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Status and usage of the MFM Suite for Diagnostic and Prognostic Reasoning
Abstract
This paper presents the status of a software system, the MFM Suite, dedicated to the design and analysis of MFM models related to diagnostic and prognostic analysis of physical processes. New and updated features of the system are described, as well as some examples of its practical use. The paper also briefly describes how the system facilitates the collaboration between control room and field operators via the Android-based MFM Viewer app.
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Multilevel Flow Modelling (MFM) is a functional modelling methodology which applies means-end and parts-whole decomposition and aggregation techniques to handle the complexity of engineering systems. It has been adopted in several case studies to model the process goal and functions of PWR systems. Two of the modelling examples can be found in HWR-990 and HWR-1059. The inherent causal reasoning capability enabled the developed MFM models to be used for diagnostic and prognostic analysis.
These MFM models have been used to develop the basis for implementing operator support tools, with the aim to facilitate the plant operators to evaluate and understand plant situations. The theoretical aspects have been established for the cooperative development of an MFM software tool, namely MFM Suite, by the Halden Reactor Project (HRP) and the Technical University of Denmark (DTU). The MFM Suite is equipped with an MFM Model Editing Interface to facilitate the modelling process and MFM model analysis modules to run diagnosis and prognosis analyses based on developed models. New features of the MFM Suite also include making corresponding process diagram for the plant being modelled with MFM and linking the MFM model to its process components.
The purpose of this report is to make a comprehensive demonstration of how to use the MFM Suite to develop MFM models and run causal reasoning for abnormal situations. This report will explain the capability of representing process and operational knowledge by using the MFM methodology, and demonstrate how the model combined with the MFM reasoning can be used to evaluate the plant state, identify the current situation and support operational decisions. The report will provide a detailed explanation of MFM concepts by modelling the primary side system of the Ringhals Westinghouse PWR and demonstrate the MFM reasoning for accident situation.
This paper reports on the results from the practical application of the ShapeShifter framework on the continued development of a graphical editing suite, the MFM Suite, for MFM and process model design and analysis. The primary use of the MFM Suite is diagnosis and prognosis of anomalies in physical processes. One of the Halden Reactor Project’s advanced NPP simulators based on a PWR is used to demonstrate the applicability of the suite in realistic situations. The paper presents a summary and suggests some plans for future research and development.
This paper demonstrates how a generic agent-oriented framework can be used in advanced automation environments, for systems analysis in general and supervision, diagnosis and prognosis purposes in particular. The framework’s background and main application areas are briefly described. Next, the function-oriented method Multilevel Flow Modeling (MFM) and its reasoning mechanisms that have proven strength in qualitative planning, modeling and diagnosis activities are introduced. The main enhancements of the framework, as well as an MFM editor based on the framework and towards function-oriented supervision, diagnosis and prognosis purposes are equally explained. Finally, the paper sums up by also addressing plans for further enhancement and in that respect integration with other tailor-made tools for joint treatment of various modeling and analysis activities upon advanced automation environments.
The paper describes the continued development of the Java-based ShapeShifter framework, previously described in papers published in the ESREL 2010 and 2011 proceedings, including updated and new base classes, visual components and essential functionality. The framework is based on the Capability-Oriented Agent Theory, advocating a multi-purpose view of socio-technical systems as made of human, organizational and technical agents and their assets. The paper further reports on how the framework is being used in the development of a graphical editor supporting the Multilevel Flow Modeling (MFM) method, to be utilized for Supervision, Diagnosis, and Prognosis (SDP) applications in advanced automation environments. The recently started development of the ShapeShifter-based Process Modeler, which in combination with the MFM Editor and the reasoning capabilities of the MFM Workbench developed by the Technical University of Denmark will constitute the MFM Suite, is also described.
This paper summarizes the development to date of the Java-based MFM Editor, a graphical editor supporting the Multilevel Flow Modeling (MFM) method, to be used for Supervision, Diagnosis and Prognosis (SDP) applications in advanced automation environments. The editor builds on the ShapeShifter graphical framework, previously described in the proceedings of the ESREL 2010, 2011 and 2012 conferences. The paper focuses on the editing capabilities and the recently added reasoning functionality (provided by the Technical University of Denmark) required to perform cause and consequence analyses (diagnosis and prognosis) of MFM models. Also, a recently developed process design module is described in some detail.
Assessing Operational Situations
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X. Zhang, "Assessing Operational Situations", PhD thesis, Department
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Applying MFM to the PWR Analysis: The experimental results and preliminary conclusions
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Diagnostic Decision Support -Recent Development and Updates of the MFM Suite
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H. P-J Thunem, "Diagnostic Decision Support -Recent Development
and Updates of the MFM Suite," Halden Report HWR-1223, Institute for
Energy Technology, August 2017
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