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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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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Advanced Computational Methods for Thermal Radiative Heat Transfer

Participating media radiation (PMR) in weapon safety calculations for abnormal thermal environments are too costly to do routinely. This cost may be s ubstantially reduced by applying reduced order modeling (ROM) techniques. The application of ROM to PMR is a new and unique approach for this class of problems. This approach was investigated by the authors and shown to provide significant reductions in the computational expense associated with typical PMR simulations. Once this technology is migrated into production heat transfer analysis codes this capability will enable the routine use of PMR heat transfer in higher - fidelity simulations of weapon resp onse in fire environments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

MASTODON Theory Manual

Multi-hazard Analysis for STOchastic time-DOmaiN phenomena (MASTODON) is a finite element application that aims at analyzing the response of 3-D soil-structure systems to natural and man-made hazards such as earthquakes, floods and fire. MASTODON currently focuses on the simulation of seismic events and has the capability to perform extensive ‘source-to-site’ simulations including earthquake fault rupture, nonlinear wave propagation and nonlinear soil-structure interaction (NLSSI) analysis. MASTODON is being developed to be a dynamic probabilistic risk assessment framework that enables analysts to not only perform deterministic analyses, but also easily perform probabilistic or stochastic simulations for the purpose of risk assessment.

42 ENGINEERING↗
DOE OSTI2018

Fluid–Solid Coupling Simulation on the Temperature Distribution of Tuyere Used for Oxygen Bottom Blowing Converter

For an oxygen bottom blowing converter, a high-temperature fire spot zone forms above the tuyere owing to oxygen reaction. The bottom blowing tuyere and surrounding brick are simultaneously heated by high-temperature fire spot and flowing molten steel. High-speed fluids flowing in the inner tube and the annular gap of the tuyere can remove part of the heat transferred from the fire spot zone and molten steel, playing a vital role in cooling the tuyere. To determine the temperature distributions of the tuyere and surrounding brick under the condition of oxygen bottom blowing, a fluid–solid coupling heat transfer numerical model that considers both the radiation of the fire spot and convection of the molten steel was established in this study. The simulation results agree well with previous experimental results; thus, the numerical model was validated. Utilizing the validated model, the influences of the tuyere inner tube material and fire spot zone temperature on the tuyere temperature distribution were studied in detail. Along with an increase in the material thermal conductivity, the maximum temperature of the inner tube at the hot face decreased, verifying the superiority of copper as the inner tube. More importantly, it was found that reducing the fire spot zone temperature by mixing CO{sub 2} in the bottom blowing oxygen fundamentally alleviated the burning loss of the tuyere and the surrounding brick.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Future Fire Impacts on Smoke Concentrations, Visibility, and Health in the Contiguous United States

Fine particulate matter (PM2.5) from U.S. anthropogenic sources is decreasing. However, previous studies have predicted that PM2.5 emissions from wildfires will increase in the midcentury to next century, potentially offsetting improvements gained by continued reductions in anthropogenic emissions. Therefore, some regions could experience worse air quality, degraded visibility, and increases in population-level exposure. We use global climate model simulations to estimate the impacts of changing fire emissions on air quality, visibility, and premature deaths in the middle and late 21st century. We find that PM2.5 concentrations will decrease overall in the contiguous United States (CONUS) due to decreasing anthropogenic emissions (total PM2.5 decreases by 3% in Representative Concentration Pathway [RCP] 8.5 and 34% in RCP4.5 by 2100), but increasing fire-related PM2.5 (fire-related PM2.5 increases by 55% in RCP4.5 and 190% in RCP8.5 by 2100) offsets these benefits and causes increases in total PM2.5 in some regions. We predict that the average visibility will improve across the CONUS, but fire-related PM2.5 will reduce visibility on the worst days in western and southeastern U.S. regions. We estimate that the number of deaths attributable to total PM2.5 will decrease in both the RCP4.5 and RCP8.5 scenarios (from 6% to 4–5%), but the absolute number of premature deaths attributable to fire-related PM2.5 will double compared to early 21st century. We provide the first estimates of future smoke health and visibility impacts using a prognostic land-fire model. Our results suggest the importance of using realistic fire emissions in future air quality projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

HRSSA – Efficient hybrid stochastic simulation for spatially homogeneous biochemical reaction networks

This paper introduces HRSSA (Hybrid Rejection-based Stochastic Simulation Algorithm), a new efficient hybrid stochastic simulation algorithm for spatially homogeneous biochemical reaction networks. HRSSA is built on top of RSSA, an exact stochastic simulation algorithm which relies on propensity bounds to select next reaction firings and to reduce the average number of reaction propensity updates needed during the simulation. HRSSA exploits the computational advantage of propensity bounds to manage time-varying transition propensities and to apply dynamic partitioning of reactions, which constitute the two most significant bottlenecks of hybrid simulation. A comprehensive set of simulation benchmarks is provided for evaluating performance and accuracy of HRSSA against other state of the art algorithms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Simulations of Laser Experiments to Study the Origin of Cosmic Magnetic Fields

Magnetic fields are ubiquitous in the universe; however, their origin is not fully understood. Cosmologists and astrophysicists have proposed a variety of ways in which small seed magnetic fields could be created. It is widely thought that the much larger values of the cosmic magnetic fields that we observe are a result of the amplification of these seed fields by the nonlinear turbulent dynamo mechanism. Such a mechanism had not yet been demonstrated in a controlled laboratory environment. We conceived experiments designed to demonstrate and study the nonlinear turbulent dynamo mechanism in the laboratory. These experiments characterize the distribution of turbulent energy among the velocity, magnetic field, and density fluctuations, providing a comprehensive picture of the energy cascade in a magnetized, turbulent plasma. The experiments build on the pathfinder experiments we have conducted on the Vulcan laser at the Rutherford-Appleton Laboratory in the UK and the OMEGA laser at Laboratory for Laser Energetics at Rochester. They utilize the high-intensity lasers at the Omega Laser Facility, the National Ignition Facility (NIF) at LLNL and the Laser Megajoule (LMJ) Facility in France – the largest laser facilities in the world. The goal of this project was to design and model the highly demanding experiments through simulation campaigns using FLASH, a highly capable radiation-MHD code we have developed, and large-scale 3D simulations on the Mira supercomputer at ANL. The simulations were vital to ensuring the experiments achieve the strong turbulence and large magnetic Reynolds numbers required for the nonlinear turbulent dynamo mechanism to operate. The simulations were also critical to determining when to fire the diagnostics, since the experiments last tens of nanoseconds but the signals of the strongly amplified magnetic fields last only a few nanoseconds. Finally, high-fidelity, validated FLASH simulations were crucial to interpreting the results of the experiments. By combining theory, experiments, and simulations, we were able to succeed in demonstrating and characterizing the nonlinear turbulent dynamo mechanism. The effort leveraged (1) the emergence of the Flash Center for Computational Science as a leader in numerical modeling of academic High Energy Density Physics (HEDP) experiments; (2) the FLASH code, which has been developed by the Flash Center and is a leadership-class, multi- physics, publicly available community code that has been applied successfully in many laser-driven experiments; (3) the expertise acquired through pathfinder experiments we performed on the Vulcan laser at the Rutherford-Appleton Laboratory in the UK and on the Omega laser facility; (4) the experience we have gained in designing and interpreting these experiments using validated simulations done with FLASH; and (5) the close collaborations we have established with outstanding experimental groups in the US and abroad. The broader impacts of the project are two-fold: (1) the work furthered the transformation of the academic community’s ability to design and analyze HEDP experiments at large laser facilities that is happening through the availability of FLASH and its widespread adoption by the academic community – a community that previously had had limited access to open and validated hydro/MHD simulation tools for HEDP experiments; and (2) the work trained young scientists to design and interpret HEDP experiments using validated simulations – a critical national need.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Performance of a Surface Barrier for Waste Isolation and Flux Reduction at the Hanford Site - 16099

Based on the knowledge gained from a decade of laboratory, field, and numerical studies, the Prototype Hanford Barrier (PHB) was designed and constructed between late 1993 and late 1994 over the 216-B-57 Crib in the 200-BP-1 Operable Unit at the Hanford Site. The PHB has been monitored since 1994 to evaluate the physical, hydrologic, and ecological performance. Two stress tests were carried out in the past: 1) an enhanced (about 3 times the multi-year average of 160 mm/year) precipitation test from water year (WY) 1995 to WY1997, which included simulated 1000-year return, 24-hour rainstorms in March of each year, and 2) a controlled fire test in 2008. The purpose of this article is to present the main findings of the PHB demonstration since 1994. From 1994 to 2013-during which time the barrier experienced 3 years of enhanced precipitation, three 1000-year return, 24-hour simulated rainstorms, and a controlled fire-the PHB limited drainage to well below the 0.5 mm yr{sup -1} design criterion and had minimal erosion. Although the test period represents only 2% of the design life, the observations suggest the PHB is robust enough to control drainage and isolate subsurface contaminants. Future barrier performance will depend on barrier stability and hydrology. Given the 19-year record of successful performance and considering all processes and mechanisms that could degrade barrier stability and hydrology in the future, the results suggest that the PHB is very likely to perform for at least the remainder of its 1000-year design life. This conclusion is based on two assumptions: 1) the exposed sub-grade receives protection against erosion and 2) institutional controls prevent inadvertent human activity on the barrier. The findings at the PHB are useful for the design and monitoring of future surface barriers at Hanford and elsewhere. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Physical Review Journal Club: Structural uncertainty assessment for fire-engulfed objects in crosswind: Establishing credibility for a multiphysics wall-modeled large-eddy simulation paradigm

This is an invited presentation for APS's monthly Journal Club where important papers that have recently been accepted for publication are highlighted in a seminar-like setting. The presentation will be "live" (May 1, 2025) and streamed across the world (including an archived recording).

Domino, Stefan Paul [Sandia National Laboratories ↗
DOE OSTI2024

Quantifying wildfire drivers and predictability in boreal peatlands using a two-step error-correcting machine learning framework in TeFire v1.0

Abstract. Wildfires are becoming an increasing challenge to the sustainability of boreal peatland (BP) ecosystems and can alter the stability of boreal carbon storage. However, predicting the occurrence of rare and extreme BP fires proves to be challenging, and gaining a quantitative understanding of the factors, both natural and anthropogenic, inducing BP fires remains elusive. Here, we quantified the predictability of BP fires and their primary controlling factors from 1997 to 2015 using a two-step correcting machine learning (ML) framework that combines multiple ML classifiers, regression models, and an error-correcting technique. We found that (1) the adopted oversampling algorithm effectively addressed the unbalanced data and improved the recall rate by 26.88 %–48.62 % when using multiple datasets, and the error-correcting technique tackled the overestimation of fire sizes during fire seasons; (2) nonparametric models outperformed parametric models in predicting fire occurrences, and the random forest machine learning model performed the best, with the area under the receiver operating characteristic curve ranging from 0.83 to 0.93 across multiple fire datasets; and (3) four sets of factor-control simulations consistently indicated the dominant role of temperature, air dryness, and climate extreme (i.e., frost) for boreal peatland fires, overriding the effects of precipitation, wind speed, and human activities. Our findings demonstrate the efficiency and accuracy of ML techniques in predicting rare and extreme fire events and disentangle the primary factors determining BP fires, which are critical for predicting future fire risks under climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

North American boreal forests are a large carbon source due to wildfires from 1986 to 2016

Wildfires are a major disturbance to forest carbon (C) balance through both immediate combustion emissions and post-fire ecosystem dynamics. Here we used a process-based biogeochemistry model, the Terrestrial Ecosystem Model (TEM), to simulate C budget in Alaska and Canada during 1986–2016, as impacted by fire disturbances. We extracted the data of difference Normalized Burn Ratio (dNBR) for fires from Landsat TM/ETM imagery and estimated the proportion of vegetation and soil C combustion. We observed that the region was a C source of 2.74 Pg C during the 31-year period. The observed C loss, 57.1 Tg C year -1 , was attributed to fire emissions, overwhelming the net ecosystem production (1.9 Tg C year -1 ) in the region. Our simulated direct emissions for Alaska and Canada are within the range of field measurements and other model estimates. As burn severity increased, combustion emission tended to switch from vegetation origin towards soil origin. When dNBR is below 300, fires increase soil temperature and decrease soil moisture and thus, enhance soil respiration. However, the post-fire soil respiration decreases for moderate or high burn severity. The proportion of post-fire soil emission in total emissions increased with burn severity. Net nitrogen mineralization gradually recovered after fire, enhancing net primary production. Net ecosystem production recovered fast under higher burn severities. The impact of fire disturbance on the C balance of northern ecosystems and the associated uncertainties can be better characterized with long-term, prior-, during- and post-disturbance data across the geospatial spectrum. Our findings suggest that the regional source of carbon to the atmosphere will persist if the observed forest wildfire occurrence and severity continues into the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The Latent Dirichlet Allocation model applied to airborne LiDAR data: A case study on mapping forest degradation associated with fragmentation and fire in the Amazon region

1. LiDAR data are being increasingly used to provide a detailed characterization of the vertical profile of forests. This characterization enables the generation of new insights on the influence of environmental drivers and anthropogenic disturbances on forest structure as well as on how forest structure influences important ecosystem functions and services. Unfortunately, extracting information from LiDAR data in a way that enables the spatial visualization of forest structure, as well as its temporal changes, is challenging due to the high dimensionality of these data. 2. In this study, we show how the Latent Dirichlet Allocation model applied to LiDAR data (LidarLDA) can be used to identify forest structural types and how the relative abundance of these forest types changes throughout the landscape. The code to fit this model is made available through the open-source r package LidarLDA in github. We illustrate the use of LidarLDA both with simulated data and data from a large-scale fire experiment in the Brazilian Amazon region. 3. Using simulated data, we demonstrate that LidarLDA accurately identifies the number of forest types as well as their spatial distribution and absorptance probabilities. For the empirical data, we found that LidarLDA detects both landscape-level patterns in forest structure as well as the strong interacting effect of fire and forest fragmentation on forest structure based on the experimental fire plots. More specifically, LidarLDA reveals that proximity to forest edge exacerbates the impact of fires, and that burned forests remain structurally different from unburned areas for at least 7 years, even when burned only once. Importantly, LidarLDA generates insights on the 3D structure of forest that cannot be obtained using more standard approaches that just focus on top-of-the-canopy information (e.g. canopy height models based on LiDAR data). 4. By enabling the mapping of forest structure and its temporal changes, we believe that LidarLDA will be of broad utility to the ecological research community.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Performance of Fire Danger Indices and Their Utility in Predicting Future Wildfire Danger Over the Conterminous United States

Abstract Predicting current and future wildfire frequency and size is central to wildfire control and management. Multiple fire danger indices (FDIs) that incorporate weather and fuel conditions have been developed and utilized to support wildfire predictions and risk assessment. However, the scale‐dependent performance of individual FDIs remains poorly understood, which leads to large uncertainty in the estimated fire sizes under climate change. Here, we calculate four commonly used FDIs over the conterminous United States using high‐resolution (4 km) climate and fuel data sets for the 1984–2019 period. The relationships of these four FDIs to the observed wildfire sizes show that higher values of FDIs correlate to larger total fire sizes; this correlation is more robust at larger spatial scales. Sensitivity analysis indicates that the daily minimum relative humidity and precipitation are the most important drivers of the annual mean fire danger. In the instances of extreme fire danger, wind speed becomes a critical factor and should be considered in the calculation of the FDI. To assess the impact of climate change on future fire size, we calculate the present‐day and end‐of‐century FDIs using the 12 km regional climate model simulations. The four FDIs generally predict consistent changes in future fire potential, suggesting an overall higher fire potential in conjunction with a prolonged wildfire season in future climate. Regionally, the four FDIs also reveal similar seasonal patterns as the enhancement arises mostly in spring and summer over the southwest US while in summer and fall over the northern and eastern US.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

An Integrated Supercritical System for Efficient Produced Water Treatment and Power Generation

The main goal of this project was to evaluate the feasibility of an integrated supercritical (SC) water desalination and power generation system for treatment of produced waters from CO 2 sequestration, oil production, and coal-bed methane recovery. This system may offer a transformative approach to generating power from coal or natural gas (NG) and purifying saline water or produced water with high total dissolved solids (TDS) in a zero-liquid discharge plant. The closed-loop steam cycle of conventional power plants was replaced with an open-loop steam cycle that heated the pretreated produced water above the SC point of water (374 °C and 221 bar) to precipitate and separate the salts dissolved in the water. After separation of the precipitated salt, the SC steam required further treatment to reduce the salt content from ~100 mg/L (ppm) to <1 ppm to make it suitable for use in turbines for power generation. A SC membrane distillation unit was used to polish the SC steam, which could be sent through a series of turbines for power generation, and the steam exiting the low-pressure turbine could be condensed by cooling water to produce pure water. Project tasks included a process simulation and a techno-economic evaluation of the integrated system; design and assembly of SC salt precipitation and membrane distillation systems; development and characterization of advanced carbon membranes for SC membrane distillation; and pretreatment, desalination, and purification of different produced water samples with salt concentrations of 30,000–200,000 ppm to a high-purity (<1 ppm) level. Process simulations were performed for 550 MW SC coal-fired or NG baseline cases and various scenarios for the proposed integrated SC system using produced water as the water source and coal or NG as the fuel source. Simulation results indicated that the net plant efficiency loss of the proposed SC cogeneration process would be in the range of <1% to ~4%, in which NG and lower TDS produced water cases would have higher efficiencies. The proposed process for coal-fired cases could provide all water needs for the power generation process and generate additional pure water for beneficial use. A techno-economic analysis was performed to estimate the cost of produced water treatment (dollars /kgal of treated water) by conventional treatment processes compared with the proposed cogeneration process. The cost estimation for the proposed cogeneration system included the cost of pretreatment, the cost of power loss to integrate the water desalination process into the power generation system, and the cost of plant modification or retrofitting. The cost of produced water treatment was calculated by assuming three different scenarios in which converting a baseline power plant to the proposed cogeneration plant would increase the cost of the boiler and feed water system by 10%, 50%, and 100%. Results indicated that the cost of produced water treatment, even with a 100% cost increase, was in the range of $8.6–11.6 dollars per kgal, which is about half of the treatment cost by conventional methods. The cost of produced water treatment by the proposed cogeneration system could be further reduced or a considerable income could be generated if the values of saltwater and freshwater products are considered. Overall, the techno-economic analysis results indicated that the proposed integrated SC system could potentially treat produced water at a cost significantly lower than the cost of produced water treatment by conventional technologies. To evaluate the feasibility of the proposed treatment system at a laboratory scale, a SC salt precipitation and membrane distillation system was designed and fabricated to treat a simulated brine or pretreated produced water by precipitating salts and further polishing the SC steam containing ~100 ppm salts to a high-purity steam. Through baseline tests with NaCl solutions, with concentrations ranging from 30,000 to 200,000 ppm, it was demonstrated that concentrated feed solutions could be treated by precipitating salt at SC conditions to a TDS level of 130 ppm. Produced water samples were collected from a potential CO 2 sequestration site, a coal-bed methane site, and an oilfield in Illinois. Representative samples were characterized for various water quality parameters, including pH; turbidity; conductivity; and concentrations of selected anions, cations, alkalinity, dissolved organic carbon, total suspended solids, TDS, and total petroleum hydrocarbons. The produced water samples were first treated by conventional pretreatment methods to remove residual oil, dissolved organic matter, and scale-forming species. Pretreatment methods included coagulation, sedimentation, filtration, activated carbon adsorption, and ion-exchange adsorption. Pretreated produced waters were treated at SC conditions in which salts were precipitated. Analysis of treated samples revealed that the concentration of Na (the main cation) in produced waters was reduced dramatically from 14,000–47,400 ppm in the feed to 21–80 ppm in treated waters. Concentrations of other main cations (Ca, Mg, Sr, K) also decreased significantly from initial values of ~1,000–22,000 ppm to ~1 ppm or less. However, a significant increase in the concentrations of Fe, Ni, Cu, and Co was observed, mainly caused by leaching of these elements from the system (vessels, filters, tubing), which is manufactured from alloys containing Fe, Ni, Cu, and Co. To polish the SC steam containing a salt content of ~100 ppm to a high-purity level of <1 ppm, a SC membrane distillation treatment using carbon membranes was employed. Different types of self-standing or supported carbon membranes were developed from graphite, graphene, carbon nanotubes, carbon nanofibers, and pyrolytic carbon. Screening tests revealed that only a limited number of developed carbon membranes were suitable for the purification of steam at SC conditions. Membranes that were either fragile and lacked mechanical strength or had large pores and showed limited salt rejection (<20%) were found to be unsuitable for the purification of SC steam. Promising carbon membranes that were successfully tested for purifying SC steam included two graphite membranes (i.e., AF-5, a porous graphite material, and FGS, a flexible graphite sheet) and a carbon nanotube membrane grown on a Hastelloy substrate and then further modified using a proprietary method (i.e., membrane C). The AF-5 membrane exhibited a stable water flux of ~50 kg/m 2 ∙h and ~40% salt rejection. The FGS membrane had a high salt rejection of 95%–98% but a lower water flux of ~15 kg/m 2 ∙h. Membrane C showed an extremely high flux of 200-800 kg/m 2 ∙h, which is one order of magnitude higher than the water flux of conventional membranes. Membrane C also exhibited 87%–93% salt rejection. Overall, a two-stage or multistage polishing treatment by these membranes could lower the salt content of the SC steam from initial values of ~100–200 ppm to the steam quality of <1 ppm or to parts per billion levels required for the power cycle.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Industry Level Feasibility of LiDAR Data into Fire Modeling Using Fire Risk Investigation in 3D (FRI3D)

Many evaluation, assessment, and modeling tasks at nuclear power plants require spatial information 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 support groups such as security. 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 presents Idaho National Lab's work with Environmental Intellect (Ei) covering two main efforts. First, to reduce the effort of "tagging" data in large 3D models. By using both existing plant database information, and artificial intelligence (AI) to find and read equipment labels. This research explores the ability of to provide a simple way for the user to tag items and verify plant data, capturing both the speed of AI and human verification. The second part of the work is the development of an interface for importing pieces needed for Modeling & Simulation. Analysis work such as that for fire, flood, or physical security all require spatial or 3D models in various levels of detail. This interface will allow for the retrieval of item location or boundaries, enabling the auto generation of models for varying tools. The application program interface (API) of the fire risk investigation in 3D (FRI3D) was used to test feasibility of exporting the LiDAR tagged spatial information. Outcomes from this work provide preliminary data to determine if the tools and methods could provide substantial industry benefit if fully matured.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Validation Assessment of Turbulent Reacting Flow Model Using The Area-Validation Metric on Medium-Scale Methanol Pool Fire Results

Accident analysis and ensuring power plant safety are pivotal in the nuclear energy sector. Significant strides have been achieved over the past few decades regarding fire protection and safety, primarily centered on design and regulatory compliance. Yet, after the Fukushima accident a decade ago, the imperative to enhance measures against fire, internal flooding, and power loss has intensified. Hence, a comprehensive, multilayered protection strategy against severe accidents is needed. Consequently, gaining a deeper insight into pool fires and their behavior through extensive validated data can greatly aid in improving these measures using advanced validation techniques. A model validation study was performed at Sandia National Laboratories in which a 30-cm diameter methanol pool fire was modeled using the SIERRA/Fuego turbulent reacting flow code. This validation study used a standard validation experiment to compare model results against, and conclusions have been published. The fire was modeled with a Large Eddy Simulation (LES) turbulence model with subgrid turbulent kinetic energy closure. Combustion was modeled using a strained laminar flamelet library approach. Radiative heat transfer was accounted for with a model utilizing the gray-gas approximation. In the present study, additional validation analysis is performed using the area validation metric (AVM). These activities are done on multiple datasets involving different variables and temporal/spatial ranges and intervals. In conclusion, the results provide insight into the use of the area validation metric on such temporally varying datasets and the importance of physics-aware use of the metric for proper analysis.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2023

Soil carbon storage capacity of drylands under altered fire regimes

The determinants of fire-driven changes in soil organic carbon (SOC) across broad environmental gradients remains unclear, especially in global drylands. Here we combined datasets and field sampling of fire-manipulation experiments to evaluate where and why fire changes SOC and compared our statistical model to simulations from ecosystem models. Drier ecosystems experienced larger relative changes in SOC than humid ecosystems—in some cases exceeding losses from plant biomass pools—primarily explained by high fire-driven declines in tree biomass inputs in dry ecosystems. Many ecosystem models underestimated the SOC changes in drier ecosystems. Upscaling our statistical model predicted that soils in savannah–grassland regions may have gained 0.64 PgC due to net-declines in burned area over the past approximately two decades. Consequently, ongoing declines in fire frequencies have probably created an extensive carbon sink in the soils of global drylands that may have been underestimated by ecosystem models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A subcellular biochemical model for T6SS dynamics reveals winning competitive strategies

Abstract The type VI secretion system (T6SS) is a broadly distributed interbacterial weapon that can be used to eliminate competing bacterial populations. Although unarmed target populations are typically used to study T6SS function in vitro, bacteria most likely encounter other T6SS-armed competitors in nature. However, the connection between subcellular details of the T6SS and the outcomes of such mutually lethal battles is not well understood. Here, we incorporate biological data derived from natural competitors of Vibrio fischeri light organ symbionts to build a biochemical model for T6SS at the single-cell level, which we then integrate into an agent-based model (ABM). Using the ABM, we isolate and experiment with strain-specific physiological differences between competitors in ways not possible with biological samples to identify winning strategies for T6SS-armed populations. Through in vitro experiments, we discover that strain-specific differences exist in T6SS activation speed. ABM simulations corroborate that faster activation is dominant in determining survival during competition. Once competitors are fully activated, the energy required for T6SS creates a tipping point where increased weapon building and firing becomes too costly to be advantageous. Through ABM simulations, we identify the threshold where this transition occurs in the T6SS parameter space. We also find that competitive outcomes depend on the geometry of the battlefield: unarmed target cells survive at the edges of a range expansion where unlimited territory can be claimed. Alternatively, competitions within a confined space, much like the light organ crypts where natural V. fischeri compete, result in the rapid elimination of the unarmed population.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Temperature-Dependence of Corrosion of Ni-Based Superalloys in Hot CO 2 -Rich Gases Containing SO 2 Impurities

Future power plants will require Ni-based superalloys resistant to high-temperature corrosion in CO 2 -rich environments containing impurities. In this work, several commercially available Ni-based alloys (617, 230, 625, 263, 740H) were exposed at 600°C, 650°C, 750°C and 1 atm to 95% CO 2 , 4% H 2 O, 1% O 2 without/with 0.1% SO 2 to simulate compositions expected in a direct-fired supercritical CO 2 power cycle. The results indicate no effect of SO 2 at 750°C, a small negative effect at 650°C, and a large negative effect at 600°C. Alloys exposed at the higher temperatures (650–750°C) formed thin Cr-rich oxide scales, whereas the lowest temperature (600°C) resulted in thicker scales consisting of non-protective oxides and sulfates. Thermodynamic analysis indicates this increased corrosion is associated with a transition in the stable compounds in contact with the gas. Understanding the factors that affect this transition will aid in the selection or design of alloys for future CO 2 -based power systems.

36 MATERIALS SCIENCE↗