Radiation field calculation for maritime nuclear emergency
- 1. Naval Academy, Beijing (China)
- 2. Key Laboratory of Neutronics and Radiation Safety, Institute of Nuclear Energy Safety Technology, Chinese Academy of Sciences, Hefei (China)
Description
Source term estimation is the primary technology employed for decision-making during nuclear emergencies. Maritime nuclear accidents have the issue of the movement of radioactive source terms and detectors. In this paper, a technical solution is proposed for the source term inversion of a marine nuclear accident, which is based on the time-spatial correction of the Gaussian cloud model and ensemble Kalman filter. Radionuclide concentrations at different positions under the Daya Bay nuclear power plant were incorporated for modeling a hypothetical nuclear accident, and the nuclear accident source strength was thereby obtained through the modified inversion method. The obtained result is found to differ from the hypothetical accident source strength by a margin of 18.4%. (authors)
Additional details
Identifiers
Publishing Information
- Journal Title
- Journal of Radiation Research and Radiation Processing
- Journal Volume
- 37
- Journal Issue
- 2
- Journal Page Range
- [7 p.]
- ISSN
- 1000-3436
INIS
- Country of Publication
- China
- Country of Input or Organization
- China
- INIS RN
- 54049798
- Subject category
- S61: RADIATION PROTECTION AND DOSIMETRY;
- Descriptors DEI
- CONCENTRATION RATIO; DAYA BAY-1 REACTOR; EMERGENCY PLANS; HYPOTHETICAL ACCIDENTS; NUCLEAR POWER PLANTS; RADIATION ACCIDENTS; RADIATION SOURCES; RADIOACTIVE CLOUDS; RADIOACTIVITY; RADIOISOTOPES; SEAS; SIMULATION; SOURCE TERMS
- Descriptors DEC
- ACCIDENTS; CLOUDS; DIMENSIONLESS NUMBERS; ENRICHED URANIUM REACTORS; ISOTOPES; NUCLEAR FACILITIES; POWER PLANTS; POWER REACTORS; PWR TYPE REACTORS; REACTORS; SURFACE WATERS; THERMAL POWER PLANTS; THERMAL REACTORS; WATER COOLED REACTORS; WATER MODERATED REACTORS
Optional Information
- Notes
- 4 figs., 2 tabs., 13 refs.; http://dx.doi.org/10.11889/j.1000-3436.2019.rrj.37.020603