Event Modeling Risk Assessment using Linked Diagrams (EMRALD)
Overview
- Simplifying the modeling process by providing a structure that corresponds to traditional PRA modeling methods
- Providing a user interface (UI) that makes it easy for the user to model and visualize complex interactions
- Allowing the user to couple with other analysis applications such as physics based simulations. This includes one-way communication for most applications and two-way loose coupling for customizable applications
- Providing the sequence and timing of events that lead to the specified outcomes when calculating results
Traditional aspects of components with basic events, fault trees, and event trees are all captured in a dynamic framework of state diagrams, which are displayed in a user-friendly modeling manner. Each component is represented by a compact state diagram with basic events driving the current state of that component. A logic tree using components corresponding to a fault tree can be evaluated dynamically during the simulations. Finally, event trees are captured in a plant response diagram, with events (including those from the dynamic logic evaluation) driving an end state result. This approach allows the user to implement dynamic methods with only needing to learn the dynamic state aspects of the model. After running the EMRALD model, the user is able to not only obtain probabilistic results, but also able to see dynamic benefits such as timing and event sequences for specified simulation results. Additionally, an open standard for communication is used which allows for coupling to other simulation-based or physics-based analysis. The open standard allows the user to include complex phenomena simulation capabilities such as flood or fire analysis directly in the PRA model.
Running and Results
An EMRALD simulation is run repeatedly according to a value specified by the user. The results from these runs are gathered. For each repeated evaluation, any key end states in the current state list, along with the time paths for those states, is logged in the results. The compilation of these results allows us to determine the probability of any outcome with an uncertainty depending on the number of simulation runs. When using equivalent models with no time related items, the results from the state model evaluation converges on the same result as traditional PRA methods.
No complex convolution adjustments are needed for time based relationships; the state diagram run automatically takes this into account. EMRALD evaluation also allows the user to determine the average or mean time of a particular outcome, or provides data for statistical evaluation for critical failure time ranges.
Software
EMRALD is open source and can be downloaded from GitHub at https://github.com/inl-labtrack/EMRALD . A version of the GUI is also hosted by INL and can be found at https://emraldapp.inl.gov/. For further information and collaboration, contact Steven.Prescott at inl.gov.
