CARBON-OPTIMIZED BUILDING MASSING WITH CONSTRUCTIVE SOLID GEOMETRY STRATEGIES: A PARAMETRIC MULTI-OBJECTIVE FRAMEWORK
DOI:
https://doi.org/10.55766/sujst11660Keywords:
Carbon Optimization, CSG Strategies, Early-Stage Performance, NSGA-II, Parametric DesignAbstract
The early-stage performance of architectural design is critical for long-term carbon optimization. This study investigates three constructive solid geometry (CSG) strategies, namely union, subtraction, and intersection, within a parametric workflow driven by the Non-dominated Sorting Genetic Algorithm II (NSGA-II), aiming to minimize operational carbon emissions (OCE) and maximize gross floor area (GFA). It connects geometric design logic with objectives to support carbon-conscious massing decisions. The study examines how CSG strategies influence simulation runtime, model validity, and design diversity; how NSGA-II optimizes form generation under regulatory constraints e.g., floor area ratio (FAR), open space ratio (OSR); and how these affect early-stage outcomes. Out of 3,000 generated configurations, the subtraction strategy achieved the lowest operational carbon intensity (181.30 kgCO₂eq/m² at 45,901.85 m² GFA) and provided greater design diversity with 151 valid configurations, while the intersection strategy demonstrated the fastest simulation runtime of 3h 40m 40s. The proposed framework effectively filtered infeasible designs and ensured regulatory compliance to maintain model validity. Convergence of optimal OCE values (~181 kgCO₂eq/m²) across strategies suggests a useful benchmark for high-rise office buildings in dense urban contexts. These findings highlight the value of integrating carbon optimization, regulatory constraints, and multi-objective parametric design into early-stage architectural workflows to improve sustainability.
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