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Updated: Jun 6, 2026

Irradiator Commissioning and Dosimetry for Assessment of LQ α and β Parameters, Radiation Dosing Schema, and in vivo Dose Deposition
Published on: March 11, 2021
A gamma radiation dose calculation method for use with Lagrangian puff atmospheric dispersion models used in
1Environmental Research Laboratory, Institute of Nuclear Technology and Radiation Protection, National Centre for Scientific Research Demokritos, Patriarchou Grigoriou (end) & Neapoleos Str., Aghia Paraskevi, Greece. sandron@ipta.demokritos.gr
Abstract:
The paper presents the development of a model for the calculation of the gamma radiation dose rate from a cloud or plume of radionuclides. The model has been implemented in the Lagrangian puff dispersion model DIPCOT which is used in the framework of the RODOS system for nuclear emergency management. The basic characteristics of the model are its speed of execution and its ability to calculate the gamma dose rates from clouds or plumes of random shape formed under non-homogeneous meteorological conditions or over complicated topography. The three-dimensional integral that would normally have to be numerically calculated in such circumstances has been transformed to a one-dimensional one through a coordinate transformation for each model puff and by using a separation of variables technique. The resulting one-dimensional integrals have been pre-calculated and their values stored for a range of parameters that cover the possible ranges of photon energies, puff dimensions and distances encountered in cases of atmospheric dispersion. During runtime the model calculates the exact values by interpolation from stored tables of values. This is a very fast and accurate method, as the evaluation study has proved. The model performance has been evaluated through simulations of a real-scale experiment involving routine emissions of (41)Ar from a reactor and comparisons of model predictions with measured fluence rates. The comparisons have revealed a satisfactory level of agreement and the model performance statistical indices are well above the acceptance criteria that are suggested in the literature.
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