Abstract
<title>Abstract</title> <p>As the demand for high-performance, sustainable buildings increases, good analysis systems are beginning to emerge to quantify and optimize them. This paper introduces a computer-aided design method based on the Grasshopper visual programming system, used for parametric modeling, simulation, and multi-objective optimization of sustainable building envelope strategies. A general method that combines algorithmic geometric control with a high-resolution performance simulation engine is used to automatically and iteratively evaluate energy consumption, solar self-sufficiency, and other environmental comfort indicators. In order to study the impact of insulation thickness, glass ratio, and shading configuration on a mid-rise educational building, a case study will be conducted. If the thickness of the exterior insulation layer is increased from 100 mm to 220 mm, the annual energy consumption will decrease by approximately 25%. If the thickness is further increased, this increase has almost no improvement. By making intermediate adjustments to the window-to-wall ratio, the increase in solar self-sufficiency can be reduced, and the thermal load can be accelerated. Reducing the depth of shading can lower the maximum indoor temperature in summer by up to 2.1℃ and meet visual comfort requirements. Grasshopper can help design teams make trade-off decisions based on quantitative evidence, obtain data-driven Pareto fronts, and easily manage the many dependencies between variables. This technology is demanding but feasible, thus it can lay a solid foundation for good performance and durability in various applications in life.</p>