Designing in complexity: Simulation, integration, and multidisciplinary design optimization for architecture. (August 2014)

• Record Type: Journal Article
• Authors: Gerber, David Jason; Lin, Shih-Hsin Eve
• Other Names: Attar Ramtin guest-editor.; O'Brien William guest-editor.; Nikolovska Lira guest-editor.; Khan Azam guest-editor.
• Is Part Of: Simulation. Volume 90:Number 8(2014:Aug.)
• Page Start: 936
• Page End: 959
• Publication Date: 2014-08
• Subjects: Parametric design -- generative design -- conceptual energy analysis -- performance-based design -- genetic algorithm -- multidisciplinary design optimization -- decision support -- design space exploration -- domain integration -- design process evaluation -- multi-objective optimization; Computer simulation -- Periodicals; 003.3
• DOI: 10.1177/0037549713482027
• Languages: English
• ISSNs: 0037-5497

Abstract

While the overall performance of buildings has been established to be heavily impacted by design decisions made during the early stages of the design process, design professionals are typically unable to explore design alternatives, or their impact on energy profiles, in a sufficient manner during this phase. The research presents a new design simulation methodology based on incorporating a prototype tool (H.D.S. Beagle) that combines parametric modeling with multi-objective optimization through an integrated platform for enabling rapid iteration and trade-off analysis across the domains of design, energy use intensity, and finance. The research evaluates how the proposed method impacts design simulation processes, by either enabling and/or disrupting the early stages of design decision making. This simulation technology is presented through two major experiment sets: (1) a series of hypothetical cases emulating the architecture, engineering, and construction (AEC) design modeling and simulation process using our integrated simulation framework and technology; and (2) a pedagogically based experiment used for establishing benchmarks. Through these experiment data sets, both quantitative and qualitative data are collected, including human designer and computational analysis speeds, quantity of generated design alternatives, and quality of resulting solution space as defined by the evaluation metric of this research. The affordances for incorporation of real world design complexity into our computational design prototype and simulation methodology are discussed through both the enabling and the disruptive impact on the early stages of the design process.