Improving Advanced Reactor Safety Analysis by Integrating Scientific Machine Learning with System Analysis Code

This seminar will discuss some recent efforts to develop a coarse mesh turbulence model with a physics-informed machine learning (ML) approach. This approach leverages deep learning technologies and utilizes fine mesh CFD data for turbulence model development. The performance of different architectures of deep neural networks, including densely connected convolutional networks and long-short-term-memory networks, are evaluated.