TY - BOOK AU - Kensek,Karen M. AU - Noble,Douglas E. TI - Building information modeling: BIM in current and future practice SN - 9781118766613 (ePub) AV - TH438.13 U1 - 690.0285 23 PY - 2014///] CY - Hoboken, New Jersey PB - Wiley. KW - Building information modeling KW - Electronic books N1 - ABOUT THE AUTHOR KAREN M. KENSEK and DOUGLAS E. NOBLE teach at the University of Southern California, School of Architecture. Prof. Kensek has received national BIM honors from the AIA TAP committee and Autodesk, hosts an annual conference on Building Information Modeling, and received the 2014 ACSA Award for Creativity with Prof. Noble. They are both past presidents of Association for Computer Aided Design In Architecture (ACADIA) and are active in the American Institute of Architects (AIA); Includes index; Foreword xvii Acknowledgments xxi Introduction xxiii Software Mentioned xxxi PART 1 Design Thinking and BIM 1 CHAPTER 1 Smart Buildings/Smart(er) Designers: BIM and the Creative Design Process Glenn Goldman Andrzej Zarzycki 1.1 Introduction 3 1.2 Evaluation of Visual Information: Form 5 1.3 Generative Abilities of Parametric Models 6 1.4 How Lighting, Thermal, and Structural Considerations Can Drive the Design 6 1.5 Limitations of Current Parametric Models 8 1.6 Physics and Materiality 9 1.6.1 Solving for Multiple Criteria 10 1.6.2 Other Data Types 10 1.6.3 Soft Constraints 11 1.7 Design and Construction 2.0 12 1.7.1 Context-Aware Data 12 1.7.2 Beyond a Single Lifespan of the Project 13 1.8 Conclusion 15 Discussion Questions 15 Bibliography 16 CHAPTER 2 Necessity of Cognitive Modeling in BIM’s Future 17 Ömer Akin 2.1 Introduction: Some Useful Concepts 17 2.2 Building Information Modeling: The Brand New World of Design Computing 20 2.3 Cognitive Strategies for BIM: Challenges and Opportunities 21 2.4 Conclusions 26 Discussion Questions 26 References 27 CHAPTER 3 Modeling Architectural Meaning 29 Mark J. Clayton 3.1 Introduction 29 3.2 Architectural Ontology 30 3.3 Regulating Lines 30 3.4 Diagrams and Semantics 36 3.5 Types 38 3.6 Conclusion 40 Discussion Questions 40 References 41 CHAPTER 4 Knowledge-Based Building Information Modeling 43 Hugo Sheward Charles Eastman 4.1 The Potential of Building Information Modeling (BIM) to Capture Design Expertise 43 4.2 “Vanilla BIM” versus Knowledge-Based BIM 44 4.3 What Is Design Expertise? 44 4.3.1 Heuristics Applied to Design Processes 45 4.3.2 Design Workfl ows and Knowledge-Based BIM 46 4.4 Capturing and Deploying Design Expertise 47 4.4.1 Capturing Design Expertise 47 4.4.2 Embedding Knowledge in BIM 47 4.4.3 Example 1: Building Service Core 49 4.4.4 Example 2: Ventilation in Laboratories 50 4.5 Examples of Deployment 53 4.5.1 Deployment in Manufacturing 53 4.5.2 Uses in Architecture, Engineering, and Construction 53 4.6 Summary 54 Discussion Questions 54 References 55 PART 2 BIM Analytics 57 CHAPTER 5 Parametric BIM SIM: Integrating Parametric Modeling, BIM, and Simulation for Architectural Design 59 Wei Yan 5.1 Executive Summary 59 5.2 Introduction 59 5.2.1 Parametric Modeling 60 5.2.2 BIM and Parametric BIM 60 5.2.3 Building Energy Simulation 61 5.2.4 A Streamlined Modeling Process 63 5.3 Complexity and Interfaces 65 5.3.1 Complexity and Computability 65 5.3.2 User Interfaces and System Interfaces 66 5.4 Case Studies 69 5.4.1 Physical BIM for Thermal and Daylighting Simulations 69 5.4.2 Parametric BIM-Based Energy Optimization 72 5.5 Conclusion 74 Acknowledgments 74 Discussion Questions 74 References 75 CHAPTER 6 Models and Measurement: Changing Design Value with Simulation, Analysis, and Outcomes 79 Phillip G. Bernstein Matt Jezyk 6.1 Introduction 79 6.2 BIM 1.0 80 6.3 Analysis and Simulation through BIM 1.0 80 6.4 BIM 2.0 83 6.5 Geometry, Behavioral Properties, Parameters, and Analysis 85 6.6 Ideation and Design Production under BIM 2.0 89 6.7 Design Empowerment 91 6.8 Conclusion: Avenues to Alternative Value Generation 91 Discussion Questions 92 References 93 CHAPTER 7 Energy Modeling in Conceptual Design 95 Timothy Hemsath 7.1 Introduction 95 7.2 Building Performance Simulation (BPS) 95 7.3 BIM’s Role in the Process 97 7.4 Conceptual Design Decisions 98 7.5 Sensitivity Analysis and Optimization 101 7.5.1 Sensitivity Analysis 101 7.5.2 Conceptual Design Optimization 102 7.6 BIM Affordances 105 7.7 Conclusion 107 Acknowledgments 107 Discussion Questions 107 References 108 CHAPTER 8 Performance Art: Analytics and the New Theater of Design Practice 109 Daniel Davis Nathan Miller 8.1 Introduction 109 viii Contents 8.2 Instruments 110 8.3 Analytics 112 8.4 Interactions 115 8.5 Conclusion: Algorithms Are Thoughts 116 Discussion Questions 117 References 117 CHAPTER 9 Automated Energy Performance Visualization for BIM 119 Paola Sanguinetti Pasi Paasiala Charles Eastman 9.1 Introduction 119 9.2 Case Study: Automated Analysis of U.S. Courthouse Models for GSA 120 9.2.1 Preliminary Concept Design (PCD) 120 9.2.2 Post-Processing for Energy Analysis 120 9.2.3 Building Model Property Defi nition 123 9.3 Performance Visualization 123 9.3.1 Aggregation of Simulation Output Variables 124 9.3.2 Visualization of Thermal Flows 124 9.4 Discussion 125 9.5 Conclusion 127 Acknowledgments 127 Discussion Questions 127 References 127 CHAPTER 10 Urban Energy Information Modeling: High Fidelity Aggregated Building Simulation for District Energy Systems 129 Nina Baird Shalini Ramesh Henry Johnstone Khee Poh Lam 10.1 Introduction 129 10.2 Understanding District Energy Systems 129 10.3 Community Energy Planning 130 10.4 Dynamic Energy Mapping 132 10.4.1 An Initial Example: Pittsburgh’s Lower Hill District 132 10.4.2 Urban Energy Simulation of the Lower Hill District 133 10.4.3 Future Improvements Using Cloud Services 134 10.4.4 First Order District System Analysis 135 10.4.5 Data Visualization for Time-of-Use Aggregate Load Profi les 136 10.4.6 Interpreting Lower Hill District Results 137 10.5 The Future: BIM in Urban Energy Information Modeling 139 Discussion Questions 140 References 140 CHAPTER 11 BIM and the Predesign Process: Modeling the Unknown 143 Michael Donn 11.1 Introduction 143 11.1.1 Current BIM Concepts Limit Performance Analysis 144 11.1.2 Performance Analysis in Early Design 144 11.2 Limits of Traditional Early Design Analysis 145 11.2.1 The Promise of BIM in Early Design 145 11.2.2 Performative (Generative) Design as a Solution 145 11.2.3 Daylight Design Example of Limits of Traditional Analysis 147 11.2.4 Modern Performance Metrics in Daylight Design 147 11.3 BIM-Based Detailed Performance Analysis 149 11.3.1 A BIM Is More than a Representation of a Building 149 11.3.2 The Role of the Analyst in Performance Simulation 150 11.3.3 Tools for Rapid Evaluation of Design Scenarios 152 11.4 Conclusion: Inventing a New BIM for Early Design Analysis 153 Discussion Questions 154 References 154 CHAPTER 12 Analytical BIM: BIM Fragments, Domain Gaps, and Other Impediments 157 Karen M. Kensek 12.1 Introduction 157 12.2 Analytical Modeling 157 12.3 Building Information Modeling 158 12.4 Levels of BIM 159 12.4.1 Pre-BIM: Planning Stages 161 12.4.2 BIM Light: A Component-Based 3D Model 161 12.4.3 BIM + Information 161 12.4.4 BIM + Knowledge 162 12.4.5 BIM + Decisions 163 12.5 FDEIC Knowledge 164 12.6 Feedback Loop 165 12.7 Fragment BIMs and Three Gaps 166 12.7.1 Architect to Energy Consultant 167 12.7.2 Architect to Contractor 167 12.7.3 Architect and Contractor to Facilities Manager and Owner 169 12.8 Conclusion 170 Acknowledgments 170 Discussion Questions 170 References 171 PART 3 Comprehensive BIM 173 CHAPTER 13 One BIM to Rule Them All: Future Reality or Myth? 175 Brian R. Johnson 13.1 Introduction 175 13.2 A Brief History of the Single Model 175 13.3 The 2D Interregnum 176 13.3.1 Drawings versus Models 176 13.4 What’s Wrong with This Picture? 177 13.4.1 Task Complexity 177 13.4.2 Software Complexity 179 13.4.3 When a Model Isn’t Enough: Data versus Process 180 13.4.4 Limitations on Data as an Expression of Intent 181 13.4.5 People and Cognition 182 13.5 One BIM to Rule Them All? 183 Discussion Questions 184 References 184 CHAPTER 14 Component-Based BIM: A Comprehensive, Detailed, Single-Model Strategy 187 Anton C. Harfmann 14.1 Executive Summary 187 14.2 The Wicked Problem of Making Architecture 188 14.2.1 Design Complexity and Uniqueness 188 14.2.2 Fragmentation and Multiple Representations 189 14.2.3 Redesign and Discovery 189 14.3 Implementing Component-Based Design 190 14.3.1 The Component-Based Paradigm: Overview 190 14.3.2 Product/Manufacturer Links 191 14.3.3 External Reasoning 191 14.3.4 BIM-Driven Component Modeling 192 14.3.5 Component-Based Model Example 192 14.3.6 Component Model as Authority 195 14.4 Conclusion 195 Discussion Questions 196 References 196 CHAPTER 15 BIM Ecosystem: The Coevolution of Products, Processes, and People 197 Ning Gu Vishal Singh Kerry London 15.1 Introduction 197 15.2 Coevolution of Products, Processes, and People 198 15.3 Understanding the Industry Context of BIM 199 15.3.1 Fundamental Characteristics of BIM and Their Evolution 199 15.3.2 Industry Perception of BIM-Related Products, Processes, and People 201 15.4 Establishing a BIM Ecosystem: Operational and Support Technical Requirements in BIM 202 15.5 Establishing a BIM Ecosystem: Collaborative Platform BIM Decision Framework 203 15.5.1 Current Scope and Development of the Decision Framework 203 15.5.2 Sections of the Decision Framework for BIM Implementation 204 15.5.3 Applying the Decision Framework in Collaborative Practice 204 15.6 Discussion and Future BIM Ecosystem 207 15.6.1 Key Issues and Implication of Future BIM Ecosystem 207 15.6.2 Preparing for Future BIM Ecosystem 208 Discussion Questions 209 References 209 PART 4 Reasoning with BIM 211 CHAPTER 16 BIM, Materials, and Fabrication 213 Christopher Beorkrem 16.1 The Uber-Detail 213 16.2 Materials 214 16.3 The Logic of Materiality 215 16.4 Soft Data 218 16.5 Backward BIM 220 16.6 BIM, Materials, and Fabrication 222 16.7 Going Forward 222 16.8 Conclusion 223 Discussion Questions 224 References 224 CHAPTER 17 Communicating Semantics through Model Restructuring and Representation 225 Ramesh Krishnamurti Varvara Toulkeridou Tajin Biswas 17.1 Introduction 225 17.2 Spatial Reasoning and Querying 227 17.2.1 BIM as an Infrastructure for Spatial Reasoning 227 17.2.2 Extraction, Restructuring, Representation 227 17.2.3 Spatial Topology Data Extraction from IFC 228 17.2.4 Prototype for Spatial Topology Queries 229 17.3 Reasoning for Green Certifi cation 230 17.3.1 Aggregation, Augmentation, Representation 231 17.3.2 Prototype for Green Certifi cation 232 17.4 Conclusion 233 Discussion Questions 233 References 234 CHAPTER 18 BIM as a Catalyst to Foster Creativity through Collaboration 237 Murali Paranandi 18.1 Introduction 237 18.2 The Role of Collaboration in Design 238 18.3 Social Framework 238 18.3.1 The Human Side 239 18.3.2 Defi ne and Manage Roles 240 18.3.3 Co-locating to Facilitate Dialog 241 18.4 Computational Workfl ows 242 18.4.1 Tools for Designing and Collaborating 242 18.4.2 Collaborative Prototyping 243 18.4.3 Crowdsourcing 244 18.4.4 Knowledge Capture and Sharing in the Cloud 245 18.5 Conclusion 247 18.5.1 Feedback to Academia 247 18.5.2 Feedback to the Profession 247 Acknowledgments 248 Discussion Questions 248 References 248 CHAPTER 19 BIM and Virtual Reconstruction: A Long-Term View of (Re-)Modeling 251 Bob Martens Herbert Peter 19.1 Executive Summary 251 19.2 Introduction 252 19.3 BIM and Virtual Reconstruction 253 19.4 Information Basis: Model Tree Structures 257 19.5 Model Porting and Data Exchange 261 19.5.1 Model Porting 262 19.5.2 Data Exchange 262 19.6 Outlook: Where Do We Go from Here? 263 19.7 Conclusion 264 Discussion Questions 264 References 264 PART 5 Professional BIM 267 CHAPTER 20 Managing BIM Projects, Organizations, and Policies: Turning Aspirations into Quantitative Measures of Success 269 Calvin Kam 20.1 Introduction 269 20.2 Scorecard Methodology 270 20.3 Project Evaluation 272 20.4 Continuous Evaluation 275 20.5 Performance Indicators 276 20.6 Portfolio Evaluation 277 20.7 Country-Level BIM Evaluations 278 20.8 Conclusion 279 Acknowledgments 280 Discussion Questions 280 References 280 CHAPTER 21 Space: The First (and Final) Frontier of BIM 281 Stephen R Hagan 21.1 Introduction 281 21.2 Historical Perspectives of Space and the Facility Life Cycle 282 21.3 Space, Measurement, and BIM 282 21.4 BIM Spatial Pioneers: Coast Guard and GSA 283 21.5 Project Spatial BIM: Connecting Program to Design, Construction, and Facility Management 288 21.6 Geospatial, Campus-Wide, and Services-Oriented Spatial BIM 289 21.7 Standardizing Spatial BIM: IFMA-BOMA, BISDM, CityGML, and Indoor Navigation 290 21.8 Conclusion 290 Discussion Questions 292 References 292 CHAPTER 22 Translating Designs for Construction + Operations: The Future of BIM in a World of Material and Energy Scarcity 295 Franca Trubiano 22.1 Buildings, Information, and Modeling 295 22.1.1 The Promise 295 22.1.2 The Critique 296 22.2 The Changing Character of Architectural Representations 297 22.3 Facilitating the Translation from Design to Construction—with Matter 299 22.4 Facilitating the Translation from Design to Operations—with Energy 308 22.5 Conclusion 310 Discussion Questions 311 References 311 CHAPTER 23 Marx, BIM, and Contemporary Labor 313 Peggy Deamer 23.1 BIM and Work 313 23.2 BIM Managers: What They Are Doing 314 23.2.1 Design versus Technology 314 23.2.2 Networked Tasks 315 23.2.3 Political/Organizational Change 316 23.3 The Enactment of Enlightened Management Theory 317 23.4 Conclusion: Post-Capitalist Architecture 319 Discussion Questions 319 References 319 PART 6 BIM Speculation 321 CHAPTER 24 Beyond BIM: Next-Generation Building Information Modeling to Support Form, Function, and Use of Buildings 323 Yehuda E. Kalay Davide Schaumann Seung Wan Hong Davide Simeone 24.1 Rationale 323 24.2 The Shortcomings of BIM 325 24.3 Form, Function, Use 327 24.3.1 Form 327 24.3.2 Function 327 24.3.3 Use 328 24.4 Dependencies 329 24.4.1 Form versus Function 329 24.4.2 Form versus Use 330 24.4.3 Function versus Use 330 24.5 Objectives 330 24.6 Methodology 330 24.7 Implementation 331 24.8 Conclusion 334 Acknowledgments 334 Discussion Questions 334 References 334 CHAPTER 25 Engines of Information: Big Data from Small Buildings 337 Chandler Ahrens Aaron Sprecher 25.1 Introduction 337 25.2 Data to Information 338 25.3 Looking through the Lens of Data 340 25.4 Building an Information Model 342 25.5 The Present Future 343 25.6 IM: Drop the (B) 344 25.7 Information to Knowledge 347 25.8 Conclusion 347 Discussion Questions 347 References 348 CHAPTER 26 BIM and MetaBIM: Design Narrative and Modeling Building Information 349 Mark Burry 26.1 Background to a Series of Dilemmas 349 26.2 A Case in Point: The Sagrada Família Basilica Sala Creuer 351 26.2.1 Sala Creuer Documentation 351 26.2.2 Project Phases 352 26.3 Creative Digital Workflow as BIM 357 26.4 Watch This Space . . . 360 Acknowledgments 362 Discussion Questions 362 Glossary 363 Author Biographies 373 Index 385 N2 - The bright future and exciting possibilities of BIM Many architects and engineers regard BIM as a disruptive force, changing the way building professionals design, build, and ultimately manage a built structure. With its emphasis on continuing advances in BIM research, teaching, and practice, Building Information Modeling: BIM in Current and Future Practice encourages readers to transform disruption to opportunity and challenges them to reconsider their preconceptions about BIM. Thought leaders from universities and professional practice composed essays exploring BIM's potential to improve the products and processes of architectural design including the structure and content of the tools themselves. These authors provide insights for assessing the current practice and research directions of BIM and speculate about its future. The twenty-six chapters are thematically grouped in six sections that present complementary and sometimes incompatible positions: Design Thinking and BIM BIM Analytics Comprehensive BIM Reasoning with BIM Professional BIM BIM Speculations Together, these authors provide stimulating ideas regarding new directions in building information modeling UR - https://onlinelibrary.wiley.com/doi/book/10.1002/9781119174752 ER -