Groundshine dose-rate conversion factors of soil contaminated to different depths.

For assessment of external doses from the ground contaminated with radionuclides, the dose-rate conversion factors (DCFs) prescribed in FGR (Federal Guidance Report) 12 have been used. Recently, significant changes were made by International Commission on Radiological Protection in dosimetric models and parameters, which include use of Reference Phantoms and revised tissue-weighting factors, as well as the updated decay data of radionuclides. The DCFs for effective and equivalent doses due to groundshine from contaminated soil were re-calculated by taking the changes into account. In this study, the DCFs for effective and equivalent doses were calculated for depths of 1, 5 and 15 cm and for infinite deposition. Doses to the Reference Phantoms were calculated by Monte Carlo simulations with the MCNPX 2.7.0 radiation transport code for 26 mono-energy photons between 0.01 and 10 MeV. Transport calculations were performed for the source volume within the converging of distances and depths practically contributing to the dose rates, which were determined by a simple model. With the resulting doses, empirical response functions were constructed as a function of photon energy. The DCFs for the radionuclides considered important were evaluated by combining the photon emission data of the radionuclide and the response functions. Finally, the contributions of accompanied beta particles to the skin equivalent doses and the effective doses were calculated separately and added to the DCFs. For radionuclides considered in this study, the new DCFs for the different depths agreed within 10 % with the data in FGR12.

Statistical approaches to forecast gamma dose rates by using measurements from the atmosphere.

In this paper, the results obtained by inter-comparing several statistical techniques for estimating gamma dose rates, such as an exponential moving average model, a seasonal exponential smoothing model and an artificial neural networks model, are reported. Seven years of gamma dose rates data measured in Daejeon City, Korea, were divided into two parts to develop the models and validate the effectiveness of the generated predictions by the techniques mentioned above. Artificial neural networks model shows the best forecasting capability among the three statistical models. The reason why the artificial neural networks model provides a superior prediction to the other models would be its ability for a non-linear approximation. To replace the gamma dose rates when missing data for an environmental monitoring system occurs, the moving average model and the seasonal exponential smoothing model can be better because they are faster and easier for applicability than the artificial neural networks model. These kinds of statistical approaches will be helpful for a real-time control of radio emissions or for an environmental quality assessment.

Determination of the source rate released into the environment from a nuclear power plant.

A study was carried out to determine the source rate from a nuclear power plant using the tracer experimental data conducted at the Yeoung-Kwang nuclear site. The least squares method optimises the agreement between the released source rate and the calculated source rate by minimising the errors between the measured concentrations and the calculated ones using the Gaussian plume model. The least squares estimator generally estimates the source rate to be within a factor of 2. The forecasting ability of the source rate is improved by applying the modified dispersion coefficients that are calculated using the experimental data. Determination of the source rate in an early phase nuclear emergency will be helpful for the decision making when taking appropriate and prompt countermeasures in the case of a radiological emergency.