AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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A parametric physics-informed neural network framework for cylinder-induced thermal flows
Thermal design and monitoring of compact heat exchangers require fields across changing operating conditions, and increasingly from a few embedded sensors, yet each new Reynolds number is a new mesh-based simulation. A physics-informed neural network (PINN) framework is presented for the coupled prediction and inverse...