Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...
Abstract: Physics-informed neural networks (PINNs) provide a flexible framework for solving neutron diffusion equations, yet their accuracy and stability are often hindered by limited spatial ...
Abstract: Based on unsupervised physics-informed neural network (PINN) framework, a two-dimensional inverse-design method for antenna superstrate is proposed, which can simultaneously realize the ...
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