Abstract
Global radionuclide dispersion from Fukushima nuclear accident urged several countries to begin evaluating the radiation effects from neighboring countries. The representative data selection simulation is one of the evaluation methods providing practical results with reasonable computational resources. However, it is mostly used in the domestic radiation effect evaluation. This study investigated and modified this simulation method for transboundary radiation effect evaluation. The effects of selected area boundaries, optional weather parameters, and sampling rate, critical parameters in the representative data selection scheme, are sequentially investigated on the calculated results. The evaluation is performed by Nuclear Accident Consequence Analysis Code (NACAC) with hypothetical accidents at Fangchenggang NPP in China. It is revealed that area boundary and optional weather parameter selection insignificantly impact the predicted results, but the sampling rate condition affects the predicted results. Good agreements comprising dispersion characteristics and total effective dose equivalent by simulation using representative and sequential data selections are shown with absolute mean bias error lower than 2.4 × 10−3 mSv, root mean square error lower than 5.7 × 10−4 mSv, and correlation coefficient value higher than 9.1 × 10−1. © 2023 Atomic Energy Society of Japan. All rights reserved.
| Original language | English |
|---|---|
| Pages (from-to) | 327–342 |
| Number of pages | 16 |
| Journal | Journal of Nuclear Science and Technology |
| Volume | 61 |
| Issue number | 3 |
| Online published | 13 Jul 2023 |
| DOIs | |
| Publication status | Published - Mar 2024 |
Research Keywords
- atmospheric dispersion
- meteorological data selection
- Radiation consequence evaluation
Publisher's Copyright Statement
- COPYRIGHT TERMS OF DEPOSITED POSTPRINT FILE: This is an Accepted Manuscript of an article published by Taylor & Francis in JOURNAL OF NUCLEAR SCIENCE AND TECHNOLOGY on 13 Jul 2023, available online: https://doi.org/10.1080/00223131.2023.2231444.