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Building Energy Model Generation Using a Digital BUILDING ENERGY MODEL GENERATION USING A DIGITAL PHOTOGRAMMETRY-BASED 3D MODEL A Thesis by MOHAMMAD S A A M ALAWADHI Submitted to the Office of Graduate and Professional Studies of Texas A&M University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE Chair of Committee, Wei Yan Committee Members, Jeff Haberl Julian Kang Head of Department, Robert Warden May 2017 Major Subject: Architecture Copyright 2017 Mohammad S A A M Alawadhi ABSTRACT Buildings consume a large amount of energy and environmental resources. At the same time, current practices for whole-building energy simulation are costly and require skilled labor. As Building Energy Modeling (BEM) and simulations are becoming increasingly important, there is a growing need to make environmental assessments of buildings more efficient and accessible. A building energy model is based on collecting input data from the real, physical world and representing them as a digital energy model. Real-world data is also collected in the field of 3D reconstruction and image analysis, where major developments have been happening in recent years. Current digital photogrammetry software can automatically match photographs taken with a simple smartphone camera and generate a 3D model. This thesis presents methods and techniques that can be used to generate a building energy model from a digital photogrammetry-based 3D model. To accomplish this, a prototype program was developed that uses 3D reconstructed data as geometric modeling inputs for BEM. To validate the prototype, an experiment was conducted where a case-study building was selected. Photographs of the building were taken using a small remotely- controlled Unmanned Aerial Vehicle (UAV) drone. Then, using photogrammetry software, the photographs were used to automatically generate a textured 3D model. The texture map, which is an image that represents the color information in the 3D model, was semantically annotated to extract building elements. The window annotations were ii used as inputs for the BEM process. In addition, a number of algorithms were applied to automatically convert both the 3D model and the annotated texture map into geometry that is compatible for a building energy model. Through the prototype, pre-defined templates were used with the geometric inputs to generate an EnergyPlus model (as an example building energy model). The feasibility of this experiment was verified by running a successful energy simulation. The results of this thesis contribute towards creating an automated and user-friendly photo-to-BEM method. iii DEDICATION To my beloved parents. iv ACKNOWLEDGMENTS I would like to express my deepest gratitude to my committee chair, Dr. Wei Yan, for his guidance, encouragement, and support. His knowledge, overwhelming dedication towards his students, and being always available to help them grow academically, has been invaluable for completing my work. I would also like to thank my committee members, Dr. Jeff Haberl and Dr. Julian Kang, for their time and advice throughout this experience. I would also like to extend my thanks to the various people who contributed to the realization of this work, including Dr. Charles Culp, who helped me gain a better understanding of EnergyPlus, and to my fellow graduate students from the BIMSIM Group, who showed me their support by being such a pleasant group. I really enjoyed their acquaintance. Finally, I wish to thank my wonderful family and friends back home, especially the two dearest persons to me, my parents, for their love, and for their encouragement throughout my study. v CONTRIBUTORS AND FUNDING SOURCES 1) Contributors This work was supported by a thesis committee consisting of Professor Wei Yan and Jeff Haberl of the Department of Architecture and Professor Julian Kang of the Department of Construction Science. All work conducted for the thesis was completed independently by the student, under the advisement of Wei Yan of the Department of Architecture. 2) Funding Sources Graduate study was supported by a scholarship from Kuwait University under the supervision of The Cultural Office of the Embassy of the State of Kuwait. vi NOMENCLATURE 2D Two-Dimensional 2.5D Two-and-a-half-Dimensional 3D Three-Dimensional AEC Architecture, Engineering, and Construction BEM Building Energy Modeling BIM Building Information Modeling BREP Boundary Representation CAD Computer-Aided Design CFD Computational Fluid Dynamics CityGML Open standard file format for GIS applications ECM Energy Conservation Measures EPW EnergyPlus file format for weather data f Face of a 3D mesh in an OBJ text file gbXML Open standard file format for engineering analysis applications GIS Geographical Information Systems HD High Definition ID Identification IDF EnergyPlus file format for building description data INP DOE-2.2 file format for building description data IR Infra-Red vii LIDAR Light Detection and Ranging LOD Level Of Detail MTL OBJ companion file format for texture definitions MVS Multi-View Stereo OBIA Object-Based Image Analysis OBJ Open standard file format for 3D geometry data RANSAC Random Sample Consensus REM Rapid Energy Modeling RGB Red, Green, and Blue color model SfM Structure from Motion TMY Typical Meteorological Year ToF Time-of-Flight UAV Unmanned Aerial Vehicle v Vertex of a 3D mesh in an OBJ text file vn Normal of a vertex in an OBJ text file vt Texture coordinate of a vertex in an OBJ text file X, Y, Z Axes in the Cartesian coordinate system x X axis value in the Cartesian coordinate system y Y axis value in the Cartesian coordinate system z Z axis value in the Cartesian coordinate system λ Lambda, a mathematical symbol representing a ratio of an area in the context of Barycentric coordinates viii TABLE OF CONTENTS Page ABSTRACT .......................................................................................................................ii DEDICATION .................................................................................................................. iv ACKNOWLEDGMENTS .................................................................................................. v CONTRIBUTORS AND FUNDING SOURCES ............................................................. vi NOMENCLATURE .........................................................................................................vii TABLE OF CONTENTS .................................................................................................. ix LIST OF FIGURES ..........................................................................................................xii LIST OF TABLES .......................................................................................................... xiv CHAPTER I INTRODUCTION ........................................................................................ 1 1.1 Research Problem ..................................................................................................... 2 1.2 Research Objectives .................................................................................................. 5 1.3 Background ............................................................................................................... 6 1.3.1 Building Energy Modeling (BEM) .................................................................... 6 1.3.2 Building Information Modeling (BIM).............................................................. 6 1.3.3 Image Analysis .................................................................................................. 7 1.4 Methodology ............................................................................................................. 8 1.4.1 Data Collection of a Building Case Study in a Field Survey Using Aerial Digital Photogrammetry ................................................................... 8 1.4.2 Processing Image-based Photogrammetry Data ................................................ 9 1.4.3 Prototyping a Building Geometry Extractor and Validation of the Prototype Through Building Energy Simulation ......................................... 9 1.5 Significance ............................................................................................................ 12 1.6 Outcomes ................................................................................................................ 12 CHAPTER II LITERATURE .......................................................................................... 13 2.1 Data Acquisition Methods ...................................................................................... 13 2.1.1 Laser Scanning ................................................................................................. 13 2.1.2 Digital Photogrammetry .................................................................................. 14 ix Page 2.1.3 Unmanned Aerial Vehicles (UAVs) ................................................................ 16 2.2 3D Geometry Data Structure .................................................................................. 17 2.2.1 3D Meshing...................................................................................................... 17 2.2.1.1 Vectors ..................................................................................................... 18 2.2.2 Texture Mapping.............................................................................................. 18 2.2.2.1 OBJ ..........................................................................................................
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