Automating PFAS Treatment and GAC System Design Refinement

Engineering design refinement is often slowed down by repetitive work and interpretation differences across teams. In water systems operations, PFAS treatment and granular activated carbon (GAC) design decisions frequently require multiple iterations to confirm assumptions, calculations, and specifications.

This project develops a GraphRAG-based chatbot that translates natural-language requests into structured design intent, retrieves relevant engineering knowledge, and supports step-by-step decision making for design refinement. The workflow helps reduce communication overhead between designers and engineers while improving efficiency and consistency.

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