Planning: Digital Twin for Building Performance Simulation and Optimization in Adaptive Reuse Planning

The adaptive reuse of existing buildings presents an essential strategy for addressing societal challenges related to aging infrastructure, urban development, and environmental sustainability. However, current methodologies often fall short in predicting and optimizing building performance due to a lack of accurate data and robust tools. In the realm of sustainable and energy-efficient building design, the untapped potential of advanced technologies such as digital twin technology, integrated with rich building data transformative solutions. Incorporating digital twin technology into adaptive reuse planning not only contributes to efficient resource utilization and waste reduction but also significantly reduces environmental impact, thereby addressing critical sustainability issues. In this project, the Principal Investigator (PI) will utilize this planning grant to develop a proof-of-concept digital twin system, specifically designed for adaptive reuse planning. The PI will conduct workshops to promote knowledge exchange among faculty members from various HBCUs and engage with potential collaborators and industry partners, laying the groundwork for the research ahead. The project involves developing a sophisticated digital twin model that incorporates diverse data sources, including architectural and structural parameters, historical data, environmental factors, and urban regulations. Leveraging the power of machine learning algorithms and high-performance computing, this model will perform real-time simulations and predictions of building performance. The project aims to enhance energy efficiency by predicting and optimizing building performance parameters, thus informing adaptive reuse planning. The PI will be developing a robust methodology for data collection, model development, performance simulation, and energy efficiency evaluation. This endeavor will result in a user-friendly framework that empowers non-experts to conduct complex simulations and make informed, energy-efficient decisions. This approach introduces a revolutionary, technology-driven method to adaptive reuse planning, potentially transforming the field by making the process more efficient and effective, ultimately fostering more sustainable cities. In this crucial planning stage, the focus is on strategic coordination, engaging potential collaborators, conducting preliminary investigations, and proof-of-concept studies, thereby laying a robust foundation for this ground-breaking research. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.