The use of stochastic point processes to model the reliability of repairable systems has been a regular approach to establish survival measures in failure versus repair scenarios. However, the traditional processes do not consider the actual state in which an item returns to operational condition. The traditional renewal process considers an "as-good-as-new" philosophy, while a non-homogeneous Poisson process is based on the minimal repair concept. In this work, an approach based on the concept of Generalized Renewal Process (GRP) is presented, which is a generalization of the renewal process and the non-homogeneous Poisson process. A stochastic modeling is presented for systems availability analysis, including testing and/or preventive maintenances scheduling. To validate the proposed approach, it was performed a case study of a hypothetical auxiliary feed-water system of a nuclear power plant, using genetic algorithm as optimization tool.

This work presents a methodology for the reduction of risks based on a reliability engineering study. In order to explain the methodology, a hypothetical case study is considered, where the scenario is the accidental release, into the environment, of a toxic chemical substance from a chemical process plant, leading to exposure of the local population. The dispersion is modelled by CFD-based software. The optimization process leads the calculated risk (individual and societal) to values below the tolerable limits in accordance with the supervisory boards. The connection between CFD, risk analysis and reliability calculations attests to the robustness and applicability of the proposed approach.

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Infiltration of water into a waste disposal facility and into the waste region is the main factor inducing the release of radionuclides from a disposal facility. Since infiltrating water flow is dependent on the natural percolation at the site and the performance of engineered barriers, its prediction requires modelling of unsaturated water flow through intact or partially/completely failed components of engineered barriers. These include the cover systems, concrete vault, backfill, waste forms, and overpacks. This paper aims to carry out a performance study regarding a near surface repository in terms of reliability engineering. It is assumed that surface water infiltrates through the barriers reaching the matrix where radionuclides are contained, thus releasing them into the environment. The repository consists of a set of barriers which are considered saturated porous medium, except geosphere. A genetic algorithm is employed to establish an optimized configuration to the structure of the repository, by determining the thicknesses of barriers and waste packages arrangement, taking into account the engineering and radiological constraints. Such restrictions aim to keep the risks associated with the migration of radionuclides at a low level.

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