Multidisciplinary concurrent optimization framework for multi-phase building design process

Abstract Modern day building design projects require multidisciplinary expertise from architects and engineers across various phases of the (conceptual, preliminary, detailed) construction processes. The Architecture Engineering Construction (AEC) community has recently shifted gears toward leveraging optimization techniques to make well-informed decisions in buildings. However, most efforts are either confined just a specific phase (conceptual/preliminary/detailed) or single disciplinary (structural/thermal/daylighting/energy) spanning multiple phases. Complexity changing setup as progresses through subsequent phases, interoperability issues between modeling physics-based analysis tools used at later stages, lack an appropriate level detail get meaningful results these sophisticated few challenges that limit multi-phase (MDO) AEC field. This paper proposes computational platform concurrent engineering such interactive problem structuring, simulation-based using meta models for energy daylighting (machine learning based) tradespace visualization. proposed MDO framework is demonstrated by it optimize sample office objectives Furthermore, limitations future avenues research listed.