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Engineering↗
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Results for “Fire Simulation”
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.
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Surface Modification of ICF Target Capsules by Pulsed Laser Ablation
Topographical modifications of spherical surfaces are imprinted on National Ignition Facility (NIF) target capsules by extending the capabilities of a recently developed full surface (4π) laser ablation and mapping apparatus. The laser ablation method combines the precision, energy density and long reach of a focused laser beam to pre-impose sinusoidal modulations on the outside surface of High Density Carbon (HDC) capsules and the inside surface of Glow Discharge Polymer (GDP) capsules. Sinusoidal modulations described in this paper have sub-micron to 10’s of microns vertical scale and wavelengths as small as 30 μm and as large as 200 μm. The modulated patterns are created by rastering a focused laser fired at discrete capsule surface locations for a specified number of pulses. The computer program developed to create these raster patterns uses inputs such as laser beam intensity profile, the material removal function, the starting surface figure and the desired surface figure. The patterns are optimized to minimize surface roughness. Lastly, in this paper, simulated surfaces are compared with actual ablated surfaces measured using confocal microscopy.
36 MATERIALS SCIENCE↗
Four equation k-omega based turbulence model with algebraic flux for supercritical flows
Hydrocarbon and nuclear fuels will contribute substantially to the growing global energy portfolio for some time to come. At the same time atmospheric carbon levels and economic concerns are increasingly shaping the power generation environment. Supercritical fluid technologies are being investigated to address both concerns. For example, direct fired supercritical CO 2 power cycles offer key advantages for carbon capture and thermal efficiency. Additionally, the supercritical water reactor Generation IV nuclear reactor allows higher power densities and more efficient operation than current pressurized or boiling water reactors. As these technologies are developed, a need exists for accurate, yet cost-effective modeling and simulation solutions to assist with design and safety calculations. Supercritical fluid properties are strongly dependent on temperature which results in a number of unique flow features. Among these features are the complex buoyancy and buoyancy-turbulence interaction behaviors exhibited by supercritical flows that are not found in liquid or gas flows. Therefore, standard turbulence models with current model coefficient values are not likely to be applicable to supercritical fluid flows. The subject of this paper is efficient modeling and simulation of supercritical flows to support nascent technologies growing to maturation and operational deployment. We present a framework for developing Reynolds-Averaged Navier-Stokes turbulence models specifically equipped for the challenges of supercritical flows. A novel formulation of the algebraic heat flux model of the buoyancy production of turbulence term is used with a traditional shear stress transport model. To produce a new turbulence model for supercritical channel flows, the empirical coefficients of the resulting four equation model were calculated from data previously published by other authors regarding upward supercritical flow through heated pipes. The presented SST k t - ω t approach was validated against heated tube experiments to show predictive capabilities in moderate flow conditions, where buoyancy effects are important but not dominating of inertial effects.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Wound Ballistics Modeling for Blast Loading Blunt Force Impact and Projectile Penetration.
Light body armor development for the warfighter is based on trial-and-error testing of prototype designs against ballistic projectiles. Torso armor testing against blast is nonexistent but necessary to protect the heart and lungs. In tests against ballistic projectiles, protective apparel is placed over ballistic clay and the projectiles are fired into the armor/clay target. The clay represents the human torso and its behind-armor, permanent deflection is the principal metric used to assess armor protection. Although this approach provides relative merit assessment of protection, it does not examine the behind-armor blunt trauma to crucial torso organs. We propose a modeling and simulation (M&S) capability for wound injury scenarios to the head, neck, and torso of the warfighter. We will use this toolset to investigate the consequences of, and mitigation against, blast exposure, blunt force impact, and ballistic projectile penetration leading to damage of critical organs comprising the central nervous, cardiovascular, and respiratory systems. We will leverage Sandia codes and our M&S expertise on traumatic brain injury to develop virtual anatomical models of the head, neck, and torso and the simulation methodology to capture the physics of wound mechanics. Specifically, we will investigate virtual wound injuries to the head, neck, and torso without and with protective armor to demonstrate the advantages of performing injury simulations for the development of body armor. The proposed toolset constitutes a significant advance over current methods by providing a virtual simulation capability to investigate wound injury and optimize armor design without the need for extensive field testing.
45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
Porting a fast-running wildfire plume model for use in national security and climate applications
In this project, the code for the fast-running Freitas wildfire plume model was successfully ported into the NARAC system, creating an operations-ready capability for predicting the transport of hazardous smoke from large wildfires. “Porting” refers to copying a section of code from one software package to another while accounting for unique dependencies in each software package. In this case, the code was ported from the Weather Research and Forecasting (WRF) Model, which is used extensively by the project team. To verify correct implementation, model results from the updated NARAC system were compared to those from WRF and the High-Resolution Rapid Refresh (HRRR) forecast model, which also employs the Freitas scheme. The NARAC User Interface (UI) and code documentation were also updated to include the new wildfire plume option, and a wildfire case was added to the NARAC test suite. The code was used in a real-time, semi-operational setup to predict smoke transport during the Cerro Pelado fire near Los Alamos National Laboratory in May 2022. The Freitas plume model was also tested for LLNL climate applications. Although the code was not ported into the Energy Exascale Earth System Model (E3SM), it was tested offline using E3SM atmospheric inputs, and results were compared to existing high-resolution plume predictions from large-eddy simulations in WRF. The code implementation and testing completed during this project will enable future work predicting smoke transport from large wildfires in LLNL national security and climate mission spaces.
54 ENVIRONMENTAL SCIENCES↗
Quantifying contributions of natural variability and anthropogenic forcings on increased fire weather risk over the western United States
Previous studies have identified a recent increase in wildfire activity in the western United States (WUS). However, the extent to which this trend is due to weather pattern changes dominated by natural variability versus anthropogenic warming has been unclear. Using an ensemble constructed flow analogue approach, we have employed observations to estimate vapor pressure deficit (VPD), the leading meteorological variable that controls wildfires, associated with different atmospheric circulation patterns. Our results show that for the period 1979 to 2020, variation in the atmospheric circulation explains, on average, only 32% of the observed VPD trend of 0.48 ± 0.25 hPa/decade (95% CI) over the WUS during the warm season (May to September). The remaining 68% of the upward VPD trend is likely due to anthropogenic warming. The ensemble simulations of climate models participating in the sixth phase of the Coupled Model Intercomparison Project suggest that anthropogenic forcing explains an even larger fraction of the observed VPD trend (88%) for the same period and region. These models and observational estimates likely provide a lower and an upper bound on the true impact of anthropogenic warming on the VPD trend over the WUS. During August 2020, when the August Complex “Gigafire” occurred in the WUS, anthropogenic warming likely explains 50% of the unprecedented high VPD anomalies.
54 ENVIRONMENTAL SCIENCES↗
Development of a 95-Year Solar Dataset for Resource Adequacy Studies
Long-term high-resolution solar data provides enhanced understanding of variability of solar generation and enhances our ability to develop strategies for a resilient and reliable electric grid under high deployment of solar energy. Therefore, it is important to develop long-term synthetic datasets that can provide multiple occurrences of various severe weather scenarios that are expected to test the limits of resource adequacy under scenarios contain various energy generation sources. Examples of such scenarios could be long periods of high temperatures when demand for electricity is high or periods where high winds could lead to a shut-down of transmission lines for long periods of time to ensure fire safety. NREL has developed the first version of such a dataset covering a 95-year period covering 2006-2100 at a 4km hourly resolution. This dataset contains all variables necessary to calculate solar generation. During development of this dataset, we focused on creating unbiased, high-resolution solar irradiance through statistical downscaling methods, using Regional Climate Model (RCM) simulations from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) as input. The National Solar Radiation Database (NSRDB) containing over 25 years of observations was used to calibrate the statistical downscaling models. This presentation will outline the primary steps in developing this dataset, including (1) regridding RCM data to a common grid at 20-km resolution, (2) correcting RCM biases with NSRDB, (3) applying temporal and spatial downscaling methods to generate high-resolution (4-km, hourly) solar and ancillary data. Additionally, we will present an evaluation of the downscaled data against the NSRDB across various zones in the CONUS. Lastly, we will present a user guide for accessing the datasets.
14 SOLAR ENERGY↗
Building a machine learning surrogate model for wildfire activities within a global Earth system model
Abstract. Wildfire is an important ecosystem process, influencing land biogeophysical and biogeochemical dynamics and atmospheric composition. Fire-driven loss of vegetation cover, for example, directly modifies the surface energy budget as a consequence of changing albedo, surface roughness, and partitioning of sensible and latent heat fluxes. Carbon dioxide and methane emitted by fires contribute to a positive atmospheric forcing, whereas emissions of carbonaceous aerosols may contribute to surface cooling. Process-based modeling of wildfires in Earth system land models is challenging due to limited understanding of human, climate, and ecosystem controls on fire counts, fire size, and burned area. Integration of mechanistic wildfire models within Earth system models requires careful parameter calibration, which is computationally expensive and subject to equifinality. To explore alternative approaches, we present a deep neural network (DNN) scheme that surrogates the process-based wildfire model with the Energy Exascale Earth System Model (E3SM) interface. The DNN wildfire model accurately simulates observed burned area with over 90 % higher accuracy with a large reduction in parameterization time compared with the current process-based wildfire model. The surrogate wildfire model successfully captured the observed monthly regional burned area during validation period 2011 to 2015 (coefficient of determination, R2=0.93). Since the DNN wildfire model has the same input and output requirements as the E3SM process-based wildfire model, our results demonstrate the applicability of machine learning for high accuracy and efficient large-scale land model development and predictions.
58 GEOSCIENCES↗
A Study of BWR Mark I Station Blackout Accident with GOTHIC Modeling
The overall objective of this study is to develop a high-fidelity simulation capability for the analysis of accident progression during Station Black-Out (SBO) scenario in Boiling Water Reactor (BWR) Mark I plant. The motivation is on predicting the effectiveness of containment venting within accident mitigation strategy and how to avoid core melt by choosing a proper time to initiate primary system venting. In this work, a GOTHIC model has been developed to support characterization of reactor safety systems performance and evaluation of the venting strategy. The GOTHIC model provides a seamless coupled simulation of the reactor coolant system and the containment system based on the design of the Peach Bottom-2 plant system. Efforts are also taken on the analysis for the primary system venting strategy. The safe time intervals (so-called “safe venting window”) to initiate the primary system depressurization in order to optimize the early cooling strategy by adding fire water and avoid core melt are also studied based on the heat removal capability (HRC) of the reactor vessel coolant. This concept is instructive for the operation of the safety systems during the SBO accident mitigation.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Distributed Wireless Antenna Sensors for Boiler Condition Monitoring
Monitoring the operational conditions of coal-fired boilers is an important task that could bring tremendous benefits, including in-situ process control, real-time health assessment of structural components, improved heat transfer efficiency, reduced downtime, etc. Moreover, in-situ distributed sensing of the boiler conditions would provide large scale in-situ measurement data that will help us gain fundamental understandings of the combustion and heat transfer processes as well as enable the developments of new simulation tools, which could eventually lead to better design and more efficient operation of the boilers. The objectives of this research were to (a) develop wireless passive antenna sensors without electronics; (b) demonstrate multi-modality sensing using a signal antenna sensor; and (c) fabricate the antenna sensor from high-temperature materials. In this project, we have demonstrated that an antenna sensor or sensor array without any electronics can be wirelessly interrogated from a distance. In addition, a low-cost compact wireless sensor interrogator was developed for dynamic interrogation of the passive antenna sensor. We validated that a dual-frequency antenna sensor is capable of simultaneous strain and temperature measurements or temperature and ash accumulation measurements; all parameters are relevant to boiler condition monitoring. By measuring the temperature and ash accumulation height simultaneously, the dielectric constant of the ash as well as its temperature dependency can also be characterized. This capability could lead to potential applications of the antenna sensor for combustion process monitoring based on the ash composition. We also investigated different techniques of fabricating the antenna sensor using high-temperature materials such as alumina substrate and platinum paste and characterized the thermal response of the antenna sensor. A linear relationship between the antenna resonant frequency and the temperature change was validated.
20 FOSSIL-FUELED POWER PLANTS↗
Final Technical Report: Impact of Wildfires on Solar Generation, Reserves, and Energy Prices
This study quantifies the potential impacts of wildfires on the California grid, specifically the impacts under three different wildfire scenarios: a "no wildfire" scenario and two wildfire-specific scenarios, "2020 wildfire" and "enhanced wildfire" (with both wildfire scenarios assuming spatial distribution of the wildfire location the same as the 2020 fires). The study combines each scenario with two solar energy infrastructures: one corresponding to the current solar installation and the other to future (midcentury) solar installation. The analysis is conducted using state-of-the-science modeling tools: primarily WRF-Chem for atmospheric modeling with chemistry to account for impacts of wildfires on solar radiation and PLEXOS for electricity market simulations. The analysis suggests that wildfires can significantly attenuate solar radiation at both short downwind distances as well as far from the emissions sources. Although the study is limited in scope, and the analysis studies only a few of the many factors that can affect photovoltaic generation and electricity markets, it indicates that wildfire smoke is an important factor that needs to be carefully considered and analyzed in planning the future grid.
electricity market↗
Drop Interactions with the Conical Shock Structure Generated by a Mach 4.5 Projectile
This work presents measurements of liquid drop deformation and breakup time behind approximately conical shock waves and evaluates the predictive capabilities of low-order models and correlations developed using planar shock experiments. A conical shock was approximated by firing a bullet at Mach 4.5 past a vertical column of water drops with a mean initial diameter of $192$ $\mu$m. The time-resolved drop position and maximum transverse dimension were characterized using backlit stereo images taken at 500 kHz. The gas density and velocity fields experienced by the drops were estimated using a Reynolds-averaged Navier–Stokes simulation of the bullet. Classical correlations predict drop breakup times and deformation in error by a factor of 3 or more. The Taylor analogy breakup (TAB) model predicts deformed drop diameters that agree within the confidence bounds of the ensemble-averaged experimental values using a dimensionless constant $C$ 2 = $2$ compared to the accepted value $C$ 2 = $2/3$. In conclusion, results demonstrate existing correlations are inadequate for predicting the drop response to the three-dimensional relaxation of the flowfield downstream of a conical-like shock and suggest the TAB model results represent a path toward improved predictions.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
EPA and Idaho National Laboratory create first of its scale
Advancing the science and engineering of decontaminating water distribution systems and safely disposing of high-volumes of contaminated water are high priorities for the EPA. To help address these science gaps, EPA homeland security researchers have developed the first-of-its-scale Water Security Test Bed (WSTB). Water is an important component of everyday life. We rely on safe, clean water for our health and the health of the environment. Protecting this vital resource is critical to living safely and securely. The U.S. Environmental Protection Agency is responsible for working with water utilities to protect water systems from contamination and to clean up systems that become contaminated. Purposeful or inadvertent distribution system contamination can result in large amounts of infrastructure and water that must be cleaned. Water distribution systems contamination can be caused by, for example, natural disasters such as Superstorm Sandy or by individuals hoping to cause harm. The WSTB, constructed at the Department of Energy’s (DOE) Idaho National Laboratory, replicates a section of a typical municipal drinking water system including a piping system with roughly 445 feet of pipe and two fire hydrants laid out in an “L” shape using 40-year-old, eight-inch cement mortar lined, ductile iron pipes, excavated after twenty years of use for water conveyance. Researchers built the WSTB above ground for easy access during experiments, and to facilitate fast leak detection. Over the next several years, EPA and partner researchers will conduct experiments using simulants of various biological, chemical, and radioactive materials that simulate high toxic versions of these agents. At this “full” sized system, researchers will demonstrate approaches to contamination detection, sensor and model testing, infrastructure decontamination, water treatment and cyber testing developed at lab and pilot scale. Researchers are also able to verify if laboratory results that were effective in controlled conditions are as effective in full-scale testing. Having the ability to conduct bench scale studies in a real world setting can help address specific research gaps, and help water researchers understand conditions in which real world drinking water systems operate.
54 ENVIRONMENTAL SCIENCES↗
Examination of entrainment, combustibility, and heat transfer due to cell venting inside simplified battery energy storage enclosures
Battery energy storage systems (ESS) assembled of modules containing lithium-ion batteries can pose fire and explosion hazards during thermal runaway because vented gases may accumulate, combust, or escape enclosures. Here, we propose a prototypical configuration composed of the main components of an ESS rack, where modules are represented as rectangles within an enclosure and vent gas is injected steadily through the top of a module. This idealized geometry allows for exploration of how rack-level characteristics can influence smaller single-cell or module-level scales. Through this geometry, we conduct numerical simulations to understand how variations in the vent velocity, temperature, and vertical location affect entrainment rates, fraction of uncombusted fuel, rich-gas coverage, and heat flux to other modules. At lower vent velocities and vertical positions, buoyancy drives enough entrainment and mixing to react with most of the vent gases on the converging plenum. As jet momentum increases and/or buoyancy decreases via higher vent position in the rack, vent gases can propagate into and burn in the divergence plenum. Heat flux to the impinged module scales strongly with vent momentum and temperature, while heat transfer to upper modules peaks when flames in the diverging plenum reach the surface and declines when combustion is suppressed.
Computational fluid dynamics↗
Novel Inorganic/Polymer Composite Membranes for CO 2 Capture
The objective of this project is to develop a cost-effective design and manufacturing process for new membrane modules that capture CO 2 from flue gas in coal-fired power plants. The membrane consisted of a thin selective layer including inorganic (zeolite) embedded in a polymer structure so that it can be made in a continuous manufacturing process. The membrane was incorporated in spiral-wound modules for the field test with actual flue gas at the National Carbon Capture Center (NCCC) in Wilsonville, AL and bench scale tests with simulated flue gas at the Ohio State University (OSU). Using the modules for post-combustion CO 2 capture is expected to achieve the DOE target of $40/tonne CO 2 captured (in 2007 dollar) for 2025. Membranes with the amine-containing polymer cover layer on zeolite-Y (ZY) nanoparticles deposited on the polyethersulfone (PES) substrate were successfully synthesized. The membranes showed a high CO 2 permeance of about 1100 GPU (gas permeation unit, 1 GPU = 10 -6 cm 3 (STP)/(cm 2 • s • cm Hg), 3000 GPU = 10-6 mol/(m 2 • s • Pa)) with a high CO 2 /N 2 selectivity of > 200 at the typical flue gas conditions at 57°C (about 17% water vapor in feed gas) and > 1400 GPU CO 2 permeance with > 500 CO 2 /N 2 selectivity at 102°C (~ 80% water vapor). The synthesis of ZY nanoparticles was successfully scaled up, and the pilot-scale membranes were also successfully fabricated using the continuous membrane machine at OSU. The transport performance of the pilot-scale membranes agreed reasonably well with the lab-scale membranes. The results from both the lab-scale and scale-up membranes were used for the techno-economic analysis. The scale-up membranes were fabricated into prototype spiral-wound membrane modules for continuous testing with simulated or real flue gas. For real flue gas testing, we worked with NCCC, in consultation with TriSep Corporation, Gradient Technology and American Electric Power (AEP). The membrane module demonstrated > 800 GPU of CO 2 permeance and > 150 CO 2 /N 2 selectivity when tested with real flue gas at NCCC. The results obtained were used to update the techno-economic analysis. In addition, the EH&S assessment of the membranes for post-combustion CO 2 capture was conducted.
20 FOSSIL-FUELED POWER PLANTS↗
Electrochemical Membrane for Carbon Dioxide Capture and Power Generation
FuelCell Energy, Inc. (FCE), in collaboration with AECOM Corporation (formerly URS Corporation) and Pacific Northwest National Laboratory, has been developing a novel Combined Electric Power and Carbon-dioxide Separation (CEPACS) system. The CEPACS system is based on electrochemical membrane (ECM) technology derived from FCE’s carbonate fuel cell products featuring internal (methane steam) reforming and carrying the trade name of Direct FuelCell®. The unique chemistry of carbonate fuel cells offers an innovative approach for separation of CO 2 from existing fossil-fuel power plant exhaust streams (flue gases). The ECM-based CEPACS system has the potential to become a transformational CO 2 -separation technology by working as two devices in one: it separates the CO 2 from the exhaust of other plants such as an existing coal-fired plant and simultaneously produces clean electric power at high efficiency using a supplementary fuel. The development effort was carried out under the U.S. Department of Energy (DOE) cooperative agreement DE-FE0007634. The overall objective of this project was to successfully demonstrate the ability of FCE’s ECM-based CEPACS system technology to separate ≥90% of the CO 2 from a simulated Pulverized Coal (PC) power plant flue gas stream and to compress the captured CO2 to a state that can be easily transported for sequestration or beneficial use. In addition, a key objective was to show, through the technical and economic feasibility study and bench scale testing, that the ECM-based CEPACS system is an economical alternative for CO 2 capture in PC power plants, and that it meets DOE’s objective related to the incremental cost of electricity (COE) for post-combustion CO 2 capture (no more than 35% increase in COE). The project was performed in three budget periods (BP). The specific objective for BP1 was to complete the Preliminary Technical and Economic Feasibility Study. The T&EF study was based on the carbon capture system size suitable for a reference 550 MW PC power plant. The specific objectives for BP2 were to perform (flue gas) contaminant effect evaluation tests, small area membrane tests using clean simulated flue gas, design a flue gas pretreatment system for processing of the gas feed to ECM, update the Technical & Economic Feasibility Study (T&EFS) incorporating results of contaminant effect tests and small area membrane tests, and to prepare a test facility for bench scale testing. The specific objectives for BP3 were to perform bench scale testing (parametric and long-duration testing) of a 11.7 m 2 ECM-based CO 2 capture, purification and compression system, and update (as final) the Technical and Economic Feasibility Study. In addition, an Environmental Health and Safety evaluation (assessment) of the ECM technology was included. This final technical report presents the progress made under the project.
20 FOSSIL-FUELED POWER PLANTS↗
Three-terminal magnetic tunnel junction synapse circuits with spike-timing-dependent plasticity.
Abstract not provided.
Akinola, Otitoaleke↗
PARALLEL PERTURBATION MODEL FOR CYCLE TO CYCLE VARIABILITY PPM4CCV
This code consists of a Fortran 90 implementation of the parallel perturbation model to compute cyclic variability in spark ignition (SI) engines. Cycle-to-cycle variability (CCV) is known to be detrimental to SI engine operation resulting in partial burn and knock, and result in an overall reduction in the reliability of the engine. Numerical prediction of cycle-to-cycle variability (CCV) in SI engines is extremely challenging for two key reasons: (i) high-fidelity methods such as large eddy simulation (LES) are required to accurately capture the in-cylinder turbulent flow field, and (ii) CCV is experienced over long timescales and hence the simulations need to be performed for hundreds of consecutive cycles. In the new technique, the strategy is to perform multiple parallel simulations, each of which encompasses 2-3 cycles, by effectively perturbing the simulation parameters such as the initial and boundary conditions. The PPM4CCV code is a pre-processing code and can be coupled with any engine CFD code. PPM4CCV was coupled with Converge CFD code and a 10-time speedup was demonstrated over the conventional multi-cycle LES in predicting the CCV for a motored engine. Recently, the model is also being applied to fired engines including port fuel injected (PFI) and direct injection spark ignition engines and the preliminary results are very encouraging.
Ameen, Muhsin Mohammed↗