A review of the application of artificial intelligence to nuclear reactors: Where we are and what's next
Q Huang, S Peng, J Deng, H Zeng, Z Zhang, Y Liu… - Heliyon, 2023 - cell.com
As a form of clean energy, nuclear energy has unique advantages compared to other energy
sources in the present era, where low-carbon policies are being widely advocated. The …
sources in the present era, where low-carbon policies are being widely advocated. The …
Physics-informed machine learning in prognostics and health management: State of the art and challenges
Prognostics and health management (PHM) plays a constructive role in the equipment's
entire life health service. It has long benefited from intensive research into physics modeling …
entire life health service. It has long benefited from intensive research into physics modeling …
HANNA: hard-constraint neural network for consistent activity coefficient prediction
We present the first hard-constraint neural network model for predicting activity coefficients
(HANNA), a thermodynamic mixture property that is the basis for many applications in …
(HANNA), a thermodynamic mixture property that is the basis for many applications in …
Long-term predictions of turbulence by implicit U-Net enhanced Fourier neural operator
Long-term predictions of nonlinear dynamics of three-dimensional (3D) turbulence are very
challenging for machine learning approaches. In this paper, we propose an implicit U-Net …
challenging for machine learning approaches. In this paper, we propose an implicit U-Net …
Symbolic genetic algorithm for discovering open-form partial differential equations (SGA-PDE)
Partial differential equations (PDEs) are concise and understandable representations of
domain knowledge, which are essential for deepening our understanding of physical …
domain knowledge, which are essential for deepening our understanding of physical …