Integration of the heterogeneous reliability data for fusion-specific components of the DONES Accelerator Systems

Abstract

A novel method in the fusion field has been established to integrate the heterogeneous reliability data for fusion-specific components of the DONES Accelerator Systems. It makes use of several data sources of different content and structures developed independently by various organizations. The algorithm is based on the commonly used Monte Carlo method. The random sampling of reliability data coming from different sources is preceded by the selection of the relevant inputs. The sampling process is implemented with respect to the within-source and between-source uncertainty of the raw input data. As a result, the empirical probability distributions are generated for the failure rates of the relevant components that can be used in safety and reliability studies of the DONES Accelerator Systems. The final objective is to improve the RAMI and safety studies by enhancing the quality of the input models. This, in turn, provides more confidence to the decision makers on the fusion systems design. The general method proposed in this work can be applied, however, for the source-to-source integration of the reliability data for a wide range of other components, thus making the statistical inferences on the system's reliability more adequate.