Modeling water-mist based suppression of 34 GJ car-deck fires using FDS
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1 Modeling water-mist based suppression of 34 GJ car-deck fires using FDS S. Li, R. Acharya, M. Colket, V. Sankaran, G. Poncia United Technologies Research Center L. Torpo Marioff Corporation March 1 st, 2013 Suppression, Detection and Signaling Research and Applications Symposium - SUPDET 2013, Orlando, Florida Copyright UTC Climate, Controls, & Security 2013
2 OUTLINE Motivation Modeling needs and Challenges Simulations tools & models Model Enhancements Results & Discussion Summary Copyright UTC Climate, Controls, & Security
3 MOTIVATION Business Drivers Fire suppression performance verified by full scale tests High cost of tests (facility / materials / safety) Standardized tests do not cover all designs / applications Full scale fire tests not possible for all applications (long tunnels) Large variability in results Stochastic / random factors Identification of worse case scenarios Scientific Drivers Limited fundamental understanding of processes involved Detailed 3D - experimental characterization difficult / expensive Tightly coupled multi-physics phenomena Turbulence / heterogeneous chemical reaction / multi-phase / radiation Better understanding increased probability of developing better fire protection systems Copyright UTC Climate, Controls, & Security
4 MODELING NEEDS - CHALLENGES UTRC/UMd Experiments SP Institute, Sweden VTT, Finland External Length Scales Room Scale 1 m 100 m Fuel/burning object 10 cm 1 m Liquid injection nozzle 1mm Internal Length Scales Droplet Scales 10 µm 250 µm Turbulence / mixing 10 mm 1 m Combustion 1mm 10mm Velocity / Time Scales Jet / spray velocity 1-50 m/sec Gas velocity 1 cm/sec 10 m/sec Fire burning time 1 min 60 min Scales associated with material properties of solid, liquid and gas phase Copyright UTC Climate, Controls, & Security
5 MODELING NEEDS - CHALLENGES High variability and complexity of fire propagation and suppression Computational burden of full scale modeling Reasonable approximations to the models describing the fundamental physics Accuracy of large-scale simulation based on the approximated models and coarse grids Robustness of the simulation Scarce availability of validation data sets Copyright UTC Climate, Controls, & Security
6 OUTLINE Motivation Modeling needs and Challenges Simulations tools & models Model Enhancements Results & Discussion Summary Copyright UTC Climate, Controls, & Security
7 SIMULATIONS TOOLS & MODELS Fire Dynamics Solver (FDS*) is a 3-D, unsteady, LES solver from NIST (SVN 10095) Physical Models Hydrodynamic model: Low-Mach number, Smagorinsky (dynamic) Combustion: LES - Lumped species transport with EDC model DNS - Finite rate Arrhenius kinetics Radiation model Finite Volume Method for discrete ordinates Spray models Lagrangian transport of mass, motion, momentum, energy Pyrolysis 1D wall normal models solid phase reactions or specified HRR Empirical models for sprinkler activation, heat & smoke detectors Numerical Models 2 nd order accurate in space & time - R-K Predictor-Corrector scheme Poisson equation for pressure - Non-iterative, fast, direct solver Structured, non-conformal mesh, parallel (MPI), Fortran 90 * Well documented, continuously updated and maintained by NIST Copyright UTC Climate, Controls, & Security
8 OUTLINE Motivation Modeling needs and Challenges Simulations tools & models Model Enhancements Results & Discussion Summary Copyright UTC Climate, Controls, & Security
9 MODEL ENHANCEMENTS Objective: Simulation of water-mist based fire suppression of wood-based burning objects Primary Fire Suppression Mechanisms 1) Wetting/cooling of fuel surface 2) Cooling flame & hot products 3) O2 dilution/displacement by water vapor 4) Radiation Attenuation Models explored (updated and fully coupled) 1) Solid-phase burning Pyrolysis models 2) Gas phase flame-extinction models 3) Droplet-radiation scattering/absorption models 4) Droplet transport / injection models Software architecture/models present in standard FDS Burning object under Water-Mist Copyright UTC Climate, Controls, & Security
10 MODEL ENHANCEMENTS Physics based enhancements slight modifications to FDS Gas Phase Extinction Model Suppressants alter local/flame φ & HRR 1. Dilution: Reduces T flame and impacts chain-branching rxns Spray Injection Model: Map two-phase mixture at location of measurement 2. Thermal: Evaporative cooling 3. Turbulence: residence time effects Model: Balance between energy produced and energy needed to keep the gas mixture at critical flame temperature A local model for gas-phase extinction in fires that accounts for all 3 effects A decoupled model for finite-rate effects of fluid-dynamics & chemical kinetics Collect droplet data Droplets (lumped Lagrangian particles) size, velocity and orientation are represented close to the actual case Both droplets and relevant entrained gas motion are added at the mapping location More detailed and accurate data account for the spray profile Copyright UTC Climate, Controls, & Security
11 SPRAY MODELS HI-FOG NOZZLE Experiment FDS Copyright UTC Climate, Controls, & Security
12 OTHER MODEL ENHANCEMENTS Wood Pyrolysis Model Two step kinetics for pyrolysis and Charoxidation reactions Consistency conditions to limit reaction rates due to un-modeled physics oxygen diffusion, char blocking porous flow through char Schematic: wood pyrolysis Mass flux correction for satisfying conservation property during solid phase to gas phase conversion Schematic: radiation scattering Droplet-radiation scattering corrections Extensions to water mist I Copyright UTC Climate, Controls, & Security
13 OUTLINE Motivation Modeling needs and Challenges Simulations tools & models Model Enhancements Results & Discussion Summary Copyright UTC Climate, Controls, & Security
14 DEMONSTRATION: BURNING WOOD CRIBS Limited validation in large scale fires Schematic of wood crib Time evolution of crib burning Experimental snap-shot Copyright UTC Climate, Controls, & Security
15 SIMULATION OF 35 GJ FIRES Freight truck fire scenario (car-deck) Courtesy: Google 16 stacks, 7 pallets each Courtesy of pictures: Marioff and VTT Reports Copyright UTC Climate, Controls, & Security
16 SIMULATION OF 35 GJ FIRES Freight truck fire scenario (car-deck) Ignitor on Pallet catches fire Ignitor off Pallets on fire Cooling mist turned on Copyright UTC Climate, Controls, & Security
17 SIMULATION OF 35 GJ FIRES Freight truck fire scenario (No suppression) Fire propagation from ignitor to pallet stack captured qualitatively well Multi-block arrangement and grid scale 72 blocks; ~ 2 million cells Pyrolysis models Prescribed heat release rate model - zoomed Animation Export Controlled - ECCN: EAR99 Animation Copyright UTC Climate, Controls, & Security
18 SIMULATION OF 35 GJ FIRES Freight truck fire scenario Comparison (no suppression) Left T4 Schematic of Car Deck Cooling mist turned on Center T5 Right T6 Fire spread and burn rate captured well until cooling mist turned on Copyright UTC Climate, Controls, & Security
19 SIMULATION OF 35 GJ FIRES Car-deck WM suppression simulations Schematic of Car Deck Coupled phenomena of fire suppression represented using models Expensive simulations: Using 72 cores takes nearly 4 weeks Copyright UTC Climate, Controls, & Security
20 SIMULATION OF 35 GJ FIRES Car-deck WM suppression simulations Schematic of Car Deck Early times simulated well Model over predicts heat release at long times 1200 Temperature (oc) model experiment Time (min) Temperature (oc) Temperature (oc) T6 T5 T Time (min) Time (min) Water mist starts Copyright UTC Climate, Controls, & Security
21 OUTLINE Motivation Modeling needs and Challenges Simulations tools & models Model Enhancements Results & Discussion Summary Copyright UTC Climate, Controls, & Security
22 SUMMARY NIST s FDS code provides good infrastructure and basic models to enable coupled calculations Fully coupled simulations of fire growth and fire suppression with water mist can be obtained Using coupled solutions: pyrolysis, spray, radiation and flame quenching Eliminated dependence on prescribed heat release rate assumption Solutions appear physically realistic and similar to data (early times) Computations are somewhat expensive Additional work required for quantitative simulations at long times Copyright UTC Climate, Controls, & Security
23 BACK-UP 23
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