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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Severe Convective Storms in Limited Instability Organized by Pattern and Distribution

Abstract Severe convection occurring in high-shear, low-CAPE (HSLC) environments is a common cool-season threat in the southeastern United States. Previous studies of HSLC convection document the increased operational challenges that these environments present compared to their high-CAPE counterparts, corresponding to higher false-alarm ratios and lower probability of detection for severe watches and warnings. These environments can exhibit rapid destabilization in the hours prior to convection, sometimes associated with the release of potential instability. Here, we use self-organizing maps (SOMs) to objectively identify environmental patterns accompanying HSLC cool-season severe events and associate them with variations in severe weather frequency and distribution. Large-scale patterns exhibit modest variation within the HSLC subclass, featuring strong surface cyclones accompanied by vigorous upper-tropospheric troughs and northward-extending regions of instability, consistent with prior studies. In most patterns, severe weather occurs immediately ahead of a cold front. Other convective ingredients, such as lower-tropospheric vertical wind shear, near-surface equivalent potential temperature (θ e ) advection, and the release of potential instability, varied more significantly across patterns. No single variable used to train SOMs consistently demonstrated differences in the distribution of severe weather occurrence across patterns. Comparison of SOMs based on upper and lower quartiles of severe occurrence demonstrated that the release of potential instability was most consistently associated with higher-impact events in comparison to other convective ingredients. Overall, we find that previously developed HSLC composite parameters reasonably identify high-impact HSLC events. Significance Statement Even when atmospheric instability is not optimal for severe convective storms, in some situations they can still occur, presenting increased challenges to forecasters. These marginal environments may occur at night or during the cool season, when people are less attuned to severe weather threats. Here, we use a sorting algorithm to classify different weather patterns accompanying such storms, and we distinguish which specific patterns and weather system features are most strongly associated with severe storms. Our goals are to increase situational awareness for forecasters and to improve understanding of the processes leading to severe convection in marginal environments.

Meteorology & Atmospheric Sciences↗
DOE OSTI2023

Severe Temperature Impact Study on Ferrite Electromagnetic Shielding for Wireless Electric Vehicle Charging

Wireless charging of an electric vehicle (EV) is an emerging technology that enables noncontact charging, which has advantages in terms of convenience and flexibility. However, the embedded charging pads under and on the ground expose the charging coils, ferrite shielding, and related components to a potentially severe external environment. To study the electromagnetic shielding performance under such extreme temperature conditions, ferrite shielding material's permeability characteristics are tested under temperatures as low as -50°C to as high as 240°C. Referring to the official recorded lowest and highest temperature of the United States, in this paper, it is assumed that the operation temperature ranges from -50°C to 57°C as the coldest winter and hottest summer environment for WPT application. Electromagnetic performance, shielding, and associated stray magnetic emissions are simulated by using three-dimensional (3D) transient simulations to study the impact of low and high temperature on electromagnetic shielding performance. Based on ferrite testing data, from -50°C low temperature to 57°C high temperature, the ferrite's relative permeability ranges from 2550 to 3727. The simulation study indicates that there won't be significant impact on the EM shielding performance for WPT operated under those severe environment temperature conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Restricting electron flow at cytochrome b6f when downstream electron acceptors are severely limited

Abstract Photosynthetic organisms frequently experience abiotic stress that restricts their growth and development. Under such circumstances, most absorbed solar energy cannot be used for CO2 fixation and can cause the photoproduction of reactive oxygen species (ROS) that can damage the photosynthetic reaction centers of PSI and PSII, resulting in a decline in primary productivity. This work describes a biological “switch” in the green alga Chlamydomonas reinhardtii that reversibly restricts photosynthetic electron transport (PET) at the cytochrome b6f (Cyt b6f) complex when the capacity for accepting electrons downstream of PSI is severely limited. We specifically show this restriction in STARCHLESS6 (sta6) mutant cells, which cannot synthesize starch when they are limited for nitrogen (growth inhibition) and subjected to a dark-to-light transition. This restriction represents a form of photosynthetic control that causes diminished electron flow to PSI and thereby prevents PSI photodamage but does not appear to rely on a ΔpH. Furthermore, when electron flow is restricted, the plastid alternative oxidase (PTOX) becomes active, functioning as an electron valve that dissipates some excitation energy absorbed by PSII and allows the formation of a proton motive force (PMF) that would drive some ATP production (potentially sustaining PSII repair and nonphotochemical quenching [NPQ]). The restriction at the Cyt b6f complex can be gradually relieved with continued illumination. This study provides insights into how PET responds to a marked reduction in availability of downstream electron acceptors and the protective mechanisms involved.

Plant Sciences↗
DOE OSTI2023

Understanding the Computing and Analysis Needs for Resiliency of Power Systems from Severe Weather Impacts

As the frequency and intensity of severe weather has increased, its effect on the electric grid has manifested in the form of significantly more and larger outages in the United States. This has become especially true for regions that were previously isolated from weather extremes. In this paper, we analyze the weather impacts on the electric power grid across a variety of weather conditions, draw correlations, and provide practical insights into the operational state of these systems. High resolution computational modeling of specific meteorological variables, computational approaches to solving power system models under these conditions, and the types of resiliency needs are highlighted as goal-oriented computing approaches are being built to address grid resiliency needs. An example analysis correlating outages to 1km day-ahead weather from two historical winter storms, calculated on a large cluster using a combination of interpolated and extrapolated inputs from multiple instrumented sites to workflows that produce primary meteorological outputs, is shown as initial proof of concept.

analysis↗
DOE OSTI2024

The influence of burn severity on dissolved organic carbon concentrations across a stream network differs based on seasonal wetness conditions

Large, high-severity wildfires in many regions across the globe have increased concerns about their impacts on carbon cycling in watersheds. Altered sources of carbon and changes in catchment hydrology after wildfire can lead to shifts in dissolved organic carbon (DOC) concentrations in streams, which can have negative impacts on aquatic ecosystem health and downstream drinking-water treatment. Despite its importance, post-fire DOC responses remain relatively unconstrained in the literature, and we lack critical knowledge of how burn severity, landscape elements, and climate interact to affect DOC concentrations. To improve our understanding of the impact of burn severity on DOC concentrations, we measured DOC at 129 sites across a stream network extending upstream, within, and downstream of a large, high-severity wildfire in Oregon, USA. We collected samples across the study sub-basin during four distinct seasonal wetness conditions. We used our high-spatial-resolution data to develop spatial stream network (SSN) models to predict DOC across the stream network and to improve our understanding of the controls on DOC concentrations. Spatially, we found no obvious wildfire signal – instead, we observed a pattern of increasing DOC concentrations from the high-elevation headwaters to the sub-basin outlet, while the mainstem maintained consistently low DOC concentrations. This suggests that effects from large wildfires may be “averaged” out at higher stream orders and larger spatial scales. When we grouped DOC concentrations by burn severity group, we observed a significant decrease in the variability of DOC concentrations in the moderate and high burn severity sub-catchments. However, our SSN models were able to predict decreases in DOC concentrations with increases in burn severity across the stream network. Decreases in DOC concentrations were also highly variable across seasonal wetness conditions, with the greatest (–1.40 to –1.64 mg L –1 ) decrease occurring in the high-severity group during the wetting season. Additionally, our models indicated that in all seasons, baseflow index was more influential in predicting DOC concentrations than burn severity was, indicating that groundwater discharge can obscure the impacts of wildfire in a stream network. Overall, our results suggested that landscape characteristics can regulate the DOC response to wildfire. Moreover, our results also indicated that the seasonal timing of sampling can influence the observed response of DOC concentrations to wildfire.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Patchy burn severity explains heterogeneous soil viral and prokaryotic responses to fire in a mixed conifer forest

ABSTRACT Effects of fire on soil viruses and virus–host dynamics are largely unexplored, despite known microbial contributions to biogeochemical processes and ecosystem recovery. Here, we assessed how viral and prokaryotic communities responded to a prescribed burn in a mixed conifer forest. We sequenced 91 viral-size fraction metagenomes (viromes) and 115 16S rRNA gene amplicon libraries from 120 samples: four samples at five timepoints (two before fire and three after fire) at six sites (four treatment, two control). We hypothesized that compositional differences would be most significant between burned and unburned soils, but instead, plot location best distinguished viral communities, more than treatment (burned or not), depth (0–3 or 3–6 cm), or timepoint. For both viruses and prokaryotes, some burned communities resembled unburned controls, while others were significantly different, revealing heterogeneous responses to fire. These patterns were explained by burn severity, here defined by soil chemistry. Viral but not prokaryotic richness decreased significantly with burn severity, and low viromic DNA yields indicated substantial loss of viral biomass at higher severity. The relative abundances of Firmicutes, Actinobacteriota, and the viruses predicted to infect them increased significantly with burn severity, suggesting survival and viral infection of these fire-responsive and potentially spore-forming taxa. The degree of burn severity experienced by each patch of soil, rather than burn status alone, differed over mere meters in the same fire. Therefore, our analyses highlight the importance of high-resolution, paired biogeochemical data to explain soil community responses to fire. IMPORTANCE The impact of fire on the soil microbiome, particularly on understudied soil viral communities, warrants investigation, given known microbial contributions to biogeochemical processes and ecosystem recovery. Here, we collected 120 soil samples before and after a prescribed burn in a mixed conifer forest to assess the impacts of this disturbance on soil viral and prokaryotic communities. We show that simple categorical comparisons of burned and unburned areas were insufficient to reveal the underlying community response patterns. The patchy nature of the fire (indicated by soil chemistry data) led to significant changes in viral and prokaryotic community composition in areas of high burn severity, while communities that experienced lower burn severity were indistinguishable from those in unburned controls. Our results highlight the importance of considering highly resolved burn severity and biogeochemical measurements, even in nearby soils after the same fire, in order to understand soil microbial responses to prescribed burns.

Microbiology↗
DOE OSTI2024

Molecular shifts in dissolved organic matter along a burn severity continuum for common land cover types in the Pacific Northwest, USA

Increasing wildfire severity is of growing concern in the western United States, with consequences for the production, composition, and mobilization of dissolved organic matter (DOM) from terrestrial to aquatic systems. Our current understanding of wildfire impacted DOM (often termed pyrogenic DOM) composition is largely built from temperature-based studies that can be difficult to extrapolate to field conditions, which are often defined by ‘burn severity’, or the post-wildfire impact observed at a site. Thus, burn severity can encapsulate a broader range of fire and environmental conditions not exclusive to temperature. Biogeochemical studies that describe DOM along burn severity continuums remain limited but are needed to better link DOM composition with field conditions post-fire. Here, in this study, we addressed this need with an experimental open air burn simulation that generated chars from vegetation representative of major land cover types in the western United States. The chars were leached to simulate DOM mobilization potential. The DOM composition was characterized by ultra-high resolution mass spectrometry (HR-MS) and UV/VIS absorbance and fluorescence. Our results indicated that the shifts of DOM production and composition along a burn-severity gradient depends on the land cover type that was burned, with the degree of change dependent on the composition of the starting parent vegetation material. Fluorescence signatures indicated a strong convergence across land cover types to more aromatic DOM with increasing severity, while HR-MS indicated an increase in the production of aromatic nitrogen containing DOM with increasing severity. Results from this study enhance our ability to describe DOM composition in a framework that can be more directly related with field and remote-sensing based metrics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Dynamic subcanopy leaf traits drive resistance of net primary production across a disturbance severity gradient

Across the globe, the forest carbon sink is increasingly vulnerable to an expanding array of low- to moderate-severity disturbances. However, some forest ecosystems exhibit functional resistance (i.e., the capacity of ecosystems to continue functioning as usual) following disturbances such as extreme weather events and insect or fungal pathogen outbreaks. Unlike severe disturbances (e.g., stand-replacing wildfires), moderate severity disturbances do not always result in near-term declines in forest production because of the potential for compensatory growth, including enhanced subcanopy production. Community-wide shifts in subcanopy plant functional traits, prompted by disturbance-driven environmental change, may play a key mechanistic role in resisting declines in net primary production (NPP) up to thresholds of canopy loss. However, the temporal dynamics of these shifts, as well as the upper limits of disturbance for which subcanopy production can compensate, remain poorly characterized. In this study, we leverage a 4-year dataset from an experimental forest disturbance in northern Michigan to assess subcanopy community trait shifts as well as their utility in predicting ecosystem NPP resistance across a wide range of implemented disturbance severities. Through mechanical girdling of stems, we achieved a gradient of severity from 0% (i.e., control) to 45, 65, and 85% targeted gross canopy defoliation, replicated across four landscape ecosystems broadly representative of the Upper Great Lakes ecoregion. We found that three of four examined subcanopy community weighted mean (CWM) traits including leaf photosynthetic rate (p = 0.04), stomatal conductance (p = 0.07), and the red edge normalized difference vegetation index (p < 0.0001) shifted rapidly following disturbance but before widespread changes in subcanopy light environment triggered by canopy tree mortality. Surprisingly, stimulated subcanopy production fully compensated for upper canopy losses across our gradient of experimental severities, achieving complete resistance (i.e., no significant interannual differences from control) of whole ecosystem NPP even in the 85% disturbance treatment. Additionally, we identified a probable mechanistic switch from nutrient-driven to light-driven trait shifts as disturbance progressed. Our findings suggest that remotely sensed traits such as the red edge normalized difference vegetation index (reNDVI) could be particularly sensitive and robust predictors of production response to disturbance, even across compositionally diverse forests. The potential of leaf spectral indices to predict post-disturbance functional resistance is promising given the capabilities of airborne to satellite remote sensing. We conclude that dynamic functional trait shifts following disturbance can be used to predict production response across a wide range of disturbance severities.

resistance↗
DOE OSTI2024

Severe and mild drought cause distinct phylogenetically linked shifts in the blue grama (Bouteloua gracilis) rhizobiome

Plants rely on a diverse rhizobiome to regulate nutrient acquisition and plant health. With increasing severity and frequency of droughts worldwide due to climate change, untangling the relationships between plants and their rhizobiomes is vital to maintaining agricultural productivity and protecting ecosystem diversity. While some plant physiological responses to drought are generally conserved, patterns of root exudation (release of small metabolites shown to influence microbes) and the consequential effects on the plant rhizobiome can differ widely across plant species under drought. To address this knowledge gap, we conducted a greenhouse study using blue grama ( Bouteloua gracilis ), a drought-tolerant C4 grass native to shortgrass prairie across North American plains, as a model organism to study the effect of increasing drought severity (ambient, mild drought, severe drought) on root exudation and the rhizobiome. Our previous results demonstrated physiological effects of increasing drought severity including an increase in belowground carbon allocation through root exudation and shifts in root exudate composition concurrent with the gradient of drought severity. This work is focused on the rhizobiome community structure using targeted sequencing and found that mild and severe drought resulted in unique shifts in the bacterial + archaeal and fungal communities relative to ambient, non-droughted controls. Specifically, using the change in relative abundance between ambient and drought conditions for each ZOTU as a surrogate for population-scale drought tolerance (e.g., as a response trait), we found that rhizobiome response to drought was non-randomly distributed across the phylogenies of both communities, suggesting that Planctomycetota , Thermoproteota (formerly Thaumarchaeota ), and the Glomeromycota were the primary clades driving these changes. Correlation analyses indicated weak correlations between droughted community composition and a select few root exudate compounds previously implicated in plant drought responses including pyruvic acid, D-glucose, and myoinositol. This study demonstrates the variable impacts of drought severity on the composition of the blue grama rhizobiome and provides a platform for hypothesis generation for targeted functional studies of specific taxa involved in plant-microbe drought responses.

Goemann, Hannah M.↗
DOE OSTI2025

Evaluating post-fire watershed response to varying burn severity and precipitation regimes using fully-distributed and integrated hydrologic models

Wildfires can cause significant changes in vegetation and soil, which may lead to increased surface runoff and soil erosion, thereby affecting water cycling within ecosystems. This study uses the Advanced Terrestrial Simulator (ATS), an integrated and fully distributed hydrologic model at the watershed scale, to examine post-fire hydrologic responses in selected watersheds with varying burn severities in the Pacific Northwest region of the United States. The model integrates surface overland flow, subsurface flow, and canopy biophysical processes. We have developed a new fire module in ATS to account for changes in soil hydraulic properties caused by fire in the topsoil layer. Modeling results indicate that, in the year following a high-severity burn, watershed-averaged evapotranspiration decreases by 25%. Additionally, post-fire peak flows increase by 18-29% in watersheds burned with medium to high severity due to changes in soil properties. Conversely, a low-severity burn results in less than a 1% increase in post-fire peak flow. Furthermore, a high-severity fire causes a 38% reduction in the infiltration rate within the affected watershed during the first post-fire wet season. Hypothetical numerical experiments with varying precipitation regimes after a high-severity fire show that post-fire peak flows can increase by 1-29% due to fire-induced changes in soil hydraulic properties. This study highlights the importance of using fully distributed hydrologic models to quantify disturbance-feedback loops, which are essential for understanding the complexities brought about by spatial heterogeneity in post-fire landscapes.

ATS↗
DOE OSTI2023

Host genetics and gut microbiota composition: Baseline gut microbiota composition as a possible prognostic factor for the severity of COVID-19 in patients with familial Mediterranean fever disease

It is known that the gut microbiome of a healthy person affects the process of COVID-19 after getting infected with SARS-CoV-2 virus. It is also believed that colchicine can alleviate the severity of COVID-19. Current investigations aimed to evaluate the associations between the baseline gut microbiota composition of healthy and Familial Mediterranean fever (FMF) - carrier Armenian men populations, and the severity of the COVID-19 disease after their infection with the SARS-CoV-2. The study has a purpose of answering three core questions: i. Do the characteristics of gut microbiome of Armenians affect the course of COVID-19 severity? ii. How does the COVID-19 disease course on go for FMF patients who have been taking colchicine as a medication over the years after getting infected with SARS-CoV-2? iii. Is there an initial gut micribiota structure pattern for non-FMF and FMF patients in the cases when COVID-19 appears in mild form? The gut microbiota composition in non-FMF and FMF patients before the first infection (mild and moderate course of COVID-19) was considered. COVID-19 was diagnosed by SARS-CoV-2 nucleic acid RT-PCR in nasopharyngeal swab and/or sputum. The number of patients with male FMF with mild COVID-19 was approximately two times higher than that of non-FMF male subjects with COVID-19. In addition, an association of COVID-19 disease severity with the baseline gut Prevotella, Clostridium hiranonis, Eubacterium biforme, Veillonellaceae, Coprococcus, and Blautia diversities in the non-FMF and FMF populations were revealed by us, which can be used as risk/prognostic factor for the severity of COVID-19.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

An editorial to the Special Issue on “Severe climate Risks”

The history of this Special Issue (https://www.sciencedirect.com/special-issue/10JD7LNJNQ0) indirectly dates back to the early 1990s, when the signature of the United Nations Framework Convention on Climate Change kicked-off an international political process based on one overarching and foundational principle: to avoid “dangerous anthropogenic interference with the climate system” at the global level. More than three decades later, such a principle remains central, though complementary aims made their way through the climate negotiation process, such as the importance of ensuring equity and justice, to give just one example here. Scientific knowledge also considerably progressed and we know more about the range of risks that climate change imposes and will continue to impose to the biosphere and humankind, worldwide and at all territorial levels. It is also clear that societal responses to these risks —“climate adaptation” as we know it— are increasingly happening, but definitely not at the pace of climate risk trends (Berrang-Ford et al., 2021, Erisken et al., 2021, Olazabal and Ruiz De Gopegui, 2021, Magnan et al., 2023a, Reckien et al., 2023, UNEP, 2023). As a result, concerns have emerged over the recent years in both the scientific and policy arenas around the idea that societies may not be able to address all climate risks, and that limits to adaptation and induced residual risks need to be considered more seriously. Such concerns further highlight the continuing importance of the imperative to minimise dangerous anthropogenic interference with the climate system, at any scale. But what does “dangerous interference” mean? How can we decide that we are entering the “dangerous” space, compared to a broader range of climate risks that would qualify as problematic but not necessarily “dangerous”? Who should make such a decision? Which conditions drive risk severity over time, including in the future? And what would be the environmental, economic, social and cultural implications of prioritising some climate risks over others? The Intergovernmental Panel on Climate Change (IPCC) was a pioneer in addressing such questions through the development of the “Key Risks” framing that describes those climate risks having the potential to become dangerous or “severe” over the course of this century (Schellnhuber et al., 2006, Schneider et al., 2007, Oppenheimer et al., 2014, O’Neill et al., 2022). The Fifth and Sixth assessment cycles (AR5 and AR6) went a step further by identifying about 120 Key Risks across regions and sectors, and clustering them into 8 “Representative Key Risks” covering a range of geographical systems (low-lying coasts, and to terrestrial and ocean ecosystems), sectors (critical infrastructure, living standards, human health, food security, and water security) and human dimensions (peace and mobility) (Oppenheimer et al., 2014, O’Neill et al., 2022). This Special Issue was born of the efforts of a range of authors, during the development of the IPCC AR6 main Assessment Report between 2019 and 2022, to characterise Key Risks and Representative Key Risks, and advance knowledge on what shapes “severe climate risks” conceptually as well as in the real-world. The series of papers forming this Special Issue is not intended to cover the topic exhaustively, but rather to give readers an overview through the following narrative: defining “severe climate risks” is highly challenging (Magnan et al., 2023b), but knowledge is expanding on the driving climate hazards (Tebaldi et al., 2023) and their implications on geographical systems, sectors and human dimensions, using here food security (Mirzabaev et al., 2023), human mobility (Gilmore et al., 2024) and peace (Buhaug et al., 2023) as illustrative examples. The overall intention is to support especially decision-makers, whatever the scale or sector considered, in asking severity-driven questions to identify sector- and context-specific “priority” risks from climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Mechanically induced thermal runaway severity analysis of Li-ion batteries and continuous energy release monitoring

The large-scale deployment of Li-ion batteries in stationary energy storage and electrical vehicle applications demands a strong focus on safety, particularly on the thermal runaway risk and severity evaluation. A standardized single-side mechanical indentation test protocol was developed to induce an internal short-circuit (ISC) and evaluate cells' thermal runaway severity at different state of charge (SOC). The observed hazard severity (OHS in five categories) and evaluated scores in this work have a comprehensive consideration of each cell's capacity, initial voltage, SOC, temperature and voltage change, allowing a better evaluation of the cells' thermal runaway potential. This method was applied to about 200 Li-ion batteries in order to build an extensive thermal runaway database covering various SOCs, capacities and chemistries. In this study, we monitored the transitions of stored electrochemical energy and applied mechanical energy into both thermal energy and acoustic emissions (AE). The surface temperature and mechanical failures were monitored by infrared imaging and AE to capture critical events within battery cells throughout the mechanical indentation tests. Furthermore, the initial temperature maps can predict two types of follow-up events: thermal runaway or gradual heat release via conduction. Analyzing each cell's severity, AEs, and leveraging the evolving database offer insights into predicting occurrences of thermal runaway. The test method, thermal runaway severity evaluation and prediction, and the corresponding database provide battery designers, manufacturers, and end-users a clear overview of Li-ion batteries' thermal runaway potential under mechanical abuse, advancing the safety design of Li-ion batteries.

Acoustic emission↗
DOE OSTI2026

Radiological Releases from Novel Fuel Forms in Advanced Reactors During Severe Accidents for Consequence Analyses

Various advanced reactor developers are exploring the potential for reductions in the size of physical security forces and emergency planning zones. These reductions are based on robust fuel forms and inherently safe reactor designs. However, such reductions in physical protection measures could increase the risk of sabotage. To assess the possibility of reducing these measures, sabotage-induced radiological consequence analyses were carried out. These analyses considered accident scenarios that were beyond design basis accidents and overly conservative (Shah, 2025a; Shah, 2025b; Shah and Hartanto, 2026), yielding very large release fractions. These fractions, which can be used to evaluate physical protection and emergency planning requirements, have been crudely determined and applied as demonstrations for a sodium-cooled fast reactor (SFR) (Shah and Hartanto, 2025a), a high-temperature gas-cooled reactor (HTGR) (Shah and Hartanto, 2025b), a heat pipe–cooled reactor (HPR) (Shah and Hartanto, 2025c), and a molten salt–cooled reactor (MSR) (Shah et al., 2026). A Sandia National Laboratories (SNL) team used MELCOR—a fully integrated severe accident analysis code—to demonstrate the code’s capability to analyze advanced (i.e., not light water–cooled) reactors (including a fluoride salt–cooled high-temperature reactor [FHR]) and calculate radiological releases to the environment during severe accidents (Wagner et al., 2022a, 2022b, 2022c, 2023a, and 2023b). Although the analyses were carried out to demonstrate MELCOR’s growing capability, the release source terms were estimated for advanced reactors, providing valuable insights into the accident progression and radiological releases. These findings from prior SNL studies, including estimated source terms and related sensitivity studies, were leveraged to derive source terms for postulated sabotage-induced accidents. Insights from these sensitivity studies informed the scaling of SNL’s estimated source terms for the defined accident scenarios. The derived release fractions for the severe accident scenarios for the respective reactor designs can be used to perform more nuanced dose consequence analyses to evaluate the reactors’ physical protection and emergency planning zone requirements. These analyses are in accordance with the risk-informed, performance-based approach proposed under 10 CFR Part 53. This study builds on the prior source term analyses and associated sensitivity studies by SNL to derive time-dependent and design-informed release fractions. Section 2 describes the diverse advanced reactor designs analyzed by the SNL team. Section 3 discusses the severe accident analyses, the release fractions calculated, and the limitations and assumptions of the demonstration project. Section 4 presents the release percentages derived for the hypothetical sabotage-induced severe accidents at the advanced reactors. Section 5 summarizes the study’s findings and conclusions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Further understanding “severe” climate risk

What makes one climate risk more “severe” or “dangerous” than others? Acknowledging that the notion of dangerousness can substantially vary from one sociocultural context to another, this Perspective paper builds on recent literature to explore three notions that are estimated to be foundational to climate risk severity: the physical, ecological and social thresholds leading to transformational and possibly abrupt changes; the irreversibility of these changes; and the cascading effects within and across the systems affected. While not necessarily the most determining dimensions of risk, they deserve more attention and integration into frameworks to assess “severe” climate risk, such frameworks remaining under-developed. The paper also takes stock of issues related to the spatial scale(s) of and the evidence base for severe climate risks. It lands on four intertwined research directions across geographies, sectors and populations, that are hypothesized to play a critical role in the coming decade, from feeding the next IPCC cycle to more broadly supporting the development of anticipatory adaptation policies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Series FACTS Devices for Increasing Resiliency in Severe Weather Conditions

Severe weather conditions are low-probability, high-impact events that affect grid operations. The majority of power outages are caused by severe weather conditions. Grid resiliency to weather events can be enhanced by decreasing the reliance on its affected sections. One way to do this is to reduce the power flow through lines vulnerable to severe weather. If a line is disconnected, its initial power flow is distributed through the neighbor lines, which may cause congestion in the grid. FACTS devices can be used to control the power flow of lines that have a higher chance of power outages. Most previous works do not consider weather events in power flow control. In this work, a linearized optimal power flow (OPF)–based algorithm is developed to minimize the real power flow of vulnerable lines considering the thermal limits of lines to prevent infeasible solutions; the simulation is fast, making it suitable for large-scale systems. The proposed optimization problem is presented as a mixed-integer linear program (MILP), making it capable of using short-term load forecasting due to its high solution speed. The proposed optimization problem considers multiple lines with different outage probabilities and the uncertainties of the weather forecast. Moreover, it estimates the power reduction in vulnerable lines due to changes in the series FACTS devices. The performance of the proposed optimization problem is tested on IEEE 14-, 30-, and 118-bus systems for several scenarios. The results are validated with the AC power flow results from MATPOWER.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Long-term drought promotes invasive species by reducing wildfire severity

Anthropogenic climate change has increased the frequency of drought, wildfire, and invasions of non-native species. Although high-severity fires linked to drought can inhibit recovery of native vegetation in forested ecosystems, it remains unclear how drought impacts the recovery of other plant communities following wildfire. We leveraged an existing rainfall manipulation experiment to test the hypothesis that reduced precipitation, fuel load, and fire severity convert plant community composition from native shrubs to invasive grasses in a Southern California coastal sage scrub system. We measured community composition before and after the 2020 Silverado wildfire in plots with three rainfall treatments. Drought reduced fuel load and vegetation cover, which reduced fire severity. Native shrubs had greater prefire cover in added water plots compared to reduced water plots. Native cover was lower and invasive cover was higher in postfire reduced water plots compared to postfire added and ambient water plots. Our results demonstrate the importance of fuel load on fire severity and plant community composition on an ecosystem scale. Management should focus on reducing fire frequency and removing invasive species to maintain the resilience of coastal sage scrub communities facing drought. In these communities, controlled burns are not recommended as they promote invasive plants.

54 ENVIRONMENTAL SCIENCES↗