Title Details

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).

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