Nuclear Reactor Core Dynamics Control Using Neural Networks

Stable power processes are never guaranteed. An assortment of unstable behaviors wrecks power apparatus, including mechanical vibration, malfunctioning control apparatus, unstable fluid flow, unstable boiling of liquids, or combinations thereof. A necessary condition for stable reactor power is that the reactor distortion accompanying a temperature rise decreases the reactivity, thus slowing any further rise in power. Nuclear Reactor may changes with time for the number of reasons: Nuclear Fuel Shuffling, Fuel burn up, Control rod motion, coolant flow Perturbations. Our paper involves coolant flow perturbations control using Artificial Neural networks. ANNs have been widely used for various tasks, such as pattern classification, time series prediction, nonlinear control, and function approximation neural networks are intrinsically parallel and non-algorithmic methods; these features of neural networks make real-time processing of data and information feasible. Neural networks, have been trying to fill the gap for which traditional techniques have, so far failed to offer a reasonable solution.