Abstract Submission: This project aims to advance research in building water systems analytics by leveraging supercomputing resources. Current plumbing research often overlooks the collective importance of tap water quality, the water-energy nexus, and associated risks within building water systems. This project will utilize multi-objective decision modeling to balance water quality, energy efficiency, and risk, taking into account various design practices, codes, and standards. To identify optimal solutions, Pittsburgh Supercomputing resources will be employed.
The principal outcomes of this research include: i) an improved understanding of key phenomena within building water infrastructure, leading to enhanced planning, design, analysis, and operational decision-making; ii) new opportunities for optimizing building water system operations and improving management strategies. This deeper understanding will result in more effective design, analysis, and operational strategies for managing building water systems.
