University of Liege Faculty of Applied Sciences SUSTAINABLE HOUSING IN VIETNAM: CLIMATE RESPONSIVE DESIGN STRATEGIES TO OPTIMIZE THERMAL COMFORT PhD thesis submitted in partial fulfillment of the requirements for the Degree of Doctor in Architecture and Urban planning by Anh Tuan NGUYEN Liège, 2013 Académie Universitaire Wallonie-Europe This document presents the original results of the doctoral research carried out by NGUYEN Anh Tuan, Architect, M.Sc Université de Liège – Faculté des Sciences Appliquées Département Architecture, Géologie, Environnement et Constructions Chemin des Chevreuils 1, Bâtiment B52/3 B-4000 Liège, Belgique natuan@ud.edu.vn; arcnguyenanhtuan@yahoo.com The present thesis has been supervised by the promoter Prof Dr Ir Sigrid Reiter Jury members Prof Dr Ir Jacques Teller Prof Dr Ir Sigrid Reiter Dr Ir Arnaud Evrard Prof Dr Ir Pierre Leclercq Prof Dr Ir André De Herde Prof Dr Khoi Doan-Minh Université de Liège, president Université de Liège, promoter Université Catholique de Louvain, member Université de Liège, member Université Catholique de Louvain, member National University of Civil Engineering (Vietnam), member The research presented in this thesis was financially supported by Ministry of Education and Training of Vietnam (Grant No 624/QÐ-BGDÐT 9/2/2010) and partly by Wallonie Bruxelles International (Grant No 23478/AMG/BE.VN/JP/jp and DWBH/FP/vtd/V084/2011) Copyright © Nguyen Anh Tuan, 2013 All rights reserved ACKNOWLEDGMENTS First of all, I would like to express my greatest thanks to Professor Sigrid Reiter for her guidance and patience over the last three years Her kind support has been key to my academic development, and her research style has had a profound influence on my work Professor Pierre Leclercq (Université de Liège) and Dr Arnaud Evrard (Université Catholique de Louvain), two members of the committee of this thesis, are acknowledged for their valuable consultancy, encouragement and final approval I would like to thank Dr Jiang Yi (Massachusetts Institute of Technology), Professor T Katayama (Kyushu University) for their support of experimental settings and results of the wind tunnel experiments Valuable inputs about CFD from Mathieu Barbason and Dr Sébastien Erpicum are greatly acknowledged The author also appreciates initial support for the use of PLEIADES-COMFIE from Dr Anne Françoise Marique I’m greatly thankful to many anonymous reviewers who have had many contributions to my publications The thermal comfort research in this thesis is completely relied on field survey data from various studies around South-East Asia I would like to express my appreciation to following professors for their donations of field survey data and useful guides: Nuyk HienWong (National University of Singapore); Henry Feriadi (Duta Wacana Christian University); Yufeng Zhang and his survey team (South China University of Technology); Mary Myla Andamon (University of Adelaide); Ibrahim Hussein (Universiti Tenaga Nasional); and other authors in ASHRAE RP-884 database I greatly thank Dr To Mai Xuan Hong (Hochiminh city University of Medicine and Pharmacy) for the support in statistics I sincerely thank Dr Michael Wetter, U.S Lawrence Berkeley National Laboratory, who kindly gave many instructions and GenOpt optimization program I’m so grateful to Professor Carl Mahoney for his instruction to rebuild the Mahoney tables I appreciate Professor Curtis Pedersen (University of Illinois at UrbanaChampaign – EnergyPlus development team) for his guide about the IRT surface used in atrium modeling Louise Regnard, among my best friends, patiently helped me in translating many of my works into English The experimental results of house No 120 Bui Thi Xuan st, Hanoi of Mr Tran Quoc Bao is also acknowledged The U.S Department of Energy, Autodesk, UCLA and the Unit of Econometrics and Applied Statistics of the Joint Research Centre (European Commission) are greatly acknowledged for making EnergyPlus program, AutoCAD 2010 and Ecotect 2011, Climate consultant 5.0 and Simlab 2.0 free of charge, respectively The Faculty of Environment – Danang University of Technology is acknowledged for many useful experimental instruments I would like to thank the Centre for the Preservation and Restoration of Hoian city and the Centre for Heritage and Tourism of Quangnam province for their support and input data of the ancient dwelling No 75 Tran Phu, Hoi An, Vietnam Météonorm (Météotest) is acknowledged for the weather files (free of charge) of many locations in Vietnam National Meteorological and Hydrographical Station - Central Vietnam is acknowledged for the weather data of Danang city during my measuring campaigns The research unit LEMA, Faculty of Applied Sciences, University of Liège within which I have conducted my PhD research since March 2010 consistently gave me supports and many opportunities I am grateful to all members of LEMA, especially Professor Jacques Teller This thesis was financially supported by Ministry of Education and Training of Vietnam (Grant No 624/QÐ-BGDÐT: 9th Feb 2010) and partly by Wallonie Bruxelles International (Grant No 23478/AMG/BE.VN/JP/jp and DWBH/FP/vtd/V084/2011) I would like to thank these institutions for their generous supports I am thankful to my family and friends for their support and encouragement, in particular to my parents who always supported me in the academic career Special thanks go to my wife and my tiny son for providing me with strength and continuous supports through the ups and downs of writing a dissertation ii ABSTRACT Housing issue in Vietnam is still a big concern as in 2008, 72.2% of the existing housing was semi-permanent or temporary and 89.2% of the poor did not have a permanent shelter As a response to sustainability, the global aim of this thesis is to develop design strategies toward comfortable, energy-efficient housing with acceptable building cost Occupants’ thermal comfort is the key assessment criterion throughout the research First of all, the thesis develops a thermal comfort model for Vietnamese people living in naturally ventilated buildings through the data from field surveys around SouthEast Asia This comfort model is then validated by survey data in Vietnam in 2012 A new simple climate analysis tool is developed, used to analyze the climate of regions in question and to draw preliminary design guidelines A comprehensive study on climate responsive design strategies of vernacular housing in Vietnam is also carried out The results to some extend reveal the remaining values of vernacular architecture and provide valuable lessons for modern applications Three most common housing prototypes in Vietnam are selected Afterward a comprehensive framework is implemented to derive thermal performances of typical housing types Various techniques (in situ monitoring, building thermal simulation, CFD and airflow network model, numerical model calibration, parametric simulation method) are employed to improve the thermal performances and natural ventilation of these houses The sensitivity of building performance to the design variables is outlined by Monte Carlo-based sensitivity analysis The thermal performances of the reference cases are optimized using the simulation-based optimization method and the most influential design variables Optimization results show the best combinations of design strategies for each climatic region The performances of the optimal solutions are compared with the references, providing an insight of the efficiency of this approach in building design Finally, the different objectives yielded in this thesis are summarized The possible future extensions of this research are outlined iii TABLE OF CONTENTS ACKNOWLEDGMENTS i ABSTRACT iii TABLE OF CONTENTS iv LIST OF PUBLICATIONS viii LIST OF SYMBOLS AND ABBREVIATIONS ix CHAPTER Introduction 1.1 Global environmental issues and the sustainability movement 1.2 Housing issues in Vietnam - Identifying problems 1.3 Research objectives 1.4 Research hypotheses 10 1.5 Limits of the research 11 1.6 Structure and methodologies of the thesis 12 CHAPTER Literature review 16 2.1 Literature review on the bioclimatic approach in architecture 16 2.1.1 Terms and definitions 16 2.1.2 Bioclimatic architecture - conventional methods and novel approaches 17 2.1.3 Classification of bioclimatic research methodologies 20 2.1.4 The challenges in Vietnam 20 2.2 Literature review on human thermal comfort in built environments 21 2.2.1 Thermal comfort and its role in built environments 21 2.2.2 Human thermal regulation mechanism 22 2.2.3 Comfort temperature in climate-controlled environments 24 2.2.4 Thermal comfort prediction in actual built environments 25 2.2.5 Thermal comfort studies in Vietnam 35 CHAPTER A thermal comfort model for Vietnamese 36 3.1 Study background and the proposed approach 36 3.2 Adaptive thermal comfort model for hot humid South-East Asia 38 3.2.1 Methodology 38 3.2.2 Raw data standardization 41 3.2.3 Results and discussions 43 3.2.4 An adaptive thermal comfort model for South-East Asia 48 iv 3.2.5 Other comfort-related issues 54 3.3 Model validation under conditions of Vietnam 56 3.3.1 The thermal comfort survey in Vietnam 56 3.3.2 Survey data and validation results 59 3.4 Long-term evaluation of the general thermal comfort condition 62 3.5 Implementation of the adaptive model into a building simulation program 63 3.6 Chapter conclusion 64 CHAPTER Climate analysis 66 4.1 An overview about the climate of Vietnam 66 4.1.1 Climatic regions in Vietnam 66 4.1.2 Characteristics of the climate of three climatic regions of Vietnam 69 4.2 Climate analyses using methods developed by some authors 71 4.2.1 Climate analysis by Climate Consultant 5.3 program 72 4.2.2 Climate analysis by Mahoney Tables 73 4.2.3 Discussions 76 4.3 An improved climate-comfort analysis method for hot humid climates using a graphical method and TMY weather data sets 76 4.3.1 Comfort zone for people living in hot humid climates 77 4.3.2 Extended comfort zones using passive cooling and heating strategies 81 4.3.3 Plotting weather data on the Building psychrometric chart 85 4.3.4 Results of the method 88 4.4 Climate analysis using the adaptive comfort model 91 4.5 General conclusions about the climates of Vietnam 93 CHAPTER Thermal performance of typical housing typologies 95 5.1 Identifying typical housing prototypes in Vietnam 95 5.2 The monitoring campaign 96 5.2.1 The selections of case-study houses 96 5.2.2 Monitoring protocol and monitoring results 98 5.2.3 Discussions on the monitoring results 101 5.3 Numerical modeling and simulation of buildings performance 102 5.3.1 Building energy simulation programs and EnergyPlus 102 5.3.2 Airflow prediction in and around buildings using Computational Fluid Dynamics 105 5.4 Modeling the case-study houses in EnergyPlus 119 5.4.1 About Airflow Network model and its role in modeling NV buildings 121 5.4.2 Calculation of wind pressure coefficient using CFD 121 5.5 Calibration of the three EnergyPlus housing models 126 v 5.5.1 Introduction to the calibration approach 126 5.5.2 Criteria to assess the agreement between simulated and measured data 127 5.5.3 Calibration runs 129 5.6 Thermal performance of the case-study houses during a year 139 5.6.1 Thermal comfort analysis 140 5.6.2 Identifying strong and weak points and potential improvements 145 5.7 Chapter conclusion 149 CHAPTER Climate responsive design strategies of vernacular housing 150 6.1 Introduction and background of the study 150 6.2 Materials and methods 151 6.3 Theory, measurement, calculation and results 153 6.3.1 Step 1: Climate zoning and selected sites of the survey 153 6.3.2 Step 2: Collecting data 153 6.3.3 Step 3: Investigation of housing climate responsive design strategies 156 6.3.4 Step 4: Full-scale measurement of micro-climate in a vernacular house 165 6.3.5 Step 5: Whole – year simulation of building performance 170 6.4 Step 6: The lessons given by vernacular architecture - Conclusions 177 CHAPTER Climate responsive design strategies to improve thermal comfort 179 7.1 Improving the thermal performance by a parametric simulation method 179 7.1.1 The effects of various external wall types 179 7.1.2 Thermal insulation for the roof and thermal performance of the houses 181 7.1.3 The effect of color of the external walls 183 7.1.4 The effect of ventilation schemes on thermal performance of the houses 184 7.1.5 Other design strategies to improve thermal performance of the houses 186 7.1.6 Efficiency of the combination of all positive strategies 188 7.2 Design strategies to enhance passive cooling by natural ventilation 190 7.2.1 Theory of passive cooling by natural ventilation 190 7.2.2 Case study on natural ventilation using the CFD technique 195 7.3 Auxiliary strategies to improve building thermal performance 211 7.3.1 Climate responsive heating techniques 211 7.3.2 Climate responsive cooling techniques 212 7.4 Chapter conclusion 214 CHAPTER Combination of design strategies to optimize thermal comfort 215 8.1 Monte Carlo-based sensitivity analysis 215 8.1.1 A brief introduction of sensitivity analysis 215 8.1.2 Methodologies of sensitivity analysis 217 8.1.3 The selected approach of SA for the present study 219 vi 8.1.4 Sensitivity analysis of the EnergyPlus thermal models 222 8.2 Optimizing building thermal performance by numerical optimization 235 8.2.1 An introduction of numerical optimization 235 8.2.2 Definition of an optimization problem and related nominations 237 8.2.3 Optimization methodology 238 8.2.4 Parameters of design and strategies considered in the optimization 240 8.2.5 The choice of optimization algorithms for the present problem 242 8.2.6 The establishment of objective functions 246 8.2.7 Optimization results 249 8.3 Discussions and comparisons 257 8.3.1 Discussions 257 8.3.2 Comparison of the findings of this work with results of earlier studies 260 8.4 Chapter conclusion 262 CHAPTER Conclusions and further works 264 9.1 Original contributions of the thesis 264 9.1.1 A simple climate-comfort analysis tool for hot humid climates 264 9.1.2 An adaptive thermal comfort model for South-East Asia 265 9.1.3 Thermal performance of vernacular housing and current housing typologies in Vietnam 265 9.1.4 A new bioclimatic approach towards sustainable architecture 266 9.2 Conclusions and recommendations 267 9.2.1 Comfort model for Vietnamese 267 9.2.2 The significance of design parameters 267 9.2.3 Climate responsive design for optimal thermal comfort 268 9.2.4 The efficiency of different design methods 270 9.3 Further works 271 9.3.1 Sustainable housing under the perspective of building materials 271 9.3.2 Feasibility of adaptive thermal comfort in climate-controlled buildings 271 9.3.3 Climate responsive solutions for non-residential buildings 272 9.3.4 Passive design towards zero energy buildings in Vietnam 272 9.4 Towards sustainable housing in Vietnam 272 REFERENCES 275 LIST OF FIGURES 286 LIST OF TABLES 292 APPENDIX A 294 APPENDIX B 299 APPENDIX C 304 vii LIST OF PUBLICATIONS The following scientific papers have been published as the result of this thesis: * In ISI journals (indexed by ISI - Thomson Reuters)1: Nguyen, A.T.; Reiter, S The effect of ceiling configurations on indoor air motion and ventilation flow rates, Building and Environment 2011; 46:1211-22 (IF=2.4) Nguyen, A.T.; Tran, Q.B.; Tran, D.Q.; Reiter, S An investigation on climate responsive design strategies of vernacular housing in Vietnam, Building and Environment 2011, 46: 2088-2106 (IF=2.4) Nguyen, A.T.; Reiter, S An investigation on thermal performance of a low cost apartment in Danang, Energy and Buildings 2012, 47:237-246 (IF=2.386) Nguyen, A.T.; Singh, M.K.; Reiter, S An adaptive thermal comfort model for hot humid South-East Asia, Building and Environment 2012, 56:291-300 (IF=2.4) Nguyen, A.T.; Reiter, S A climate analysis tool for passive heating and cooling strategies in hot humid climate based on Typical Meteorological Year data sets, Energy and Buildings 2012, http://dx.doi.org/10.1016/j.enbuild.2012.08.050 (IF=2.386) Nguyen, A.T.; Reiter, S Passive designs and strategies for low-cost housing using simulation-based optimization and different thermal comfort criteria, Journal of Building Performance Simulation 2013, doi:10.1080/19401493.2013.770067 (IF=0.718) * In Proceedings of International Conferences: Nguyen, A.T.; Reiter, S Analysis of passive cooling and heating potential in Vietnam using graphical method and Typical Meteorological Year weather file, in Proceedings CISBAT 2011 International conference, Lausanne, 2011 Nguyen, A.T.; Reiter, S Optimum design of low-cost housing in developing countries using nonsmooth simulation-based optimization, in Proceedings of International conference of Passive and Low Energy Architecture 2012, Lima, 2012 Source: © Thomson Reuters Journal Citation Reports (2012) viii Figure 7-16: Plan of the original apartment (left) and the improved apartment (right) The true North and wind directions in CFD analysis are highlighted in the center 205 Figure 7-17: The 7-storey building, the apartment on the 4th floor and the grid system in the center of the CFD domain 206 Figure 7-18: Velocity contour on the horizontal plan 1.1 m above the floor in the original apartment (left) and the improved apartment (right) The contour keys are shown on the left (From top to bottom: North wind, East wind, South wind and West wind, respectively) 208 Figure 7-19: Static pressure distribution around the openings of the improved apartment in the case of East wind 209 Figure 7-20: Comparison of mean air velocity (of 56 points on the working plan - 1.1 m above the floor) and ventilation flow rates in the original bedrooms and the improved bedrooms 210 Figure 7-21: Examples of an equator –facing façade and Trombe wall 212 Figure 7-22: Roof spray and roof pond in nighttime and day time, respectively – adapted from (Givoni, 1994) 213 Figure 8-1: The full process of a SA using SimLab and EnergyPlus 222 Figure 8-2: Cobwebs plot of 180 input vectors generated by the LHS method 227 Figure 8-3: Sensitivity rankings via the PCC and SRRC – the row house 228 Figure 8-4: Correlations between the roof color and the TDHs and TECs 229 Figure 8-5: Sensitivity rankings via the PCC and SRRC - the detached house 230 Figure 8-6: Non-linear non-monotonic relationship between ventilation strategies and TDHs (a) and strong correlation if the codified names were reordered (b) 231 Figure 8-7: Sensitivity rankings via the PCC and SRRC – the apartment 232 Figure 8-8: Probability distribution of simulation outputs 234 Figure 8-9: Coupling principle between GenOpt and EnergyPlus 239 Figure 8-10: Diagram of the Hooke-Jeeves search logic 245 Figure 8-11: A typical optimization process (AC detached house, cost function [C]) 250 Figure 8-12: Comparison of the TDHs in the NV houses The horizontal line indicates the acceptable threshold of the TDH 251 Figure 8-13: Minimum cost of the NV houses that satisfy thermal comfort criterion 252 Figure 8-14: Optimal LCCs, compared with LCCs of the reference cases 253 Figure 8-15: The simple rectangular housing model (Nguyen & Reiter, 2013) 259 Figure 8-16: Design guides for an isolated rectangular housing model (AC houses use a fixed thermostat and an ‘adaptive’ thermostat) 260 291 LIST OF TABLES Table 1-1: Percentage of the final energy consumption used in commercial and residential buildings in 2004 (Pérez-Lombarda, et al., 2008) Table 1-2: Monthly income per capita by urban and rural region - unit: 1000 VND (At exchange rate of 1USD ≈ 17.000 VND) (CPHSC, 2010) Table 1-3: Living area per capita by type of house, urban-rural region (Unit: m2) Table 1-4: Percentage of house by housing condition, urban - rural area (CPHSC, 2010) Table 2-1: Three major bioclimatic approaches in the evolutional order 20 Table 2-2: ASHRAE and Bedford thermal sensation scales 26 Table 2-3: Thermal sensation prediction by temperature and humidity (adapted from (La Roche, 2012)) 27 Table 2-4: Sensation prediction and neutral temperature of different groups of subjects 27 Table 2-5: Thermal sensation and comfort scale of the two-node model 32 Table 3-1: Summary of the field survey database for the present adaptive model 39 Table 3-2: Mean observed neutral temperature in South-East Asia 47 Table 3-3: The role of Griffiths constant in the establishment of adaptive comfort equation and its correlation R2 50 Table 3-4: Results of some statistical significance tests of some parameters and variables’ attributes in NV buildings 55 Table 3-5: Technical specifications of measuring instruments 58 Table 3-6: Statistical results of the survey 59 Table 3-7: Comparison between predicted and observed comfort temperature 62 Table 4-1: Comfort of the climates of Vietnam and corresponding design guidelines proposed by Climate Consultant 5.3 72 Table 4-2: Design strategies recommended by Mahoney tables 76 Table 4-3: Potential comfort improvement by each strategy 89 Table 4-4: Results of climate analysis by the adaptive comfort model 93 Table 5-1: Basic features of the case-study houses 98 Table 5-2: Details of the boundary conditions and computational parameters 115 Table 5-3: Wind pressure coefficient of the row house 124 Table 5-4: Wind pressure coefficient of the detached house 124 Table 5-5: Wind pressure coefficient of the apartment 125 Table 5-6: Row house calibration runs 129 Table 5-7: Detached house calibration runs 133 292 Table 5-8: The apartment - calibration runs 136 Table 5-9: Classification system of thermal performance for NV buildings 141 Table 5-10: Thermal performance in a year of the row houses 141 Table 5-11: Thermal performance in a year of the detached house (only major thermal zones of the house were considered) 141 Table 5-12: Thermal performance in a year of the apartment 142 Table 6-1: General information about the houses in question 155 Table 6-2: Types of materials used in the houses investigated 155 Table 6-3: Most used materials and their properties 156 Table 6-4: Qualitative investigation of bioclimatic design strategies used in traditional architecture in Vietnam 158 Table 6-5: Measurement instruments and their properties 166 Table 6-6: Vietnam building code of natural illumination for residential facilities 166 Table 6-7: Characteristics of air flow field through the model 171 Table 7-1: Retrofit choices for the external walls and their corresponding U-values 180 Table 7-2: Retrofit choices for the roof and their corresponding U-values 182 Table 7-3: Description of the ventilation strategies 184 Table 7-4: Recommended changes for the houses to obtain improved performances 188 Table 7-5: Thermal classification of the improved houses 190 Table 7-6: Recommendations and rules of thumb for better natural ventilation 193 Table 7-7: Mean wind velocity in the main occupied spaces 198 Table 7-8: Mean air velocity and ventilation flow rate in the bedrooms 209 Table 8-1: Common ventilation schemes applied in NV buildings 222 Table 8-2: Variables considered in the SA of the NV row house 223 Table 8-3: Variables considered in the SA of the AC row house 225 Table 8-4: Statistical features of the samples of simulation outputs 234 Table 8-5: Design parameters used in the optimization of the NV apartment 240 Table 8-6: Design parameters used in the optimization of the AC apartment 241 Table 8-7: Other costs and fees (exchange rate 1$ = 20840VND) 248 Table 8-8: Lowest values of the objective functions found in 27 optimization runs 249 Table 8-9: Time and convergence issues in the optimization of the detached house 250 Table 8-10: Thermal classification of the optimal houses 252 Table 8-11: Design guides for optimal thermal comfort in NV residential buildings 254 Table 8-12: Design guides for low-cost house with acceptable indoor thermal comfort 256 Table 8-13: Design guides for AC residential buildings 257 Table 8-14: Findings of the present work and those of other authors and tools 261 Table 9-1: Design guides and recommendations for building renovation 268 Table 9-2: Optimal combinations of design variables for new buildings 269 293 APPENDIX A VARIABLES NATURES AND RANGES IN THE SENSITIVITY ANALYSIS Table A-1: The NV detached house Description of input variables tested in the SA Var name Variable type Probability distribution function Range* Ventilation strategy (open or close the openings) x1 Discrete 400 – 409, step = Max equipment power – all zones Max equipment power -kitchen x2 Continuous With weight factors Normal x3 Continuous Normal Thickness wooden floor x4 Continuous Uniform Insulation thickness ground floor x5 Continuous Uniform 0.01 – 0.025 m – 0.03 m External wall type x6 Discrete With weight factors 100 – 106, step = Thickness roof insulation x7 Continuous Uniform – 0.04 m Thickness of internal partitions x8 Continuous Uniform 0.08 - 0.25 m Brick density (external wall) x9 Continuous Normal Mean Standard deviation 120 W 20 400 W 40 1600 kg/m³ 0.07 m 200 0.008 Thickness - brick x10 Continuous Normal External wall color x11 Continuous Uniform Thickness ceiling concrete slab x12 Continuous Normal 0.12 m 0.01 Density ceiling concrete slab x13 Continuous Normal 2700 kg/m³ 200 0.035 W/m.K 0.003 0.25 - 0.85 Roof color x14 Continuous Uniform Conductivity EPS insulation x15 Continuous Normal Window type x16 Discrete Uniform 200; 201; 202; 203 Thickness of internal mass x17 Discrete With weight factors Length of window overhang x18 Continuous Uniform 0.1; 0.15; 0.2; 0.25; 0.3 m – 0.8 m Max number of occupant x19 Discrete Uniform 294 0.25 - 0.85 3; 4; 5; 6; Probability distribution function Range* Mean Standard deviation Description of input variables tested in the SA Var name Variable type Power of gas stove x20 Continuous Normal 500 W 200 Crack of the roof x21 Continuous Normal 0.065 kg/m.s 0.01 Crack window - bedrooms x22 Continuous Uniform 0.001 – 0.005 kg/m.s Crack window – other rooms x23 Continuous Uniform 0.001 – 0.006 kg/m.s Discharge coeff bedrooms x24 Continuous Uniform 0.18 – 0.35 Mean Standard deviation -27° 10 Discharge coeff other rooms x25 Continuous Uniform 0.2 – 0.4 North windows’ height x26 Continuous Uniform 2.6 – 3.2 m South windows’ height x27 Continuous Uniform 2.6 – 3.2 m East windows’ height x28 Continuous Uniform 2.6 – 3.2 m West windows’ height x29 Continuous Uniform Table A-2: The AC detached house Range* Description of input variables tested in the SA Var name Variable type Building azimuth x1 Continuous Probability distribution function Normal Max equipment power – all zones Max equipment power -kitchen x2 Continuous Normal 120 W 20 x3 Continuous Normal 400 W 40 Thickness wooden floor x4 Continuous Uniform Insulation thickness ground floor x5 Continuous Uniform 0.01 – 0.025 m – 0.03 m External wall type x6 Discrete With weight factors 100 – 106, step = Thickness roof insulation x7 Continuous Uniform – 0.04 m Thickness of internal partitions x8 Continuous Uniform 0.08 - 0.25 m Brick density (external wall) x9 Continuous Normal 200 Thickness - brick x10 Continuous Normal 1600 kg/m³ 0.07 m 0.008 External wall color x11 Continuous Uniform Thickness ceiling concrete slab x12 Continuous Normal 0.12 m 0.01 Density ceiling concrete slab x13 Continuous Normal 2700 kg/m³ 200 Roof color x14 Continuous Uniform Conductivity EPS insulation x15 Continuous Normal 0.035 W/m.K 0.003 295 0.25 - 0.85 0.25 - 0.85 Mean Standard deviation Normal 500 W 200 Continuous Normal 0.01 m³/s 0.002 x22 Continuous Normal 0.01 m³/s 0.002 x23 Continuous Normal 0.01 m³/s 0.002 Infiltration remaining zones x24 Continuous Normal 0.01 m³/s 0.002 HVAC Cooling setpoint x25 Continuous Uniform 26° - 27.5° North windows’ height x26 Continuous Uniform 2.6 – 3.2 m South windows’ height x27 Continuous Uniform 2.6 – 3.2 m East windows’ height x28 Continuous Uniform 2.6 – 3.2 m West windows’ height x29 Continuous Uniform 2.6 – 3.2 m HVAC Fan blades efficiency x30 Continuous Uniform 0.6 – 0.7 HVAC Fan motor efficiency x31 Continuous Uniform 0.8 – 0.9 HVAC Cooling coil COP x32 Continuous Normal 0.13 HVAC Heating coil efficiency x33 Continuous Uniform 0.95 - HVAC Heating setpoint x34 Continuous Uniform 20° – 23° Mean Standard deviation 200 W 22 Description of input variables tested in the SA Var name Variable type Probability distribution function Range* Window type x16 Discrete Uniform 200; 201; 202; 203 Thickness of internal mass x17 Discrete With weight factors Length of window overhang x18 Continuous Uniform 0.1; 0.15; 0.2; 0.25; 0.3 m – 0.8 m Max number of occupant x19 Discrete Uniform Power of gas stove x20 Continuous Infiltration of the attic x21 Infiltration bedrooms Infiltration kitchen 3; 4; 5; 6; Table A-3: The NV apartment Item Var name Variable type Probability distribution function Range* Ventilation strategy x1 Discrete 400 – 409, step = Max equipment power – living room x2 Continuous With weight factors Normal Max equipment power – bedroom x3 Continuous Normal 60 W 10 Max equipment power – bedroom x4 Continuous Normal 80 W 12 External wall type x5 Discrete With weight factors 100 – 105, step = Size overhang windows bedroom Size of window bedroom x6 Continuous Uniform 0.1- 0.8 m x7 Continuous Uniform – 2.2 m 5.2-6.4 Size of window bedroom x8 Continuous Uniform – 2.2 m 2-3.2 296 Mean Standard deviation 1600 kg/m³ 200 Normal 0.09 m 0.01 Normal 2600 kg/m³ 200 Continuous Normal 0.035 W/m.K 0.003 x15 Discrete Uniform 200; 201; 202; 203 Thickness of brick internal mass Max number of occupant x16 Discrete x17 Discrete With weight factors Uniform 10; 15; 20; 25 mm 2; 3; Item Var name Variable type Probability distribution function Brick density (external wall) x9 Continuous Normal Thickness - brick x10 Continuous Uniform External wall color x11 Continuous Uniform Concrete slab thickness x12 Continuous Concrete slab density x13 Continuous EPS Insulation conductivity x14 Window type Range* 0.06 – 0.1 m 0.25-0.85 Power of gas stove x18 Continuous Normal 400 W 100 Discharge coefficient windows - bedroom Crack of windows - bedroom x19 Continuous Normal 0.4 0.1 x20 Continuous Uniform Discharge coefficient window – living room x21 Continuous Normal 0.3 0.08 Crack of window – living room x22 Continuous Uniform Discharge coefficient door – living room Crack of door – living room x23 Continuous Normal 0.35 0.08 x24 Continuous Uniform 0.003 – 0.008 kg/m.s Variable type Probability distribution function Range* Mean Standard deviation 0.0040.014 kg/m.s 0.003 – 0.008 kg/m.s Table A-4: The AC apartment Item Var name Building azimuth x1 Continuous Normal 135° 10 Max equipment power – living room x2 Continuous Normal 200 W 22 Max equipment power – bedroom x3 Continuous Normal 60 W 10 Max equipment power – bedroom External wall type x4 Continuous Normal 80 W 12 x5 Discrete With weight 297 100 – 105, Item Var name Variable type Range* Mean Size overhang windows bedroom x6 Continuous Probability distribution function factors Uniform Size of window bedroom x7 Continuous Uniform – 2.2 m 5.2-6.4 Size of window bedroom x8 Continuous Uniform – 2.2 m 2-3.2 Brick density (external wall) x9 Continuous Normal Thickness - brick x10 Continuous Uniform External wall color x11 Continuous Uniform Concrete slab thickness x12 Continuous Concrete slab density x13 EPS Insulation conductivity step = 0.2- 0.8 m Standard deviation 1600 kg/m³ 200 Normal 0.09 m 0.01 Continuous Normal 2600 kg/m³ 200 x14 Continuous Normal 0.035 W/m.K 0.003 Window type x15 Discrete Uniform 200; 201; 202; 203 Thickness of brick internal mass x16 Discrete With weight factors 10; 15; 20; 25 mm Max number of occupant x17 Discrete Uniform 2; 3; Power of gas stove x18 Continuous Normal 400 W 100 Infiltration x19 Continuous Uniform 0.25 – 0.5 ACH HVAC Heating setpoint x20 Continuous Uniform 20° - 23° HVAC Cooling setpoint x21 Continuous Uniform 26° - 27.5° HVAC Fan blades efficiency x22 Continuous Uniform 0.6 – 0.7 0.8 – 0.9 0.13 HVAC Fan motor efficiency x23 Continuous Uniform HVAC Cooling coil COP HVAC Heating coil efficiency x24 x25 Continuous Continuous Normal Uniform 298 0.06 – 0.1 m 0.25-0.85 0.95 - APPENDIX B OPTIMIZATION PARAMETERS Table B-1: Design parameters used in the optimization of the NV row house Numerical (continuous) variables and their variation ranges Design parameter Opt variable Min value Initial value Max value Step size Number of case Solar absorptance – external wall [dimensionless] x1 0.25 0.35 0.75 0.1 Solar absorptance – roof [dimensionless] x2 0.25 0.35 0.75 0.1 Crack infiltration - Opening level 1[kg/s-m] x3 0.004 0.008 0.012 0.002 Crack infiltration - Opening level [kg/s-m] x4 0.004 0.006 0.012 0.002 Opening sizing factor – roof attic [kg/s-m] x5 0.2 0.4 1.0 0.2 Width - Front window (height = 1.9m) [m] x6 1.0 2.0 2.2 0.2 Width - Entrance door (height = 2.9m) [m] x7 1.6 3.2 3.6 0.4 Width - Backward window level (height = 1.2m) [m] x8 1.5 0.5 Length - Front facade shading device [m] x9 0.05 0.05 0.65 0.2 Categorical design options and strategies (discrete variables) Design parameter Design choices Opt variable x10 Discrete value 100* Item cost ($/m2) 20 220mm brick wall with no gap 101 28 220mm brick wall with air gap 2cm 102 29 220mm brick wall with 1cm central EPS 103 30 220mm brick wall with 2cm central EPS 104 32.5 220mm brick wall with 3cm central EPS 105 35 110mm two-side plaster brick wall External walls 220mm brick wall with 4cm central EPS 106 38 200* 43 Bronze film glazed 6mm - 201 60 Double clear glazed with air gap 6mm 202 90 Double bronze film glazed with air gap 6mm Double reflective glazed - 13mm Argon 203 115 204 135 300* 11 Corrugated metal roof + 1cm insulation 301 13.5 Corrugated metal roof + cm insulation 302 15 Clear glazed 6mm Window glazing type x11 Corrugated metal roof Roof types x12 299 Number of case 5 Ventilation strategy Ground floor types Corrugated metal roof + cm insulation 303 16.5 Corrugated metal roof + cm insulation 304 18.5 From 400, 401, 402*, , 409 (see details of these ventilation strategies in Table 7-3) x13 No cost 10 Concrete slab + ceramic tile finish x14 500* 34 Concrete slab+ 1cm insulation + wooden tile finish 501 43.5 Concrete slab+ 2cm insulation + wooden tile finish 502 45 Concrete slab+ 3cm insulation + wooden tile finish 503 47 600* 20 Thermal mass 170mm thickness Thermal mass 240mm thickness 601 602 26 31 Thermal mass 310mm thickness 603 36.5 Thermal mass 100mm thickness Internal thermal mass x15 *: Initial value The search-space includes x 42 x 57 x 62 x 72 x 10 ≈ 6.62 x 1010 candidate solutions Table B-2: Design parameters used in the optimization of the AC row house Numerical (continuous) variables and their variation ranges Design parameter Opt variable x1 Min value 0.25 Initial value 0.35 Max value 0.75 Step size 0.1 Number of case Solar absorptance – roof [dimensionless] x2 0.25 0.35 0.75 0.1 Total infiltration - level 1[kg/s-m] x3 0.008 0.01 0.018 0.002 Total infiltration - level [kg/s-m] x4 0.004 0.008 0.012 0.002 Total infiltration - bedroom [kg/s-m] x5 0.004 0.006 0.012 0.002 Width - Front window (height = 1.9m) [m] x6 1.0 2.0 2.2 0.2 Width - Entrance door (height = 2.9m) [m] x7 1.6 3.2 3.6 0.4 Width - Backward window level (height = 1.2m) [m] x8 1.5 0.5 Length - Front facade shading device [m] x9 0.05 0.05 0.65 0.2 Solar absorptance – external wall [dimensionless] Categorical design options and strategies (discrete variables) Design parameter Design choices Opt variable Discrete value Item cost ($/m2) Number of case x10 100* 20 220mm brick wall with no gap 101 28 220mm brick wall with air gap 2cm 102 29 220mm brick wall with 1cm central EPS 103 30 220mm brick wall with 2cm central EPS 104 32.5 220mm brick wall with 3cm central EPS 105 35 110mm two-side plaster brick wall External walls 300 220mm brick wall with 4cm central EPS 106 38 200* 43 Bronze film glazed 6mm - 201 60 Double clear glazed with air gap 6mm 202 90 Double bronze film glazed with air gap 6mm 203 115 Clear glazed 6mm Window glazing type x11 Double reflective glazed - 13mm Argon 204 135 300* 11 Corrugated metal roof + 1cm insulation 301 13.5 Corrugated metal roof + cm insulation 302 15 Corrugated metal roof + cm insulation 303 16.5 Corrugated metal roof + cm insulation 304 18.5 500* 34 Concrete slab+ 1cm insulation + wooden tile finish 501 43.5 Concrete slab+ 2cm insulation + wooden tile finish 502 45 Concrete slab+ 3cm insulation + wooden tile finish Thermal mass 100mm thickness 503 47 600* 20 Thermal mass 170mm thickness 601 26 Thermal mass 240mm thickness 602 31 Thermal mass 310mm thickness 603 36.5 Corrugated metal roof Roof types x12 Concrete slab + ceramic tile finish Ground floor types Internal thermal mass x13 x14 *: Initial value The search-space includes x 42 x 56 x 63 x 72 4 ≈ 7.94 x 109 candidate solutions Table B-3: Design parameters used in the optimization of the NV detached house Numerical (continuous) variables and their variation ranges Design parameter Opt variable x1 Min value 0.25 Initial value 0.35 Max value 0.75 Step size 0.1 Number of case Solar absorptance – roof [dimensionless] x2 0.25 0.35 0.75 0.1 Crack infiltration – window bedrooms [kg/s-m] x3 0.002 0.002 0.008 0.002 Crack infiltration – window other rooms [kg/s-m] x4 0.002 0.002 0.008 0.002 Crack infiltration – the roof attic [kg/s-m] x5 0.02 0.06 0.1 0.02 Height – East windows [m] x6 1.2 1.6 1.8 0.2 Height – West windows [m] x7 1.2 1.6 1.8 0.2 Height – North and South windows [m] x8 1.2 1.6 1.8 0.2 Length – East window overhang [m] x9 0.2 0.6 0.8 0.2 Length – West window overhang [m] x10 0.2 0.6 0.8 0.2 Solar absorptance – external wall [dimensionless] Categorical design options and strategies (discrete variables) Design parameter Design choices Opt variable 301 Discrete value Item cost ($/m2) Number of case 110mm two-side plaster brick wall External walls x11 100 20 220mm brick wall with no gap 101* 28 220mm brick wall with air gap 2cm 102 29 220mm brick wall with 1cm central EPS 103 30 220mm brick wall with 2cm central EPS 104 32.5 220mm brick wall with 3cm central EPS 105 35 220mm brick wall with 4cm central EPS 106 38 200* 43 Bronze film glazed 6mm - 201 60 Double clear glazed with air gap 6mm 202 90 Double bronze film glazed with air gap 6mm 203 115 Double reflective glazed - 13mm Argon 204 135 300* 11 Corrugated metal roof + 1cm insulation 301 13.5 Corrugated metal roof + cm insulation 302 15 Corrugated metal roof + cm insulation 303 16.5 Corrugated metal roof + cm insulation 304 18.5 Clear glazed 6mm Window glazing type x12 Corrugated metal roof Roof types Ventilation strategy Ground floor types Internal thermal mass x13 5 From 400, 401, 402*, , 409 (see details of these ventilation strategies in Table 7-3) x14 400 to 409 No cost 10 Concrete slab + ceramic tile finish x15 500 34 Concrete slab+ 1cm insulation + wooden tile finish 501* 43.5 Concrete slab+ 2cm insulation + wooden tile finish 502 45 Concrete slab+ 3cm insulation + wooden tile finish Thermal mass 100mm thickness 503 47 600* 20 Thermal mass 170mm thickness 601 26 Thermal mass 240mm thickness 602 31 Thermal mass 310mm thickness 603 36.5 x16 *: Initial value The search-space includes x 42 x 57 x 62 x 72 x 10 ≈ 6.62 x 1010 candidate solutions Table B-4: Design parameters used in the optimization of the AC detached house Numerical (continuous) variables and their variation ranges Design parameter Opt variable Min value Initial value Max value Step size Number of case Solar absorptance – external wall [dimensionless] x1 0.25 0.35 0.75 0.1 Solar absorptance – roof [dimensionless] x2 0.25 0.35 0.75 0.1 Infiltration bedroom [m³/s] x3 0.002 0.006 0.01 0.002 302 Infiltration other zone [m³/s] x4 0.002 0.006 0.01 0.002 Infiltration – roof attic [m³/s] x5 0.004 0.004 0.01 0.002 Height – East windows [m] x6 1.2 1.6 1.8 0.2 Height – West windows [m] x7 1.2 1.6 1.8 0.2 Height – North and South windows [m] x8 1.2 1.6 1.8 0.2 Length – East window overhang [m] x9 0.2 0.6 0.8 0.2 Length – West window overhang [m] x10 0.2 0.6 0.8 0.2 Categorical design options and strategies (discrete variables) Design choices Design parameter Opt variable 110mm two-side plaster brick wall External walls x11 20 28 220mm brick wall with air gap 2cm 102 29 220mm brick wall with 1cm central EPS 103 30 220mm brick wall with 2cm central EPS 104 32.5 220mm brick wall with 3cm central EPS 105 35 220mm brick wall with 4cm central EPS 106 38 200* 43 Bronze film glazed 6mm - 201 60 Double clear glazed with air gap 6mm 202 90 Double bronze film glazed with air gap 6mm Double reflective glazed - 13mm Argon 203 115 204 135 x12 300* 11 Corrugated metal roof + 1cm insulation x13 301 13.5 Corrugated metal roof + cm insulation 302 15 Corrugated metal roof + cm insulation 303 16.5 304 18.5 500 34 Concrete slab+ 1cm insulation + wooden tile finish 501* 43.5 Concrete slab+ 2cm insulation + wooden tile finish 502 45 Concrete slab+ 3cm insulation + wooden tile finish 503 47 600* 20 Thermal mass 170mm thickness 601 26 Thermal mass 240mm thickness 602 31 Thermal mass 310mm thickness 603 36.5 Concrete slab + ceramic tile finish x14 Thermal mass 100mm thickness Internal thermal mass 100 Corrugated metal roof + cm insulation Ground floor types Number of case 101* Corrugated metal roof Roof types Item cost ($/m2) 220mm brick wall with no gap Clear glazed 6mm Window glazing type Discrete value x15 *: Initial value The search-space includes x 42 x 56 x 63 x 72 303 5 4 ≈ 7.94 x 109 candidate solutions APPENDIX C DETAILS OF THE OPTIMIZATION RESULTS Table C-1: Optimization results of the NV houses – objective function [A] Hanoi Danang Hochiminh Row house Detached house Apart Row house Detached house Apart Row house Detached house Apart x1 0.2625 0.75 0.25 0.25 0.75 0.25 0.25 0.25 0.25 x2 0.25 0.4125 0.004 0.25 0.25 0.004 0.25 0.25 0.004 x3 0.004 0.002 0.008 0.004 0.002 0.006 0.004 0.002 0.008 x4 0.004 0.002 1.2 0.004 0.002 1.2 0.004 0.004 1.2 x5 0.2 0.02 1.2 0.225 0.02 1.2 0.06 1.2 x6 1.2 0.8 1.2 0.4 1.2 0.8 x7 1.6 1.2 0.8 1.6 1.2 0.8 1.6 1.2 0.8 x8 1.2 0.6 1.2 0.4 1.03125 1.2 0.6 x9 0.65 0.8 0.55 0.65 0.8 0.2 0.65 0.8 0.4 x10 106 0.2 106 106 0.25 106 106 0.8 106 x11 204 106 204 204 106 204 204 106 204 x12 304 204 406 304 204 406 304 204 401 x13 406 304 603 406 304 603 407 304 603 x14 500 406 500 406 500 403 x15 603 500 603 500 603 500 x16 603 603 603 Table C-2: Optimization results of the NV houses – objective function [B] Hanoi Row house Detached house x1 x2 No solution Danang Hochiminh Apart Row house Detached house Apart Row house Detached house Apart 0.25 0.35 0.35 0.25 0.25 0.25 0.25 0.004 0.25 0.25 0.008 0.25 0.25 0.008 x3 0.004 0.012 0.004 0.006 0.004 0.004 0.008 x4 1.2 0.004 0.008 1.4 0.012 0.008 1.2 x5 1.2 0.6 0.08 1.2 0.04 1.2 x6 0.1 1.2 1.2 x7 1.6 1.2 1.6 1.2 304 Hanoi Danang Hochiminh Apart Row house Detached house Apart Row house Detached house Apart 0.2 1.2 0.2 1.2 0 0.05 0.2 0.2 0.05 0.2 104 100 0.2 100 100 0.2 100 x11 204 200 100 200 200 100 200 x12 406 300 200 406 300 200 401 x13 600 408 301 600 409 300 600 x14 500 406 500 406 x15 600 500 600 500 Row house Detached house x8 x9 x10 No solution x16 600 600 Table C-3: Optimization results of the AC houses – objective function [C] Hanoi Danang Hochiminh Row house Detached house Apart Row house Detached house Apart Row house Detached house Apart x1 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 x2 0.25 0.25 0.004 0.25 0.25 0.004 0.25 0.25 0.004 x3 0.008 0.002 0.029 0.008 0.002 0.029 0.008 0.002 0.029 x4 0.004 0.002 1.2 0.004 0.002 1.2 0.004 0.002 1.2 x5 0.004 0.004 1.2 0.004 0.01 1.2 0.004 0.004 1.2 x6 1.2 0.8 1.2 0.8 1.2 0.8 x7 1.6 1.2 0.8 1.6 1.2 0.8 1.6 1.2 0.8 x8 1.2 1.2 1.2 x9 0.05 0.2 0.05 0.2 0.05 0.2 x10 106 0.2 105 104 0.2 102 106 0.2 106 x11 204 106 204 204 104 204 204 106 204 x12 304 204 600 304 204 600 304 204 600 x13 x14 500 600 304 500 500 600 304 500 500 600 304 500 x15 600 600 305 600 [...]... hypothesis according to which the common housing design in Vietnam can be improved to provide better thermal comfort and to consume less energy The solutions obtained will be a consistent response towards sustainable housing in Vietnam Other research hypotheses are also outlined below The 1st hypothesis: Many studies have pointed out that thermal conditions required for human comfort in NV buildings are not... climatology has to provide necessary information on the local climate Finally, a rational architectural solution is proposed based on the engineering sciences (Olgyay, 1963) Climate responsive design strategies are simply the concretization of the bioclimatic approach in building design practice Today, climate responsive design has become a cornerstone to achieve more sustainable buildings Climate responsive. .. the thermal comfort condition of Vietnamese, corresponding to each climatic region, by using both predictive models and field surveys on thermal comfort; - Identifying strengths and weaknesses of the current housing design in Vietnam through an investigation on thermal performance of the current housing stock; - Discovering our ancestors’ wisdom underlining the design principles of traditional and vernacular... difficulty in combining sustainability requirements with many other design constraints and criteria To fill this gap, this thesis is aimed to develop design solutions towards sustainable housing in Vietnam based on a comprehensive approach The global aim of this research is to improve the quality of living environment and occupant’s comfort while ensuring acceptable cost, reducing building energy consumption... Many other comfort related issues are also discussed Chapter 4: In this chapter, the climates of Vietnam are first described and categorized into three major climatic regions A new simple climate analysis tool is developed in order to analyze the climate of these 3 regions and to draw preliminary design guidelines This tool is also applied in CHAPTER 6 to evaluate thermal comfort of some indoor conditions... consumption and minimizing adverse effects of buildings on the natural environment by promoting applications of advances in building science This thesis cannot, of course, cover all the aspects of sustainable housing Instead, it focuses on with the most sensitive aspect that challenges architects and engineers in Vietnam: climate responsive design strategies for human thermal comfort and energy savings A study... and building engineers to define an indoor environment in which a major part of building occupants will find thermally comfortable Thermal comfort is therefore directly related to the issue of occupants’ satisfaction, health and productivity Furthermore, the comfort range given by a thermal comfort standard is usually used to establish the HVAC thermostat in AC buildings Consequently, thermal comfort. .. achieved have to be adapted to the context of Vietnam through the effective use of building materials, the great attention to climate responsive design and intelligent combination of various design parameters All solutions must consistently satisfy requirements of sustainable development To obtain this target, the following specific aims need to be achieved: - Good understanding of the thermal comfort condition... simulation method in building design practice Particularly, with the raised concern on energy consumption, Hyde proposed to redefine the terminology “bioclimatic housing according to which “energy efficiency” is now considered as the central issue in the design of more efficient building systems, rather than examining on thermal comfort and passive elements of a building This means that climate responsive. .. their applicability in modern housing development; 9 Chapter 1: Introduction - Developing passive solutions to improve thermal performance of the current design, based on required thermal conditions for Vietnamese; and quantifying the effectiveness of these solutions; - Successfully providing general guidelines and recommendations for housing design towards comfortable and sustainable architecture