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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Site Integration and Regulatory Considerations for a Nuclear Power Plant Colocated with Industrial Facilities: Colocation Studies for a Petroleum Refinery, Methanol Plant, and Wood Pulp Plant

This research explores the colocation of nuclear power plants (NPPs) with industrial applications. Three existing industrial sites were considered to demonstrate the siting process and illuminate technological gaps for future work. The three applications demonstrated for colocation here are a petroleum refinery, a methanol production plant, and a pulp and paper plant. This study uses a modified version of the EPRI siting criteria to explore the geological and demographic characteristics of the location of the current industrial site, as well as exploring external hazards from the industrial plant and its surrounding land use. Data was collected from public databases to estimate site characteristics. We then discuss how the site characteristics may impact the ability to colocate an NPP with an industrial application. The application site and 5 additional sites were explored for each application to give a general indication of the siting implications for an NPP in each area. The hazards for each industrial application was also explored to determine how colocation may impact reactor safety. The following gaps have been identified and should be explored in future research on colocation of NPPs with petroleum refineries, methanol plants, and pulp and paper plants: - There is a variety of industrial use, hazards, and pipelines in the surrounding area. A more thorough review of these hazards should be considered for colocation. - In general, the whole region around some applications seems to have softer soil, with implications for large site preparation costs. Further site investigations should prioritize looking into the geotechnical conditions. - Applications along coastlines are susceptible to flooding and hurricanes. The benefits of colocation should be weighed against the potential design implications. - The benefits of natural gas pipeline infrastructure in place should be explored further. If heat supply from the NPP is not required or not feasible due to the distance between the NPP and the application, there may be an opportunity to supply hydrogen to the plant through an existing pipeline. - Because there are several collocated industrial plants in the regions for the refinery and methanol plant, the benefits of sharing resources from the NPP should be explored further. This may open up additional sites for colocation. The following knowledge gaps were identified for the colocation of NPPs with these three industries, and industrial applications in general. These gaps are: - While the STAND tool contains many important characteristics for the reactor siting process, it is not calibrated for the colocation of NPPs with industrial facilities. - There are aspects of both the NPP and industrial application that need to be quantified for a siting analysis. Particularly, we need to understand the water intake requirements for NPPs and each application. - Further work may focus on adapting the STAND site comparison methodology to comparison of sites for co-location. This will involve using the data documented in this report as a starting point and performing a comprehensive and quantitative comparison. - Without spending significant resources, it would be impossible to gather data for each site to evaluate all aspects of siting. One approach to finding data and understanding its implications to siting is looking at FSARs for existing plants. For example, most sites considered in this study have small Vs30 values, indicating soft soil. However, there are NPPs located in the vicinity of most of the sites (e.g., Waterford Steam Electric Station near New Orleans) and reviewing available site characteristics and geotechnical data for these NPPs, might provide further information for siting. - The siting analysis in this study indicates that colocation of the NPP with the industrial site could be difficult based on external hazards, cooling requirements, weather, or population. We need to determine the impact of distance between the two facilities on cost and quality of energy transport. - This study did not touch on socioeconomic impacts for NPP colocation with industrial facilities. The input-output analysis methodology could be applied to the communities referenced in this study to determine the socioeconomic impact of these projects. - Similarly, the impacts of colocation on emergency planning was not explored in this study. The impacts on emergency planning infrastructure are somewhat related to the socioeconomic impacts, and could be explored using a similar methodology. - This study also did not address physical and cybersecurity, which will be important aspects of co-location [ref] . Cybersecurity will be important, regardless of the distance, but physical security will be important if the facilities are located very closely. Physical security might also be important for the steam lines between the plants, unless they are determined to be non-safety significant. - In many site l

08 HYDROGEN↗
DOE OSTI2025

Site Integration and Regulatory Considerations for an NPP Colocated with a Petroleum Refinery, Methanol Plant, and Wood Pulp Plant

This research explores the colocation of nuclear power plants (NPPs) with industrial applications. Three existing industrial sites were considered to demonstrate the siting process and illuminate technological gaps for future work. The three applications demonstrated for colocation here are a petroleum refinery, a methanol production plant, and a pulp and paper plant. This study uses a modified version of the EPRI siting criteria to explore the geological and demographic characteristics of the location of the current industrial site, as well as exploring external hazards from the industrial plant and its surrounding land use. Data was collected from public databases to estimate site characteristics. We then discuss how the site characteristics may impact the ability to colocate an NPP with an industrial application. The application site and 5 additional sites were explored for each application to give a general indication of the siting implications for an NPP in each area. The hazards for each industrial application was also explored to determine how colocation may impact reactor safety. The following gaps have been identified and should be explored in future research on colocation of NPPs with petroleum refineries, methanol plants, and pulp and paper plants: - There is a variety of industrial use, hazards, and pipelines in the surrounding area. A more thorough review of these hazards should be considered for colocation. - In general, the whole region around some applications seems to have softer soil, with implications for large site preparation costs. Further site investigations should prioritize looking into the geotechnical conditions. - Applications along coastlines are susceptible to flooding and hurricanes. The benefits of colocation should be weighed against the potential design implications. - The benefits of natural gas pipeline infrastructure in place should be explored further. If heat supply from the NPP is not required or not feasible due to the distance between the NPP and the application, there may be an opportunity to supply hydrogen to the plant through an existing pipeline. - Because there are several collocated industrial plants in the regions for the refinery and methanol plant, the benefits of sharing resources from the NPP should be explored further. This may open up additional sites for colocation. The following knowledge gaps were identified for the colocation of NPPs with these three industries, and industrial applications in general. These gaps are: - While the STAND tool contains many important characteristics for the reactor siting process, it is not calibrated for the colocation of NPPs with industrial facilities. - There are aspects of both the NPP and industrial application that need to be quantified for a siting analysis. Particularly, we need to understand the water intake requirements for NPPs and each application. - Further work may focus on adapting the STAND site comparison methodology to comparison of sites for co-location. This will involve using the data documented in this report as a starting point and performing a comprehensive and quantitative comparison. - Without spending significant resources, it would be impossible to gather data for each site to evaluate all aspects of siting. One approach to finding data and understanding its implications to siting is looking at FSARs for existing plants. For example, most sites considered in this study have small Vs30 values, indicating soft soil. However, there are NPPs located in the vicinity of most of the sites (e.g., Waterford Steam Electric Station near New Orleans) and reviewing available site characteristics and geotechnical data for these NPPs, might provide further information for siting. - The siting analysis in this study indicates that colocation of the NPP with the industrial site could be difficult based on external hazards, cooling requirements, weather, or population. We need to determine the impact of distance between the two facilities on cost and quality of energy transport. - This study did not touch on socioeconomic impacts for NPP colocation with industrial facilities. The input-output analysis methodology could be applied to the communities referenced in this study to determine the socioeconomic impact of these projects. - Similarly, the impacts of colocation on emergency planning was not explored in this study. The impacts on emergency planning infrastructure are somewhat related to the socioeconomic impacts, and could be explored using a similar methodology. - This study also did not address physical and cybersecurity, which will be important aspects of co-location [ref] . Cybersecurity will be important, regardless of the distance, but physical security will be important if the facilities are located very closely. Physical security might also be important for the steam lines between the plants, unless they are determined to be non-safety significant. - In many site l

08 - HYDROGEN↗
DOE OSTI2025

Soil carbon accrual and biopore formation across a plant diversity gradient

Plant diversity promotes soil organic carbon (SOC) gains through intricate changes in root-soil interactions and their subsequent influence on soil physical and biological processes. We assessed SOC and pore characteristics of soils under a range of switchgrass-based plant systems 12 years after their establishment. The systems represented a gradient of plant diversity with species richness ranging from 1 to 30 species. We focused on soil biopores as indicators of the legacy of root activity and explored biopore relationships with SOC accumulation. Biopores were measured using X-ray computed micro-tomography. Plant functional richness explained 29 % of bioporosity and 36 % of SOC variation, while bioporosity itself explained 36 % of the variation in SOC. The most diverse plant system (30 species) had the highest SOC, while long-term bare soil fallow and monoculture switchgrass had the lowest. Of particular note was a 2-species mixture of switchgrass (Panicum virgatum L.) and ryegrass (Elymus canadensis), which exhibited the highest bioporosity and achieved SOC levels comparable to those of the systems with 6 and 10 plant species, and were inferior only to the system with 30 species. We conclude that plant diversity may enhance SOC through biopore-mediated mechanisms and suggest a potential for identifying specific plant combinations that may be particularly efficient for fostering biopore formation and, subsequently, SOC sequestration.

Kim, Kyungmin [Seoul National Univ. (Korea, Republ↗
DOE OSTI2024

Dynamic ecosystem assembly and escaping the “fire trap” in the tropics: insights from FATES_15.0.0

Abstract. Fire is a fundamental part of the Earth system, with impacts on vegetation structure, biomass, and community composition, the latter mediated in part via key fire-tolerance traits, such as bark thickness. Due to anthropogenic climate change and land use pressure, fire regimes are changing across the world, and fire risk has already increased across much of the tropics. Projecting the impacts of these changes at global scales requires that we capture the selective force of fire on vegetation distribution through vegetation functional traits and size structure. We have adapted the fire behavior and effects module, SPITFIRE (SPread and InTensity of FIRE), for use with the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a size-structured vegetation demographic model. We test how climate, fire regime, and fire-tolerance plant traits interact to determine the biogeography of tropical forests and grasslands. We assign different fire-tolerance strategies based on crown, leaf, and bark characteristics, which are key observed fire-tolerance traits across woody plants. For these simulations, three types of vegetation compete for resources: a fire-vulnerable tree with thin bark, a vulnerable deep crown, and fire-intolerant foliage; a fire-tolerant tree with thick bark, a thin crown, and fire-tolerant foliage; and a fire-promoting C4 grass. We explore the model sensitivity to a critical parameter governing fuel moisture and show that drier fuels promote increased burning, an expansion of area for grass and fire-tolerant trees, and a reduction of area for fire-vulnerable trees. This conversion to lower biomass or grass areas with increased fuel drying results in increased fire-burned area and its effects, which could feed back to local climate variables. Simulated size-based fire mortality for trees less than 20 cm in diameter and those with fire-vulnerable traits is higher than that for larger and/or fire-tolerant trees, in agreement with observations. Fire-disturbed forests demonstrate reasonable productivity and capture observed patterns of aboveground biomass in areas dominated by natural vegetation for the recent historical period but have a large bias in less disturbed areas. Though the model predicts a greater extent of burned fraction than observed in areas with grass dominance, the resulting biogeography of fire-tolerant, thick-bark trees and fire-vulnerable, thin-bark trees corresponds to observations across the tropics. In areas with more than 2500 mm of precipitation, simulated fire frequency and burned area are low, with fire intensities below 150 kW m−1, consistent with observed understory fire behavior across the Amazon. Areas drier than this demonstrate fire intensities consistent with those measured in savannas and grasslands, with high values up to 4000 kW m−1. The results support a positive grass–fire feedback across the region and suggest that forests which have existed without frequent burning may be vulnerable at higher fire intensities, which is of greater concern under intensifying climate and land use pressures. The ability of FATES to capture the connection between fire disturbance and plant fire-tolerance strategies in determining biogeography provides a useful tool for assessing the vulnerability and resilience of these critical carbon storage areas under changing conditions across the tropics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

OPEN-Augmented Reality GUI for Bioenergy Crop Phenotyping and Precision Agriculture (Donald Danforth Plant Science Center Final Scientific Technical Report)

The project led by the Donald Danforth Plant Science Center, in collaboration with Arizona State University, George Washington University, and Saint Louis University, has made significant strides in advancing the phenotypic analysis of bioenergy crops through the development of an innovative AI processing pipeline. This initiative was primarily funded by ARPA-E, with additional cost-sharing provided by the participating institutions. The project successfully utilized a variety of sensors—3D scanners, thermal, RGB, and hyperspectral—to refine algorithms for data-driven trait signature identification and improve the classification and visualization of plant traits. The developed AI processing pipeline is capable of handling the complex, multidimensional data characteristic of dynamic agricultural environments. 1) Contributions to understanding: The research has advanced the field of plant phenomics by showcasing the synergistic use of various sensor data to enhance the precision of trait analysis in bioenergy crops. Through the integration of 3D scanners, thermal, RGB, and hyperspectral sensors, the project has developed robust data-driven trait signature algorithms and visualization techniques. These innovations have facilitated detailed monitoring and management of plant traits, providing vital insights into plant growth dynamics and stress responses. Further, the project has broadened our understanding of how machine learning can be effectively applied in multi-sensor environments to refine trait analysis. By leveraging diverse datasets, the research has not only improved the accuracy of phenotypic assessments but also established a versatile methodological framework that can be extended beyond agriculture to other fields requiring detailed phenotypic analysis. 2) Technical effectiveness and economic feasibility: The AI processing pipeline developed in this project demonstrated significant technical effectiveness, achieving high throughput analysis of extensive phenotypic data and meeting targeted accuracies. This system exemplified the capability of advanced machine learning technologies to efficiently manage and analyze large, complex datasets. Economically, the implementation of the project-developed pipelines may offer substantial cost savings across multiple sectors. It enhances data analysis processes and significantly reduces the need for manual data interpretation, thereby decreasing both the time and resources required. 3) Public benefit: The project has significantly broadened the scope of agricultural methodologies to enhance phenotypic analysis, with potential applications in various sectors beyond agriculture. Additionally, the initiative fostered an enriching educational and collaborative environment, significantly enhancing the technical skills of participants. It also made substantial contributions to the scientific community by providing open-access data sets and tools, encouraging ongoing research and development across various disciplines. Overall, the project not only met its scientific goals but also showcased the extensive utility of integrating advanced machine learning and sensor data analysis technologies. These advancements have proven instrumental in driving forward both theoretical research and practical applications, setting a strong foundation for future explorations and innovations in data-driven science.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

CERF: IM3 Projected Western US Power Plant Locations

Overview The Capacity Expansion Regional Feasibility (CERF) model is an open-source geospatial python package that provides new power plant locations at a 1km resolution. The model ingests U.S. state or regional-scale electricity system capacity expansion plans, such as those produced by the Global Change Analysis Model (GCAM-USA), and identifies feasible, site-specific locations for individual new power plants (renewable and non-renewable). CERF combines high-resolution geospatial suitability analyses with an economic algorithm that selects individual plant siting locations based on grid interconnection costs and the locational marginal value of new generation. The model incorporates a wide range of dynamic constraints and opportunities, such as protected lands, population density, existing infrastructure, and water availability. This dataset provides CERF power plant siting results for IM3 Phase 2 simulations across eight different scenarios for the Western US through 2055. The scenarios include combinations of two Shared Socioeconomic Pathways (SSP3 and SSP5) with four high-resolution climate projections specific to the United States (see, https://tgw-data.msdlive.org/). These climate projections include "hotter" and "cooler" variants for two Representative Concentration Pathways (RCP4.5 and RCP8.5). The resulting eight simulations are: rcp45cooler_ssp3 rcp45cooler_ssp5 rcp45hotter_ssp3 rcp45hotter_ssp5 rcp85cooler_ssp3 rcp85cooler_ssp5 rcp85hotter_ssp3 rcp85hotter_ssp5 CERF siting results in this dataset correspond to capacity expansion plans in the GCAM-USA IM3 Phase 2 simulation data and are available for each of the above scenarios. Data Details Temporal Range: 2015-2055 in 5-year timesteps. Note that 2015 is the experiment base year and 2020 and beyond represent model simulation years. Spatial Range: Plant locations are provided for the eleven states in the Western US including Arizona, California, Colorado, Idaho, Montana, New Mexico, Nevada, Oregon, Utah, Washington, and Wyoming. Spatial Resolution: 1 km-squared, provided in x and y coordinates Geospatial Projection: Albers Equal Area Conic (ESRI:102003) File Type: csv The dataset contains subdirectories for each of the eight scenarios described in the overview. Each scenario folder contains two subfolders with the following information: 1. Power Plant Data This directory contains a single .csv file of power plant locations for both pre-existing (non-CERF sited plants in operation in 2015) and new (CERF-sited) power plants across the temporal range along with additional CERF model output parameters for CERF-sited plants. Plant with a siting year earlier than 2020 correspond to facilities that are operational leading into the first timestep CERF simulation. For a more detailed description of CERF model output parameters, see the CERF model documentation. Note that the cerf_plant_id parameter is unique within each scenario file but not across scenario files. Parameter Descriptions scenario - Name of scenario cerf_plant_id - Unique siting identifier cerf_sited - If True, indicates that plant was sited by CERF model. If False, indicates pre-existing facility region_name - Name of region (state) tech_id - Technology ID tech_name - Full generation technology name inclusive of cooling type (if applicable) and additional characteristics tech_simple - Simplified generation technology type unit_size_mw - Power plant unit size (MW) xcoord - X coordinate in the default CRS (meters) ycoord - Y coordinate in the default CRS (meters) index - Index position in the flattend 2D array buffer_in_km - Exclusion buffer around site (km) sited_year - Year of siting retirement_year - Year of retirement lmp_zone - Locational marginal price (LMP) zone ID locational_marginal_price_usd_per_mwh - Locational marginal price ($/MWh) generation_mwh_per_year - Generation output (MWh/yr) operating_cost_usd_per_year - Cost of plant operations ($/yr) net_operational_value - Net operational value based on LMP and and operating costs ($/yr) interconnection_cost - Cost of interconnection for transmission & gas pipeline (if applicable) net_locational_cost -- Difference of interconnection cost and operating value ($/yr) capacity_factor_fraction - Capacity factor (fraction) carbon_capture_rate_fraction - Carbon capture rate (fraction) fuel_co2_content_tons_per_btu - Fuel CO2 content (tons/Btu) fuel_price_usd_per_mmbtu - Fuel price ($/MMBtu) fuel_price_esc_rate_fraction - Fuel price escalation rate (fraction) heat_rate_btu_per_kWh - Heat rate (Btu/kWh) lifetime_yrs - Technology lifetime for annuity (years) operational_life_yrs - Operational lifetime for retirement (years) variable_om_usd_per_mwh - Variable operation and maintenance costs of yearly capacity use ($/MWh) variable_om_esc_rate_fraction - Variable operation and maintenance costs escalation rate (fraction) carbon_tax_usd_per_ton - Carbon tax ($/ton) carbon_tax_esc_rate_fraction - Carbon tax escalation rate (fraction) 2. Storage Data This directory contains information on new and pre-existing energy storage facilities operational in each timestep along with various storage operational parameters. The 2015 timestep provides pre-existing energy storage data and corresponds with facilities that are operational leading into the first model simulation timestep. Note that coordinates in the storage files correspond to the interconnection point on the grid (substation location), not individual energy storage locations. Energy storage is added in a cumulative process at each given interconnection point. That is, each individual file provides the total operational storage capacity interconnected to the specified substation for the given timestep, inclusive of previously installed storage at that location and new storage installed in that timestep at that location. Parameters scenario - Name of scenario timestep - Simulation timestep name - Unique storage identifier s_typ - Type of energy storage technology (battery or pumped storage hydro) s_node - Node ID of interconnecting substation xcoord - X coordinate in the default CRS (meters) ycoord - Y coordinate in the default CRS (meters) charge_rate - Maximum charge rate (power capacity) of storage system (MW) discharge_rate - Maximum discharge rate (power capacity) of storage system (MW) duration - Duration of storage system (hours) max_SoC - Allowed maximum state of charge (energy capacity) of storage system (MWh) min_SoC -Allowed minimum state of charge (energy capacity) of storage system (MWh) charge_eff - Efficiency of charge (fraction between 0 and 1) discharge_eff - Efficiency of discharge (fraction between 0 and 1) Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program.

CERF↗
DOE OSTI2025

Uncovering Sequence and Structural Characteristics of Fungal Expansin‐Related Proteins With Potential to Drive Substrate Targeting

Expansins loosen plant cell wall networks through disrupting non-covalent bonds between cellulose microfibrils and matrix polysaccharides. Whereas expansins were first discovered in plants, expansin-related proteins have since been identified in bacteria and fungi. The biological function of microbial expansins remains unclear; however, several studies have shown distinct binding preferences toward different structural polysaccharides. Earlier studies of bacterial expansin-related proteins uncovered sequence and structural features that correlate to substrate binding. Herein, 20 fungal expansin-related sequences were recombinantly produced in Komagataella phaffii, and the purified proteins were compared in terms of substrate binding to cellulosic and chitinous substrates. The impact of pH on the zeta potential of prioritized substrates was also measured, and Principal Component Analysis was performed to uncover correlations between protein characteristics (e.g., pI, hydrophobicity, surface charge distribution) and measured substrate binding preferences. Whereas acidic proteins with a predicted pI less than 5.0 preferentially bound to chitin, basic proteins with pI greater than 8.0 preferentially bound to xylan and xylan-containing fiber. Similar to many cellulases, binding to cellulose was correlated to relatively high aromatic amino acid content in the protein sequence and presence of a carbohydrate binding module (CBM), which in the case of expansins is a C-terminal CBM63. Whereas overall sequence characteristics could be correlated to substrate binding preference, the identity of amino acids occupying conserved positions that impact protein activity was better correlated with loosenin versus expansin classifications.

chitin↗
DOE OSTI2025

Characterizing falling particle curtain receivers at commercially relevant scales: Research Performance Progress Report (RPPR-1)

Sandia will construct a cold flow receiver test platform in order to characterize falling particle curtain receivers at commercially relevant scales. While Sandia has extensive experience in R&D of falling particle curtain receivers, most have been at pilot scale and smaller - on the order of 1 MW th with characteristic dimensions of nominally 1-2 m to adequately collect solar energy from the heliostat field at the National Solar Thermal Test Facility (NSTTF). However, scaling up receivers to commercially relevant scales (25 MW th and above) will require a thorough understanding of particle curtain dynamics at larger scales, especially longer drop heights, for design certainty. The goal of this project will be to construct a cold falling particle curtain test rig capable of simulating particle characteristics that are expected in a commercial scale CSP plant, namely the drop height, curtain thickness, and particle mass flow rate (normalized by length of curtain). This will enable data collection on curtain opacity and spread, both of which are correlated to receiver efficiency and reliable construction, for commercially relevant scales. It will also permit validation of numerical models that will enable detailed receiver characterization and design past currently validated scales.

14 SOLAR ENERGY↗
DOE OSTI2025

Characterizing falling particle curtain receivers at commercially relevant scales: Research Performance Progress Report (RPPR-1)

Sandia will construct a cold flow receiver test platform in order to characterize falling particle curtain receivers at commercially relevant scales. While Sandia has extensive experience in R&D of falling particle curtain receivers, most have been at pilot scale and smaller - on the order of 1 MWth with characteristic dimensions of nominally 1-2 m to adequately collect solar energy from the heliostat field at the National Solar Thermal Test Facility (NSTTF). However, scaling up receivers to commercially relevant scales (25 MWth and above) will require a thorough understanding of particle curtain dynamics at larger scales, especially longer drop heights, for design certainty. The goal of this project will be to construct a cold falling particle curtain test rig capable of simulating particle characteristics that are expected in a commercial scale CSP plant, namely the drop height, curtain thickness, and particle mass flow rate (normalized by length of curtain). This will enable data collection on curtain opacity and spread, both of which are correlated to receiver efficiency and reliable construction, for commercially relevant scales. It will also permit validation of numerical models that will enable detailed receiver characterization and design past currently validated scales.

14 SOLAR ENERGY↗
DOE OSTI2025

Litter Production and Foliar Nutrient Resorption in Pioneer and Non-Pioneer Species in a Selective Logging Experiment in the Central Amazon, BIONTE, ZF-2, Manaus, 2022-23

This dataset was collected near the city of Manaus, Brazil, at the Experimental Station of Tropical Forestry (EEST, aka “ZF2”), inside the BIONTE (BIOmass and NuTrient Experiment). The experiment included three levels of increasing selective logging intensity, along with control, with 1-hectare permanent plots (12 total) located at the center of 4-hectare treatment plots. The vegetation has a high floristic diversity, the soils of the region are poor in nutrients, and the topography is characterized by plateaus (where BIONTE is located), and also valley bottoms and slopes. Three treatments of differing logging intensities were applied in the BIONTE experiment (T1, T2 and T3). The study was conducted in Treatment 3 (Block I – permanent plot), which represents the most intensive logging treatment, with 69% of the basal area (m²∙ha⁻¹) removed in 1988. The present dataset spans the period from May 1, 2022, to May 1, 2023. The data package includes leaf_nutrient_data, litterfall_total_data, leaf_litterfall_species_specific_data, and species_info, all provided in .csv format. These formats allow users to process and analyze the data in various software applications and programming languages, such as Python and R. This dataset was collected to advance knowledge on nutrient cycling in Amazonian forests, specifically distinguishing between species with two distinct functional traits: fast-growing and slow-growing. It also aims to improve Earth System Models, such as the E3SM Functionally Assembled Terrestrial Ecosystem Simulator (FATES). Additionally, it was used in a paper currently in preparation (Carvalho et al., in prep.), which aims to quantify seasonal litter production and foliar nutrient resorption in pioneer (fast-growing) and non-pioneer (slow-growing) tree species in the central Amazon. Specifically, it seeks to answer two key questions: 1) Is there a difference in leaf litter production, leaf nutrient flux and leaf nutrient concentration between pioneers and non-pioneers species? Is there a difference in the efficiency of foliar nutrient resorption between pioneers and non-pioneers species?

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Digital camera imagery for vegetation phenology, Seward Peninsula, Alaska, 2019-2021

Time lapse camera images from Kougarok mile marker (MM) 64 and Teller MM 27 NGEE-Arctic field sites on the Seward Peninsula, Alaska, captured from July 2019 to August 2021. Thirty three Wingscape Timelapse Pro cameras were deployed targeting patches of low and tall shrubs (including Alnus sp. and Salix sp.) and general vegetation and landscape views. Images from were recorded at hourly intervals from 11 AM to 2 PM, continuously for 25 months and capture vegetation phenology, snow accumulation and snow melt events. This data package includes images (*.jpg), organized by site and camera ID, and metadata with details of the cameras used, number of images recorded, start and end dates, GPS locations and example fields of view. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Digital camera imagery for vegetation phenology, Seward Peninsula, Alaska, 2022-2023

Timelapse camera images from Council Mile Marker (MM) 71, Kougarok MM 64, Kougarok Fire Complex (KFC), and Teller MM 27 NGEE-Arctic field sites on the Seward Peninsula, Alaska, captured from July 2022 to July 2023. Eight Wingscape Timelapse Pro cameras, and thirty-one Power-interval Camera Automation Modules (PiCAMs) designed by Brookhaven National Laboratory?s Terrestrial Ecosystem Science and Technology (TEST) group were deployed targeting patches of low and tall shrubs (including Alnus sp. and Salix sp.) and general vegetation and landscape views. Images from Wingscape cameras were recorded at hourly intervals from 11 AM to 2 PM, and images from PiCAMs were recorded at 5 hourly intervals from 12 AM to 8 PM, continuously for 12 months and capture vegetation phenology, snow accumulation and snow melt events. This data package includes images (*.jpg), organized by site and camera ID, and metadata with details of the cameras used, number of images recorded, start and end dates, GPS locations and example fields of view. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape: Modeling Archive

This modeling archive is in support of the Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) publication "Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape", by Murphy et al. (2025). This archive contains model input files and outputs from landscape-scale simulations conducted using ELM, the land model component of the Department of Energy’s Energy Exascale Earth System Model (E3SM), at the Council NGEE Arctic field site (Council Road mile marker 71) on Alaska’s Seward Peninsula. Input data and model output from two sets of ELM simulations are provided. The first set of simulations were conducted with the two default ELM Arctic plant functional types (PFTs; broadleaf deciduous boreal shrub and a C3 grass) and the second set of simulations were conducted with a set of nine Arctic-specific PFTs including nonvascular mosses and lichens, graminoids, forbs, evergreen dwarf shrubs, three height classes of deciduous shrubs (dwarf, low, and low to tall), and deciduous alder shrubs (Sulman et al., 2021). Parameter names and major parameter changes in the Arctic-specific PFT configuration are described in Sulman et al. (2021) and archived in the Sulman et al. (2021) dataset (see below). Simulations were spatially explicit, covering an approximately 6.4X3.3 km domain at the Council site with a spatial resolution of 100 m for a total of 2,112 simulated grid cells under each ELM PFT configuration. The modeling archive contains meteorological forcing (seven *.nc files and one *.txt file), a domain definition file (one *.nc files), land surface configuration files (two *.nc files), parameter files (two *.nc files), annual ELM output files spanning 1980-2014 (68 *.nc files), and a User’s Guide (*pdf file). Additional information on the provided files is in the “Modeling Archive Contents” section of the User’s Guide. Model outputs are aggregated to the column scale (i.e. PFT-specific outputs are not provided here).

Murphy, Bailey [ORNL] (ORCID:0000000203995221)↗
DOE OSTI2025

Mortality correlates with tree functional traits across a wood density gradient in the Central Amazon

Introduction: Understanding the mechanisms of tree mortality in tropical ecosystems remains challenging, in part due to the high diversity of tree species and the inherently stochastic nature of mortality. Plant functional traits offer a mechanistic link between plant physiology and performance, yet their ability to predict growth and mortality remains poorly understood. Given recent increases in tree mortality rates in the Amazon forest following extreme drought and wind events, we tested if lower wood density and acquisitive plant functional traits were associated with increased growth and mortality for common co-occurring trees in the Central Amazon. Methods: Seventeen trees of different species with similar sizes but a range in wood density (WD) and wood traits were felled, then assessed for 27 different individual functional parameters, including whole tree architecture, stem xylem anatomical and hydraulic traits and leaf traits. Traits of the individual trees were related to stand-level growth and mortality rates collected periodically over 30 years from nearby permanent inventory plots. Results: Higher wood density was associated with smaller leaf size, lower foliar base cations, lower stem water content and sapwood fraction, in agreement with the fast-slow plant economics spectrum. Lower wood density was associated with more acquisitive characteristics with greater hydraulic capacity and foliar nutrient concentrations, correlating with greater growth and mortality rates. Discussion: Our results show that lower wood density is part of a coordinated suite of traits linked to high resource acquisition, fast growth, and increased mortality risk, providing a functional framework for predicting species performance and forest vulnerability under future climate stress.

demographics↗
DOE OSTI2025

Root‐Pore Interactions, the Underestimated Driver for Rhizosphere Structure and Rhizosheath Development

Physical characteristics of rhizosphere and rhizosheath, that is, root-adhering soil, are crucial for plant performance. Yet, the drivers of the rhizosphere's structural properties and their relationships with rhizosheath development remain unclear. We used X-ray computed micro-tomography (i) to explore two drivers of rhizosphere porosity: root-induced changes vs. preferential root growth into soil with certain pore characteristics and (ii) to estimate their contributions to rhizosphere macroporosity gradients and rhizosheath formation. Rhizosheath development was assessed in relation to rhizosphere macroporosity and rhizodeposition after ¹⁴C labeling. Our results confirmed that both root-induced changes and growth preferences shape rhizosphere structure, with their relative significance depending on the inherent macropore availability. In intact soils, growth preferences were the dominant factor, while in sieved soils the root-induced changes became equally important. Rhizosheath formation was associated with roots compacting their surrounding and releasing carbon. However, no correlation was found between rhizosheath formation and the actual rhizosphere, that is, the volume of soil adjacent to the roots. The study offers new process-level understanding of rhizosphere porosity gradients, while emphasizing caution in interpreting root growth data from sieved soil studies. Similarly, traditional destructively sampled rhizosheath may not fully capture the true characteristics of the actual rhizosphere, underscoring importance of intact-soil analyses.

macroporosity gradients↗
DOE OSTI2024

Inverter Intensive Hybrid Power Plant Modeling with Small-Signal Stability Augmentation through Flexible Operation Mode Transition

Hybrid power plants (HPPs) prompt the penetration of inverter-based renewable energy sources (RES) in transmission systems; however, given their low-inertia nature, HPPs are dominated by power electronic inverters, so there are inevitable challenges in system stability when increasing numbers of HPPs are integrated into the modern power grids. To boost the penetration level of HPPs without jeopardizing system stability, it is desirable to equip them with operational characteristics (i.e., grid-forming capabilities) that are comparable to those of conventional power plants dominated by synchronous generators (SGs). In this paper, a holistic model of inverter intensive HPP is derived and a bi-level hierarchical control is developed to allow HPPs to flexibly switch among the designed operation modes (i.e., P-Q, P-V, and isochronous modes). Compared to SGs, which have limited controllability, the operation mode of each HPP could vary as requested. Such flexible mode transitions could be integrated into the secondary plant-level control and be leveraged as an additional control degree to further augment system stability. Further, the system small-signal stability margin is quantified with varying HPP operation modes. More importantly, modal analysis is thereby conducted to quantify the impacts of mode transition on the system oscillatory modes. The effectiveness of the proposed HPP bi-level hierarchical control is verified using extensive case studies based on the simplified real-world island power grid, and the results validate that the system small-signal stability margin can be enhanced with the additional degree of control flexibility enabled by HPP operation mode transition. The real-time hardware-in-the-loop (HIL) results are also provided to verify the proposed method.

grid-forming control↗
DOE OSTI2025

Compositing and Characterization of SE Quadrant Waste Exemplars

This report outlines the experimental investigation and characterization of transport properties in Hanford SE quadrant High-Level Waste (HLW). The goal of the study was to establish baseline behaviors of bulk composite rheology and settling characteristics to facilitate waste treatment process design for the Waste Treatment and Immobilization Plant (WTP) and avoid waste conditions and properties favorable to bubble cascade gas release events. The study focused on two major objectives: 1) identifying, obtaining, and preparing relevant Hanford tank waste samples for evaluation and 2) quantifying the “as-received” rheology and transport properties of the samples. Twenty-three centrifuged core segments originating from tanks AN-101, AN-106, and AW-105 were selected based on compositional relevance to SE quadrant PUREX cladding waste. These materials were composited into five waste composites enriched with target analytes: aluminum (Al), iron (Fe), phosphate (PO 4 ), uranium (U), and zirconium (Zr). Physical property and transport testing examined particle size distributions, bulk densities, settling behaviors, rheological properties, shear strengths, and just-suspended mixing speeds (NJS). Testing revealed two distinct composite classifications based on rheological characteristics: non-Newtonian composites (Fe and PO 4 ) and Newtonian composites (Al, U, and Zr). The Fe and PO 4 composites exhibited slow settling rates and reduced mobilization proclivity, attributable to strong particle-particle interactions and the formation of yield structures within non-Newtonian slurries. In contrast, the Al, U, and Zr composites displayed rapid settling and dense compaction behaviors, indicative of minimal structuring and interactions. Shear strengths for all composites were generally low relative to prior studies of SE quadrant waste, with only the U composite showing elevated strength approaching values reported in previous literature. Repeat shear strength measurements revealed contributions from dense granular material in the U composite and stronger cohesive properties in the Al composite. Settling data highlighted hindered settling behavior, with rates falling more than one order of magnitude below estimates based on Stokes’ law and rate decreasing as composite UDS content increased. NJS testing demonstrated different mobilization behaviors between cohesive and granular composites. The Fe composite required the highest mixing rate for resuspension, while the Al composite was the easiest to resuspend. Comparison of measured NJS against predictions made using the Zwietering correlation suggests non-Newtonian behavior alters resuspension mechanics, rendering non-Newtonian systems more stable against resuspension lift forces relative to their granular counterparts.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Tropical root responses to global changes: A synthesis

Tropical ecosystems face escalating global change. These shifts can disrupt tropical forests' carbon (C) balance and impact root dynamics. Since roots perform essential functions such as resource acquisition and tissue protection, root responses can inform about the strategies and vulnerabilities of ecosystems facing present and future global changes. However, root trait dynamics are poorly understood, especially in tropical ecosystems. We analyzed existing research on tropical root responses to key global change drivers: warming, drought, flooding, cyclones, nitrogen (N) deposition, elevated (e) CO 2 , and fires. Based on tree species- and community-level literature, we obtained 266 root trait observations from 93 studies across 24 tropical countries. We found differences in the proportion of root responsiveness to global change among different global change drivers but not among root categories. In particular, we observed that tropical root systems responded to warming and eCO 2 by increasing root biomass in species-scale studies. Drought increased the root: shoot ratio with no change in root biomass, indicating a decline in aboveground biomass. Despite N deposition being the most studied global change driver, it had some of the most variable effects on root characteristics, with few predictable responses. Episodic disturbances such as cyclones, fires, and flooding consistently resulted in a change in root trait expressions, with cyclones and fires increasing root production, potentially due to shifts in plant community and nutrient inputs, while flooding changed plant regulatory metabolisms due to low oxygen conditions. The data available to date clearly show that tropical forest root characteristics and dynamics are responding to global change, although in ways that are not always predictable. This synthesis indicates the need for replicated studies across root characteristics at species and community scales under different global change factors.

54 ENVIRONMENTAL SCIENCES↗