3 papers
cs.LG2026
Neural Operator-Based Surrogate Model for CFD:Helical Coil Steam Generator in Small Modular Reactor
Minseo Lee, Seongmin Oh, Chaehyeon Song +5
Real-time thermal-hydraulic simulation is essential for digital twin (DT) technology that supports the safe and efficient operation of small modular reactors (SMRs). Computational…
cs.LG2026
XRePIT: A deep learning-computational fluid dynamics hybrid framework implemented in OpenFOAM for fast, robust, and scalable unsteady simulations
Shilaj Baral, Youngkyu Lee, Sangam Khanal +1
Autoregressive neural surrogates offer computational acceleration for fluid dynamics but inherently suffer from error accumulation and non-physical drift during long-term rollouts.…
cs.LG2025
Comparison of CNN-based deep learning architectures for unsteady CFD acceleration on small datasets
Sangam Khanal, Shilaj Baral, Joongoo Jeon
CFD acceleration for virtual nuclear reactors or digital twin technology is a primary goal in the nuclear industry. This study compares advanced convolutional neural network (CNN)…