Integrating expertise and parametric analysis for a data-driven decision-making practice. (December 2020)

• Record Type: Journal Article
• Authors: Bernal, Marcelo; Okhoya, Victor; Marshall, Tyrone; Chen, Cheney; Haymaker, John
• Other Names: Henriques Gonçalo Castro guest-editor.; Sousa José Pedro guest-editor.; Gomez-Zamora Paula guest-editor.; Achten Henri guest-editor.
• Is Part Of: International journal of architectural computing. Volume 18:Number 4(2020)
• Page Start: 424
• Page End: 440
• Publication Date: 2020-12
• Subjects: Performance analysis -- parametric analysis -- design space -- design expertise -- data analysis -- optimization; Architecture -- Data processing -- Periodicals; Architecture -- Informatique -- Périodiques; Virtual reality in architecture -- Periodicals; Computer-aided design -- Periodicals; Architecture -- Data processing; Periodicals; 720.2840285536
• DOI: 10.1177/1478077120940975
• Languages: English
• ISSNs: 1478-0771

Abstract

This study explores the integration of expert design intuition and parametric data analysis. While traditional professional design expertise helps to rapidly frame relevant aspects of the design problem and produce viable solutions, it has limitations in addressing multi-criteria design problems with conflicting objectives. On the other hand, parametric analysis, in combination with data analysis methods, helps to construct and analyze large design spaces of potential design solutions and tradeoffs, within a given frame. We explore a process whereby expert design teams propose a design using their current intuitive and analytical methods. That design is then further optimized using parametric analysis. This study specifically explores the specification of geometric and material properties of building envelopes for two typically conflicting objectives: daylight quality and energy consumption. We compare performance of the design after initial professional design exploration, and after parametric analysis, showing consistently significant performance improvement after the second process. The study explores synergies between intuitive and systematic design approaches, demonstrating how alignment can help expert teams efficiently and significantly improve project performance.