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At least 811 records · Page 45

Effects of Repeated Fire on Florida Oak-Saw Palmetto Scrub

Background: The dominant species of Florida oak-saw palmetto scrub sprout after burning from belowground rhizomes or fire-resistant aboveground buds with rapid reestablishment of cover. Responses to single fires are well documented; however, responses to repeated fires may differ. Fire return intervals, differences among sites, and species may influence responses. We used transect data from four sites on Kennedy Space Center/Merritt Island National Wildlife Refuge to test whether growth differed through repeated fires. Two sites burned five times in 36 years, one site burned five times in 25 years, and one burned four times in 18 years. We used linear mixed models that account for repeated measures to determine if the number of fires affected height, total cover ≥ 0.5 m and < 0.5 m, bare ground, and cover of the dominant oak (Quercus) ≥ 0.5 m and of saw palmetto (Serenoa repens) ≥ 0.5 m. We compared community composition through repeated fires using nonmetric multidimensional scaling ordination. Results: Height, total cover ≥ 0.5 m, and cover of the dominant oak ≥ 0.5 m and of saw palmetto ≥ 0.5 m increased with time since burn; total cover < 0.5 m and bare ground decreased. A quadratic term in the growth model was significant except for total cover < 0.5 m. There were site differences for all variables except bare ground. The number of fires decreased height, total cover ≥ 0.5 m, and cover of the dominant oak ≥ 0.5 and increased total cover < 0.5 m and bare ground but had no effect on cover of Serenoa repens ≥ 0.5 m. Community changes after repeated fires were similar in nonmetric multidimensional ordinations with time since burn correlated to the first or second axis. Conclusions: Scrub recovered from repeated fires at a range of intervals and seasons, but short return intervals reduced growth with responses differing among species.

Florida↗

Overview of the NASA Earth Action Strategies Wildland Fire Initiative

As part of NASA’s new Earth Action strategy, the Wildland Fire initiative was established, which includes both the NASA Wildland Fire Program (WFP) and the FireSense project. NASA has over 50 years of experience generating data and technology to enhance fire science and operational management. The WFP’s mission is threefold: 1) assemble communities of practice through collaborative efforts with government, academia, and the private sector; 2) co-develop knowledge and applications with relevant partners and stakeholders in the wildfire community; and 3) improve wildland fire management through the transitioning of NASA data, technology, tools, and science to stakeholder organizations. The WFP is focusing on supporting proactive fire management, including situational awareness, preparedness, and risk mitigation. This will be accomplished through selected projects that identify management challenges, relevant to partners and end users, and the NASA data that will be utilized to deliver innovative solutions to enhance the management of wildland fires. Examples include: i) investigation of evaporative stress from OpenET to help predict the risk of wildfire occurrence in watersheds; ii) incorporation of space based LiDAR for the generation of 3-dimensional forest fuel metrics, used to improve wildfire risk and behavior models; iii) integration of global, multi-platform geostationary active-fire data in near-real-time into NASA’s Fire Information for Resource Management System (FIRMS); and iv) identification of post-fire ecohydrological conditions using thermal, multispectral, synthetic aperture radar (SAR), and hyperspectral remotely-sensed data to improve flood hazard forecast models. The FireSense project is a US-focused 5-year project that will focus on delivering NASA’s unique Earth science and technological capabilities to operational agencies, striving towards enhancing fire fighting and air quality management. The project will include airborne campaigns and new technology that will likely have global implications. Initial stakeholder engagement led FireSense to focus on four use-cases focused on the characterization and measurement of: (i) pre-fire fuels conditions, (ii) active fire-dynamics; (iii) post-fire impact and threats; and iv) air quality impacts and forecasting, each-developed with identified stakeholders.

Wildland Fire program↗

Reusable Solid Rocket Motor Nozzle Joint-4 Thermal Analysis

This study provides for development and test verification of a thermal model used for prediction of joint heating environments, structural temperatures and seal erosions in the Space Shuttle Reusable Solid Rocket Motor (RSRM) Nozzle Joint-4. The heating environments are a result of rapid pressurization of the joint free volume assuming a leak path has occurred in the filler material used for assembly gap close out. Combustion gases flow along the leak path from nozzle environment to joint O-ring gland resulting in local heating to the metal housing and erosion of seal materials. Analysis of this condition was based on usage of the NASA Joint Pressurization Routine (JPR) for environment determination and the Systems Improved Numerical Differencing Analyzer (SINDA) for structural temperature prediction. Model generated temperatures, pressures and seal erosions are compared to hot fire test data for several different leak path situations. Investigated in the hot fire test program were nozzle joint-4 O-ring erosion sensitivities to leak path width in both open and confined joint geometries. Model predictions were in generally good agreement with the test data for the confined leak path cases. Worst case flight predictions are provided using the test-calibrated model. Analysis issues are discussed based on model calibration procedures.

Clayton, J. Louie↗

Firesense: Supporting Operational Partners Through Co-Development

Fire is a natural disturbance and fundamental to many ecosystems, but, across the United States and many areas globally, fires have become more common, larger and more likely to occur at the same time. This has the potential to challenge resource allocation and response and requires coordinated integration of technology and tools at the spatial and temporal scales required by practitioners who make wildland fire management decisions. In the US wildfire is currently managed across state, federal, and tribal agencies who leverage various datasets to guide management decisions. FireSense, a NASA Science Mission Directorate project, aims to develop and deliver trailblazing technology and tools for use before, during, and after wildland fires by working together with land managers and practitioners. FireSense is focused on turning information into solutions by expanding partnerships and collaborations with operational agencies to inform and deliver data and technology to support decisions for wildland fire management. Through implementation across the US and with campaign activities in a variety of landscapes, coordinated research and development work will build upon adaptive and use-inspired approaches that can be put into operation. By leveraging and complementing partner activities through coordinated investment, we support a more comprehensive and cohesive response that can advance fire science to better understand fire behavior and effects through integrated measurement, monitoring and modeling. We present updates from in-progress technology development and field campaigns within the US which include sampling and application across scales with information from multiple sensors collocated with field measurements and highlighting the importance of cross-scale observations during the fire lifecycle. Coordinated investment in new science and technology for the complete fire lifecycle supports a comprehensive and cohesive fire response that help to overcome barriers and anticipate and manage the new reality of extreme fires in a warming world.

Jacquelyn Shuman↗

Data and scripts associated with the manuscript evaluating the hydrologic responses of the Pacific Northwest watersheds to wildfires (v2)

This data package is associated with the publication “Evaluating Post-fire Watershed Response to Varying Burn Severity and Precipitation Regimes Using Fully-distributed and Integrated Hydrologic Models” submitted to Journal of Hydrology (Li et al. 2025). In this study, we employed the Advanced Terrestrial Simulator (ATS), an integrated watershed model that couples surface flow, subsurface flow, and canopy biophysical processes, to investigate post-fire hydrologic responses in a few selected watersheds with varying burn severity.The data package contains the required input data (meteorological forcing, Leaf Area Index, wildfire burn severities, etc.) to run the model, configuration files, the Jupyter notebooks in Python to pre-process and post-process data, the figures in the manuscript, and the modeling output files. The variables include watershed-averaged evapotranspiration, watershed-averaged surface/subsurface/canopy water content, and river discharge at watershed outlet.The data package contains a file-level metadata that lists and describes all the files contained in the data package (ATS_flmd.csv), a data dictionary file that defines columns headers across all csv files contained in the data package (ATS_dd.csv), a data package level readme file (the current file), and four zipped folders.The ‘data’ folder provides data needed to run the model in .h5, .i2s, .xyz, .shp, and .exo formats. The sub-folders are for each data types. The ‘model’ folder provides input files (.xml format) and essential model outputs. Each sub-folder provides the files from each simulated watershed. The ‘notebooks’ folder provides the Jupyter notebooks (.ipynb format) for pre- and post- processing model files, and for producing the figures in the manuscript. The ‘figures’ folder provides the figures associated with manuscript in .pdf and .png formats.The ‘model’ folder and the ‘data’ folder have been split into 5GB-large pieces using the Linux command ‘split -b 5120m model.zip model.zip.’ and ‘split -b 5120m data.zip data.zip.’, respectively. They can be merged back using the Linux command ‘cat model.zip.* > model.zip’ and ‘cat data.zip.* > data.zip’, respectively.

54 ENVIRONMENTAL SCIENCES↗

Large-scale optimal control of interconnected natural gas and electrical transmission systems

We present a detailed optimal control model that captures spatiotemporal interactions between gas and electric transmission networks. We use the model to study flexibility and economic opportunities provided by coordination. A large-scale case study in the Illinois system reveals that coordination can enable the delivery of significantly larger amounts of natural gas to the power grid. In particular, under a coordinated setting, gas-fired generators act as distributed demand response resources that can be controlled by the gas pipeline operator. This enables more efficient control of pressures and flows in space and time and overcomes delivery bottlenecks. We demonstrate that the additional flexibility not only can benefit the gas operator but can also lead to more efficient power grid operations and results in increased revenue for gas-fired power plants. We also use the optimal control model to analyze computational issues arising in these complex models. We demonstrate that the interconnected Illinois system with full physical resolution gives rise to a highly nonlinear optimal control problem with 4400 differential and algebraic equations and 1040 controls that can be solved with a state-of-the-art sparse optimization solver. (C) 2016 Elsevier Ltd. All rights reserved.

Chiang, Nai-Yuan↗

Hybrid Powered Command Trailers Cost-Benefit Analysis Tool: User Guide and Examples

U.S. Forest Service (USFS) wildfire base camps use portable power for electrical needs, including yurts and trailers from which logistics staff work during the incident. These yurts and trailers are conventionally powered by portable diesel generators. Hybrid portable power systems consisting of a combination of solar photovoltaics (PV), battery energy storage systems (BESS), and/or backup diesel generators have been used in recent years and were piloted by the National Technology and Development Program (NTDP) on incidents in fall 2024 as part of NTDP's Portable Power Project. As part of that project, this work included the development of two Excel-based tools and two reports explaining the tools. The first tool, the Incident Energy Systems Model, is an Excel-based tool that models the power output of hybrid portable power systems powering yurts and/or trailers at fire camps over a typical day. The associated report (published separately) outlines a user guide for the model and walks through two scenarios. The two scenarios are 1) trailers powered by rooftop solar PV, batteries, and a back-up diesel generator, and 2) trailers powered by ground mount solar PV, batteries, and a back-up diesel generator. The second tool is a high-level cost-benefit analysis of the same two types of portable power systems, and is location independent.

14 SOLAR ENERGY↗

Half-ice, half-fire-driven ultranarrow phase crossover in one-dimensional decorated 𝑞-state Potts ferrimagnets: An AI-co-led exploration

OpenAI’s reasoning model o3-mini-high was used to carry out an exact analytic study of one-dimensional ferrimagnetic site- and bond-decorated 𝑞-state Potts models. We demonstrate that the finite-temperature ultranarrow phase crossover (UNPC), driven by a hidden “half-ice, half-fire” state recently discovered in the 𝑞=2 case (Ising model), persists for 𝑞>2. Moreover, we identify unique features for 𝑞>2, including the dome structure in the field-temperature phase diagram, and for large 𝑞 a secondary high-temperature UNPC to the fully disordered paramagnetic state. As the UNPC quickly approaches a genuine transition by enhancing 𝐽, the interaction between the backbone spins, two distinct behaviors emerge: In the site-decorated Potts model, 𝑇 0 is independent of 𝐽 and thus remains unchanged (Type-I UNPC), and in the bond-decorated Potts model with 𝑞>2, 𝑇 0 depends on 𝐽 and quickly shifts toward a finite temperature as 𝐽 increases (Type-II UNPC). These results establish a versatile framework for engineering controlled fast state-flipping switches in low-dimensional systems. Our nine-dan artificial intelligence (AI)-contribution framework assigns AI the meritorious status of AI-co-led discovery in this work.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Low-Carbon District Heating: Performance Modeling of Hybrid Solar, Heat Pump, and Thermal Storage Systems for District Thermal Energy in the United States

District heating requires thermal energy in the temperature range of 40 degrees C - 120 degrees C. Typically, the thermal energy input for these systems has largely been met through fossil energy. However, the temperature range is low enough that it presents an opportunity for low-carbon technologies such as solar thermal and electrified thermal generators like heat pumps to decarbonize the heat generation. In this paper, a heat pump model was applied to estimate the performance and economics of a real-world low-carbon district heating substation. This system is comprised of a flat plate solar collector field paired with a mechanical vapor compression heat pump and hot water thermal storage, augmented by gas-fired boilers. Plant data was used to tune the model and estimate the system's benefits in terms of both standard financial metrics (IRR and payback), and environmental metrics, including avoided CO2 emissions. The model is subsequently employed to estimate the technical and economic potential of solar + heat pump + ther-mal storage hybrid systems as retrofits for district heating systems in eight US Markets.

district heating↗

StratoFIRE: Modeling Wildfire Smoke in the Stratosphere

The most extreme manifestation of a fire–weather interaction is the formation of pyrocumulonimbus (pyroCb) thunderstorms, triggered by super-heated updrafts, which can eject smoke at altitudes exceeding 20 Km. In this study, we investigated climate-related impacts from the most intensive pyroCb-triggered injection of smoke in the stratosphere: the Australian New Year wildfires in 2019/2020. We first provide a general overview of the vision and objectives of the StratoFIRE project. With the aid of the global chemistry-climate model EMAC, we then simulate radiative and chemical perturbations in the stratosphere in relation to 0.9 Tg smoke in the stratosphere assuming different injection heights, from 13 to 16 Km. The simulation of stratospheric optical depth perturbations were found to be sensitive to the assumed injection height, with a maximum height at 16 Km showing the best agreement with the GLOSSAC and SAGE-ISS aerosol extinction observations.

PyroCb↗

On how fast ions enhance the regulation of drift wave turbulence by zonal flows

Abstract This paper presents a mechanism for enhanced regulation of drift wave turbulence by zonal flows in the presence of a fast ion population. It demonstrates that dilution effects due to the energetic particles (EPs) have a far-reaching impact on all aspects of the nonlinear dynamics. The modulational growth of zonal flow shear and the corresponding evolution of drift wave energy are calculated with dilution effects. The coupled zonal flow growth and drift wave energy equations are reduced to a predator–prey model. This is solved for the fixed points, which represents the various states of the system. Results display a strong dependence on dilution, which leads to greatly reduced levels of saturated turbulence and transport. Implications for the FIRE mode plasma of KSTAR are discussed in detail. This model is perhaps the simplest dynamical one which captures the beneficial effects of EPs on confinement.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

TPSAS-NF1676L-11382-DND

Long-range transport of ozone precursor species and carbonaceous aerosols emitted by wildfires may affect the atmospheric composition and regional climate far away from the location of the fires. Major outbreaks of fires occurred in 3 areas of Asia, Kazakhstan, Siberia, and Thailand, during the spring of 2008. Satellite and aircraft-based observations and trajectory studies have identified the transit of the plumes from these fires across the Pacific. We have conducted simulations of the effects of these fires on the atmospheric composition using the Real-time Air Quality Modeling System (RAQMS). RAQMS is a global scale meteorological and chemical modeling system with unified (stratosphere/troposphere) chemistry module. Model results, for example, indicate that increases of 10 ppbv in upper tropospheric ozone at 180W longitude and northern mid-latitudes in April, 2008 could be attributed to these fires. Large increases in aerosol optical depth due to carbonaceous aerosols are also seen nearer the fire location. Both tropospheric ozone and carbonaceous aerosols influence the atmospheric energy balance and climate. We use an off-line radiative transfer model along with the RAQMS chemical and aerosol analyses to calculate the direct radiative forcing during April, 2008, due to Asian wildfire emissions. Arctic indirect radiative forcing due to these emissions are evaluated using RAQMS aerosol extinction analyses in conjunction with MODIS retrievals of cloud liquid water and effective radius. We will discuss the radiative forcing results and the relative influences of the different fire events.

Murali Natarajan↗

Climatic Effects of Regional Nuclear War

We use a modern climate model and new estimates of smoke generated by fires in contemporary cities to calculate the response of the climate system to a regional nuclear war between emerging third world nuclear powers using 100 Hiroshima-size bombs (less than 0.03% of the explosive yield of the current global nuclear arsenal) on cities in the subtropics. We find significant cooling and reductions of precipitation lasting years, which would impact the global food supply. The climate changes are large and longlasting because the fuel loadings in modern cities are quite high and the subtropical solar insolation heats the resulting smoke cloud and lofts it into the high stratosphere, where removal mechanisms are slow. While the climate changes are less dramatic than found in previous "nuclear winter" simulations of a massive nuclear exchange between the superpowers, because less smoke is emitted, the changes seem to be more persistent because of improvements in representing aerosol processes and microphysical/dynamical interactions, including radiative heating effects, in newer global climate system models. The assumptions and calculations that go into these conclusions will be described.

Oman, Luke D.↗

Thermal Analysis and Testing of Fastrac Gas Generator Design

The Fastrac Engine is being developed by the Marshall Space Flight Center (MSFC) to help meet the goal of substantially reducing the cost of access to space. This engine relies on a simple gas-generator cycle, which burns a small amount of RP-1 and oxygen to provide gas to drive the turbine and then exhausts the spent fuel. The Fastrac program envisions a combination of analysis, design and hot-fire evaluation testing. This paper provides the supporting thermal analysis of the gas generator design. In order to ensure that the design objectives were met, the evaluation tests have started on a component level and a total of 15 tests of different durations were completed to date at MSFC. The correlated thermal model results will also be compared against hot-fire thermocouple data gathered.

Nguyen, H.↗

Combustion Model of Supersonic Rocket Exhausts in an Entrained Flow Enclosure

This paper describes the Computational Fluid Dynamics (CFD) model developed to simulate the supersonic rocket exhaust in an entrained flow cylinder. The model can be used to study the plume-induced environment due to static firing tests of the Taurus-II launch vehicle. The finite-rate chemistry is used to model the combustion process involving rocket propellant (RP-1) and liquid oxidizer (LOX). A similar chemical reacting model is also used to simulate the mixing of rocket plume and ambient air. The model provides detailed information on the gas concentration and other flow parameters within the enclosed region, thus allowing different operating scenarios to be examined in an efficient manner. It is shown that the real gas influence is significant and yields better agreement with the theory.

Vu, Bruce T.↗

Simulating Pyrocumulonimbus Clouds Using a Multiscale Wildfire Simulation Framework

Pyrocumulonimbus (pyroCb) clouds, driven by extreme fires under favorable meteorological conditions, can inject smoke into the stratosphere at magnitudes comparable to those of moderate volcanic eruptions, potentially altering the global radiative balance and atmospheric composition. However, simulating pyroCb is particularly challenging in Earth system models. Using the Energy Exascale Earth System Model (E3SM), we developed a novel global multiscale framework to model pyroCb events in California, which includes a high‐resolution fire radiative power time series, a one‐dimensional plume‐rise parameterization, a fire‐induced vertical water vapor transport scheme, and a surface wildfire sensible heat flux representation. Our simulation successfully reproduces many pyroCb features, including cloud height, spatiotemporal evolution, and convective intensity in comparison with satellite and ground‐based observations. Sensitivity experiments show that realistic pyroCb simulation depends on vertical water vapor transport. These advances provide a basis for future exploration of pyroCb impacts at regional and global scales within climate models.

E3SM↗

DETECTING FIRE WITH MACHINE LEARNING-ENABLED VISUAL MONITORING FOR NUCLEAR POWER PLANT ENVIRONMENTS

Nuclear power plants are experiencing significant cost challenges to remain competitive with other energy-generation utilities. Unlike other industries, the cost of operation and maintenance activities is mostly attributed to workforce costs. To mitigate this, nuclear power plant stakeholders are increasingly interested in the development and deployment of machine learning methods to potentially automate or augment manually intensive tasks to reduce costs, especially for monitoring activities. One monitoring function that is visually demanding and that can occur frequently to meet the requirements of a fire protection program is visually monitoring an area for fire occurrence. Currently, fire watch activities consist of a worker physically stationed at a given location with the sole responsibility of observing a given area to ensure a fire is detected and mitigated promptly. This effort focused on the development and evaluation of a suitable deep convolutional neural network to classify individual video frames at a sub-second frequency for the occurrence of “fire” and “no fire” in varying industrial environments similar to nuclear power plants. It is believed that a trained neural network model could be integrated with existing facility video surveillance camera feeds to generate alerts when fire inferences occur in individual frames captured at sub-second temporal resolutions. Extensive effort was dedicated to identifying and curating suitable imagery training data representing varying environments and scene settings with and without flame features to maximize generalization in nuclear power plant environments. The data collection effort resulted in the aggregation of a large, labeled image library exceeding 12,000 images to support model training for diverse industrial environments. A deep neural network model incorporating parallel multi-scale capabilities was developed and trained to support accurate image-based detection of flame incidents of varying sizes and spectral feature properties within heterogeneous scenes. Analysis results show that the trained model can achieve high inference accuracy despite heterogeneous scene environments and components. Testing accuracy exceeded 95.0 percent with very low false positive and false negative inferences.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗