Automated carbon-aware assessment of openBIM-based ductwork design using knowledge graph–augmented LLM multi-agent framework

Ductwork systems, as critical components of mechanical, electrical, and plumbing (MEP) systems, significantly influence buildings' embodied carbon and operational efficiency. Prior studies in carbon-aware assessment for ductwork systems have been limited in efficiency problems and lacking automated analysis. Although large language models (LLMs) provide a solution, hallucination problems exist in generic LLMs. The proper representation of LLM operation inputs and LLM agent integration with the particular workflow remain challenges. Therefore, this paper proposes an automated openBIM-based approach for carbon-aware ductwork design assessment. It starts with developing an integrated ductwork KG (DKG) schema of carbon-aware ductwork assessment, which is followed by developing conversion algorithms to automatically transform the ductwork IFC design to the DKG file. Lastly, a KG-augmented LLM multiagent framework is developed to automatically implement carbon-aware assessment tasks and generate analysis. An office building was used to demonstrate, showing the high accuracy and time efficiency of the proposed method.