Analyzing Defense-in-Depth Properties of Nuclear Power Plant Instrumentation and Control System Architectures Using Ontologies

The overall instrumentation and control (I&C) architecture of a nuclear power plant (NPP) is comprised of several I&C systems and their dependencies. The architecture needs to fulfil the principle of defense in depth (DiD). Defense-in-depth is the principal method for preventing accidents and mitigating the potential consequences of accidents. The levels of DiD should be independent of each other. The primary means to achieve independence are diversity, physical separation, and functional isolation. Approaches with extensive tool support for ensuring that the design solutions of nuclear overall I&C architectures realize relevant DiD properties are scarce. An ontology of the semantic web is a specification of a representational vocabulary for a shared domain of discourse, containing definitions of classes, individuals, and their relationships. An ontology-based knowledge base, built on named graphs, enables a computer to combine pieces of information into valuable knowledge based on queries. In this paper, we present an ontology-based approach for assessing that an NPP I&C architecture fulfils different DiD properties. In our approach, we aim at checking requirements related to physical separation, electrical isolation, communication independence, diversity, safety classification, and failure tolerance. We also discuss the developed work process and tool chain for ontology-based analysis. We demonstrate the use of the ontology and the work process based on two case studies

Constructing Ontology for Knowledge Sharing of Materials Failure Analysis

Materials failure indicates the fault with materials or components during their performance. To avoid the reoccurrence of similar failures, materials failure analysis is executed to investigate the reasons for the failure and to propose improved strategies. The whole procedure needs sufficient domain knowledge and also produces valuable new knowledge. However, the information about the materials failure analysis is usually retained by the domain expert, and its sharing is technically difficult. This phenomenon may seriously reduce the efficiency and decrease the veracity of the failure analysis. To solve this problem, this paper adopts ontology, a novel technology from the Semantic Web, as a tool for knowledge representation and sharing and describes the construction of the ontology to obtain information concerning the failure analysis, application area, materials, and failure cases. The ontology represented information is machine-understandable and can be easily shared through the Internet. At the same time, failure case intelligent retrieval, advanced statistics, and even automatic reasoning can be accomplished based on ontology represented knowledge. Obviously this can promote the knowledge sharing of materials service safety and improve the efficiency of failure analysis. The case of a nuclear power plant area is presented to show the details and benefits of this method