A framework for designing kinetic fabric shading systems optimizing integrated energy, daylight, and view clarity metrics

This study addresses the gap in evaluating the performance of Dynamic Fabric Shading Systems (DFSS) by integrating energy, daylight, and view clarity metrics in early-stage architectural design. While kinetic facades are recognized for energy efficiency, few efforts have explored their simultaneous optimization with the Openness Factor (OF) of fabric materials to maintain occupant views. This research proposes a comprehensive framework using an evolutionary-based Multi-Objective Optimization (MOO) approach to automate the exploration of Spatial Daylight Autonomy (sDA), Annual Sun Exposure (ASE), Lighting Energy (LE), and View Clarity Index (VCI). The framework is applied to an educational space at Southern Illinois University Carbondale, comparing three kinetic patterns: Al-Bahar Tower (ABT), SDU Campus Kolding (SDU), and Kiefer Technic Showroom (KTS). Simulation results, validated against physical daylight sensing (CV RMSE ~10%), indicate that the ABT pattern achieves the most effective balance of performance metrics. The findings suggest that patterns with moderate to high Opening Fractions (OPF) and low to moderate fabric OF offer optimal trade-offs, providing a robust model for sustainable educational facility design.