Fire Modeling Background
Fire analysis is a key component of assessing risk in nuclear (and other) facilities. It is required as part of a Probabilistic Risk Assessment (fire PRA).
Fauske & Associates, LLC (FAI) performs detailed fire modeling of nuclear and industrial facilities using our own in-house software and widely used public domain tools. We have more than ten year’s experience in model development, validation, participation in international exercises and application to nuclear power stations and fuel cycle facilities. Because we have developed and benchmarked our own models, we understand the strong points and the limitations of public domain tools, so that we can correctly judge the applicability of results for individual scenarios and the impact of modeling uncertainties.
Fire modeling services include:
Logic for Selection of Fire Modeling Software
|Public domain CFD
|FAI-developed & licensed Nuclear QA
|Public domain "zone"
|Best for complicated flow patterns and temperature profiles are anticipated
|Best for multiple room situations, heavier –than-air gases and tracking radioactive & toxic aerosols
|Good for quick modeling of one or two rooms
|Improved target model available soon, not practical for multiple rooms
|Target model similar to FDS, hybrid of zone with multi-dimensional targets
|No aerosol capability
From the U.S. perspective, fire PRA methodology is outlined in a key document created jointly by EPRI and NRC, EPRI-1011989, NUREG/CR-6850. Tasks 8 and 11 pertain to fire modeling and cover scoping and detailed modeling respectively.
Defining a fire modeling scenario means selecting an initial ignition source targets that could be damaged or catch fire, the geometry of the room (or rooms) and details of relationships between ignition sources, targets and other obstacles; the geometry of flow paths; the configuration of doors and vents that may vary with time; and the influence of engineered systems such as forced flows and fire protection.
Three basic levels of modeling software are used in practice. The essence of the challenge is that no single method is perfect, so that in practice all three approaches are usually followed in order of complexity for a given application.
A “scenario model and inputs” means definition of details of the heat release rate (HRR) history from the combustible load, appropriate peak HRR and growth and decay characteristics, definition of how the geometries of the room, fire, targets and other obstacles are rendered, definition of pyrolysis characteristics that influence the potential for propagation and definition of performance of engineered systems.
The key challenge in drawing conclusions from fire modeling results is simply how do you know if the results are correct, conservative or non conservative? This challenge is met through the experience of the analyst and familiarity with experimental data that are used to validate the fire models. The analyst must understand the similarities and differences between experimental configurations and scenarios and those plant configurations and scenarios that are being modeled.
Fauske & Associates, LLC (FAI) provides a full range of services related to fire modeling. Levels of attack include modeling to support a full fire PRA, modeling to support safe shutdown analysis; a “triage plan” to determine where fire modeling would certainly resolve issues, could potentially resolve issues, or cannot realistically provide benefit; or a management plan to determine realistic cost and schedule associated with such undertakings given a plant –specific state of information.
From a U.S. perspective, fire PRA methodology is outlined in a key document created jointly by EPRI and NRC, EPRI-1011989, NUREG/CR-6850. Challenges in applying the cable selection and circuit analysis methodology are discussed here following the order of work flow in practical application.
The PRA/Risk model quantifies the logical dependencies between components and whether or not failures propagate. One challenge is to ensure collectively exhaustive, finest-grain, one-to-one correspondence between components used in the risk model and components for circuit analysis. A risk model originally created for a safe shutdown analysis may need to be revised for a PRA, for example to include more components and to consider multiple paths to success. When multiple components are considered in an “OR” gate in the risk model, circuit analysis and cable routing need to be capable of revealing any common mode failures / dependencies, for example, cases when two components share a power supply or cables share routing. The interface challenge is also related to the boundary problem for circuit analysis.
The primary challenge is to identify all the required safety functions for a given piece of equipment. For example, both failure to start and failure to run (continued operation) are typical failure modes for pumps and diesels. The ability to both open and close a valve may be required. The risk model should either explicitly consider supporting equipment such as room chillers in the equipment list, or there need to be documented work-arounds for each piece of supporting equipment.
The “analysis boundary” challenge is associated with circuit analysis strategy and state of documentation. An example is how multiple paths to success are quantified, and choosing to allow for automatic actions, operator actions in the control room, and/or manual local operations. Another example is that the power distribution system must be well-understood, so that boundaries are clear for component analyses.
Analysis issues challenges are typically related to the analysis strategy and state of documentation. An example is how multiple paths to success are quantified, and choosing to allow for automatic actions, operator actions in the control room, and/or manual local operations. Another example is that the power distribution system must be well-understood, so that boundaries are clear for component analyses.
FAI has the experience and expertise to provide a full range of services related to cable selection and study to determine the quality of prerequisite information in order to create a management plan and schedule to generate qualified data for such studies.