Original scientific paper
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
Abstract
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.
Keywords
point kernel, neutron buildup factor, support vector regression, shielding
Hrčak ID:
247098
URI
Publication date:
28.10.2019.
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