Published January 2019 | Version v1
Journal article

GPU-based implementation of a real-time model for atmospheric dispersion of radionuclides

  • 1. Comissão Nacional de Energia Nuclear - IEN/CNEN, Rua Helio de Almeida, 75, Ilha do Fundão, 21941- 906, Rio de Janeiro (Brazil)
  • 2. Universidade Federal do Rio de Janeiro - PEN/COPPE/UFRJ, Ilha do Fundão, 21941-901, Centro de Tecnologia, Rio de Janeiro (Brazil)

Description

Highlights: • A refined version of a NPP atmospheric dispersion model was developed. • The refined model demonstrated to be more accurate on dose rates estimation. • To deal with the computational overhead, GPU acceleration was applied. • The GPU-accelerated program is 36 times faster than the sequential version. -- Abstract: This work presents the latest development related to the improvement of the atmospheric dispersion system (ADS) used in Central Nuclear Almirante Alvaro Alberto (CNAAA) nuclear power plant (NPP). The ADS upgrade includes a refinement of spatial resolution at the expense of computational time. To overcome such difficulty, the use of parallel computing (PC) has been proposed. In the considered ADS, the physical calculations are performed by 4 main modules: the source term, the wind field, the plume dispersion and the plume projection modules. As the source term module is not affected by the proposed refinements, it has not been focused until this moment. On the other hand, the remaining modules are strongly affected by the spatial resolution. In the first stage of the project, a GPU-based version of the wind field module was developed using the Compute Unified Device Architecture (CUDA), which was 30 times faster than the sequential version. Motivated by such promising results, the present work focuses in the development and evaluation of the GPU-based (also using CUDA) version of the plume dispersion module, which main feature is to calculate transport and diffusion of radionuclide in the atmosphere by using a three-dimensional puff model with Lagrangian trajectory and Gaussian diffusion. As a result, the execution time of the most refined simulation decreased from 2499 s (running on an Intel-Core I5 7500 CPU) to 68 s (running on a GTX-1070 GPU), meaning a considerable speedup of about 36 times. Here, the most important issues of the parallel implementation, as well as comparative results, are presented and discussed.

Additional details

Identifiers

DOI
10.1016/j.pnucene.2018.09.015;
PII
S0149197018302439;

Publishing Information

Journal Title
Progress in Nuclear Energy
Journal Volume
110
Journal Page Range
p. 245-259
ISSN
0149-1970
CODEN
PNENDE

Optional Information

Copyright
Copyright (c) 2018 Elsevier Ltd. All rights reserved.