Source inversion of both long- and short-lived radionuclide releases from the Fukushima Daiichi nuclear accident using on-site gamma dose rates.

Following a nuclear accident, on-site gamma dose rates provide the most complete record of atmospheric releases of both long- and short-lived radionuclides. However, they are seldom used for source inversion, because the radionuclide composition is unknown. This prevents the estimation of short-lived radionuclide releases. In this study, a method using on-site gamma dose rates is developed with the aim of determining the source term, including both long- and short-lived radionuclides. To reduce the uncertainties involved in source inversion, the proposed method uses reactor physics to obtain an a priori radionuclide composition and a reverse source term estimate as an a priori release rate. A weighted additive model is derived to handle the conflicts between the priors from different mechanisms and simultaneously incorporate them into the source inversion. The proposed method is applied to the Fukushima Daiichi accident and validated against both the on-site gamma dose rates and the regional measurements of Cs-137. The results demonstrate that the resolved a posteriori source term combines the advantages of both priors and substantially improves the predictions of the on-site gamma dose rates. Given a detailed a priori release rate, this approach also improves the regional predictions of both airborne and deposited Cs-137 concentrations.

Numerical analysis of granular flows in a silo bed on flow regime characterization.

The flow characteristics of a gravity-driven dense granular flow in a granular bed with a contracted drainage orifice are studied by using discrete element method and quantitative analysis. Three values of discharging rates, ranging from fast to slow dense flows, are investigated. Time variations and derivatives of mean forces and velocities, as well as their respective correlations, are analyzed to quantitatively depict the characteristics of granular flow as well as flow regime categorization. The auto-correlation functions, as well as their Fourier spectrums, are utilized to characterize the differences between the mechanisms of slow and fast granular flows. Finally, it is suggested that the flow regimes of slow and fast flows can be characterized by the kinetic and kinematic flow properties of particles.