PSAM 16 - Paper Overview

PSAM 16 Conference Paper Overview

Welcome to the PSAM 16 Conference paper and speaker overview page.

Lead Author: Pavel Krcal Co-author(s): Ola Bäckström Ola.Backstrom@lr.org Helena Troili Helena.Troili@lr.org

Control Logic Encoding using RiskSpectrum ModelBuilder
A goal of model-based safety assessment is to bring dependability modeling closer to the system design and allow for automated analysis of these high-level models. A system design description consists of system components and their relations. In many applications, a dependability model can copy the system design very closely. The dependability logic can be specified in a generic form per component type, applicable to all instances of this component type. A model might require a limited amount of specific, irregular, dependability information, such as relations or conditions affecting failures and their propagation. To prepare a model for an analysis, it remains to specify a configuration and safety/availability/production criteria. The modeling language for describing the dependability logic of component types used in RiskSpectrum ModelBuilder is called Figaro and has evolved and matured over decades. It is an object-oriented modeling language with elements of declarative programming. It allows specifying interactions between components in the first-order logic. By this, a general description applies to all valid system topologies. The expressive power of this language has been demonstrated by numerous applications especially in the Nuclear Safety domain. A series of publications describe use cases where it has been successfully applied. In this paper, we demonstrate how the Figaro language and the concept of knowledge bases empowers dependability experts. It allows them to formalize and codify dependability knowledge for a specific domain or application type. It can be then used by non-experts in the form of a component library to build any model from this domain. The knowledge base can be systematically updated or extended whenever there is a need. We focus on the possibilities to encode complex control logic in the component definitions. In general, one can specify any logic that can be described by a finite state machine or by a flow-chart. Communication between components, interactions between the state of a component and the state of related components, and interleaving between stochastic events and control actions necessary for the control are also discussed. We exemplify the power of Figaro on Digital I&C for Nuclear Power Plants, where the ModelBuilder approach allows to relatively easily extend the modeling to include intelligent voting. Automatic fault tree generation avoids the tedious and error-prone process of manual modeling for this complicated feature. We also develop main features of a control unit for a heterogenous power generating station scheduling different power sources to match the demand. As the last example, we consider a control of a Spent Fuel Pool that takes the water level in the pool into account. The latter two applications utilize Monte Carlo simulations for the analysis.

Control Logic Encoding using RiskSpectrum ModelBuilder

A goal of model-based safety assessment is to bring dependability modeling closer to the system design and allow for automated analysis of these high-level models. A system design description consists of system components and their relations. In many applications, a dependability model can copy the system design very closely. The dependability logic can be specified in a generic form per component type, applicable to all instances of this component type. A model might require a limited amount of specific, irregular, dependability information, such as relations or conditions affecting failures and their propagation. To prepare a model for an analysis, it remains to specify a configuration and safety/availability/production criteria. The modeling language for describing the dependability logic of component types used in RiskSpectrum ModelBuilder is called Figaro and has evolved and matured over decades. It is an object-oriented modeling language with elements of declarative programming. It allows specifying interactions between components in the first-order logic. By this, a general description applies to all valid system topologies. The expressive power of this language has been demonstrated by numerous applications especially in the Nuclear Safety domain. A series of publications describe use cases where it has been successfully applied. In this paper, we demonstrate how the Figaro language and the concept of knowledge bases empowers dependability experts. It allows them to formalize and codify dependability knowledge for a specific domain or application type. It can be then used by non-experts in the form of a component library to build any model from this domain. The knowledge base can be systematically updated or extended whenever there is a need. We focus on the possibilities to encode complex control logic in the component definitions. In general, one can specify any logic that can be described by a finite state machine or by a flow-chart. Communication between components, interactions between the state of a component and the state of related components, and interleaving between stochastic events and control actions necessary for the control are also discussed. We exemplify the power of Figaro on Digital I&C for Nuclear Power Plants, where the ModelBuilder approach allows to relatively easily extend the modeling to include intelligent voting. Automatic fault tree generation avoids the tedious and error-prone process of manual modeling for this complicated feature. We also develop main features of a control unit for a heterogenous power generating station scheduling different power sources to match the demand. As the last example, we consider a control of a Spent Fuel Pool that takes the water level in the pool into account. The latter two applications utilize Monte Carlo simulations for the analysis.

Paper PA131 Preview

Author and Presentation Info

Lead Author Name: Pavel Krcal (Pavel.Krcal@lr.org)

Bio: Pavel Krcal finished his PhD in Theoretical Computer Science (Formal Verification of Real-Time Systems) at Uppsala University, Sweden, in 2009. Since then, he is working as a part of the software development team of RiskSpectrum, where he gained profound expertise in Reliability Theory and is now responsible for R&D in the area of modeling and analysis. Pavel maintains the thought leader profile of RiskSpectrum also by collaboration with universities and by scientific publications.

Country: Sweden
Company: LR RiskSpectrum
Job Title: RiskSpectrum Methods Research Lead

PSAM 16 Conference Paper Overview

Welcome to the PSAM 16 Conference paper and speaker overview page.

Paper PA131 Preview

Author and Presentation Info

Download paper PA131.

Download the presentation pdf file.