DESIGN SCENARIOS METHODOLOGY – ENABLING REQUIREMENTS-DRIVEN DESIGN SPACES A DISSERTATION SUBMITTED TO THE DEPARTMENT OF CIVIL AND ENVIRONMENTAL ENGINEERING AND THE COMMITTEE ON GRADUATE STUDIES OF STANFORD UNIVERSITY IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY Victor Gane May 2011 © 2011 by Victor Gane. All Rights Reserved. Re-distributed by Stanford University under license with the author. This work is licensed under a Creative Commons Attribution- Noncommercial 3.0 United States License. http://creativecommons.org/licenses/by-nc/3.0/us/ This dissertation is online at: http://purl.stanford.edu/qs170jk0633 ii I certify that I have read this dissertation and that, in my opinion, it is fully adequate in scope and quality as a dissertation for the degree of Doctor of Philosophy. Martin Fischer, Primary Adviser I certify that I have read this dissertation and that, in my opinion, it is fully adequate in scope and quality as a dissertation for the degree of Doctor of Philosophy. John Haymaker, Co-Adviser I certify that I have read this dissertation and that, in my opinion, it is fully adequate in scope and quality as a dissertation for the degree of Doctor of Philosophy. Mark Cutkosky I certify that I have read this dissertation and that, in my opinion, it is fully adequate in scope and quality as a dissertation for the degree of Doctor of Philosophy. Vladimir Bazjanac Approved for the Stanford University Committee on Graduate Studies. Patricia J. Gumport, Vice Provost Graduate Education This signature page was generated electronically upon submission of this dissertation in electronic format. An original signed hard copy of the signature page is on file in University Archives. iii Victor Gane Abstract During the conceptual design process, the building shape, orientation, materials and other major properties are established, all of which have a substantial impact on multi- aspect performance. In this process, multidisciplinary teams define project objectives, create various alternatives, and try to understand their impacts and value. With non- parametric Computer Aided Design (CAD) methods designers produce and analyze as few as three alternatives, whereas with parametric CAD – they can generate thousands. However, with current parametric methods, CAD experts lack a comprehensive method to build and analyze multi-objective parametric models. Therefore the resulting models do not effectively encapsulate multi-objective value measures. This research introduces the Design Scenarios Methodology (DS), which builds on research from Systems Engineering, Process Modeling, and Parametric Modeling. With DS, Enablers use Methods to create Elements using five interconnected models to define (1) project stakeholders and their objectives, (2) designer logic used to address objectives, (3) the connection between designer logic and computable models to generate alternatives, (4) the predicted impact and (5) value of the generated alternatives. I implemented DS as a web-based software prototype and tested it on an industry project. The results provide evidence that the DS method provides CAD experts with well-defined logic and parameters for addressing objectives and the process enables creating parametric alternatives with clear multi-objective values that potentially provide clients with better building designs. This thesis lays the foundation for future research on automating the design alternative generation and analyses processes by leveraging such well-established methods as Multi-Disciplinary Optimization. iv Victor Gane Acknowledgments The last few years have been an extraordinary journey of learning, discovery, collaboration, friendship, frustration, and joy. Having completed my Ph.D. is perhaps my most fundamental achievement to date. I came out of it a more seasoned and ever more curious thinker, yearning to continue on the path of challenging myself and contributing to the advancement of the science. I attribute a great part of this success to many great individuals, to whom I express my gratitude. I would like to first of all thank John Haymaker, my advisor. John has been instrumental in inspiring me to pursue a Ph.D. He is a true friend, who has always helped guide and support my research. No matter whether I was working locally on my papers, or remotely on industry case studies, John always asked hard questions, gave great feedback, and encouraged my intuition for developing prototype solutions for my research problem. I’d like to express my gratitude to my co-advisor, Martin Fischer, whose drive for excellence was an important inspiration over the years. Martin helped focus the contribution of my research and sharpen the story. His comments to my papers, as well as feedback to numerous informal and formal presentations were invaluable. I am grateful to my reading committee members Vlado Bazjanac, Mark Cutkosky, and Axel Kilian. I met Vlado during one of his visits to Stanford and immediately grew to respect and appreciate his holistic view of the building design process. Professor Cutkosky’s wealth of knowledge from other design disciplines such as mechanical engineering and robotics offered an important alternative perspective to my research. Axel Kilian from Princeton University was an early motivation to this research when he taught a workshop on computational design methods during my graduate studies at the Massachusetts Institute of Technology when I became interested in applying parametric Computer Aided Design in the conceptual design of buildings. Axel is a true friend and his humility and profound knowledge is inspiring. Many others helped shape this experience. I thank the Precourt Center for Energy Efficiency for partially funding my research. David Anderson is the software architect v Victor Gane that helped implement my ideas into a testable software prototype. John Kunz, Renate Fruchter, Ray Levitt asked fundamental questions and reinforced the rigorous scientific thinking that a Ph.D. process entails. I thank the CIFE faculty for introducing me early on to the “Horseshoe” concept of structuring my Ph.D. research, without which it might have been much harder to stay focused and understand where in the overall research process I stood. I thank Ross Wimer, Bill Baker, Mark Sarkisian, Bernie Gandras, Luke Leung, and Eric Zachrison from Skidmore, Owings and Merrill who were instrumental in enabling me to test my research on industry projects and learn firsthand the anticipated practical impact. Finally, I am grateful to my many friends and peers at Stanford who throughout the years contributed to making this a great journey: Reid Senescu, Ben Welle, Rene Morcos, Tobias Maile, Ben Suter, Caroline Clevenger, Wendy Li, Akiko Yamada. And last but not least, I dedicate this dissertation to my parents, my most ardent supporters. Without their unconditional belief in my abilities, encouragement, and support of higher scholarly pursuits, it would be hard to imagine I would be where I am today. vi Victor Gane Table of Contents Abstract ........................................................................................................................ iv Acknowledgments ......................................................................................................... v Table of Contents ........................................................................................................ vii List of Tables ................................................................................................................. x List of Illustrations ...................................................................................................... xi Chapter 1: Introduction ............................................................................................... 1 1 Observed problem ........................................................................................................... 2 2 Research questions .......................................................................................................... 5 3 Points of departure .......................................................................................................... 5 4 Research method / tasks .................................................................................................. 6 5 Research results / validation ......................................................................................... 10 6 Contributions to knowledge .......................................................................................... 11 7 Predicted practical impact ............................................................................................ 12 8 Conclusion ...................................................................................................................... 13 9 References ....................................................................................................................... 13 Chapter 2: Benchmarking current conceptual design processes ........................... 16 1 Abstract .......................................................................................................................... 16 2 Introduction: Need for Effective Conceptual High-Rise Design Processes .............. 16 2.1 Points of departure: What are current high-rise design processes and how do we document and measure them? .................................................................................. 18 2.1.1 Design theory ..........................................................................................