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The Fire Research Division develops and maintains a set of computational tools to analyze fire behavior. These tools include the Consolidated Model of Fire and Smoke Transport (CFAST) zone model, the Fire Dynamics Simulator (FDS) computational fluid dynamics model, and Smokeview, which visualizes output from both CFAST and FDS. This research will extend the capabilities of these models, as well as improve their accuracy and reliability. More specifically, we will improve the prediction of burning rates for liquids and simple solid fuels, and carbon monoxide and soot concentrations in FDS. We will also develop the capability within FDS to handle curvilinear flow obstructions. Among other things, this will facilitate more accurate two-way coupling between FDS and finite-element structural models, which will computational prediction modeling of structural-fire resistance of steel constructed structures. Lastly, we will simplify the CFAST computational engine and improve its verification test suit, making CFAST a more reliable tool.
Objective- To develop the necessary numerical framework to (1) allow Fire Dynamic Simulator (FDS) and Smokeview) to use curvilinear gas phase numerical grids, (2) predict the burning rate of fully-furnished compartments using only bench-scale thermophysical and flammability property data, and (3) develop a verification suite for Consolidated Model of Fire and Smoke Transport (CFAST) that is consistent with FDS.
What is the new technical idea? In commercial structures, the fire protection costs are $63B (approximately 12% of the overall construction costs). Studies have shown that this cost can be cut in half while still maintaining the same level of fire safety if the building codes switched to performance-based (rather than prescriptive-based) metrics. In other words, the cost can be reduced if the building codes defined the fire performance specifications, rather than defining the specific fire safety features.
FDS, CFAST, and Smokeview are the basis for supporting this switch to performance-based design (PBD) building codes. Using our tools, engineers are able get lower cost building designs approved that maintain the required level of fire safety. Fire investigators, safety officials, engineers, architects, and builders use these tools to simulate the impact of fire dynamics and smoke transport in specific building environments. Architects and fire protection engineers, for example, have reduced commercial building costs by millions of dollars by using these programs to identify lower cost building and fire safety designs (e.g., placement and design of stairs and smoke alarms) that provide the same level of fire safety.
Over the last several years we have developed extensive automated techniques and computational methods to demonstrate the predictive capabilities of FDS and CFAST. These automated processes enable effective verification and validation (V&V) for fire models developed by NIST and others.
Coupling FDS with finite-element structural models would result in more efficient and accurate computations for performance-based design (PBD). Developing this capability would also enable more sophisticated treatment of the solid phase, such as 3D heat and mass transport and moving phase boundaries. Two-way coupling with structural codes with moving boundaries would allow simulations of multi-stage structural fire collapse of buildings
This research will take the next step in improving the accuracy and reliability, and extend the capabilities of these computational tools. More specifically, the research will lead to the following:
What is the research plan? In addition to general support for the public release of both FDS and CFAST, the project is separated into 7 research tasks, all of which are critical to the project's objective. The first 6 tasks are FDS development. Task 7 is CFAST maintenance.
Task 1 is to develop and implement a hybrid Cutcell (CC)-Immersed Boundary Method (IBM) in FDS as a solution to handling more complex geometries. IBM is a method of representing complex solid obstructions within a uniform rectangular mesh, allowing high fidelity large-eddy simulation of fire phenomena and fire-structure interaction. IBM will (1) allow direct use of computer-aided design in the processing of FDS fire scenarios, (2) allow users to couple complex geometry with structural finite element solvers (FEM) (e.g., ANSYS), and (3) lead to more accurate prediction of the heat flux to solid surfaces for real materials in buildings . A proof-of-concept version of IBM is currently implemented in FDS. The hybrid CC-IBM is in development. The task is currently preparing to demonstrate a fully FDS and Smokeview coupled with FEM solver fire-structure model.
Task 2 is to develop the functionality within Smokeview to visualize arbitrary geometrical shapes, complementing the development of the Cutcell-Immersed Boundary Method in Task 1. Visualization techniques are needed to verify the underlying CC-IBM computations and guide CC-IBM development. Various rectilinear visualization techniques used with the existing version of Smokeview (e.g., displaying data contours on surfaces) need to be adapted for use with CC-IBM in order to obtain insight from numerical computations. Preliminary methods for visualizing CC-IBM objects in Smokeview are critical to development of the flow solver. The task is currently preparing to implement the visualization techniques for moving geometries based on adapt surface data contouring.
Task 3 is to reliably predict the burning rate of liquids and simple solid materials in FDS. New data generated through solid-phase modeling will guide the development of a framework for submodels on material burning . In year 1 (FY14), we will demonstrate through small scale validation work , the feasibility of modeling real materials. Real materials are typically mixtures of different components. Over the last several years, we have made progress on simulating burning of homogeneous bulk plastic. This task is currently focused on predicting the burning behavior of more complex materials and geometries (e.g., furniture).
Task 4 is verification and validation of carbon monoxide (CO) prediction in FDS. Most fire deaths are attributed to CO poisoning. This tasks aims at significantly improving the accuracy and reliable of CO prediction, which is critical to effective use of these models for predicting and recreating fire scenarios. The chemistry submodel in FDS has been generalized to handle detailed chemical mechanisms. This task currently is verifing implementation of an improved CO model in FDS by developing capability in the turbulence-chemistry model to properly handle subgrid temperature distributions with Arrhenius chemistry.
Task 5 is to develop an improved soot model in FDS. Deposition of soot generated from fires is important for tenability, smoke management, detector response, and fire forensics. This tasks aims at significantly improving the accuracy and reliable of soot prediction, which is critical to effective use of these models for predicting and recreating fire scenarios. The current soot algorithm predicts that smoke alarms will activate earlier than experimentally measured. It is suspected that FDS is over-predicting the deposition rate. Soot also participates in radiative feedback driving mass loss rates in liquid pool fires. Any method to predict pool fire burning rates without an accurate prediction of the soot concentration field would be ad hoc.
The new soot model will include formation, growth, oxidation, transport, agglomeration, and deposition submodels. The research is currently developing the model source terms for soot formation, growth, oxidation, agglomeration, and deposition.
Task 6 is to improve the extinction model in FDS. In this task, the FDS extinction model will be extended to handle thermal, aerodynamic, and kinetic suppression mechanisms. This task is currently developing the thermal extinction and water mist suppression model. Shortly, the task should implementing and validating the aerodynamic and kinetic suppression.
Task 7 is to add a suite of verification cases for CFAST and to make it more consistent with FDS in terms of input parameters and functionality. CFAST is a two-zone fire model used to calculate the evolving distribution of smoke, fire gases and temperature throughout compartments of a building during a fire. CFAST is a vital design tool for the engineering community because its calculations can be run in minutes as opposed to hours or days for FDS. Over the last couple years, CFAST has been updated to be in compliance with modern Fortran standards and combustion chemistry that is more consistent with FDS. This task is currently improving the estimation of effective gas temperatures near fire sources. This will improve the modeling of heat transfer to and ignition of nearby targets.
Smokeview rendering of a fire in a cable spreading room of a nuclear power plant. Image: NIST
Start Date:October 1, 2011
Lead Organizational Unit:el
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