Deep and stable geological formations with low permeability have been considered for high level waste definitive repository. A common problem is the modeling of radionuclide migration in a fractured medium. Initially, we considered a system consisting of a rock matrix with a single planar fracture in water saturated porous rock. Transport in the fracture is assumed to obey an advection-diffusion equation, while molecular diffusion is considered the dominant mechanism of transport in porous matrix. The partial differential equations describing the movement of radionuclides were discretized by finite difference methods, namely, fully explicit, fully implicit, and Crank-Nicolson schemes. The convective term was discretized by the following numerical schemes: backward differences, centered differences, and forward differences. The model was validated using an analytical solution found in the literature. Finally, we carried out a simulation with relevant spent fuel nuclide data with a system consisting of a horizontal fracture and a vertical fracture for assessing the performance of a hypothetical repository inserted into the host rock. We have analysed the bentonite expanded performance at the beginning of fracture, the quantified radionuclide released from a borehole, and an estimated effective dose to an adult, obtained from ingestion of well water during one year.
The crew of a nuclear-powered submarine under development in Brasil plays an important role in its safety. For this reason, crew members must be trained in procedures against undesired events. However, information that would help to accurately decrease human error probability (HEP) on board nuclear-powered submarines is not available in the literature. Therefore, a methodology is required to obtain this information. This study introduces importance measures to evaluate the contribution of performance shaping factors (PSFs) and their levels to HEP. Importance measures Fussell-Vesely, risk reduction worth, risk achievement worth, and Birnbaum importance, commonly used in probabilistic safety assessment, are introduced to identify PSFs and PSF levels that contribute the most to HEP. The proposed approach is focused on identifying HEP's main contributors, oriented toward decision-making.The methodology uses the PSFs established in the Standardized Plant Analysis Risk-Human Reliability Analysis method and a Bayesian network to quantify HEP. Moreover, the results of an application case demonstrate the method's effectiveness in integrating expert opinions into representative values of HEP and in identifying critical PSFs and PSF levels that should be the object of the decision-making process to improve human performance.
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