Data-Driven Modeling

High Fidelity Data Surrogates for Enhancing Co-Simulation Capabilities of Energy Simulation Tools

Energy modeling tools are used by engineers and researchers to evaluate the impact of different design features, products, and materials systems on an building's energy, thermal, and hygrothermal performance. These frameworks and their simulation …

Integrating Deep Learning with Computational Fluid Dynamics Solvers

The work aims to demonstrate capabilities doing in-situ co-simulations strategies of Machine Learning and Computational Fluid Dynamics Solver (OpenFOAM)

Integrating Data-Driven and High Fidelity Computational Models for Buildings Energy Systems

Residential and commercial buildings account for 41% of total energy consumption in the United States. Optimizing energy consumption and designing more Energy Efficient Green Buildings is a promising approach to reducing energy consumption. Modeling …

Construction of Perron Frobenius Operator from Computational Fluid Dynamics (CFD) Data

A data-driven approach is developed to construct the Perron-Frobenius operator on-line using the OpenSource CFD tool OpenFOAM.