A STUDY OF NATURAL VENTILATION OF PUBLIC HOUSING IN SINGAPORE USING COMPUTATIONAL FLUID DYNAMICS (CFD) SIMULATIONS

, Volume 2, Number 2, p.35-45, 2001 A STUDY OF NATURAL VENTILATION OF PUBLIC HOUSING IN SINGAPORE USING COMPUTATIONAL FLUID DYNAMICS (CFD) SIMULATIONS N.H. Wong and A. Loke Department of Building, School of Design and Environment, National University of Singapore, Singapore (Received 22 March 2001; Accepted 19 June 2001) ABSTRACT The aim of this paper is to discuss the application of CFD for the study of natural ventilation of public housing flats in Singapore. The flat types chosen for this study include the 3-room and 4-room flats. Two cases are simulated based on these flat types, one having the internal doors closed and the other opened. The results show that naturally ventilated flats are able to achieve reasonable ventilation performance especially when the internal doors within the flats are opened for cross-ventilation. When the internal doors are closed, the ventilation performance drops drastically especially in the bedrooms which are side-sided ventilated. The results have also demonstrated that a reasonable degree of accuracy can be attained in the CFD simulations when the results obtained are compared with the field measurements. 1. INTRODUCTION Singapore is an island city-state where a multiracial population of 3.9 million live and work on a landmass of less than 648 km 2 to create a nation that enjoys one of the highest living standards in the world. On an island that is devoid of natural resources, the country has only one valuable resource to tap on, its human resources. Singapore is presently reviewing its land uses based on an estimated population of five million. In order to accommodate the rising demographic population under the huge constraint of limited land, the only option is to move upwards. With the move in this vertical fashion, the issue of ventilation comes into discussion. The ventilation of a building can be either natural or artificial. Natural ventilation, put simply is the air movement, which is caused by pressure or temperature differences across building apertures. Mechanical ventilation, on the other hand is the energy-driven alternatives to natural ventilation, it uses fans and ducts to supply and extract air in localized areas. Air conditioning, another form of mechanical ventilation treats and supplies air. This method is particularly useful to cool air below ambient temperatures. The decision that designers make in regard to the natural ventilation is often one made with little information since natural ventilation is an area where many uncertainties exist. At present, the government is also studying the viability of having a central air-conditioning unit for the public residential dwellings. Somehow, recent development in mechanical ventilation have encouraged researchers to focus more on the use of mechanical ventilation as the solution for thermal comfort and health. However, the problem with mechanical ventilation is that it is energy intensive. Singapore, being an island endowed with no natural resources has to get supply from overseas markets. On the other hand, the use of natural ventilation as a solution for ventilation requires no such resources and is a much cheaper alternative. CFD simulation has been used very extensively for the studies of velocity and temperature distribution in an enclosure that is mechanically ventilated [1-6]. However, the use of CFD for the studies of natural ventilation is still limited [7-9]. This is partially due to the dynamic fluctuation of the wind speeds and directions. Furthermore, these parameters are also governed by many other factors such as the surrounding obstructions, terrain factors, geometrical configuration of the building etc [10]. This study therefore attempts to explore the potential of using CFD for the study of natural ventilation in public housing in Singapore. The study will involve two different flat types, i.e. 3- room and 4-room flats. In order to validate the CFD simulation results, site measurements are also conducted. The CFD software employed for the purpose of this study is Phoenics [11]. 2. METHODOLOGY 2.1 Buildings and Sites Selection Two different flat types were used in this study: 3- room and 4-room flat types that serve as the classic examples of residential high-rise HDB buildings in Singapore. The site plans of the 3-room and 4-35

room blocks are shown in Figs. 1 and 2. The 3- room flat block of 15 storeys high is surrounded by a number of high-rise blocks of equal height on the south-west, with a low-rise school located to its north-east. For the 4-room flat block, it is surrounded by a number of high-rise blocks on three sides except the eastern part, which is unobstructed. N omni-directional hot wire anemometers (Fig. 4) and their automatic logging meet the ASNI/ASHRAE 55-1992 [12] and ISO 7726 [13] specifications for accuracy and response time. The range of measurement of the hot wire anemometers used was 0.1 to 5 ms -1 with accuracy of 5 %. Sampling of the wind speed is taken at half an hour interval with an integration time of 180 seconds and the monitored results are then printed out every half hourly. In this case, 3-minute average wind speed data at half hourly intervals was obtained. The anemometers were also placed on the outside of the windows that are used for the establishment of the boundary conditions of the inlets in the CFD modeling. Another hot wire anemometer was also placed at the rooftop to track the wind speeds and directions that were assumed to be unobstructed. Housing blocks Location of site measurement Fig. 1: Site plan of the 3-room flat block N Fig. 3: DANTEC multi-channel flow analyzer Housing blocks Location of site measurement Fig. 2: Site plan of the 4-room flat block 2.2 Field Studies DANTEC multi-channel flow analyzer type 54N10 (see Fig. 3) with 12 hot wire anemometers were used to measure the wind velocities within each room of the investigated units as well as the outdoor wind condition. The transducers were Fig. 4: Omni-directional hot-wire anemometer The plan of each dwelling unit and the positioning of the indoor sensors are shown in Figs. 5 and 6, with measuring points placed near the windows and at the center of each room. The measurements were taken at a height of 1.5 m above the floor level, which is almost half the height of the ceiling of the room and represents the approximate height 36

of occupants at standing level. The windows of each unit investigated are widely opened to investigate the effect of cross ventilation. Measurements were done for two conditions: internal door fully opened to determine the effect of cross ventilation; and internal door fully closed. The measurements were carried out over two days from 9 a.m. to 10 p.m. The characteristics of the investigated units and the measuring periods are summarized in Table 1. Table 1: Data for investigated dwellings Flat type Housing estate Measuring period Floor of the building Measuring time 3-room ST George s Lane June 22 nd 23 rd 7 th 9 a.m. 10 p.m. 4-room Ang Mo Kio June 2 nd 3 rd 11 th 48 hrs for 2 days W1 Door-BAT1 8 N W2 Door-BAT 6 9 7 12.45m Door-MB Door-SR 3 Door-BR1 5 4 1 2 W3 6 m W4 Fig. 5: Plan of 3-room flat and locations of indoor sensors 37

W1 N Door-BAT1 9 W3 W2 Door-BAT 10 3 5 4 Door-BR2 6 Door-MB Door-BR3 2 8 12.95 m 1 7 W5 4.5 m W4 Fig. 6: Plan of 4-room flat and locations of indoor sensors 2.3 CFD Simulations 2.3.1 Grid Structure and Boundary Conditions A simulation domain size of 6.00 m in the X- direction, 12.45 m in the Z-direction and 2.45 m in the Y-direction was used for the modeling of the 3- room flat. For the 4-room flat, the simulation domain size of 9 m along the X-axis, 12.95 m along the Z-axis and 2.45 m along the Y-axis was adopted. The grid structures used in the four simulations are shown in Table 2. All floors and walls are defined as BLOCKAGE and made of concrete block with medium weight and adiabatic in nature. All inlets and outlets are defined as OPENING. The degree of opening of the internal doors as well as the crack width at the top and bottom of the doors were measured on site and modeled accordingly. Since measurement of the temperatures in the vertical profile shows that the difference is very minimal, the buoyancy effect is ignored. Table 3 shows the boundary conditions used in the four cases. 2.3.2 Assumptions 3-Dimensional steady state flow. 38

Table 2: Grid distribution for the simulations Cases Grid distribution X-direction Y-direction Z-direction C1 30 12 65 C2 30 12 65 C3 45 12 65 C4 45 12 65 Table 3: Boundary conditions for the 3-room and 4-room flat Cases Case 1 Case 2 Case 3 Case 4 Inlet velocity (ms -1 ) W2 (Z-direction) -0.542-1.312 W5 (Z-direction) 1.684 0.223 W1 (Z-direction) -1.040-0.864 W4 (Z-direction) 0.618 0.067 Angle of openings of internal doors (degree) Door-MB 0 290 0 290 Door-BR2 0 0 290 Door-BR1 0 110 Door-BR3 0 110 Door-BAT 0 290 0 290 Door-BAT1 0 290 0 290 Door-SR 0 290 0 110 Crack Width when internal doors are closed (mm) 12 12 All structural elements like floors, walls etc are assumed to be adiabatic in nature. The effects of gravity were disregarded in order to achieve a more speedy convergence since such forces would have minimum impact on the simulations. k-e turbulence model. Other than the inlets and outlets, all other external leakage paths are ignored. The global convergence criterion is taken as 0.001%. 3. DATA ANALYSIS 3.1 Overview The analysis will be covered in 3 aspects: Analysis of the individual cases Comparison between the two cases Comparison between simulation results and site measurements. Since the results obtained from the CFD simulations are in terms of absolute air velocities, this would render the comparisons between different cases difficult as the boundary conditions used in each case are different. A common approach is to use the concept of velocity coefficient (C v ) by normalizing the velocity at each point with a reference velocity. The formula is shown below: C v = V 1 /V 2 where V 1 is the velocity at the point of interest, and V 2 is the reference velocity. In this case, the reference velocity is obtained from site measurement at the rooftop, in which the average 3-minute wind speed data was recorded concurrently with that obtained for the indoor points. 39

3.2 3-Room Cases Fig. 7 and Table 4 show the velocity distribution and C v of the 3-room flat with the internal doors closed (Case 1). It can be seen that cross ventilation occurs effectively between the Living Room and Kitchen since their windows are directly facing each other. This has contributed to the high C v of 0.9 for both the Living Room and Kitchen. For the Master Bedroom, even though the window is facing the prevailing wind, the airflow within the room is minimal. This has contributed to a low C v of 0.2. The closing of the internal doors has prevented cross ventilation from taking place. Bedroom 1 has the lowest C v of 0.1. Being situated in the leeward side of prevailing wind and the door being closed, there is adequate reason for the dire state that this room is experiencing. The only airflow experienced in this room is due to the infiltration through the internal door of the bedroom. Fig. 8 and Table 4 show the velocity profile and C v of the 3-room flat with the internal doors opened (Case 2). For the Living Room and Kitchen, cross ventilation is further enhanced with the opening of internal doors resulting in the high C v of 1.0 and 1.5 respectively. The higher C v of Kitchen indicates that some of the airflow from the Kitchen are being diverted to Bedroom 1. With the opening of the internal door of Master Bedroom, the C v has increased to 0.5. However, the C v is the lowest among the rooms. For Bedroom 1, there is a drastic improvement of C v from 0.1 to 1.4 when the internal door is opened. The velocity profile shows that air from both Kitchen and Master Bedroom is channeled into Bedroom 1. A close examination of the two cases in Table 4 shows that Case 2 performed much better than Case 1 in terms of C v values. The C v values of all the rooms show an increase, with the greatest increase in Bedroom 1 of almost 93%. In the Living Room, the increase in C v is little, from 0.9 to 1.0 (10% improvement). Case 2 shows a 40% increase in the C v value for the Kitchen. In the Master Bedroom, the room enjoys better ventilation when the internal door is opened, evidenced by the 60% rise in the C v. However, even with the opening of the internal door, the ventilation condition in Master Bedroom is still fared badly with respect to the other rooms. This could be explained by the orientation of the window opening in relation to the door opening. It is apparent that when the internal door is opened, the room is able to have more significant airflow. However, the effect of cross-ventilation does not have much of an impact, given the fact that the fresh air coming from the inlet does not cover some areas of the room before leaving the room through the door opening. With regard to Bedroom 1, this room definitely benefits from the opening of the internal door. Having a 93% rise in C v value is clear instance of how cross-ventilation is helping to improve the ventilation condition of this room. The vectors diagram (Fig. 8) shows that the bedroom not only enjoys the airflow coming from the Master Bedroom, but also from the Living Room due to the proximity of the door opening to the path of the main airflow from the Kitchen. Under such favorable condition, there is no doubt that this room is well ventilated. 3.3 4-Room Cases Fig. 9 and Table 5 show the velocity distribution and C v of the 4-room flat with the internal doors closed (Case 3). For the Living Room, the vector diagram shows that the main path of airflow is from the Living Room s window to the Kitchen s window. Since the two windows are not directly opposite each other, there is a turning of the air currents at the side of the Master Bedroom. This has resulted in the reduction of the effectiveness of the cross ventilation with the Living Room having a low C v of 0.5. The Kitchen, on the other hand, is better ventilated having a higher C v of 0.9. The Master Bedroom has a C v of only 0.05 indicating that there is barely any airflow inside the room. This can be explained by the fact that the bedroom door is orientated towards the Storeroom instead of the Living Room. Thus, the room is not able to experience the infiltration from the Living Room. For Bedroom 2, this room is again under-ventilated having a low C v of only 0.1. However, it is better ventilated than the Master Bedroom since infiltration can occur from both the Living Room and Bedroom 3 due to the orientation of the bedroom door. The ventilation in Bedroom 3 is reasonable, considering that it shares the same C v of 0.5 for the Living Room. Table 4: Comparison of C v in 3-room flat with internal doors opened and closed Room types Case 1 Case 2 % Improvement C v C v [(Case 2 Case 1)/Case 1] x 100% Living Room 0.90 1.00 10% Kitchen 0.90 1.50 40% Master Bedroom 0.20 0.50 60% Bedroom 1 0.10 1.40 93% 40

Average 0.53 1.10 52% Fig. 7: Velocity distribution in 3-room flat with internal doors closed (Case 1) Fig. 8: Velocity distribution of the 3-room flat with internal doors opened (Case 2) 41

Fig. 10 and Table 5 show the velocity profile and C v of the 4-room flat with the internal doors opened (Case 4). For the Living Room, it is surprised to see that the opening of the internal doors has resulted in a slight reduction of C v from 0.5 to 0.4. A close examination of the velocity profile reveals that the opening of the internal doors has minimal effect on the cross ventilation that occurs between the Living Room and Kitchen. As for the Kitchen, the C v has reduced from 0.9 to 0.4. The Master Bedroom is the worst ventilated, having the lowest C v of 0.1. The obvious reason is again due to the location of the door that does not allow much air to enter the room. Instead, the projecting edge of the Master Bedroom deflects the air away to the direction of the Storeroom. The airflow in the room is induced in this case by the suction effect of the airflow passing through the door of the bedroom. The ventilation in Bedroom 2 is slightly better than the Master Bedroom having a C v of 0.2. The velocity vectors in this room indicate that the airflow comes mainly from Bedroom 3 with some airflow channeled from the Living Room. For Bedroom 3, being situated opposite Bedroom 2, this room has a higher C v of 0.3. This can be due to the fact that the windows here are windward and that the door of the Bedroom is facing that of Bedroom 2. This allows cross ventilation to occur effectively. A close examination of the two cases as shown in Table 5 shows that by opening the internal doors, C v values especially in the Living Room, Kitchen and Bedroom 3 have reduced. On the other hand, there is improvement for both Master Bedroom and Bedroom 2. The Kitchen shows the largest reduction in C v of 125%, followed by Bedroom 3 of 67% and Living Room of 25%. Both Master Bedroom and Bedroom 2 show improvement of 50%. Table 5: Comparison of C v in 4-room flat with internal doors opened and closed Room types Case 3 Case 4 % Improvement C v C v [(Case 2 Case 1)/Case 1] x 100% Living Room 0.50 0.40-25% Kitchen 0.90 0.40-125% Master Bedroom 0.05 0.10 50% Bedroom 2 0.10 0.20 50% Bedroom 3 0.50 0.30-67% Average 0.41 0.28-46% Fig. 9: Velocity distribution of the 4-room flat with internal doors closed (Case 3) 42

Fig. 10: Velocity distribution of the 4-room flat with internal doors opened (Case 4) 3.4 Comparative Analysis between the 3- Room Cases and the 4-Room Cases Comparing the C v values for 3-room and 4-room flats (Tables 4 and 5) under the close door condition, it can be seen that 3-room flat has better ventilation in most locations than the 4-room flat. For the Kitchen and Living Room of the 3-room flat, the vertical alignment of the windows of Kitchen and Living Room enhances cross ventilation resulting in high C v of 0.9 in both locations. However, this is not the case for the 4- room flat. This accounts for the low C v of 0.5 for the Living Room in 4-room flat. The Master Bedroom of 3-room flat also shows higher C v than that of the 4-room flat. This is due to the orientation of the door that faces Bedroom 1 and Living Room, thus promoting infiltration/ exfiltration to occur from/to both Living Room and Bedroom 1. However, in the case of 4-room flat, the door of the Master Bedroom is orientated towards the Store. As a result, it is unable to capture effectively the airflow from the Living Room. On the other hand, comparing Bedroom 1 of 3-room flat with Bedroom 3 of 4-room flat, Bedroom 3 shows a higher C v of 0.5 as compared to 0.1 in Bedroom 1. Comparing the C v values under the open door condition, it is obvious that the 3-room flat performs much better than the 4-room flat in all locations. By comparing the velocity profile between the two cases (Figs. 8 and 10), it can be seen that for 3-room flat, the opening of the door of Bedroom 1 has enhanced the cross ventilation between the Living Room, Kitchen as well as Bedroom 1. However, in the case of 4- room flat, this is not the case by opening the door of the Master Bedroom. The cross ventilation between Kitchen and Living Room is not enhanced. In this case, suction effect due to the airflow parallel to the door causes minor wind effect in the Master Bedroom. 3.5 Comparison of CFD Simulations with Field Measurements Figs. 11 and 12 show the comparison of the velocities at various locations between CFD simulations and field measurements for both 3- room and 4-room flats. The results show that in general, CFD simulations produce lower velocities than site measurements. For 3-room flat, the main deviations occur in points 4 and 5, which are located in Bedroom 1. For all the other points, the simulation results are comparable to that of the field measurements. With respect to the 4-room flat, the velocities obtained from CFD simulations are much closer to that obtained from field measurements except for point 5. The results show that the discrepancy tends to occur at the window locations at the leeward side of the flats. During the measurement, it was observed that the wind speed fluctuated quite significantly in these areas. This has added to the uncertainty in the comparison. 43

Wind Velocity (m/s) 3 2.8 2.6 2.4 2.2 2 1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0 1 2 3 4 5 6 7 8 9 Location CFD-Case 1 Site Measurements - Case 1 CFD-Case 2 Site Measurements - Case 2 Fig. 11: Comparison of velocity between CFD simulations and site measurements for 3-room flat 0.8 0.7 0.6 0.5 Velocity (m/s) 0.4 0.3 0.2 0.1 0 1 2 3 4 5 6 7 8 9 10 Location CFD-Case 3 Site Measurements-Case 3 CFD-Case 4 Site measurements-case 4 Fig. 12: Comparison of velocity between CFD simulations and site measurements for 4-room flat 1. CONCLUSION The aim of this study is to provide an insight into the application of CFD techniques in the modelling of 3-room and 4-room public housing flats. Two cases are simulated for each flat type, in order to compare the difference in the overall ventilation performance of the unit, given that the internal doors are opened or closed. The results show that the CFD techniques could provide the designers very useful information in terms of the impact of flat layout on the velocity distribution so that optimum designs can be achieved to reap the full potential of the natural ventilation. The case studies on the two flat types demonstrated that the 3-room flat is better ventilated than the 4-room flat in both situations when the internal doors are opened and closed. The simulation results also show that when the bedroom doors are closed, the ventilation performance of bedrooms is drastically affected in most cases. This is primarily due to the fact that the rooms become single-sided ventilated. The studies also show that by strategically 44

orientating the bedroom door to face the direction where cross ventilation could occur, it can improve the airflow inside the room through better infiltration/ exfiltration. The finding has demonstrated that CFD techniques have the potential to predict airflow to a reasonable degree of accuracy. However, the accuracy achieved was attainable only with a certain level of familiarization of the CFD program employed and elementary knowledge of fluids dynamics principles. Judgment on the part of the user is required both in the CFD modelling process and in the interpretation of the CFD results. In the CFD modelling process, users need to establish the correct boundary conditions such as the wind direction and magnitude. This could prove to be difficult at times and such error made in the CFD simulations will manifest in the CFD results. 10. M. Grosso, Wind pressure distribution around buildings: a parametrical model, Energy and Buildings, Vol. 18 (1992). 11. PHOENICS on-line information system, CHAM LTD. 12. ASHRAE standard 55-1992, Thermal environmental conditions for human occupancy, ASHRAE, GA, USA (1992). 13. ISO 7726:1985, Thermal environments instruments and methods for measuring physical quantities, International Standard Organisation (ISO), Geneva, Switzerland (1985). REFERENCES 1. W.K. Chow and W.Y. Fung, Numerical studies on the indoor air flow in the occupied zone of ventilated and air-conditioned space, Building and Environment, Vol. 31, No. 4, pp. 319-344 (1996). 2. P.J. Jones and P.E. O Sullivan, Development of a model to predict air flow and heat distribution in factories, SERC final report (1994). 3. H.B. Awbi and G.H. Gan, Predicting air flow and thermal comfort in offices, ASHRAE Journal, Vol. 36, No. 2, pp. 17-21 (1994). 4. K.W.D. Cheong, S.C. Sekhar, K.W. Tham and E. Djunaedy, Airflow pattern in air-conditioned seminar room, Indoor Air 99, Proc. 8th Int. Conf. on Indoor Air Quality and Climate, Vol. 2, pp. 54-59 (1999). 5. P.T. Williams, A.J. Baker and R.M. Kelso, Numerical calculation of room air motion - Part 3: Three dimensional CFD simulation of a full scale room air experiment, ASHRAE Transactions, Vol. 100, No. 1, pp. 549-564 (1994). 6. P.T. Williams, A.J. Baker and R.M. Kelso, Development of a robust finite element CFD procedure for predicting indoor room air motion, Building and Environment Vol. 29, No. 3, pp. 261-273 (1994). 7. G.H. Gan, Effective depth of fresh air distribution in rooms with single-sided natural ventilation, Energy and Buildings, Vol. 31, Issue 1, pp. 65-73 (2000). 8. K.A. Papakonstantinou, C.T. Kiranoudis and N.C. Markatos, Numerical Simulation of air flow field in single-sided ventilated buildings, Energy and Buildings, Vol. 33, Issue 1, pp. 41-48 (2000). 9. R. Southall and M. McEvoy, Validation of a computational fluid dynamics simulation of supply air ventilated windows, Durlin Conference, CIBSE. 45