Abstract

The whole-core transport code nTRACER has made many advances in recent years. Several innovative cross section treatment methods were developed, a new axial transport solver was introduced for stabilizing the 2D/1D scheme, and substantial computational enhancements were achieved using NVIDIA CUDA and Intel Math Kernel Library (MKL). In addition, gamma transport solver was implemented to predict the power distributions more physically, and the flexibility of the restart calculation was improved using an offline processing code nTIG (nTRACER Input Generator). This paper is the compilation of the recent progresses in nTRACER developments.

Highlights

  • NTRACER [1] is a 2D/1D direct whole-core transport code being developed at Seoul National University

  • The methodology of the subgroup method was improved with the introduction of Macro Level Grid (MLG) scheme and Equivalent Dancoff factor Cell (EDC) method to significantly reduce the time consumed by the resonance treatment without loss of accuracy [7]

  • Computational enhancements were achieved with cutting-edge high performance computing (HPC) technologies like NVIDIA CUDA and Intel Math Kernel Library (MKL)

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Summary

INTRODUCTION

NTRACER [1] is a 2D/1D direct whole-core transport code being developed at Seoul National University. It was demonstrated that using asymptotic scattering kernel of hydrogen in epithermal energy range and neglecting angle dependence of multi-group cross sections in resonance energy range introduce huge biases in spectra and in reaction rates. These problems were resolved by using free-gas scattering kernel of hydrogen in epithermal energy range and by using region-wise spectral SPH factors, respectively. Computational enhancements were achieved with cutting-edge high performance computing (HPC) technologies like NVIDIA CUDA and Intel Math Kernel Library (MKL) Capabilities such as gamma transport and nTIG (nTRACER Input Generator) were developed to extend the applicability. The readers are encouraged to refer to the reference papers for more detailed information

METHODOLOGICAL IMPROVEMENTS
COMPUTATIONAL ENHANCEMENTS
ADDITIONAL FEATURES
Effectiveness of advanced cross section treatments
Computational enhancements
16 Cores of Intel Xeon E5-2640 v3
CONCLUSIONS
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