ITcon Vol. 23, pg. 157-178,

Design space construction: a framework to support collaborative, parametric decision making

submitted:July 2017
revised:June 2018
published:June 2018
editor(s):Kumar B.
authors:John Haymaker, AIA, PhD
Director of Research, Director of Process Lab, Perkins+Will;

Marcelo Bernal, PhD, Senior Researcher & Computational Designer, Assistant Professor
Perkins+Will; Department of Architecture, Universidad Técnica Federico Santa María;

Marionyt Tyrone Marshall, AIA, Senior Researcher, Co-Director Energy Lab, Perkins+Will

Victor Okhoya, Assoc. AIA, Senior Researcher, Design Applications Manager; PhD Candidate
Perkins+Will; School of Architecture, Carnegie Mellon University

Anton Szilasi, Researcher, Perkins+Will

Roya Rezaee, PhD, CPHC, Research Scientist, Perkins+Will

Cheney Chen, PhD, P.Eng., Senior Sustainable Building + Energy Engineer, Perkins+Will

Andrew Salveson, Software Engineer, Perkins+Will

Justin Brechtel, Senior Computational Designer, Perkins+Will

Luc Deckinga, Digital Practice Manager, Perkins+Will

Hakim Hasan, Researcher, Perkins+Will

Phillip Ewing, Researcher, Perkins+Will

Benjamin Welle, PhD, PE, BD+C, BEMP, Director of Energy Lab, Perkins+Will
summary:This paper describes a framework of concepts and processes that support teams to construct and explore design spaces maximizing social, environmental, and economic value. The framework guides teams through processes of problem formulation, alternative generation, impact analysis, and value assessment. The paper describes an extensible supporting computational infrastructure based on a system integration approach and structured in four layers: parametric user interface, analysis engines, software interfaces, and data visualization. The paper describes implemented functionality in terms of goal and preference-setting, parametric modeling, energy, daylight, view, first cost, lifecycle cost and lifecycle carbon, and demonstrates application through a test case. The paper concludes with evidence about the power and flexibility of the DSC framework with the results of a professional case study, and a survey of professional and student architects who have been trained in constructing and exploring parametric, performance-based design spaces.
keywords:design space, problem formulation, parametric modeling, performance, value, decision making
full text: (PDF file, 5.173 MB)
citation:John Haymaker J, Bernal M, Tyrone Marshall T M, Okhoya V, Szilasi A, Rezaee R, Chen C, Salveson A, Brechtel J, Deckinga L, Hasan H, Ewing P, Welle B (2018). Design space construction: a framework to support collaborative, parametric decision making, ITcon Vol. 23, pg. 157-178,