Designing-in performance: A framework for evolutionary energy performance feedback in early stage design

作者：Lin Shih Hsin Eve; Gerber David Jason^*

来源：Automation in Construction, 2014, 38: 59-73.

DOI：10.1016/j.autcon2013.10.007

• Multidisciplinary design optimization (MOO)
• Conceptual energy analysis
• Performance based design
• Genetic Algorithm (GA)
• Multi-objective optimization
• Design decision support
• Design automation
• Domain integration

Multidisciplinary design optimization (MDO) has been identified as a potential means for integrating design and energy performance domains but has not been fully explored for the specific demands of early stage architectural design. In response a design framework, titled Evolutionary Energy Performance Feedback for Design (EEPFD), is developed to support early stage design decision-making by providing rapid iteration with performance feedback through parameterization, automation, and multi-objective optimization. This paper details the development and initial validation of EEPFD through two identified needs of early stage design: 1) the ability to accommodate formal variety and varying degrees of geometric complexity; and 2) the ability to provide improved performance feedback for multiple objective functions. Through experimental cases the research presents effective application of EEPFD for architectural design.

• 出版日期2014-3