Shading Design For Outdoor Learning in Warm And Hot Climates Using Evolutionary Computation: A Case Study In Houston TX

This research proposes a parametric workflow to environmentally optimize the shading design of outdoor educational spaces using multiobjective evolutionary algorithms. The design variants that are parametrically evaluated against thermal and visual comfort indices and the economy of the structure are shading growth and permeability. Part of the investigation is optimizing geometric modeling, environmental parameter benchmarking, evolutionary solver parameters definition, solution analysis, and the solution selection process. Outdoor thermal comfort is assessed using the Universal Thermal Climate Index, and visual comfort using horizontal illuminance levels and daylight uniformity. Minimizing the required shading area is used as a material resource consideration. The results showed that the solver could reach stability early on; therefore, a smaller population could lead to similar results and that material consideration is fundamental to the optimization process. The validation of the selected solution proved the effectiveness of the shading and the ability of the methodology to assist early design.