Improved OPAL Monitoring and Management System (CIEAM)

The project aims at the development of advanced monitoring and plant management capability for the new Open Pool Australian Light-water reactor (OPAL), by examining the use of model-based condition monitoring techniques that would extend common rule-based mechanisms (such as implemented in the prospective Avantis.CM), and the use of advanced integration technology to incorporate other databases and data sets, the implementation of an integrated plant management visualisation interface, and streaming data processing and warehousing technology.

This project is part of the CIEAM program Systems Integration & IT and is conducted in collaboration with the Knowledge and Software Engineering Department at Johannes Kepler University Linz, Austria.

Project Aspects

The three major research areas of the project are data integration, condition monitoring, and sensor data processing & data warehousing.

The data integration deals with the integration between the OPAL 3D data model and SAP, the analysis of OPAL data to monitor regulatory compliance of OPAL operation, to provide output usable for the generation of standard OPAL reports, and the transformation of the data into formats amenable to use within the planned Data Warehousing module.

The condition monitoring covers analysis of the rule-based monitoring and analysis facility provided by standard industry tools with an identification of possible extensions. Technically, a rule-based approach has known limitations in terms of expressiveness and flexibility. Other approaches include model-based approaches using higher level declarative languages and neural network based approaches.

The notion of Data Warehousing is based on the assumption of storing aggregate business data (e.g., accumulated per week or month etc.) to enable visualisation and analysis of the state and trends of the business processes. Business data are processed in batches (nightly or weekly) for entry into the warehouse. In a real-time or near-real time sensor data processing situation, this is expected to happen more frequently. Time scale and aggregation hierarchies are different, as are the typical queries expected to be asked. This requires the development of proper description techniques for the situation encountered with the OPAL reactor, and examination of the question whether standard Datawarehousing products can be used.

Project Leaders

Researchers