An ontological approach to modelling interdependencies in dam failure mode risk studies
Various regulatory bodies governing several industries have established guidelines for conducting Failure Modes and Effects Analysis (FMEA) and Potential Failure Modes Analysis (PFMA). A common approach in these guidelines is to break down the systems into subsystems, and components to identify potential failures across all levels. Existing controls are then identified, and mitigation measures and emergency response measures are developed based on relevant knowledge and strategies for the project at hand. The complex interdependencies that exist within systems and failure modes, especially for hydropower dams and tailing storage facilities, are not explicitly captured in the conventional FMEA or PFMA tabular data structure. This may result in overlooking the global impact of shared control measures, risk reduction opportunities, and cause and effect relationships influencing the cascading failure effects.
The analysis of such information is crucial for data-driven decision-making which forms the foundation for efficient emergency response plannings. To overcome these issues, this paper proposes a new ontology approach to capture, model and visualize the logical relationships between potential failure modes, controls, mitigation measures and emergency response plans. These relationships are embedded in a knowledge graph through ontology engineering principles, allowing for informed quantification of the impacts and enabling sophisticated queries from the captured information. In addition, this approach allows for a consistent data structure, opening the door for further analysis and integration of the domain knowledge.