Implementing Aerosol Coagulation in the QUIC-Fire/QUIC-SMOKE model
Explore the source record for details and available documents.
Brink, Hannah Christina↗
SEARCH · Search NASA
Results for “fire modelling”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Sodium Fire Collaborative Study Progress (CNWG FY 2019)
This report discusses the progress on the collaboration between Sandia National Laboratories (Sandia) and Japan Atomic Energy Agency (JAEA) on the sodium fire research in fiscal year 2019. First, the current sodium pool fire model in MELCOR, which is adapted from CONTAIN-LMR code, is discussed. The associated sodium fire input requirements are also presented. A proposed model improvement developed at Sandia is discussed. Finally, the validation study of the sodium pool fire model in MELCOR carried out by a JAEA's staff is described. To validate this model, a JAEA sodium pool fire experiment (F7-1 test) is used. A preliminary calculation is performed using a modified MELCOR model from a previous experiment simulation. The results of the calculation are discussed as well as suggestions for improvement. Finally, recommendations are made for new MELCOR simulations for next fiscal year, 2020.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
IMPLEMENTING THE NFPA 805 PROCESS: Observations of a Technical Reviewer
In June 2004 the U.S. Nuclear Regulatory Commission (NRC) amended its fire protection requirements to permit existing nuclear power reactor licensees to voluntarily adopt fire protection requirements contained in National Fire Protection Association (NFPA) Standard 805. NFPA 805 is a performance-based standard for nuclear power plant fire protection that is an alternative to the deterministic, prescriptive fire protection requirements, such as 10 CFR 50 Appendix R, that was issued in 1980. One aspect of implementing NFPA 805 is that the licensee adopts the performance goals, objectives, and criteria for nuclear safety specified in the Standard. These goals, objectives, and criteria can be met through the implementation of deterministic approaches or performance-based approaches, including engineering analyses, probabilistic risk assessment, and fire modeling. Licensees voluntarily adopting the fire protection requirements in NFPA 805 must submit a license amendment request (LAR) to the NRC. The LAR provides the new proposed fire protection licensing basis, including the methodology and results of required evaluations and analyses that show how the NFPA 805 performance criteria are met. As of August 2014, licensees have submitted LARs for 26 nuclear power plants, representing 42 nuclear reactor units. Of these, 7 nuclear power plants, representing 10 nuclear reactor units, have been issued a safety evaluation (SE) by the NRC approving transition of their fire protection licensing basis to one that complies with NFPA 805. Pacific Northwest National Laboratory (PNNL) supports the NRC staff’s technical review of the LARs in the areas of fundamental fire protection, safe shutdown analysis, and Probabilistic Risk Assessment (PRA). PNNL, of course, cannot speak for the nuclear industry and its choice of implementation strategies or the NRC staff’s assessment of the approaches being taken to adopt NFPA 805. However, as a reviewer of the technical details of these submittals, PNNL is in a position to observe the array of implementation tactics taken in these submittals, and observe different ways licensees are making the NFPA 805 process work. For example, we see differences in how fire areas are being transitioned, the kinds of plant modifications being implemented, the changes being made to plant procedures, the number and types of recovery actions being credited, and the kinds and extent of detailed modeling being performed in support of the Fire PRAs. As a caveat, we note that it is probably too early to comment on the overall success or limitations of the NFPA 805 process or provide lessons learned for the future. Furthermore, it is not our intention to endorse any particular approach taken in a submittal over another or to critique the industry or the regulator. Rather our goal in this paper is to summarize a set of interesting and useful differences across submittals that may provide context for further future discussions about what we (i.e., reviewers, industry, and regulators) have learned in being part of the NFPA process; and how to best use that information to inform future NFPA 805 activities or other risk-informed endeavors.
NFPA 805, PRA, PSA, probabilistic risk assessment,↗
Prediction Based Design of Fire Detection for Buildings with Ceiling Heights between 9m and 18m
The purpose of this paper is to provide the experimental and theoretical background necessary to extend guidelines to ceiling heights between 9 m and 18 m. Based on the results of experiments conducted in 15 m and 22 m high hangars, detector activation thresholds and detector spacing are analyzed for both smoke and heat detectors. Only ceiling mounted detection devices are analyzed in this paper. In addition to the detector threshold study, the predictive capabilities of computer fire model simulations were compared with experimental results. This comparison, which is based on 12 fire tests, resulted in the development of a new ceiling jet algorithm to model phenomena which had not been included in previous algorithms. The improved algorithm provides a better representation of the development of the ceiling jet temperature to a growing hot layer and a better estimation of plume centerline temperature. Guidelines are examined, based on the experimental results, for fire detector spacing, placement, and sensitivity. Recommendations concerning the use of computer fire models at these heights are made as a function of fire size and hot layer development. The role of draft curtains is discussed and their impact on detector activation is demonstrated.
Davis, W. D.↗
Sensitivity Analysis and Verification of a 1-D Surface Solid Combustion Model for a Fire CFD Boundary Condition.
Abstract not provided.
Brown, Alexander↗
Investigating Application of LiDAR for Nuclear Power Plants
Many evaluation, assessment, and modeling tasks at nuclear power plants require spatial in-formation; this often requires physical visits to locations within the facility because the 2D or 3D schematics and current models do not contain enough detail or do not capture as-built and real-world conditions. These visits require extensive manual labor for not only the requesting party, but also support groups, such as security. Light Detection and Ranging (LiDAR) mapping is trying to solve that problem by providing very detailed 3D models for low costs. However, the use of these models can be very limited because either component reference information is missing and too costly to add or there is no way to extract specific spatial data needed for other tools. This report outlines two main efforts. First, to reduce the effort of “Tagging” data in large 3D models, a general Application Programming Interface (API) was developed to import a variety of existing plant database information into a 3D-visualization engine. Filters allow the user to have only zone-specific items listed; then, they can simply click and assign the information to a specific spot or component in the 3D model. The second part of the work is the development of an interface for importing pieces from the3D-LiDAR model into other systems needed for modeling and simulation, outlined around fire modeling. This interface allows for the retrieval of item location and boundaries, enabling the auto generation of models for varying tools.
3D Modelling↗
Fire, insect and disease‐caused tree mortalities increased in forests of greater structural diversity during drought
Abstract Structural diversity is an emerging dimension of biodiversity that accounts for size variations in organs among individuals in a community. Previous studies show significant effects of structural diversity on forest growth, but its effects on forest mortality are not known, particularly at a large scale. To address this knowledge gap, we quantified structural diversity using stem structural diversity (SSD) based on both tree diameter and height. We obtained U.S. Forest Service Forest Inventory and Analysis (FIA) data from over 2400 plots across southcentral U.S. forests that have suffered a recent drought. Using data from multiple sampling times, we calculated SSD and compared the relative importance of SSD, species diversity, functional diversity and other stand attributes in determining tree mortalities caused by fire, insects and diseases. We also used FIRETEC, a physics‐based fire model, to test the effect of SSD on canopy consumption by fire. Our results showed that (1) SSD was positively associated with tree mortalities caused by all three disturbances; (2) species richness was negatively associated with insect‐ and disease‐caused mortalities; (3) functional diversity was negatively associated with fire‐ and disease‐caused mortalities and (4) more phylogenetically related species had more similar mortality rates by insect and disease but not fire. Moreover, the FIRETEC model showed increasing canopy consumption by fire in stands with greater SSD. Together, the different tree mortalities during drought associated with SSD more consistently than the other biodiversity metrics were evaluated. Synthesis . Our results suggest that SSD could be considered in modelling forest dynamics and planning management to sustain forest health under disturbances.
54 ENVIRONMENTAL SCIENCES↗
FATE Unified Modeling Method for Spent Nuclear Fuel and Sludge Processing, Shipping and Storage - 13405
A unified modeling method applicable to the processing, shipping, and storage of spent nuclear fuel and sludge has been incrementally developed, validated, and applied over a period of about 15 years at the US DOE Hanford site. The software, FATE{sup TM}, provides a consistent framework for a wide dynamic range of common DOE and commercial fuel and waste applications. It has been used during the design phase, for safety and licensing calculations, and offers a graded approach to complex modeling problems encountered at DOE facilities and abroad (e.g., Sellafield). FATE has also been used for commercial power plant evaluations including reactor building fire modeling for fire PRA, evaluation of hydrogen release, transport, and flammability for post-Fukushima vulnerability assessment, and drying of commercial oxide fuel. FATE comprises an integrated set of models for fluid flow, aerosol and contamination release, transport, and deposition, thermal response including chemical reactions, and evaluation of fire and explosion hazards. It is one of few software tools that combine both source term and thermal-hydraulic capability. Practical examples are described below, with consideration of appropriate model complexity and validation. (authors)
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Synergy between land use and climate change increases future fire risk in Amazon forests
Tropical forests have been a permanent feature of the Amazon basin for at least 55 million years, yet climate change and land use threaten the forest's future over the next century. Understory forest fires, which are common under the current climate in frontier forests, may accelerate Amazon forest losses from climate-driven dieback and deforestation. Far from land use frontiers, scarce fire ignitions and high moisture levels preclude significant burning, yet projected climate and land use changes may increase fire activity in these remote regions. Here, we used a fire model specifically parameterized for Amazon understory fires to examine the interactions between anthropogenic activities and climate under current and projected conditions. In a scenario of low mitigation efforts with substantial land use expansion and climate change – Representative Concentration Pathway (RCP) 8.5 – projected understory fires increase in frequency and duration, burning 4–28 times more forest in 2080–2100 than during 1990–2010. In contrast, active climate mitigation and land use contraction in RCP4.5 constrain the projected increase in fire activity to 0.9–5.4 times contemporary burned area. Importantly, if climate mitigation is not successful, land use contraction alone is very effective under low to moderate climate change, but does little to reduce fire activity under the most severe climate projections. These results underscore the potential for a fire-driven transformation of Amazon forests if recent regional policies for forest conservation are not paired with global efforts to mitigate climate change.
54 ENVIRONMENTAL SCIENCES↗
Synergy Between Land Use and Climate Change Increases Future Fire Risk in Amazon Forests
Tropical forests have been a permanent feature of the Amazon basin for at least 55 million years, yet climate change and land use threaten the forest's future over the next century. Understory forest fires, which are common under the current climate in frontier forests, may accelerate Amazon forest losses from climate-driven dieback and deforestation. Far from land use frontiers, scarce fire ignitions and high moisture levels preclude significant burning, yet projected climate and land use changes may increase fire activity in these remote regions. Here, we used a fire model specifically parameterized for Amazon understory fires to examine the interactions between anthropogenic activities and climate under current and projected conditions. In a scenario of low mitigation efforts with substantial land use expansion and climate change – Representative Concentration Pathway (RCP) 8.5 – projected understory fires increase in frequency and duration, burning 4–28 times more forest in 2080–2100 than during 1990–2010. In contrast, active climate mitigation and land use contraction in RCP4.5 constrain the projected increase in fire activity to 0.9–5.4 times contemporary burned area. Importantly, if climate mitigation is not successful, land use contraction alone is very effective under low to moderate climate change, but does little to reduce fire activity under the most severe climate projections. These results underscore the potential for a fire-driven transformation of Amazon forests if recent regional policies for forest conservation are not paired with global efforts to mitigate climate change.
Le Page, Yannick↗
Using Machine Learning to Develop a Predictive Model for Future Fire Seasons
The deep learning model shows promise for predicting areas of high wildfire potential. Full evaluation of the model performance is ongoing. Currently, the developed deep learning model is better overall at predicting the number of fires over the acres burned. Acres burned is dependent on location, suppression plan, and current conditions. Antecedent conditions are only one piece of the equation. In-season changes are not accounted for. An ignition source is required, which further complicates the model training and prediction.
White, Andrew T.↗
Fire control method and analytical model for large liquid hydrocarbon pool fires
The dominate parameter governing the behavior of a liquid hydrocarbon (JP-5) pool fire is wind speed. The most effective method of controlling wind speed in the vicinity of a large circular (10 m dia.) pool fire is a set of concentric screens located outside the perimeter. Because detailed behavior of the pool fire structure within one pool fire diameter is unknown, an analytical model supported by careful experiments is under development. As a first step toward this development, a regional pool fire model was constructed for the no-wind condition consisting of three zones -- liquid fuel, combustion, and plume -- where the predicted variables are mass burning rate and characteristic temperatures of the combustion and plume zones. This zone pool fire model can be modified to incorporate plume bending by wind, radiation absorption by soot particles, and a different ambient air flow entrainment rate. Results from the zone model are given for a pool diameter of 1.3 m and are found to reproduce values in the literature.
Fenton, D. L.↗
Enclosure fire hazard analysis using relative energy release criteria
A method for predicting the probable course of fire development in an enclosure is presented. This fire modeling approach uses a graphic plot of five fire development constraints, the relative energy release criteria (RERC), to bound the heat release rates in an enclosure as a function of time. The five RERC are flame spread rate, fuel surface area, ventilation, enclosure volume, and total fuel load. They may be calculated versus time based on the specified or empirical conditions describing the specific enclosure, the fuel type and load, and the ventilation. The calculation of these five criteria, using the common basis of energy release rates versus time, provides a unifying framework for the utilization of available experimental data from all phases of fire development. The plot of these criteria reveals the probable fire development envelope and indicates which fire constraint will be controlling during a criteria time period. Examples of RERC application to fire characterization and control and to hazard analysis are presented along with recommendations for the further development of the concept.
Coulbert, C. D.↗
Assessment of risk due to the use of carbon fiber composites in commercial and general aviation
The development of a national risk profile for the total annual aircraft losses due to carbon fiber composite (CFC) usage through 1993 is discussed. The profile was developed using separate simulation methods for commercial and general aviation aircraft. A Monte Carlo method which was used to assess the risk in commercial aircraft is described. The method projects the potential usage of CFC through 1993, investigates the incidence of commercial aircraft fires, models the potential release and dispersion of carbon fibers from a fire, and estimates potential economic losses due to CFC damaging electronic equipment. The simulation model for the general aviation aircraft is described. The model emphasizes variations in facility locations and release conditions, estimates distribution of CFC released in general aviation aircraft accidents, and tabulates the failure probabilities and aggregate economic losses in the accidents.
Fiksel, J.↗
Deep Learning Provides Substantial Improvements to County‐Level Fire Weather Forecasting Over the Western United States
Abstract The recent wildfires in the western United States during 2018 and 2020 caused record‐breaking fire damage and casualties. Despite remarkable advances in fire modeling and weather forecasting, it remains challenging to anticipate catastrophic wildfire events and associated damage. One key missing component is a fire weather prediction system with sufficiently long lead time capable of providing useful regional details. Here, we develop a hybrid prediction model of wildfire danger called CFS with super resolution (CFS‐SR) as a proof of concept to fill that void. The CFS‐SR model is constructed by integrating the Climate Forecast System version 2 with a deep learning (DL) technique from Single Image Super Resolution, a method widely used in enhancing image resolution. We show that for the 2018–2019 fire season, the CFS‐SR model significantly improves accuracy in forecasting fire weather at lead times of up to 7 days with an enhanced spatial resolution up to 4 km. This level of high resolution provides county‐level fire weather forecast, making it more practical for allocating resources to mitigate wildfire danger. Our study demonstrates that a proper combination of ensemble climate predictions with DL techniques can boost predictability at finer spatial scales, increasing the utility of fire weather forecasts for practical applications.
54 ENVIRONMENTAL SCIENCES↗
Physics-Informed AI for Climate and Weather Risk Prediction (Final Report)
As part of the work Terrafuse developed 1) a model for wildfire risk in California, and 2) a model for downscaled wind fields from Numerical Weather Prediction (NWP) numerical models. The wildfire model is based on 20 years of historical data and captures the dependence of wildfire incidence and spread on climatic, weather and land-use variables by training a machine learning model. Nonlinear relationships between input features are learned and expressed by the model and model transparency allows features to be ranked and interpreted. The fire model is of use for accurately predicting real-time daily and long-term wildfire risk for use cases in energy and insurance. The downscaled wind model is a spatio-temporal deep learning model that emulates the influence of high-resolution variables on wind speed, allowing coarse-resolution operational NWP models to be accurately expressed on fine grids at high resolution, with application to wind energy and weather forecasting.
54 ENVIRONMENTAL SCIENCES↗
The Annular Suspension and Pointing System /ASPS/
The Annular Suspension and Pointing System (ASPS) may be attached to a carrier vehicle for orientation, mechanical isolation, and fine pointing purposes applicable to space experiments. It has subassemblies for both coarse and vernier pointing. A fourteen-degree-of-freedom simulation of the ASPS mounted on a Space Shuttle has yielded initial performance data. The simulation describes: the magnetic actuators, payload sensors, coarse gimbal assemblies, control algorithms, rigid body dynamic models of the payload and Shuttle, and a control system firing model.
Anderson, W. W.↗
Estimating canopy fuel characteristics for predicting crown fire potential in common forest types of the Atlantic Coastal Plain, USA
We computed four stand-level canopy stratum variables important for crown fire modelling – canopy cover, stand height, canopy base height and canopy bulk density – from forest inventory data. We modelled the relationship between the canopy variables and a set of common inventory parameters – site index, stem density, basal area, stand age or stand height – and number of prescribed burns. We used a logistic model to estimate canopy cover, a linear model to estimate the other canopy variables, and the information theoretic approach for model selection. Coefficients of determination across five forest groups were 0.72–0.91 for stand height, 0.36–0.83 for canopy base height, 0.39–0.80 for canopy cover, and 0.63–0.78 for canopy bulk density. We assessed crown fire potential (1) for several sets of environmental conditions in all seasons, and (2) with increasing age, density and number of prescribed burns using our modelled canopy bulk density and canopy base height variables and local weather data to populate the Crown Fire Initiation and Spread model. Results indicated that passive crown fire is possible in any season in Atlantic coastal plain pine stands with heavy surface fuel loads and active crown fire is most probable in infrequently burned, dense stands at low fuel moistures.
Forestry↗