The management of spent nuclear fuel assemblies of nuclear reactors is a priority subject among member states of the International Atomic Energy Agency. For the majority of these countries, the destination of such fuel assemblies is a decision that is yet to be made and the “wait-and-see” policy is thus adopted by them. In this case, the irradiated fuel is stored in on-site spent fuel pools until the power plant is decommissioned or, when there is no more racking space in the pool, they are stored in intermediate storage facilities, which can be another pool or dry storage systems, until the final decision is made. The objective of this study is to propose a methodology that, using optimization algorithms, determines the ideal time for removal of the fuel assemblies from the spent fuel pool and to place them into dry casks for intermediate storage. In this scenario, the methodology allows for the optimal dimensioning of the designed spent fuel pools and the casks’ characteristics, thus reducing the final costs for purchasing new Nuclear Power Plants (NPP), as the size and safety features of the pool could be reduced and dry casks, that would be needed anyway after the decommissioning of the plant, could be purchased with optimal costs. To demonstrate the steps involved in the proposed methodology, an example is given, one which uses the Monte Carlo N-Particle code (MCNP) to calculate the shielding requirements for a simplified model of a concrete dry cask. From the given example, it is possible to see that, using real-life data, the proposed methodology can become a valuable tool to help making nuclear energy a more attractive choice costwise.

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The objective of this chapter is to discuss two approaches for reliability analysis of digital instrumentation and control systems in nuclear power plants taking into account the regulatory side. Dynamic Flowgraph Methodology (DFM) and Markov/Cell-to-Cell Mapping Technique (CCMT) are discussed and case studies developed are presented. These case studies involve simplified control systems for a steam generator and a pressurizer of a Pressurized Water Reactor (PWR) plant for the purpose of evaluating each method. Advantages and limitations of each approach are addressed. For the DFM approach, three concerns in the literature are addressed: modeling of the system itself, incorporation of the methodology results into existing Probabilistic Safety Assessments (PSA), and identification of software failures. The Markov/CCMT, which has been used in dynamic probabilistic safety assessments, is approached by means of a simplified digitally controlled water volume control system. The Markov/CCMT methodology results in detailed data of the system reliability behavior in relation to time. However, it demands a higher computational effort than usual as the complexity (i.e., number of components and failure states) of the system increases. As a regulatory research conclusion, the methodologies presented can be used on PSA risk informed assessment, contributing to the regulatory side.