Izvorni znanstveni članak

Point Kernel Modification Including Support Vector Regression Neutron Buildup Factor Models

Paulina Dučkić, ; University of Zagreb, Faculty of Electrical Engineering and Computing Unska 3, 10000 Zagreb, Croatia
Krešimir Trontl, ; University of Zagreb, Faculty of Electrical Engineering and Computing Unska 3, 10000 Zagreb, Croatia
Davor Grgić, ; University of Zagreb, Faculty of Electrical Engineering and Computing Unska 3, 10000 Zagreb, Croatia
Mario Matijević ; University of Zagreb, Faculty of Electrical Engineering and Computing Unska 3, 10000 Zagreb, Croatia

Sažetak

This work presents the results of radiation shielding calculations using modified point kernel
code QAD-CGGP. The modification includes a new approach to neutron buildup factor estimations
based on machine learning technique called Support vector regression (SVR). SVR neutron buildup
factor models for common shielding materials are developed and built into the QAD-CGGP. The
development of the models consisted of acquiring the data to be used for learning the model,
optimizing the SVR parameters, and application of active learning methods for improving the
learning process. The modified code is tested, and the results are compared with the MCNP6 results.

Ključne riječi

point kernel, neutron buildup factor, support vector regression, shielding

Hrčak ID:

247098

URI

https://hrcak.srce.hr/247098

Datum izdavanja:

28.10.2019.

Posjeta: 719 *