Home / Store / Journals / Electronic Articles / Nuclear Technology / Volume 128 / Number 2
Seung Hwan Seong, Un Chul Lee, Si Hwan Kim, Jin Wook Jang
Volume 128 / Number 2 / November 1999 / Pages 276-283
Format:electronic copy (download)
A new analytic model based on hidden-layer neural networks is designed to analyze load-follow operation in a pressurized water reactor (PWR). The new model is mainly made up of four error backpropagation neural networks and procedures to calculate core parameters such as k and xenon distributions in a transient core. The first two neural networks are designed to retrieve the power distribution, the third is for axial offset, and the fourth is for reactivity corresponding to a given core condition. The training data sets are generated by three-dimensional nodal code and the measured data of the first-day load-follow operation. The simulation results of the 5-day load-follow test in a PWR using the new analytic model show that it is an attractive tool for plant simulations in terms of accuracy, computing time, cost, and adaptability to measurements.
Your cart is empty.
Home|Invoice Payment|Nuclear Links