Dynamic Modeling and Simulation of a Large Scale Direct-Fired Supercritical CO2 Power Cycle for Off-Design Operating Conditions
7th International sCO2 Power Cycles Symposium, Virtual, February 21-24, 2022
Chinen, Anderson Soares↗
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Dynamic Simulation of a Sub-Critical Coal Fired Power Plant
In order to address the demanding operating conditions for remaining coal-fired power plants, a dynamic model and a suite of tools have been developed for studying load cycling and to find optimization opportunities. A sub-critical steam cycle power plant was modeled in a flow-sheet modeling tool, APROS™. The model represented the firing system, economizer, evaporator, superheat, and reheat systems. Four loads from 100% TMCR to 25% TMCR were calibrated and tested such that low-to-high cycling could be studied. The model was run through various load cycles; one of which is presented here. This modeling is a prototype for general use in developing cutting edge controls products and for maximizing economic, low-emissions, and efficient operation of the existing coal power fleet.
Braun, Timothy↗
Aerospace Test Facilities at NASA LeRC Plumbrook
An overview of the facilities and research being conducted at LeRC's Plumbrook field station is given. The video highlights four main structures and explains their uses. The Space Power Facility is the world's largest space environment simulation chamber, where spacebound hardware is tested in simulations of the vacuum and extreme heat and cold of the space plasma environment. This facility was used to prepare Atlas 1 rockets to ferry CRRES into orbit; it will also be used to test space nuclear electric power generation systems. The Spacecraft Propulsion Research Facility allows rocket vehicles to be hot fired in a simulated space environment. In the Cryogenic Propellant Tank Facility, researchers are developing technology for storing and transferring liquid hydrogen in space. There is also a Hypersonic Wind Tunnel which can perform flow tests with winds up to Mach 7.
Source record↗
Analysis of Fire-Induced Circulations during the FireFlux2 Experiment
Despite recent advances in both coupled fire modeling and measurement techniques to sample the fire environment, the fire–atmosphere coupling mechanisms that lead to fast propagating wildfires remain poorly understood. This knowledge gap adversely affects fire management when wildland fires propagate unexpectedly rapidly and shift direction due to the fire impacts on local wind conditions. In this work, we utilized observational data from the FireFlux2 prescribed burn and numerical simulations performed with a coupled fire–atmosphere model WRF-SFIRE to assess the small-scale impacts of fire on local micrometeorology under moderate wind conditions (10–12 m/s). The FireFlux2 prescribed burn provided a comprehensive observational dataset with in situ meteorological observations as well as IR measurements of fire progression. To directly quantify the effects of fire–atmosphere interactions, two WRF-SFIRE simulations were executed. One simulation was run in a two-way coupled mode in which the heat and moisture fluxes emitted from the fire were injected into the atmosphere, and the other simulation was performed in a one-way coupled mode for which the atmosphere was not affected by the fire. The difference between these two simulations was used to analyze and quantify the fire impacts on the atmospheric circulation at different sections of the fire front. The fire-released heat fluxes resulted in vertical velocities as high as 10.8 m/s at the highest measurement level (20 m above ground level) gradually diminishing with height and dropping to 7.9 m/s at 5.77 m. The fire-induced horizontal winds indicated the strongest fire-induced flow at the lowest measurement levels (as high as 3.3 m/s) gradually decreasing to less than 1 m/s at 20 m above ground level. The analysis of the simulated flow indicates significant differences between the fire-induced circulation at the fire head and on the flanks. The fire-induced circulation was much stronger near the fire head than at the flanks, where the fire did not produce particularly strong cross-fire flow and did not significantly change the lateral fire progression. However, at the head of the fire the fire-induced winds blowing across the front were the strongest and significantly accelerated fire progression. The two-way coupled simulation including the fire-induced winds produced 36.2% faster fire propagation than the one-way coupled run, and more realistically represented the fire progression.
Benik, Jeremy T.↗
Simulations of flaming combustion and flaming-to-smoldering transition in wildland fire spread at flame scale
Our objective in the present study is to provide basic insights into the coupling between external-gas and solid biomass vegetation processes that control the dynamics of flame spread in wildland fire problems. Here we focus on a modeling approach that resolves processes occurring at vegetation and flame scales, i.e., the formation of flammable vapors due to the thermal degradation of the solid biomass, the subsequent combustion in ambient air, the thermal feedback to the biomass through radiative and convective heat transfer, and the possible transition from flaming combustion (taking place outside of the solid biomass) to smoldering combustion (taking place inside the solid biomass). The capability uses a multiphase combustion framework and treats external-gas processes through a Large Eddy Simulation solver and solid biomass processes through a discrete particle model. The discrete particle model adopts a one-dimensional porous medium formulation, includes descriptions of drying, thermal pyrolysis, oxidative pyrolysis, and char oxidation, as well as a description of the external-gas-to-solid-biomass diffusion of oxygen mass; the discrete particle model thereby provides a treatment of in-depth oxidative processes and allows the simulation of smoldering combustion. The modeling capability is applied to the simulation of fire spread across a surrogate biomass vegetation bed corresponding to a discrete array of cylindrical-shaped, vertically-oriented, pine wood sticks, characterized by a monomodal size distribution, in horizontal flat terrain and under wind-aided conditions. The numerical results demonstrate that the model can simulate successful flaming-to-smoldering transition followed by complete biomass consumption.
01 COAL, LIGNITE, AND PEAT↗
FY24 – FY25 Efforts to Revive the ANS-54.8 Liquid Metal Fire Protection in LMR Plants Standard
The current multi-year effort seeks to utilize national laboratory support from Argonne to expedite revival of the ANS-54.8 standard titled “Liquid Metal Fire Protection in LMR Plants.” To achieve that objective, the following tasks were identified: Task 1 involves working directly with ANS to revive the ANS-54.8 Working Group. This was to be accomplished by completing necessary paperwork, submitting that paperwork to ANS for approval, enlisting potential working group members from industry, the NRC, national laboratories, and universities, and organizing and leading Working Group activities. The overall purpose of the Working Group is to develop an updated draft of ANS-54.8 for review and approval by ANS consensus committees, the ANS Standards Board, and certification from ANSI. Task 2 focuses on leveraging historical information and expertise at Argonne related to sodium fire protection systems and strategies. For more than a decade, Argonne has worked on both international and domestic projects related to sodium fire protection system development and evaluation. The goal of this task is to utilize that experience to help inform the ANS-54.8 Working Group on important considerations that may be addressed in an updated draft of ANS-54.8. Task 3 focuses on leveraging Argonne experience in the development of and use of analysis methods and tools for the simulation of sodium fire scenarios and evaluation of the effectiveness of sodium fire protection systems and strategies. For more than a decade, Argonne has recovered, modified, and utilized several historical sodium fire analysis software tools. The goal of this task is to utilize that experience to help inform the ANS-54.8 Working Group of best practices for sodium fire progression analysis that may be addressed in an updated draft of ANS-54.8.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Characterizing Fit Factor of a One Size Fits-Most Emergency Mask using Subjects with Smaller Neck Circumferences
The Emergency Mask (EM) is an integral part of fire response on ISS, Orion and Gateway. The EM is a hood type protection respirator sealing around the subject’s neck, with an additional nose cup covering the subject’s oral nasal region. When integrated with a pair of Fire Cartridges (FCs), this system can be used to provide safe breathing air in a post-fire environment. The initial EM was certified as a ‘one size fits most’, however a recent requirements scrub discovered that the neck circumferences of the smallest possible crew population were not included in the initial requirement set. The test described in this paper uses the same slightly modified industry standard respirator test called a ‘Fit Factor’ used to certify the existing EM for larger subjects. Tests were performed on eight test subjects with neck circumference smaller than the initial EM requirement to determine if the current EM provided adequate protection during post-fire scenarios. The test included subjects donning an EM and then performing a number of head movements in a tent filled with approximately 50,000 particles/cm3 of smoke particulate. During these motions, particulate measurements were obtained from within the EM and compared with particulate measurements in the surrounding environment to determine the protection the EM provided in a simulated post-fire environment. This paper provides descriptions of the test hardware, methodology and results, which have provided rationale to design and build an EM to accommodate subjects with smaller necks.
Respirator↗
A Multi-Analysis Approach for Estimating Regional Health Impacts from the 2017 Northern California Wildfires
In the evening of October 8 and early hours of October 9, 2017, high winds in Northern California downed trees and power lines, igniting some of the most devastating wildfires the state had seen, and within hours unhealthy air quality impacted millions of people. We simulated these air quality conditions using fire detection information from the MODIS, VIIRS, and GOES-16 ABI satellite instruments, and applying a set of three WRF–CMAQ simulations, one data fusion, and three machine learning methods. We investigated using the 5-min available GOES-16 fire detection data to simulate timing of fire activity to allocate emissions hourly for the WRF-CMAQ air quality modeling system. Interestingly, this approach did not necessarily improve results compared to the baseline case, which used a default time profile. However, this approach was key to simulating the initial 12-hr explosive fire activity and smoke impacts. The WRF-CMAQ simulations compared well with observational data for the October 8-15 time period and tended to overestimate concentrations October 16-20. To improve these results, we applied three machine learning algorithms. We also had a unique opportunity to evaluate results with temporary monitors deployed specifically for wildfires, and performance was markedly different. For example, at the permanent monitoring locations, the WRF-CMAQ simulations had a Pearson correlation of 0.65, and the data fusion approach improved this (Pearson correlation = 0.95), while at the temporary monitor locations across the WRF-CMAQ, data fusion, and machine learning datasets, the best Pearson correlation was 0.5. The data fusion and machine learning results were biased low and WRF-CMAQ results were biased high. Finally, we applied the optimized PM2.5 exposure estimate in a short-term exposure-response function. Total estimated mortality attributable to PM2.5 exposure during the smoke episode was 83 (95% confidence interval: 0, 196) with 47% of these deaths attributable to wildland fire smoke.
O'Neill, Susan↗
Research Plan for Fire Signatures and Detection
Viewgraphs on the prevention, suppression, and detection of fires aboard a spacecraft is presented. The topics include: 1) Fire Prevention, Detection, and Suppression Sub-Element Products; 2) FPDS Organizing Questions; 3) FPDS Organizing Questions; 4) Signatures, Sensors, and Simulations; 5) Quantification of Fire and Pre-Fire Signatures; 6) Smoke; 7) DAFT Hardware; 8) Additional Benefits of DAFT; 9) Development and Characterization of Sensors 10) Simulation of the Transport of Smoke and Fire Precursors; and 11) FPDS Organizing Questions.
Source record↗
Dynamic ecosystem assembly and escaping the “fire trap” in the tropics: insights from FATES_15.0.0
Abstract. Fire is a fundamental part of the Earth system, with impacts on vegetation structure, biomass, and community composition, the latter mediated in part via key fire-tolerance traits, such as bark thickness. Due to anthropogenic climate change and land use pressure, fire regimes are changing across the world, and fire risk has already increased across much of the tropics. Projecting the impacts of these changes at global scales requires that we capture the selective force of fire on vegetation distribution through vegetation functional traits and size structure. We have adapted the fire behavior and effects module, SPITFIRE (SPread and InTensity of FIRE), for use with the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a size-structured vegetation demographic model. We test how climate, fire regime, and fire-tolerance plant traits interact to determine the biogeography of tropical forests and grasslands. We assign different fire-tolerance strategies based on crown, leaf, and bark characteristics, which are key observed fire-tolerance traits across woody plants. For these simulations, three types of vegetation compete for resources: a fire-vulnerable tree with thin bark, a vulnerable deep crown, and fire-intolerant foliage; a fire-tolerant tree with thick bark, a thin crown, and fire-tolerant foliage; and a fire-promoting C4 grass. We explore the model sensitivity to a critical parameter governing fuel moisture and show that drier fuels promote increased burning, an expansion of area for grass and fire-tolerant trees, and a reduction of area for fire-vulnerable trees. This conversion to lower biomass or grass areas with increased fuel drying results in increased fire-burned area and its effects, which could feed back to local climate variables. Simulated size-based fire mortality for trees less than 20 cm in diameter and those with fire-vulnerable traits is higher than that for larger and/or fire-tolerant trees, in agreement with observations. Fire-disturbed forests demonstrate reasonable productivity and capture observed patterns of aboveground biomass in areas dominated by natural vegetation for the recent historical period but have a large bias in less disturbed areas. Though the model predicts a greater extent of burned fraction than observed in areas with grass dominance, the resulting biogeography of fire-tolerant, thick-bark trees and fire-vulnerable, thin-bark trees corresponds to observations across the tropics. In areas with more than 2500 mm of precipitation, simulated fire frequency and burned area are low, with fire intensities below 150 kW m−1, consistent with observed understory fire behavior across the Amazon. Areas drier than this demonstrate fire intensities consistent with those measured in savannas and grasslands, with high values up to 4000 kW m−1. The results support a positive grass–fire feedback across the region and suggest that forests which have existed without frequent burning may be vulnerable at higher fire intensities, which is of greater concern under intensifying climate and land use pressures. The ability of FATES to capture the connection between fire disturbance and plant fire-tolerance strategies in determining biogeography provides a useful tool for assessing the vulnerability and resilience of these critical carbon storage areas under changing conditions across the tropics.
54 ENVIRONMENTAL SCIENCES↗
Aerojet - Attitude Control Engines
All the engines were both qualification and acceptance tested at Marquardt s facilities. After we won the Apollo Program contract, we went off and built two vacuum test facilities, which simulated altitude continuous firing for as long as we wanted to run an engine. They would run days and days with the same capability we had on steam ejection. We did all of the testing in both for the qualification and the acceptance test. One of them was a large ball, which was an eighteen-foot diameter sphere, evacuated again with a big steam ejector system that could be used for system testing; that s where we did the Lunar Excursion Module testing. We put the whole cluster in there and tested the entire cluster at the simulated altitude conditions. The lowest altitude we tested at - typically an acceptance test - was 105,000 feet simulated altitude. The big ball - because people were interested in what they called goop formation, which is an unburned hydrazine product migrating to cold surfaces on different parts of spacecraft - was built to address those kinds of issues. We ran long-life tests in a simulated space environment with the entire inside of the test cell around the test article, liquid nitrogen cooled, so it could act as getter for any of the exhaust products. That particular facility could pull down to about 350,000 feet (atmosphere) equivalent altitude, which was pushing pretty close to the thermodynamic triple point of the MMH. It was a good test facility. Those facilities are no longer there. When the guys at Marquardt sold the company to what eventually became part of Aerojet, all those test facilities were cut off at the roots. I think they have a movie studio there at this point. That part of it is truly not recoverable, but it did some excellent high-altitude, space-equivalent testing at the time. Surprisingly, we had very few problems while testing in the San Fernando Valley. In the early 1960s, nobody had ever seen dinitrogen tetroxide (N2O4), so that wasn't too big a deal. We really did only make small, red clouds. In all the hundreds of thousands of tests and probably well over one million firings that I was around that place for, in all that thirty-something years, we had a total of one serious injury associated with rocket engine testing and propellants. Because we were trying to figure out what propellants would really be good, we tried all of the fun stuff like the carbon tetrafluoride, chlorine pentafluoride, and pure fluorine. The materials knowledge wasn't all that great at the time. On one test, the fluorine we had didn't react well with the copper they were using for tubing, and it managed to cause another unscheduled disassembly of the facility. It was very serious. It's like one of those Korean War stories. The technician happened to be walking past the test facility when it decided to blow itself up. A piece of copper tubing pierced one cheek and came out the other. That was the only serious accident in all of the engines handled in all those years. Now, we did have a problem with the EPA later because they figured out what the brown clouds were about. We built a whole bunch of exhaust mitigation scrubbers to take care of engine testing in the daytime. In general, we operated the big shuttle (RCS) engine, the 870- pounder at nominal conditions; they scrubbed the effluents pretty well. If you operated that same 870-pound force engine at a level where you get a lot of excess oxidizer, yeah, there s a brown cloud. But, you know, it doesn't show up well in the dark. They did do some of that. But, that s gone; it was addressed one way or another. RELEASED -
Pfeifer, Gerald R.↗
ELM2.1-XGBfire1.0: improving wildfire prediction by integrating a machine learning fire model in a land surface model
Wildfires have shown increasing trends in both frequency and severity across the contiguous United States (CONUS). However, process-based fire models have difficulties in accurately simulating the burned area over the CONUS due to a simplification of the physical process and cannot capture the interplay among fire, ignition, climate, and human activities. The deficiency of burned area simulation deteriorates the description of fire impact on energy balance, water budget, and carbon fluxes in the Earth system models (ESMs). Alternatively, fire models based on machine learning (ML), which capture statistical relationships between the burned area and environmental factors, have shown promising burned area predictions and corresponding fire impact simulation. We develop a hybrid framework (ELM2.1-XGBFire1.0) that integrates an eXtreme Gradient Boosting (XGBoost) wildfire model with the Energy Exascale Earth System Model (E3SM) land model (ELM) version 2.1. A Fortran–C–Python deep learning bridge is adapted to support online communication between ELM and the ML fire model. Specifically, the burned area predicted by the ML-based wildfire model is directly passed to ELM to adjust the carbon pool and vegetation dynamics after disturbance, which are then used as predictors in the ML-based fire model in the next time step. Evaluated against the historical burned area from Global Fire Emissions Database 5 from 2001–2019, the ELM2.1-XGBFire1.0 outperforms process-based fire models in terms of spatial distribution and seasonal variations. The ELM2.1-XGBFire1.0 has proven to be a new tool for studying vegetation–fire interactions and, more importantly, enables seamless exploration of climate–fire feedback, working as an active component of E3SM.
54 ENVIRONMENTAL SCIENCES↗
Improving North American Wildfire Prediction by Integrating a Machine-Learning Fire Model in a Land Surface Model
Wildfires have shown increasing trends in both frequency and severity across the Contiguous United States (CONUS). However, process-based fire models have difficulties in accurately simulating the burned area over the CONUS due to a simplification of the physical process and cannot capture the interplay among fire, ignition, climate, and human activities. The deficiency of burned area simulation deteriorates the description of fire impact on energy balance, water budget, and carbon fluxes in the Earth System Models (ESMs). Alternatively, machine learning (ML) based fire models, which capture statistical relationships between the burned area and environmental factors, have shown promising burned area predictions and corresponding fire impact simulation. We develop a hybrid framework (ML4Fire-XGB) that integrates a pretrained eXtreme Gradient Boosting (XGBoost) wildfire model with the Energy Exascale Earth System Model (E3SM) land model (ELM) version 2.1. A Fortran-C-Python deep learning bridge is adapted to support online communication between ELM and the ML fire model. Specifically, the burned area predicted by the ML-based wildfire model is directly passed to ELM to adjust the carbon pool and vegetation dynamics after disturbance, which are then used as predictors in the ML-based fire model in the next time step. Evaluated against the historical burned area from Global Fire Emissions Database 5 from 2001-2020, the ML4Fire-XGB model outperforms process-based fire models in terms of spatial distribution and seasonal variations. Sensitivity analysis confirms that the ML4Fire-XGB well captures the responses of the burned area to rising temperatures. The ML4Fire-XGB model has proved to be a new tool for studying vegetation-fire interactions, and more importantly, enables seamless exploration of climate-fire feedback, working as an active component in E3SM.
54 ENVIRONMENTAL SCIENCES↗
Global burned area increasingly explained by climate change
Fire behaviour is changing in many regions worldwide. However, nonlinear interactions between fire weather, fuel, land use, management and ignitions have impeded formal attribution of global burned area changes. Here, in this work, we demonstrate that climate change increasingly explains regional burned area patterns, using an ensemble of global fire models. The simulations show that climate change increased global burned area by 15.8% (95% confidence interval (CI) [13.1–18.7]) for 2003–2019 and increased the probability of experiencing months with above-average global burned area by 22% (95% CI [18–26]). In contrast, other human forcings contributed to lowering burned area by 19.1% (95% CI [21.9–15.8]) over the same period. Moreover, the contribution of climate change to burned area increased by 0.22% (95% CI [0.22–0.24]) per year globally, with the largest increase in central Australia. Our results highlight the importance of immediate, drastic and sustained GHG emission reductions along with landscape and fire management strategies to stabilize fire impacts on lives, livelihoods and ecosystems.
54 ENVIRONMENTAL SCIENCES↗
The interactive global fire module pyrE (v1.0)
Fires affect the composition of the atmosphere and Earth’s radiation balance by emitting a suite of reactive gases and particles. An interactive fire module in an Earth system model (ESM) allows us to study the natural and anthropogenic drivers, feedbacks, and interactions of open fires. To do so, we have developed pyrE, the NASA GISS (Goddard Institute for Space Studies) interactive fire emissions *module. The pyrE module is driven by environmental variables like flammability and cloud-to-ground lightning, calculated by the GISS ModelE ESM, and parameterized by anthropogenic impacts based on population density data. Fire emissions are generated from the flaming phase in pyrE (active fires). Using pyrE, we examine fire occurrence, regional fire suppression, burned area, fire emissions, and how it all affects atmospheric composition. To do so, we evaluate pyrE by comparing it to satellite-based datasets of fire count, burned area, fire emissions, and aerosol optical depth (AOD). We demonstrate pyrE’s ability to simulate the daily and seasonal cycles of open fires and resulting emissions. Our results indicate that interactive fire emissions are biased low by 32 %–42 %, depending on emitted species, compared to the GFED4s (Global Fire Emissions Database) inventory. The bias in emissions drives underestimation in column densities, which is diluted by natural and anthropogenic emissions sources and production and loss mechanisms. Regionally, the resulting AOD of a simulation with interactive fire emissions is underestimated mostly over Indonesia compared to a simulation with GFED4s emissions and to MODIS AOD. In other parts of the world pyrE’s performance in terms of AOD is marginal to a simulation with prescribed fire emissions.
Fires↗
Cuspy dark matter density profiles in massive dwarf galaxies
ABSTRACT Rotation curves of galaxies probe their total mass distributions, including dark matter. Dwarf galaxies are excellent systems to investigate the dark matter density distribution, as they tend to have larger fractions of dark matter compared to higher mass systems. The core-cusp problem describes the discrepancy found in the slope of the dark matter density profile in the centres of galaxies (β*) between observations of dwarf galaxies (shallower cores) and dark matter-only simulations (steeper cusps). We investigate β* in six nearby spiral dwarf galaxies for which high-resolution CO J = 1–0 data were obtained with ALMA (Atacama Large Millimeter/submillimeter Array). We derive rotation curves and decompose the mass profile of the dark matter using our CO rotation curves as a tracer of the total potential and 4.5 $\mu$m photometry to define the stellar mass distribution. We find 〈β*〉 = 0.6 with a standard deviation of ±0.1 among the galaxies in this sample, in agreement with previous measurements in this mass range. The galaxies studied are on the high stellar mass end of dwarf galaxies and have cuspier profiles than lower mass dwarfs, in agreement with other observations. When the same definition of the slope is used, we observe steeper slopes than predicted by the FIRE and NIHAO simulations. This may signal that these relatively massive dwarfs underwent stronger gas inflows towards their centres than predicted by these simulations, that these simulations overpredict the frequency of accretion or feedback events, or that a combination of these or other effects are at work.
Cooke, Lauren H. (ORCID:0000000284337553)↗
Measurements of the response of transport aircraft ceiling panels to fuel pool fires
Tests were performed to characterize the responses of various aircraft ceiling panel configurations to a simulated post-crash fire. Attention was given to one currently used and four new ceiling configurations exposed to a fuel pool fire in a circulated air enclosure. The tests were controlled to accurately represent conditions in a real fire. The panels were constructed of fiberglass-epoxy, graphite-phenolic resin, fiberglass-phenolic resin, Kevlar-epoxy, and Kevlar-phenolic resin materials. The phenolic resin-backed sheets performed the best under the circumstances, except when combined with Kevlar, which became porous when charred.
Bankston, C. P.↗
Carbon Dioxide Dispersion in the Combustion Integrated Rack Simulated Numerically
When discharged into an International Space Station (ISS) payload rack, a carbon dioxide (CO2) portable fire extinguisher (PFE) must extinguish a fire by decreasing the oxygen in the rack by 50 percent within 60 sec. The length of time needed for this oxygen reduction throughout the rack and the length of time that the CO2 concentration remains high enough to prevent the fire from reigniting is important when determining the effectiveness of the response and postfire procedures. Furthermore, in the absence of gravity, the local flow velocity can make the difference between a fire that spreads rapidly and one that self-extinguishes after ignition. A numerical simulation of the discharge of CO2 from PFE into the Combustion Integrated Rack (CIR) in microgravity was performed to obtain the local velocity and CO2 concentration. The complicated flow field around the PFE nozzle exits was modeled by sources of equivalent mass and momentum flux at a location downstream of the nozzle. The time for the concentration of CO2 to reach a level that would extinguish a fire anywhere in the rack was determined using the Fire Dynamics Simulator (FDS), a computational fluid dynamics code developed by the National Institute of Standards and Technology specifically to evaluate the development of a fire and smoke transport. The simulation shows that CO2, as well as any smoke and combustion gases produced by a fire, would be discharged into the ISS cabin through the resource utility panel at the bottom of the rack. These simulations will be validated by comparing the results with velocity and CO2 concentration measurements obtained during the fire suppression system verification tests conducted on the CIR in March 2003. Once these numerical simulations are validated, portions of the ISS labs and living areas will be modeled to determine the local flow conditions before, during, and after a fire event. These simulations can yield specific information about how long it takes for smoke and combustion gases produced by a fire to reach a detector location, how large the fire would be when the detector alarms, and the behavior of the fire until it has been extinguished. This new capability could then be used to optimize the location of fire detectors and fire-suppression ports as well as to evaluate the effectiveness of fire suppressants and response strategies. Numerical data collected from these simulations could also be used to develop a virtual reality fire event for crew training and fire safety awareness. This work is funded by NASA's Bioastronautics Initiative, which has the objective of ensuring and enhancing the health, safety, and performance of humans in space. As part of this initiative, the Microgravity Combustion Science Branch at the NASA Glenn Research Center is conducting spacecraft fire safety research to significantly improve fire safety on inhabited spacecraft.
Wu, Ming-Shin↗