise office buildings, and buildings with an entertainment function, such as a cinemaand a concert hall. The height of the current surrounding buildings varies from 12 m to amaximum of 95 m for the “ABN-AMRO” office building (Fig. 1a) located on the southwest sideof the ArenA.The aerodynamic roughness length y0 of the surroundings, which is needed for the CFDsimulations, is determined from the updated Davenport roughness classification [3]. The area onthe north side of the ArenA can be classified as “closed terrain” due to the urban character that ispresent in a radius of 10 km upwind. The estimated y0 for this area is 1.0 m (Fig. 1b). The southside area of the ArenA is not as rough as the north side due to the presence of agricultural andnatural areas and can be characterised with an y0 of 0.5 m (Fig. 1b).

Figure 1: (a) Amsterdam ArenA and its surroundings. The two arrows indicate the ArenA stadium and thehighest building in its proximity (ABN-AMRO: 95 m). (b) Terrain surrounding the stadium with a radius of 10

km and estimated aerodynamic roughness length y0. The white square represents the computational domainused in this study.

STADIUM

The Amsterdam ArenA is a so-called oval stadium (Fig. 2a). The roof is dome shaped and can beclosed by moving two large panels with a projected horizontal area of 110 x 40 m2 (L x W). Theroof consists of a steel frame, largely covered with semi-transparent polycarbonate sheets, whilesteel sheets are applied at the edge of the roof until a distance of 18 m from the gutter. The standconsists of two separate tiers and runs along the entire perimeter. Figures 2a-c show a detailedplan view and the two cross-sections αα’ and ββ’. The exterior stadium dimensions are 226 x 190x 72 m3 (L x W x H). The stadium has a capacity of 51,628 seated spectators and an interiorvolume of about 1.2 x 106 m3.

Figure 2: (a) Horizontal cross-section of stadium. The arrows indicate the four large openings (gates) in thecorners of the stadium. (b) Cross-section αα’; (c) cross-section ββ’. The four measurement positions () for

air temperature and CO2 concentration inside the stadium are indicated Dimensions in m.

The ArenA is one of the many multifunctional stadiums that have been built in Europe during thelast two decades. Apart from sports events, they also host a wide variety of other activities, suchas concerts, conferences and festivities. For this purpose, many of these stadia are equipped witha roof construction that can be opened and closed depending on the weather conditions and thetype of event. However, they are generally not equipped with HVAC systems to control theconditions of the very large indoor air volume (up to 106 m3), which is also the case for theArenA. Indoor air quality problems can occur for the configuration with closed roof because ofthe large number of spectators and insufficient natural ventilation. During the summer,overheating can be an additional problem. In absence of HVAC systems, natural ventilation isthe only means to ensure indoor air quality. Natural ventilation can occur through the openingsthat are present in the envelope of the stadium. The ArenA has several of such openings. Thesemi-transparant roof is the largest potential opening. During concerts and other festivitieshowever, which are usually held in the summer period, the roof is closed most of the time toprovide shelter for the spectators and the technical equipment. When the roof is completely open,it is the largest opening (4,400 m2) in the stadium envelope. When it is closed, natural ventilationof the stadium can only occur through a few smaller openings. The four gates in the corners ofthe stadium (Fig. 2a) together form the second largest (potential) opening (4 x 41.5 m2). They areopen most of the time, but are sometimes closed during concerts to limit noise nuisance for thesurroundings. Additionally, two relatively narrow openings are present in the upper part of thestadium. The first opening is situated between the stand and the steel roof construction, and runsalong the entire perimeter of the roof (Fig. 3a). The total surface area of this opening is 130 m2.The other opening is situated between the fixed and movable part of the roof (Fig. 3b). Thisopening is only present along the two longest edges of the stadium. The total surface area of thisopening is about 85 m2. Of these openings, only the roof and gates can be opened/closed. In thebasic current configuration analysed in this study, the roof is closed, and all other openings areopen.

Figure 3: (a) Ventilation opening between the stand and the roof construction and (b) between the fixed andthe movable part of the roof.

FULL-SCALE MEASUREMENTS

AIR EXCHANGE RATE

To assess the natural ventilation in the stadium, CO2 measurements were performed at fourdifferent locations (Fig. 2a-c), and converted to air exchange rates using the concentration decaymethod:

0 1

1 0

ln lnC CACH

(1)

With ACH = air exchange rate in h-1, C(τ0) is the concentration at time 0 in ppm, C(τ1) theconcentration at τ1 in ppm and (τ1- τ0) the time between the two measurements. The CO2concentration at the four positions was measured during three consecutive evenings on whichconcerts took place: June 1st until June 3rd, and were made after each concert, when CO2concentrations had reached a maximum level caused by the attendants. During themeasurements, the potential (y0 = 0.03 m) daily averaged wind speed U10 measured by theKNMI at Schiphol airport on these three evenings was about 3.5 m/s and the wind direction onall three days was about 40° from north. The outdoor temperature during the concerts on allevenings was about 19˚C on average, and the indoor air temperature was about 26˚C. Because ofthe similar conditions, the calculated air exchange rate on these three nights was averaged. Table1 shows that the average air exchange rate for all four measurement positions is about 0.7 h-1 onthese evenings, whereas the minimum air exchange rate according to ASHRAE Standard 62-1[4] should be at least 1.5 h-1.

Table 1: Average air exchange rate at four positions measured after three concerts.

Position Air exchange rate (h-1)North, first tier (NE1) 0.65North, second tier (NE2) 0.74Southeast, first tier (SE1) 0.69

Southeast, second tier (SE2) 0.61

WIND VELOCITY

For CFD validation purposes, the 3D wind velocity in and around the stadium was measured inthe period September-November 2007, on days with strong winds (reference wind speed above 8m/s). Measurements were made with ultrasonic anemometers, positioned on mobile posts, at aheight of 2 m above the ground. The measurement positions included the four openings in thecorners of the stadium. Reference wind speed (Uref; meas) was measured on top of a 10 m mast onthe roof of the 95 m high ABN-AMRO office building, which is the highest building in theproximity of the stadium (Fig. 1). The data were sampled at 5 Hz, averaged into 10-minutevalues and analysed. The measurement results will be reported together with the simulationresults in the validation section.

INDOOR THERMAL CONDITIONS

To analyse the indoor conditions, full-scale measurements were also made of indoor and outdoorair temperature and relative humidity. Furthermore, the irradiance of the sky was measured toinvestigate the influence of solar radiation on the indoor air temperature. These measurementsshowed that the indoor temperature depends strongly on the solar radiation, and can exceed theoutdoor temperature by up to 6°C (Fig. 4), which indicates that the natural ventilation is notcapable of removing enough warm air during the day. The CO2 measurements already showedthat the air exchange rate during and after the three concert evenings does not meet the ASHRAErequirements.

Figure 4: The measured air temperature a inside and outside the stadium and the measured irradiance E, ona sunny day (July 18, 2007) and a cloudy day (July 20, 2007)

CFD SIMULATIONS: COMPUTATIONAL MODEL AND PARAMETERS

MODEL GEOMETRY AND COMPUTATIONAL DOMAIN

The computational model of the stadium reproduces its geometrical complexity with highresolution, down to details of 0.02 m. This is required to accurately model the flow through thenarrow ventilation openings (Fig. 3a,b). Because data with such high resolution are not availablefrom GIS and/or city databases, the construction drawings of the stadium were used. The

buildings that are situated in a radius of 500 m from the stadium are modelled explicitly, but onlyby their main shape. Buildings that are located at a greater distance are modelled implicitly, byimposing an increased equivalent sand-grain roughness height kS and roughness constant CS atthe bottom of the computational domain. These values are based on the aerodynamic roughnesslength y0 of the terrain in and beyond the computational domain and on the relationship betweenkS, CS and y0 for the specific CFD code [5].The computational domain has dimensions L x W x H = 2,900 x 2,900 x 908.5 m³. Themaximum blockage ratio is 1.6%, which is below the recommended maximum of 3% [6-7].Franke et al. [6] also state that the distance from the building to the side, to the inlet and to thetop of the domain should be at least five times the height of the building and the distance fromthe building to the outlet should be fifteen times the height. Since the stadium is 72 m high andthe smallest distance to the inlet of the domain is 1,130 m, these requirements are also fulfilled.

GRID

The computational grid consists of 5.6 million prismatic and hexahedral cells. The grid is ahybrid grid; it is partially structured and partially unstructured. Special attention was paid to theprecise modelling and high grid resolution of the ventilation openings of the stadium. A high gridresolution is used in the proximity of these openings in order to accurately model the flow. Agrid sensitivity analysis was performed with grids containing 3.0 million, 5.6 million and 9.2million cells. The 5.6 million grid was found to provide fairly grid-independent results. Someparts of the computational grid are displayed in Figure 5a,b.

Figure 5: (a) View from north showing part of the computational grid on the surfaces of the stadium and itssurroundings. (b) Bird-eye view of the geometry and grid on the southeast side of the stadium, illustrating

details such as the roof gutter which is modelled in detail for the air flow through the ventilation opening shownin Fig. 3a.

BOUNDARY CONDITIONS

At the inlet of the domain a logarithmic wind speed profile is imposed with an aerodynamicroughness length y0 of 0.5 m and 1.0 m, depending on the wind direction, and a reference windspeed U10 of 10 m/s. The corresponding turbulent kinetic energy and the turbulent dissipationrate profiles are also imposed at the inlet.The roughness of the bottom of the domain is taken into account by imposing appropriate valuesfor the sand-grain roughness ks and the roughness constant Cs which are calculated usingEquation 2 [5]:

09.793S

S

ykC

(2)

To avoid the use of excessively large cells near the ground when using the default values for Cs,the sand-grain roughness ks in the Fluent 6.3.26 code has been taken equal to 0.7 m and in orderto achieve horizontal homogeneity of the approach-flow mean wind speed profile in thissituation, the value for Cs is set equal to 7 with a user defined function (UDF). More informationon this matter is provided in [5,8]. For the ground surface in the direct vicinity around theexplicitly modelled buildings and the stadium, y0 = 0.03 m is taken, which is imposed by settingkS = 0.59 m and CS = 0.5. The temperature of the inlet air is set to 20ºC. Zero static pressure isset at the outlet of the domain and the top is modelled as a slip wall (zero normal velocity andzero normal gradients of all variables). To roughly take into account the increasing airtemperature inside the stadium because of solar irradiation, estimated surface temperatures areimposed on several surfaces inside the stadium. These surface temperatures vary from 22ºC to50ºC. Note that the intention of these simulations was only to compare the performance ofdifferent ventilation configurations. It was not intended to model the exact transient thermalbehaviour of the stadium under transient meteorological conditions.

OTHER COMPUTATIONAL PARAMETERS

The 3D steady RANS equations are solved in combination with the realizable k-ε turbulencemodel using the commercial CFD code Fluent 6.3.26 [9]. The realizable k-ε turbulence model ischosen because of its general good performance for wind flow around buildings [10]. Pressure-velocity coupling is taken care of by the SIMPLE algorithm, pressure interpolation is standardand second order discretisation schemes are used for both the convection terms and the viscousterms of the governing equations. The Boussinesq approximation is used for thermal modelling.

CFD SIMULATIONS: VALIDATION AND RESULTS

VALIDATION

CFD validation for the stadium is based on the wind speed measurements mentioned previously.The measured wind speed at the locations in the four gates is divided by the reference windspeed measured on top of the ABN-AMRO office building. This wind speed ratio is alsocalculated with CFD and both ratios are compared. The validation is performed for two winddirections, and for a closed and opened roof, depending on the configuration of the roof duringthe measurements. For brevity, results are only shown for a wind direction of 228˚ and aclosed roof, since the configuration with the closed roof is the most interesting one from aventilation point of view. Figure 6 compares simulated and measured mean wind speed,indicating a good agreement for the wind speed ratios (Fig. 6a) and for the wind direction in thegates (Fig. 6b), except for gate D. The CFD simulation predicts a flow parallel to the opening ofgate D, whereas the measurements showed flow directed into the stadium. Overall, a fair to goodagreement is obtained for the simulations, and the stadium model is used to evaluate differentventilation configurations.

Figure 6: Comparison between numerical and experimental results in the four gates A, B, C and D, for closedroof and reference wind direction φ of 228º. (a) wind speed ratio U/Uref; (b) local wind direction φ.

RESULTS

Simulations are performed with eight wind directions: = 16°, 61°, 106°, 151°, 196°, 241°, 286°and 331°, all perpendicular or under an angle of 45° to the symmetry axis of the stadium . Forwind directions between 286° and 16°, no immediate buildings are present upstream of thestadium, as opposed to between 61° and 241°. The most, and also the largest, buildings aresituated upstream of the stadium for a wind direction of 196° (Fig. 1a). The reference wind speedU10 at 10 m height at the inlet is 10 m/s for all simulations. For each ventilation configuration,the simulated mass flow rates through each opening are used to determine the ACH with Eq. (3)[11].

3600QACHV

(3)

where Q is the volumetric air flow rate into the enclosure (m3/s) and V the volume of theenclosure (m3).The results of the calculations are shown in Figure 7 and indicate that the ACH indeed stronglydepends on the wind direction.The air exchange rate for a wind direction of 16° for example istwice as high as for a wind direction of 196°, which is the wind direction with the lowest airexchange rate. This low air exchange rate for = 196º can be explained by the presence of agroup of large buildings upstream of the stadium. These buildings provide some shelter fromwind. Figure 8 shows the contours of the wind speed ratio U/U10 around the ArenA for = 196º

(SSW) in horizontal planes at heights of 10, 20, 40 and 60 m above the ArenA deck, at which thelowest openings (gates) are situated. The lower values around the ArenA indicate that thestadium is indeed situated in the wake of the office buildings, causing the lower ACH for thiswind direction, which is the prevailing wind direction in the Netherlands. Note that these valuesare much higher than the measured ACH because of the much higher wind speed and differentmeteorological conditions as during the measurements.

Figure 7: Air exchange rates obtained with CFD for eight wind directions (U10 = 10 m/s). Large differencesare present for the various wind directions.

DISCUSSSION

In this study the air exchange range of a large multifunctional stadium has been calculated usingCFD simulations. Further research is needed on several aspects of the study that has beenperformed.First of all, the CFD simulations in this study were performed steady-state, concerning both theflow and the heat transfer. Transient thermal simulations can be performed with CFD in thefuture for a more detailed thermal analysis. Another possibility is to use a Building EnergySimulation tool to simulate the transient thermal behaviour in a coupled approach with CFDsimulations for the air flow pattern. This coupling will be subject of future research by theauthors. Transient CFD simulations will also be performed to study the influence of pulsatingflow and large eddies on the air exchange between the building interior and the external flow.Although the validation study showed a good agreement between the measurements and theRANS simulations, it would be interesting to compare the air exchange rates obtained withRANS simulations with results of transient simulations that do take into account time-dependentflow properties [12,13]. Transient simulations will be performed using Large Eddy Simulation(LES) and/or Detached Eddy Simulation (DES). Secondly, the balance between wind andbuoyancy as driving forces for natural ventilation will be subject of future research. CFDsimulations will be performed to gain more knowledge on the interaction of both driving forces.

Figure 8: Contours of wind speed ratio U/U10 in four horizontal planes, for φ = 196° (SSW) and U10 = 10 m/s;at (a) 10 m; (b) 20 m; (c) 40 m and (d) 60 m above the ArenA deck. The lower wind speed ratios around the

stadium indicate that it is situated in the wake of the surrounding buildings, which explains the lower airexchange rates for this wind direction.

CONCLUSIONS

Coupled CFD simulations are performed to assess natural ventilation in a large semi-enclosedstadium for a range of wind directions. The following conclusions are made:

Measurements have shown that the air exchange rate of the stadium, with its roofclosed, was insufficient to avoid overheating during summer. Furthermore, the airexchange rate measured after three concerts was about 0.7 h-1 during themeasurement period, this is only half of the recommended air exchange rate byASHRAE.

Wind speed measurements have been used to validate the CFD model of thestadium and its surroundings and a good agreement has been found.

A grid sensitivity analysis has been performed that has shown that a grid with 5.6million cells is adequate for this study.

The results demonstrate the importance of modelling the surrounding urbanenvironment for natural ventilation analysis. Furthermore, this study shows theneed to perform simulations with a range of wind directions, especially if onewants to take into account the effect of the urban environment and buildingasymmetry on natural ventilation.

ACKNOWLEDGEMENTS

The first author is currently a PhD student funded by both Eindhoven University of Technologyin the Netherlands and the Katholieke Universiteit Leuven in Flanders, Belgium. The work inthis paper is a result of his master thesis project at Eindhoven University of Technology. Themeasurements reported in this paper were supported by the Laboratory of the Unit BuildingPhysics and Systems (BPS). Special thanks go to Ing. Jan Diepens, head of LBPS, and Wout vanBommel, Ing. Harrie Smulders and GeertJan Maas, members of the Laboratory of the Unit BPS,for their important contribution. The authors also want to thank Martin Wielaart, manager at theAmsterdam ArenA, for his assistance during the measurements.

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