Development of estate level outdoor ventilation prediction models for HDB estates in singapore 1

DEVELOPMENT OF ESTATE LEVEL OUTDOOR VENTILATION PREDICTION MODELS FOR HDB ESTATES IN SINGAPORE LEE ROU XUAN @ LEE SEU QUIN (B.Sc. Building (Hons.), NUS; M.Sc. (Building Science), NUS) A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY DEPARTMENT OF BUILDING NATIONAL UNIVERSITY OF SINGAPORE 2013 ACKNOWLEDGEMENTS I would like to express my gratitude to all the people who helped me in completing this thesis. First and foremost, I want to thank my supervisor and mentor, Prof. Wong Nyuk Hien, for all his advice, guidance and encouragement during all the stages of this research. My thanks also go to Dr. Demetris Clerides, Mr. Peter Ewing and Mr. Kynan Maley from CD-Adapco for providing all the necessary technical support in the use of the Star-CCM+ software throughout my candidature here. My appreciation also goes to Mr. Komari Bin Tubi, from the School of Design and Environment (SDE) Wind Tunnel Laboratory, for his kind technical assistance in helping to prepare the equipment and sensors before actual experiments. Also, thanks to Mr. Tan Dong Xing, the student assistant for helping me to construct the scaled wind tunnel models and even took the trouble to come back during his exams period. Next, my heartfelt thanks goes to Mr. Clement Choo, the IT expert for helping me to tackle some of my computer hardware problems. I am grateful to Dr. Steve Kardinal Jusuf for answering many of my questions regarding research methodologies and for all his insightful comments and suggestions. Moreover, I would also want to thank my fellow course-mate Mr. Terrance Tan, for letting me use his more powerful computer to supplement my massive simulation studies; without which, the whole process might stretch out for another one year. Also many thanks go to my entire lab mates - Alex Tan, Erna Tan and also Kelvin Li, for making all these years a funnier and wackier experience to remember. From all the laughs and their suggestions with this research, this certainly contributed to the betterment of this study. Furthermore, I am certainly grateful to acknowledge the financial support that comes from the scholarship funding from the National University of Singapore i (NUS) that has helped to ease some of my financial burden during my study here. Next, I want to thank my parents for bringing me to this world, my siblings for all their love, encouragement and endless moral support. Special thanks goes to my late grandparents who came all the way from China to settle down in Singapore and also drummed us the belief that girls should be given an equal opportunity to study like boys. Lastly, I would like to thank my husband and best friend Soong Chee Keong for sharing his knowledge in CFD research, incredible support, encouragement, taking care of me and making me see light when everything else seems hopeless. ii TABLE OF CONTENTS ACKNOWLEDGEMENTS i  TABLE OF CONTENTS iii  SUMMARY xi  LIST OF TABLES . xiv  LIST OF FIGURES xxii  LIST OF ABBREVIATIONS . l  CHAPTER : INTRODUCTION 1  1.1 Background and Motivation 1.1.1 Reduction of Wind Speed . 1.1.2 Research Motivation . 1.1.3 Developments in this Research Area 1.1.4 Design Standards for Optimal Ventilation 1.1.4.1 Singapore – HDB Present Situation . 1.1.4.2 Other Countries’ Situation . 1.2 Research Objectives . 11 1.3 Structure of Thesis . 12 CHAPTER : LITERATURE REVIEW 15  2.1 Effects of Wind 15 2.2 Effects of Urban Environments on Wind Flow . 15 2.3 Description of Airflow Phenomenon . 20 2.3.1 Indicator of Good Ventilation . 20 2.3.2 Parameters that Affect Wind Flow in Urban Environments . 21 2.3.2.1 Important Findings from Previous Researches 22 2.3.2.2 Other Factors that Affect Wind Flow 40  iii 2.4 Experimental Designs Adopted for Airflow and Ventilation Studies . 41 2.4.1. Computational Fluid Dynamics (CFD) 42 2.4.1.1 Points to Note in CFD Simulations 43 2.4.1.2 Turbulence Models 47 2.4.1.3 Near-wall Treatment 52 2.4.2 Wind Tunnel Studies . 53 2.5 HDB Building Designs and Site Planning . 54 2.6 Research Gap . 57 CHAPTER : HYPOTHESIS AND METHODOLOGY 59  3.1 Hypothesis 59 3.2 Methodology 60 3.2.1 Scenarios or Cases Adopted 63 3.2.1.1 Orientation of Canyon (ORIENT) . 65 3.2.1.2 Building Shape (BS) 66 3.2.1.3 Geometry (GEO) 67 3.2.1.4 Gross Building Coverage Ratio (GBCR) . 70 3.2.1.5 Permeability (PERM) . 73 3.2.1.6 Buildings’ Height Variation (HV) . 78 3.2.1.7 Staggering of Blocks Arrangement (STAG) 81 3.2.2. Computational Fluid Dynamics Simulations . 83 3.2.2.1 Model Description . 83 3.2.2.2 Model Assumptions and Limitations . 84 3.2.2.3 Computational Domain 86 3.2.2.4 Boundary Conditions . 88 3.2.2.5 Meshing Type and Size 91 iv 3.2.3 Wind Tunnel Studies . 93 3.3 Conclusion . 98 3.4 Importance and Potential Contribution of the Research 99 CHAPTER : WIND TUNNEL STUDY 103  4.1 Introduction 103 4.2 Wind Tunnel Testing . 103 4.2.1 Testing Facilities . 103 4.2.2 Simulation of the Atmospheric Boundary Layer (ABL) 105 4.2.3 Wind Tunnel Blockage and Model Span 107 4.2.4 Similarity Parameters 109 4.2.5 Locations of the Sensor Taps 112 4.2.6 Selected Cases . 113 4.2.7 Assumptions 115 4.2.8 Results . 115 CHAPTER : PARAMETRIC STUDY OF THE INFLUENCE OF MORPHOLOGICAL VARIABLES ON ESTATE LEVEL VENTILATION .121 5.1 Introduction 121 5.2 Parametric Approach . 122 5.3 Findings from Parametric Study 122 5.3.1 Gross Building Coverage Ratio (GBCR) 122 5.3.1.1 Point Blocks . 125 5.3.1.1.1 Point Blocks, Pedestrian Level . 125 5.3.1.1.1.1 Point Blocks, Pedestrian Level - Random Configuration 127 5.3.1.1.1.2 Point Blocks, Pedestrian Level - Group Configuration . 128 5.3.1.1.1.3 Point Blocks, Pedestrian Level - Courtyard Configuration . 130 v 5.3.1.1.2 Point Blocks, Mid-Level . 132 5.3.1.1.2.1 Point Blocks, Mid-Level - Random Configuration 133 5.3.1.1.2.2 Point Blocks, Mid-Level - Group Configuration . 134 5.3.1.1.2.3 Point Blocks, Mid-Level - Courtyard Configuration . 136 5.3.1.2 Slab Blocks 137 5.3.1.2.1 Slab Blocks, Pedestrian Level . 137 5.3.1.2.1.1 Slab Blocks, Pedestrian Level - Random Configuration . 139 5.3.1.2.1.2 Slab Blocks, Pedestrian Level – Group Configuration 140 5.3.1.2.1.3 Slab Blocks, Pedestrian Level – Courtyard Configuration 142 5.3.1.2.2 Slab Blocks, Mid-Level 145 5.3.1.2.2.1 Slab Blocks, Mid-Level - Random Configuration . 146 5.3.1.2.2.2 Slab Blocks, Mid-Level - Group Configuration 148 5.3.1.2.2.3 Slab Blocks, Mid-Level - Courtyard Configuration 149 5.3.2 Buildings’ Height Variation (HV) 150 5.3.2.1 Point Blocks . 152 5.3.2.1.1 Point Blocks, Pedestrian Level . 152 5.3.2.1.1.1 Point Blocks, Pedestrian Level - Random Configuration 153 5.3.2.1.1.2 Point Blocks, Pedestrian Level - Stratified Configuration . 154 5.3.2.1.2 Point Blocks, Mid-Level . 156 5.3.2.1.2.1 Point Blocks, Mid-Level - Random Configuration 157 5.3.2.1.2.2 Point Blocks, Mid-Level - Stratified Configuration 158 5.3.2.2 Slab Blocks 160 5.3.2.2.1 Slab Blocks, Pedestrian Level . 160 5.3.2.2.1.1 Slab Blocks, Pedestrian Level - Random Configuration . 161 5.3.2.2.1.2 Slab Blocks, Pedestrian Level - Stratified Configuration 163 vi 5.3.2.2.2 Slab Blocks, Mid-Level 165 5.3.2.2.2.1 Slab Blocks, Mid-Level - Random Configuration . 166 5.3.2.2.2.2 Slab Blocks, Mid-Level - Stratified Configuration 167 5.3.3 Permeability (PERM) 168 5.3.3.1 Point Blocks . 171 5.3.3.1.1 Point Blocks, Pedestrian Level . 171 5.3.3.1.1.1 Point Blocks, Pedestrian Level – Ground Floor Only Permeability 172 5.3.3.1.1.2 Point Blocks, Pedestrian Level – Ground Floor and Mid-height Permeability . 173 5.3.3.1.1.3 Point Blocks, Pedestrian Level – Mid-height Only Permeability 175 5.3.3.1.2 Point Blocks, Mid-Level . 177 5.3.3.1.2.1 Point Blocks, Mid-Level – Ground Floor Only Permeability 179 5.3.3.1.2.2 Point Blocks, Mid-Level – Ground Floor and Mid-height Permeability . 181 5.3.3.1.2.3 Point Blocks, Mid-Level – Mid-level Only Permeability 183 5.3.3.2 Slab Blocks 185 5.3.3.2.1 Slab Blocks, Pedestrian Level . 185 5.3.3.2.1.1 Slab Blocks, Pedestrian Level – Ground Floor Only Permeability 187 5.3.3.2.1.2 Slab Blocks, Pedestrian Level – Ground Floor and Mid-height Permeability . 187 5.3.3.2.1.3 Slab Blocks, Pedestrian Level – Mid-level Only Permeability . 190 5.3.3.2.2 Slab Blocks, Mid-Level 191 5.3.3.2.2.1 Slab Blocks, Mid-Level – Ground Floor Only Permeability . 192 5.3.3.2.2.2 Slab Blocks, Mid-Level – Ground Floor and Mid-height Permeability . 195 5.3.3.2.2.3 Slab Blocks, Mid-Level – Mid-Height Only Permeability 197 vii 5.3.4 Geometry (GEO) . 199 5.3.4.1 Point Blocks . 202 5.3.4.1.1 Point Blocks, Pedestrian Level . 202 5.3.4.1.1.1 Point Blocks, Pedestrian Level – Geometrical Height Variation (H) 203 5.3.4.1.1.2 Point Blocks, Pedestrian Level – Geometrical Width Variation (W) 205 5.3.4.1.1.3 Point Blocks, Pedestrian Level – Combined Results of Geometric Height (H) and Width (W) Variation . 208 5.3.4.1.2 Point Blocks, Mid-Level . 210 5.3.4.1.2.1 Point Blocks, Mid-Level – Geometrical Height Variation (H) 211 5.3.4.1.2.2 Point Blocks, Mid-Level – Geometrical Width Variation (W) 213 5.3.4.1.2.3 Point Blocks, Mid-Level – Combined Results of Geometric Height (H) and Width (W) Variation . 217 5.3.4.2 Slab Blocks 219 5.3.4.2.1 Slab Blocks, Pedestrian Level . 219 5.3.4.2.1.1 Slab Blocks, Pedestrian Level – Geometrical Height Variation (H) 220 5.3.4.2.1.2 Slab Blocks, Pedestrian Level – Geometrical Width Variation (W) 222 5.3.4.2.1.3 Slab Blocks, Pedestrian Level – Combined Results of Geometric Height (H) and Width (W) Variation . 225 5.3.4.2.2 Slab Blocks, Mid-Level 227 5.3.4.2.2.1 Slab Blocks, Mid-Level – Geometrical Height Variation (H) . 228 5.3.4.2.2.2 Slab Blocks, Mid-Level – Geometrical Width Variation (W) . 230 5.3.4.2.2.3 Slab Blocks, Mid-Level – Combined Results of Geometric Height (H) and Width (W) Variation . 231 5.3.5 Staggering of Blocks Arrangement (STAG) . 233 5.3.5.1 Point Blocks . 239 viii (48) Hall, R.C. 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(133) Yamartino, R.J. and Wiegand, G. (1986). Development and Evaluation of Simple Models for the Flow, Turbulence and Pollution Concentration Fields within an Urban Street Canyon. Atmospheric Environment, 20, 2137-2156. (134) Yang, T. (2004). CFD and Field Testing of a Naturally Ventilated FullScale Building. PhD Thesis. University of Nottingham. (135) Yoshida, H. and Omae, M. (2005). An approach for analysis of urban morphology: methods to derive morphological properties of city blocks by using an urban landscape model and their interpretations. Computers, Environment and Urban Systems, 29, 223-247. (136) Zhang, A., Gao, C-L. and Zhang, L. (2005). Numerical simulation of the wind field around different building arrangements. Journal of Wind Engineering and Industrial Aerodynamics, 93, 891-904. 376 GLOSSARY Buildings’ Height Variation (HV) Defined as the standard deviation of the height variation for all the high-rise buildings within the precinct or estate. N It is formulated as HV = ∑ ∑(Hi − Have) where Have is N i=1 the average height (metres) of all the buildings within the precinct, Hi is the height (metres) of each individual building and N is the number of buildings in the precinct. Building Shape (BS) An urban morphological variable that is quantified by the Capacity Factor (CF). Compacity Factor (CF) Defined mathematically as C F =∑ areaofbuil dingenvelo pe volumeofbu ilding . It is a summation of all the buildings’ surface areas (metres square) over their building volumes (metres cube). The surface area of the building envelope consists of all the vertical external wall area, the roof (top) and ground floor area (bottom). The building volume is simply the section area of the building multiplied by the building height. Geometry (GEO) An urban morphological variable that is quantified by the Maximum Hydraulic Diameter (HDMax). Maximum Hydraulic Diameter (HDMax) Defined as the summation of all the largest hydraulic diameter (HD) of individual outdoor grid space, that are each area-weighted over the whole given precinct. HDMax = ∑ [(Largest HD of Area i)*(% of Area i in Precinct)]  HD is the hydraulic diameter of the studied area HD = 2HW/ (H+W) found within the precinct, where H = average height (metres) of both the upwind and downwind buildings on both sides of an open space or canyon, W = horizontal distance (or canyon width) between the buildings (metres). The calculation of HD is performed along linear traverses at each grid area by selecting the largest value from the superimposed matrices from the two traversal directions. The HDMax is computed by using the summation of area-weighted average of the spatial distribution of the largest composite HD value from each grid area. Open areas and street intersections will be calculated by using H as the average height of all the buildings 377 within the estate and W as the largest dimension of the whole estate (e.g. 500m for base case) to work out the HD value. Gross Building Coverage Ratio (GBCR) The ratio between gross ground floor area of a building to a given site area (land to building footprint). It is defined mathematically as ∑ builtarea , which is simply λp = ∑ builtarea + ∑ unbuiltare a the ground area covered by buildings (metres square) over the area of the whole precinct (metres square). Orientation (ORIENT) An urban morphological variable that focuses on the orientation of all the spaces in-between (urban canyons) the buildings within a precinct, each at an angle to the prevailing wind direction. It is quantified by using the Relative Sinuosity Index (Sθ). Relative Sinuosity ( S θ ) Defined mathematically as S θ = ∑ Li cos (θ i ) , where ∑ Li Li is the length (metres) of the linear segment i, and θi is the angle (degrees) between the given azimuth (of flow) and the azimuth of linear segment i. It is the summation of all linear canyon segments e.g. Main streets or breezeways, relative to the wind direction and indicates the degree of wind penetration into the whole precinct. Permeability (PERM) Defined as the summation of continuous pore space i, perpendicular to or an angle to wind direction, describing the corridor for wind flow within the building itself. Li is the length (metres) of the linear segment i (within the building), and θi is the angle (degrees) between the given azimuth (of wind flow) and the azimuth of linear segment i. HD is the hydraulic diameter (metres) of the cross-section area of the opening of continuous pore space i (within the building), which can be described as HD = 2HW/ (H+W). H = average height (metres) of the opening, W = average width (metres) of the opening. PERM = ∑ [(cos θi)2 * (π/4 * HD2)i * Li]bldg / ∑ Vbldg i Porosity volume within all the buildings in the precinct (m3) Total volume of all the buildings within the precinct (m3) But in situations whereby porosity occurring on all the four walls of a building (e.g. HDB void decks or sky gardens) instead of a continuous pore space opening at the front and end only, the opening at the 378 longer side of the building is treated as the width (W) to work out the HD, together with the height (H) of the pore space. The shorter side of the building will be treated as the length of the linear pore space (L). In this case (cos θi)2 can be considered as one unit as the four sides of the wall are open for wind to flow in unrestricted. Staggering of Blocks It is quantified by the Frontal Area Ratio (Afront) Arrangement (STAG) Index A front = ∑ i =1 Ai , frontalarea / ATOTALwallarea . [( n )] Afront is defined as the summation of all buildings’ frontal areas (metres square) that face the wind direction normally, over the total vertical wall area (metres square) of all buildings within the given site or precinct area. Ai,frontal area is the frontal area of each building i that faces the wind direction normally, and ATOTALwallarea is the total wall area of all the buildings within the given site area. Urban canyon A relatively narrow street with buildings lined up continuously along both sides. 379 APPENDICES 380 APPENDIX Derivation of Roughness Length (Z0) and Power-law Coefficient (α) Figure A1-1 shows the published field roughness determinations that were gathered for over thirty years from hundreds of field investigators who measured the roughness in all possible landscapes. Care was taken to make sure that the data were checked for quality in terms of their correct documentation of the investigated terrain, adequacy of the observation and evaluation methods, proper use of measurement arrays and making sure the described roughness came from a long enough fetch (Wieringa, 1992). Figure A1-1: Range of homogeneous surface roughness (Z0) from good experiments (Wieringa, 1992) Power-law Coefficient (α) The ABL is created by aerodynamic friction resulting from the motion of the air relative to the earth’s surface and thermal gradients between the upper atmosphere and the surface. The resultant is a vertical wind shear that varies not only in magnitude but also in structure. The variation in mean wind speeds with height above ground is often defined using the power-law relationship (Cochran, 2002). The magnitude of the power law coefficient (α) may vary between 0.1 in exceptionally smooth terrain to approximately 0.35 in very rough terrain such as built-up urban areas (Snyder, 1981). An estimate for the value of the powerlaw coefficient can be obtained from the surface roughness length (Z0), using the relationship from Counihan (Counihan, 1975): α = 0.24 + 0.096 log10 Z0 + 0.016(log10 Z0)2 = 0.24 + 0.096 log10 (0.50) + 0.016(log10 0.50)2 = 0.21 381 Figure A1-2 shows typical values for n (α in this case) and Z0 for various terrains ranging from seas to highly built-up urban areas, along with plots of the associated vertical velocity profiles. Figure A1-2: Longitudinal velocity profiles over uniform terrain in neutral flow (n here is actually α which is the power-law coefficient) (Cochran, 2002) Turbulence Intensity (TI) In addition to producing velocity deficit near the surface, the presence of aerodynamic friction and thermal gradients are also responsible for the creation of atmospheric turbulence (Cochran, 2002). The variation in the longitudinal turbulence intensity, TI, within the lower portion of the atmospheric boundary layer from to 100m above ground, can be defined from the following relationship from Snyder (Snyder, 1981): TI = α ln (30/Z0) ÷ ln (Z/Z0) ←valid for Z from 0.0~100.0m above ground = 0.21 ln (30/0.50) ÷ ln (100/0.50) = 0.16228 ≈ 0.16 (at 100m above ground) At heights above 100m, Snyder suggests that the turbulence intensity can be estimated by assuming a TI value of 0.01 at 600m and assuming a linear relationship between 100m and 600m. From Z > 100m onwards, assume a linear relationship between 100m~600m, where at 600m → TI = 0.01 Figure A1-3 shows the corresponding variation in longitudinal turbulence as a function of height above ground for the same terrain features shown in vertical velocity profiles indicated in Figure A1-2. 382 Figure A1-3: Turbulent intensity profiles over uniform terrain in neutral flow (n here is actually α which is the power-law coefficient) (Cochran, 2002) A reasonable estimate of 0.05 for TI will be suitable for strongly stable wind (TI < 0.08) for free-stream air (Wharton and Lundquist, 2012). Slope = (0.01-0.16) / (600 – 100) = -0.0003 At TI = 0.05, the height above ground (H) is equal to: -0.0003 = (0.05 – 0.16) / (H – 100) H = 466.67m ≈ 467m (above ground) The free stream velocity at 467m is around 5.56m/s (power-law plot from BCA’s average wind velocity of 2.7m/s at 15m) (BCA, 2012). Figure A1-4 shows the wind velocity profile worked out from BCA’s specifications using α=0.21. 383 Figure A1-4: Power-law wind velocity plot of worked out from BCA’s specifications (α=0.21) Turbulence Kinetic Energy (TKE) and Dissipation Rate (ε) TKE = 3/2 (U*TI)2 = 3/2 (5.56 * 0.05)2 = 0.115926 J/kg ≈ 0.11593 J/kg ε = [Cμ3/4 TKE3/2]/L , where L = 0.07*characteristic length. = [(0.09)3/4 (0.11593)3/2] / (0.07*500) = 1.8530414E-4 J/kg-s = 1.85304E-4 J/kg-s The characteristic length = 500m (longest dimension of the precinct). 384 [...]... blocks, mid -level of GBCR - courtyard configuration 14 9 Table 5 .15 : Tabulated values of HV for the parametric study for point and slab blocks 15 1 Table 5 .16 : Parametric study findings and their explanations for point blocks, pedestrian level of HV - random configuration 15 3 Table 5 .17 : Parametric study findings and their explanations for point blocks, pedestrian level of HV -... positions for point blocks (top) and slab blocks (bottom) 11 4  Figure 4.5: Comparison of wind tunnel and CFD readings for point blocks, 0˚ north wind orientation, at both the pedestrian and mid -level 11 6  Figure 4.6: Comparison of wind tunnel and CFD readings for point blocks, 22.5˚ north wind orientation, at both the pedestrian and mid -level 11 7  Figure 4.7: Comparison of wind tunnel... readings for point blocks, 45˚ north wind orientation, at both the pedestrian and mid -level 11 7  Figure 4.8: Comparison of wind tunnel and CFD readings for slab blocks, 0˚ north wind orientation, at both the pedestrian and mid -level 11 8  Figure 4.9: Comparison of wind tunnel and CFD readings for slab blocks, 45˚ north wind orientation, at both the pedestrian and mid -level 11 8  Figure 4 .10 :... Figure 4 .10 : Comparison of wind tunnel and CFD readings for slab blocks, 90˚ north wind orientation, at both the pedestrian and mid -level 11 9  xxvi Figure 4 .11 : Box-plot for the difference between CFD and wind tunnel readings (CFD minus wind tunnel readings in m/s) for (a) point blocks and (b) slab blocks 12 0  Figure 5 .1: Pedestrian level area-averaged VR against GBCR for (a) random, (b)... perimeter outline of the enclosed precinct area 327  Figure 8.9: Plan view of proposed HDB precinct base design indicating the perimeter outline of the enclosed precinct area and individual outdoor grid space 329  xxxi Figure 8 .10 : Plan view of proposed HDB precinct base design indicating the building perimeter that faces the wind direction normally without being blocked (red) for wind orientation... findings and their explanations for point blocks, pedestrian level of GBCR - courtyard configuration 13 1 xv Table 5.6: Parametric study findings and their explanations for point blocks, mid -level of GBCR - random configuration 13 4 Table 5.7: Parametric study findings and their explanations for point blocks, mid -level of GBCR - group configuration 13 5 Table 5.8: Parametric study findings... explanations for point blocks, mid -level of GBCR - courtyard configuration 13 6 Table 5.9: Parametric study findings and their explanations for slab blocks, pedestrian level of GBCR - random configuration 14 1 Table 5 .10 : Parametric study findings and their explanations for slab blocks, pedestrian level of GBCR - group configuration 14 2 Table 5 .11 : Parametric study findings and their... patterns of behavior have important implications for building and urban planning development of residential estates in future and support the possibility of using all these variables in the form of morphological indices (independent variables) – to build an overall Wind Velocity Ratio model using the area-averaged Wind Velocity Ratio (VR) as the dependent variable The development of the models (one for. .. 15 5 Table 5 .18 : Parametric study findings and their explanations for point blocks, mid -level of HV - random configuration 15 8 xvi Table 5 .19 : Parametric study findings and their explanations for point blocks, mid -level of HV - stratified configuration 15 9 Table 5.20: Parametric study findings and their explanations for slab blocks, pedestrian level of HV - random configuration 16 2... explanations for slab blocks, pedestrian level of GBCR - courtyard configuration 14 4 Table 5 .12 : Parametric study findings and their explanations for slab blocks, mid -level of GBCR - random configuration 14 7 Table 5 .13 : Parametric study findings and their explanations for slab blocks, mid -level of GBCR - group configuration 14 8 Table 5 .14 : Parametric study findings and their explanations for . Motivation 1 1. 1 .1 Reduction of Wind Speed 2 1. 1.2 Research Motivation 2 1. 1.3 Developments in this Research Area 4 1. 1.4 Design Standards for Optimal Ventilation 5 1. 1.4 .1 Singapore – HDB. 5.3 .1. 1 .1 Point Blocks, Pedestrian Level 12 5 5.3 .1. 1 .1. 1 Point Blocks, Pedestrian Level - Random Configuration 12 7 5.3 .1. 1 .1. 2 Point Blocks, Pedestrian Level - Group Configuration 12 8 . LEVEL VENTILATION 12 1 5 .1 Introduction 12 1 5.2 Parametric Approach 12 2 5.3 Findings from Parametric Study 12 2 5.3 .1 Gross Building Coverage Ratio (GBCR) 12 2 5.3 .1. 1 Point Blocks 12 5