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研究生： 楊明勝
Thang Minh Duong
論文名稱： APPROXIMATE ESTIMATE OF INDOOR THERMAL AND WIND SPATIAL DISTRIBUTION
APPROXIMATE ESTIMATE OF INDOOR THERMAL AND WIND SPATIAL DISTRIBUTION
指導教授： 呂守陞
Sou-Sen Leu
口試委員: 楊亦東
I-Tung Yang
陳鴻銘
Hung-Ming Chen
學位類別： 碩士
Master
系所名稱： 工程學院 - 營建工程系
Department of Civil and Construction Engineering
論文出版年： 2018
畢業學年度： 106
語文別： 英文
論文頁數： 103
中文關鍵詞： Natural ventilation simulation 、Thermal simulation 、Computational Fluid Dynamic
外文關鍵詞： Natural ventilation simulation, Thermal simulation, Computational Fluid Dynamic
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    • As urbanization is speeding all over the world, buildings have responsible for 20% to 40% of global energy consumption and more than 30% of global greenhouse gas emission. With energy efficient designs, buildings can potentially reduce their energy consumption up to 50%, thus climate change improvement can be realized. Recently, several green building rating systems developed as assessment tools to assess the sustainable level of buildings. In many green building rating systems, energy and indoor environmental quality are the top two categories that contributed into the credit points. Those green building rating tools encourages energy efficient designs through optimized thermal performance, incorporating natural ventilation and energy efficient technologies. Natural ventilation is crucial for conserving the energy, reducing carbon emission, and improving the comfort level of the indoor air quality and the built environment. To optimize the natural ventilation and air-conditioning design in the early stage of building design, simulation is the only way. Computational Fluid Dynamic is increasingly being used as a tool for the analysis of outdoor and indoor air flow and thermal conditions. For natural ventilation and thermal simulation combines modeling layout, design variable and also setting conditions, running simulation accounts for lots of time.
    The goal of this research is to provide the raw data for building designer, researcher and also calculate the approximate equation to predict others data with the highest accurate as much as possible. This research uses different building layouts, opening ratios, shading coefficients, materials as the design variable to run simulation.

    As urbanization is speeding all over the world, buildings have responsible for 20% to 40% of global energy consumption and more than 30% of global greenhouse gas emission. With energy efficient designs, buildings can potentially reduce their energy consumption up to 50%, thus climate change improvement can be realized. Recently, several green building rating systems developed as assessment tools to assess the sustainable level of buildings. In many green building rating systems, energy and indoor environmental quality are the top two categories that contributed into the credit points. Those green building rating tools encourages energy efficient designs through optimized thermal performance, incorporating natural ventilation and energy efficient technologies. Natural ventilation is crucial for conserving the energy, reducing carbon emission, and improving the comfort level of the indoor air quality and the built environment. To optimize the natural ventilation and air-conditioning design in the early stage of building design, simulation is the only way. Computational Fluid Dynamic is increasingly being used as a tool for the analysis of outdoor and indoor air flow and thermal conditions. For natural ventilation and thermal simulation combines modeling layout, design variable and also setting conditions, running simulation accounts for lots of time.
    The goal of this research is to provide the raw data for building designer, researcher and also calculate the approximate equation to predict others data with the highest accurate as much as possible. This research uses different building layouts, opening ratios, shading coefficients, materials as the design variable to run simulation.

    ACKNOWLEDGEMENT ii ABSTRACT iv Table of contents v List of figures ix List of tables xii CHAPTER 1 INTRODUCTION 1 1.1 Research background 1 1.2 Research scope, motivation and objectives, and assumptions 3 1.2.1 Research scope 3 1.2.2 Research motivation and objectives 4 1.2.3 Research assumptions 4 1.3 Research outline 5 CHAPTER 2 LITERATURE REVIEW 7 2.1 The use of Computational Fluid Dynamics in Building Science 8 2.1.1 Using CFD in simulating natural ventilation 8 2.1.2 Using CFD in simulating Solar heating 10 2.2 Kriging 14 CHAPTER 3 RESEARCH METHODOLOGY 16 3.1 Taguchi method 17 3.2 Simulation software – an overview 19 3.2.1 Energy simulation 19 3.2.2 Natural ventilation simulation 20 3.2.3 Thermal simulation 22 3.3 Computational fluid dynamic CFD – Autodesk 22 3.3.1 Natural Ventilation analysis 23 3.3.2 Thermal analysis 24 3.4 Data analysis method 25 3.4.1 Universal Kriging for 3D Spatial Data 25 3.4.2 Multi regression 29 Multi linear regression 29 Multi non – linear regression 29 3.5 Error measurement 30 CHAPTER 4 MODELLING AND PARAMETERS 32 4.1 Research content and parameters 33 4.1.1 Apartment area type 33 4.1.2 Openable surface and orientation 36 4.1.3 Opening ratio 41 4.1.4 Shading coefficient 42 4.1.5 Material properties 43 Wall properties 45 Glass properties 45 4.2 Define parameters for simulation 46 4.2.1 Defining layout 46 4.2.2 Defining material 51 4.2.3 Defining Boundary Condition 51 Boundary conditions for natural ventilation 51 Boundary conditions for Solar heat gain simulation 54 4.2.4 Creating the mesh and solving parameters 55 4.2.5 Result plane 56 CHAPTER 5 DATA ANALYSIS AND POST PROCESSING 58 5.1 Analyzing CFD Autodesk output data 58 5.2 Baseline function 59 5.2.1 Natural ventilation 59 5.2.2 Solar heating 62 5.3 Adjustment function 64 5.3.1 Natural ventilation 65 5.4 Solar heating effected by natural ventilation 77 5.5 Validation equation 78 5.5.1 Baseline function 78 Natural ventilation 78 Solar heating 79 5.5.2 Adjustment function 80 5.6 Application of results 82 5.6.1 Natural ventilation 82 5.6.2 Solar heating 83 CHAPTER 6 CONCLUSION AND FUTURE RESEARCH 84 6.1 Conclusion 84 6.2 Future researches 84 REFERENCES 86

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