BIM Automation: Design optioneering towards energy performance B optimizationRashid, Razan (Avtor) Cerovšek, Tomo (Mentor) civil engineeringmaster thesisBIMBIM automationdesign optimizationenergy-efficiencydesign optioneeringdata analysisautomation workflowsRevitDynamoPythonThe building sector accounts for a significant amount of energy consumption, exerting a substantial environmental impact. Hence, prioritizing the enhancement and optimization of building energy performance is imperative for designers. However, designing such efficient buildings is a complex process, often leading designers to overlook this aspect. Many available tools primarily target energy prediction in final design stages rather than the conceptual phases, where critical decisions are made. Consequently, streamlining the initial design stage is essential. This is where Building Information Modeling (BIM) emerges as a potent force, reshaping the Architecture, Engineering, and Construction (AEC) industry. By harnessing BIM tools for automation, designers and architects can readily create energy-efficient, optimized buildings. This research aims to delve into the diverse applications of BIM automation techniques in design optimization and energy efficiency practices. The study seeks to ascertain and evaluate the potential advantages of integrating BIM automation during the design phase to bolster energy efficiency in buildings. The investigation employed several qualitative and quantitative methodologies. The methodology is concluded into three key phases: analysis of methodologies from prior studies, selecting the base-case for the study, and examining the proposed automation workflows. The study-case is a simple building designed by the author, serving as a base to assess the different workflows. The exploration encompasses three levels of methodological automation. The first level involves manual workflow application, which, while time consuming and prone to human errors, limits the design options exploration. The second level focused on visual programming workflows but struggled due to limitations and inflexibility of tools like Dynamo for automation. It's evident that sole reliance on visual programming might not suffice for comprehensive automation. Integrating textual programming scripts emerges to augment and expedite the process more effectively. The final level merges both visual and textual programming, particularly Python. This workflow focused on fully automating design options generation, exporting to gbXML, optimization, and data analysis. The use of Python demonstrates its prowess in automation and data analysis, allowing for rapid, accurate creation of numerous design options. Through these investigations, the study gauges the efficacy and best practices of BIM automation in design optimization. The outcomes of the study culminate in proposed workflows for automating design optimization during early stages. Though limitations persist due to closed-source design tools, the role of programming in the design process is increasingly pivotal, offering unencumbered access to data for informed decisions.[R. Rashid]20232023-09-20 07:45:51Magistrsko delo/naloga150514UDK: 004.946:620.9-044.963(043.3)VisID: 159448COBISS_ID: 187675139sl