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Updated: Apr 27, 2026

Laser-heating and Radiance Spectrometry for the Study of Nuclear Materials in Conditions Simulating a Nuclear Power Plant Accident
Published on: December 14, 2017
Off-site risk area delineation under severe nuclear accident conditions: A deterministic-probabilistic coupled
Shengyu Liu1, Hongchun Ding2, Alice Hu1
1Department of Mechanical Engineering, City University of Hong Kong, Kowloon Tong, Hong Kong, China.
Abstract:
Emergency preparedness and response must adopt proactive roles to foster public awareness of risks associated with severe Nuclear Power Plants (NPPs) emergencies. However, the inadequacy in defining risk areas impedes the effective management of uncertainties in NPP emergencies involving the off-site release of radioactive materials. In this study, we propose a deterministic-probabilistic coupled consequence analysis framework to characterize radionuclide dispersion dynamics and assess radiation consequences, with the aim of elaborately delineating risk areas for emergency public health planning during severe nuclear accidents, fully accounting for multiple uncertainties. A Monte Carlo simulation approach is designed to operationalize an atmospheric dispersion model, based on the CALPUFF software, accounting for uncertainties arising from source terms and meteorological factors. Probabilistic risk measures, based on Value-at-Risk (VaR), are used to statistically interpret radiological hazards into effective dose distributions for defining risk boundaries in various directions around an NPP. The proposed framework is verified considering severe nuclear accidents with release amounts sampled to exceed those of the Fukushima accident. Illustrative results from the Fukushima Daiichi NPP (FDNPP) demonstrate its effectiveness in preparing risk area delineations that encompass the real government-mandated Emergency Planning Zone (EPZ) with a radius of 20 km. The comparative analysis shows the framework's universality of different NPPs and reveals that the directional differences of risk area distribution arise from both terrain and meteorological conditions, with terrain impeding dispersion at higher altitudes and meteorology dominating when terrain effects weaken. Besides, the seasonal spatial heterogeneity characteristic analysis for FDNPP highlights that prevailing winds enhance the directional difference of risk area distribution, underscoring the need to incorporate monthly or seasonal meteorological statistics to ensure robust and effective risk area delineations.
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