BIM AND AI AGENT-ASSISTED PARAMETRIC DESIGN OF CLIMATE-RESPONSIVE FACADE SHADING ELEMENTS IN UZBEKISTAN USING RHINO 8 AND GRASSHOPPER

Abstract

This paper proposes a methodological framework for the parametric design of fixed solar-shading elements for building facades, taking into account the substantial seasonal and regional climatic variability of Uzbekistan. Building information modeling (BIM) is considered as a means of organizing and documenting the geometric and non-geometric information of the proposed façade systems. The workflow combines the generation of adjustable geometry in Rhino 8 and Grasshopper, the analysis of location-specific EnergyPlus Weather (EPW) data using Ladybug Tools, the connection of daylight and building-energy models to Radiance and EnergyPlus/OpenStudio through Honeybee, and the screening of design alternatives against applicable regulatory constraints. Three architectural precedents inform the proposed prototypes: traditional Uzbek shabaka screens, deep ayvans (covered verandas), and the three-dimensional concrete shading screens characteristic of Tashkent modernism. A conceptual multi-agent artificial intelligence (AI) workflow is structured around climate-data validation, geometric option generation, regulatory traceability, simulation-result assessment, and BIM data management. This is a conceptual and methodological study. Neither an operational multi-agent system nor a completed Rhino/Grasshopper model has been experimentally validated within the present work; likewise, no new results from simulations using an independently verified EPW file are reported.