Solar Shading

Solar shading research focuses on optimizing designs to control sunlight entering buildings, balancing daylighting benefits with glare and overheating. Current efforts leverage machine learning, particularly neural networks and algorithms like Random Forests, to rapidly predict shading performance across various building and shading configurations, often using parametric models and large datasets to train these models. This accelerates the design process, enabling faster and more efficient exploration of optimal solutions for improved indoor environmental quality and energy efficiency in architecture and urban planning. The resulting tools promise significant time and cost savings for architects and urban planners.