In the current conception of some permanent repositories for radioactive wastes, these are trapped, after proper conditioning, in cement matrices within special drums. These drums, in turn, are placed in a concrete container called a "module", in which the space between the drums is back-filled with grout. Finally, several modules are stacked within the concrete walls of the repositories. Through this multiple barrier design, typical of the nuclear industry, the disposal facility is expected to ensure adequate protection of man and environment against the radiological impacts of the wastes by meeting various functional objectives which aim at limiting the release of radionuclides. Because one of the principal mechanisms of release of radionuclides is through water infiltration into the various constituents of the repository and subsequent percolation into the groundwater system, it is of utmost importance to study the phenomena of advection and dispersion of radionuclides in the artificial porous matrices hosting the waste (near field) and, subsequently, in the natural rock matrix of the host geosphere (far field). This paper addresses the issue of radionuclide transport through the artificial porous matrices constituting the engineered barriers of the repository's near field. The complexity of the phenomena involved, augmented by the heterogeneity and stochasticity of the media in which transport occurs, renders classical analytical-numerical approaches scarcely adequate for realistic representation of the system of interest. Hence, we propound the use of a Monte Carlo simulation method based on the Kolmogorov and Dmitriev theory of branching stochastic processes. © 2002 Elsevier Science Ltd. All rights reserved.
All Science Journal Classification (ASJC) codes
- Nuclear Energy and Engineering
- Waste Management and Disposal
Marseguerra, M., Zio, E., Patelli, E., Giacobbo, F., Risoluti, P., Ventura, G., & Mingrone, G. (2003). Modeling the effects of the engineered barriers of a radioactive waste repository by Monte Carlo simulation. Annals of Nuclear Energy, 30(4), 473 - 496. https://doi.org/10.1016/S0306-4549(02)00072-5