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NASA NTRSDate not supplied

TPSAS-NF1676L-11678-DND

Cloud vertical profiles retrieved from CALIPSO and CloudSat data provide additional information that greatly improves the estimate of atmospheric radiative heating rates and potentially improves the estimate of the global surface radiation budget. To utilize CALIPSO and CloudSat cloud vertical profiles, we combined their profiles and generated merged profiles. Weused the merged cloud profiles and MODIS derived cloud profiles by the CERES cloud algorithm in irradiance computations. In this study, the improvement of the irradiance by CALIPSO and CloudSat derived merged cloud vertical profiles is evaluated by comparing modeled irradiances with and without merged cloud profiles. Because of lower cloud base heights provided by the merged profiles compared with cloud base heights derived from an empirical formula using the MODIS derived cloud top height and optical thickness, the global annual mean surface longwave downward irradiance increases approximately by 7 Wm-2. While CALIPSO version 3 data have not been incorporated in the irradiance computation and the effect of the new CALIPSO data needs to be assessed, a comparison with surface observations suggests an improvement of surface downward longwave irradiance computations. The surface downward longwave irradiance computed with CALIPSO and CloudSat merged clouds agrees better with surface observations than the irradiance computed with MODIS only does. The bias difference over ARM SGP sites with 2 years of data decreases from -5 W m-2to -2 Wm-2, and it decreases from -9 Wm-2to no bias over polar validation sites. The result suggests that CALIPSO CloudSat derived merged clouds significantly improve surface longwave irradiance estimates once they are combined with MODIS derived cloud properties and with temperature and humidity profiles from reanalysis.

Seiji Kato↗

NASA NTRS2020

Monitoring Water-Related Ecosystems with Earth Observation Data in Support of Sustainable Development Goal (SDG) 6 Reporting

Lack of national data on water-related ecosystems is a major challenge to achieving the Sustainable Development Goal (SDG) 6 targets by 2030. Monitoring surface water extent, wetlands, and water quality from space can be an important asset for many countries in support of SDG 6 reporting. We demonstrate the potential for Earth observation (EO) data to support country reporting for SDG Indicator 6.6.1, ‘Change in the extent of water-related ecosystems over time’ and identify important considerations for countries using these data for SDG reporting. The spatial extent of water-related ecosystems, and the partial quality of water within these ecosystems is investigated for seven countries. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 5, 7, and 8 with Shuttle Radar Topography Mission (SRTM) are used to measure surface water extent at 250 m and 30 m spatial resolution, respectively, in Cambodia, Jamaica, Peru, the Philippines, Senegal, Uganda, and Zambia. The extent of mangroves is mapped at 30 m spatial resolution using Landsat 8 Operational Land Imager (OLI), Sentinel-1, and SRTM data for Jamaica, Peru, and Senegal. Using Landsat 8 and Sentinel 2A imagery, total suspended solids and chlorophyll-a are mapped over time for a select number of large surface water bodies in Peru, Senegal, and Zambia. All of the EO datasets used are of global coverage and publicly available at no cost. The temporal consistency and long time-series of many of the datasets enable replicability over time, making reporting of change from baseline values consistent and systematic. We find that statistical comparisons between different surface water data products can help provide some degree of confidence for countries during their validation process and highlight the need for accuracy assessments when using EO-based land change data for SDG reporting. We also raise concern that EO data in the context of SDG Indicator 6.6.1 reporting may be more challenging for some countries, such as small island nations, than others to use in assessing the extent of water-related ecosystems due to scale limitations and climate variability. Country-driven validation of the EO data products remains a priority to ensure successful data integration in support of SDG Indicator 6.6.1 reporting. Multi-country studies such as this one can be valuable tools for helping to guide the evolution of SDG monitoring methodologies and provide a useful resource for countries reporting on water-related ecosystems. The EO data analyses and statistical methods used in this study can be easily replicated for country-driven validation of EO data products in the future.

water-related ecosystems; surface water extent; ma↗

NASA NTRSDate not supplied

Battery Evaluation Profiles for X-57 and Future Urban Electric Aircraft

Battery energy density is one of the most critical design parameters for sizing all-electric aircraft, however it’s easily overestimated. Establishing the effective, usable energy density is confused by varying degrees of margin needed to account for structural and thermal management between different cell chemistry and pack designs. Therefore, a better methodology is needed to fairly compare emerging battery technologies for electric aircraft. Currently, there is a loss of critical information when vehicle trade studies are performed using “nominal” published cell-level performance metrics. Aircraft power demands rarely match these nominal power profiles, and aircraft designers lack the ability to accurately simulate the battery performance and temperature off-nominally unless the battery chemistry is well established. Conversely, battery suppliers have no generalized reference cases to publish more realistic performance metrics. This can lead to poor assumptions, such as aircraft studies assuming a fixed discharge efficiency of a battery, when in reality the usable energy in a pack is dependent on the power and thermal profile. Information needed to properly assess weight penalties for thermal management is also typically poorly characterized when assessing candidate batteries. This paper serves to better inform battery development, and similarly, provide aircraft designers with more realistic assumptions for applying knockdown margins in their designs. Detailed power and thermal performance estimates are provided, which provide a starting point for sizing power and thermal budgets using experimentally derived battery models. Results show that the X-57 battery-to-shaft efficiency is 77.3% for a particular optimized mission. Considering a 25% reserve on the battery capacity, this means that only roughly half of the original 55.3kWh ‘nominal’ pack energy can be converted to useful work during a mission. Further estimates on a clean-sheet VTOL optimization show an average 82.7% battery-to-shaft efficiency, using 98% peak efficiency inverters and 97.4% peak efficiency motors. Although higher battery efficiencies are possible, the resulting weight penalty negates improvement in vehicle performance. These trade-offs and resulting power profiles are provided as a starting point to better assess future battery designs.

Battery Electric Aircraft↗

NASA NTRSDate not supplied

Battery Evaluation Profiles for X-57 and Future Urban Electric Aircraft

Battery↗

NASA NTRS2021

Technology Readiness Level (TRL) as the foundation of Human Readiness Level (HRL)

As space programs became more complex, it became evident to NASA that a means of defining a methodological way to evaluate the maturity of technologies for spacecraft design was needed for risk assessment that could affect technical, cost and schedule. NASA first saw that infusing technology intoNASA programs required some means to assess technology maturity like flight readiness for a mission. Hence, a seven-point technology readiness level scale was developed in the mid-70s by a NASA researcher and later formally defined in 1989 (Sadin et al., 1989) that comprised of seven levels (See Table 1). These levels provided a definitive meaning of what complexity a research and technology development program should be followed. NASA recognized the approach as a useful way of an effective assessment of,and communication regarding the maturity of new technologies, using a simplistic figure of merit, the state of maturity of a technology-particularly, critical technology necessary to meet a mission/application objective

George Salazar↗

NASA NTRS2020

Monitoring Water-Related Ecosystems with Earth Observation Data in Support of Sustainable Development Goal (SDG) 6 Reporting

Lack of national data on water-related ecosystems is a major challenge to achieving the Sustainable Development Goal (SDG) 6 targets by 2030. Monitoring surface water extent, wetlands, and water quality from space can be an important asset for many countries in support of SDG 6reporting. We demonstrate the potential for Earth observation (EO) data to support country reporting for SDG Indicator 6.6.1, ‘Change in the extent of water-related ecosystems over time’ and identify important considerations for countries using these data for SDG reporting. The spatial extent of water-related ecosystems, and the partial quality of water within these ecosystems is investigated for seven countries. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 5, 7, and 8 with Shuttle Radar Topography Mission (SRTM) are used to measure surface water extent at 250 m and 30 m spatial resolution, respectively, in Cambodia, Jamaica, Peru, the Philippines, Senegal, Uganda, and Zambia. The extent of mangroves is mapped at 30 m spatial resolution using Landsat 8 Operational Land Imager (OLI), Sentinel-1, and SRTM data for Jamaica, Peru, and Senegal. Using Landsat 8 and Sentinel 2A imagery, total suspended solids and chlorophyll-a are mapped overtime for a select number of large surface water bodies in Peru, Senegal, and Zambia. All of the EO datasets used are of global coverage and publicly available at no cost. The temporal consistency and long time-series of many of the datasets enable replicability over time, making reporting of change from baseline values consistent and systematic. We find that statistical comparisons between different surface water data products can help provide some degree of confidence for countries during their validation process and highlight the need for accuracy assessments when using EO-based land change data for SDG reporting. We also raise concern that EO data in the context of SDG Indicator 6.6.1reporting may be more challenging for some countries, such as small island nations, than others to use in assessing the extent of water-related ecosystems due to scale limitations and climate variability. Country-driven validation of the EO data products remains a priority to ensure successful data integration in support of SDG Indicator 6.6.1 reporting. Multi-country studies such as this one can be valuable tools for helping to guide the evolution of SDG monitoring methodologies and provide a useful resource for countries reporting on water-related ecosystems. The EO data analyses and statistical methods used in this study can be easily replicated for country-driven validation of EO data products in the future.

Raha Hakimdavar↗

NASA NTRS2022

NASA Analysis of Alternatives Study for Icing Research

In 2020, NASA’s Aeronautics Research Mission Directorate commissioned a study of the icing research area to provide a broad and comprehensive assessment of priority needs for NASA and enduring needs for the aviation community. Priority needs were those that supported four key focus areas for NASA Aeronautics—Transonic Truss-Braced Wing, Electrified Aircraft Propulsion, Small-Core Turbine Engine, and High-Rate Composite Manufacturing—as well as other priority areas, such as Advanced Air Mobility, Certification by Analysis, and Commercial Supersonic Technology. Enduring needs were the additional long-term capabilities and expertise identified by the aviation community as being critical for NASA to provide. This study is called an Analysis of Alternatives (AoA) because a large number of icing research needs were identified and analyzed to determine the highest priorities for NASA key focus areas and those that will endure into the future. This report offers a detailed description and results of the AoA study for icing research.

Aircraft Icing, Aircraft Icing, Rotorcraft Icing, ↗

NASA NTRSDate not supplied

Maipo River Valley Agriculture: Determining Crop Coefficients Using Remote Sensing for the Maipo River Valley Basin in Chile

Agriculture is the primary use of water in the Maipo River basin of Central Chile, accounting for ~ 75% of the total demand. Assessment of irrigation needs for agricultural production has commonly relied on reference crop coefficients (Kc) derived from geographic and climatic conditions that differ from those of Chile. In partnership with the Centro de Información de Recursos Naturales (CIREN), this work focused on calculating site-specific crop coefficients tailored to crop production in the water-stressed Maipo River Valley. Two distinct approaches were implemented, each relying on remotely-sensed Earth observation datasets from NASA over consecutive growing seasons from 2019 to 2022. The first method estimated Kc values based on their linear relationship with the Normalized Difference Vegetation Index (NDVI) obtained from either Terra Moderate Resolution Imaging Spectroradiometer (MODIS) or Landsat 8 Operational Land Imager (OLI) surface reflectance. The second technique leveraged information from the ISS Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) by computing the ratio between actual crop evapotranspiration (ET) and potential evapotranspiration (PET). Both procedures showed promising results that can build on one another. The former approach best captured vegetation signals of annual crops while the latter appeared suited for perennials. Overall, this study provides a strong basis and novel way to accurately estimate Kc using remote sensing, with the potential for improved irrigation management and reduction in water consumption.

Benjamin Goffin↗

NASA NTRSDate not supplied

Determining Crop Coefficients Using Remote Sensing for the Maipo River Valley Basin in Chile

Agriculture is the primary use of water in the Maipo River Valley of Central Chile, accounting for ~ 75% of the total demand. Assessment of irrigation needs for agricultural production has commonly relied on reference crop coefficients (Kc) derived from geographic and climatic conditions that differ from those of Chile. This work focused on calculating site-specific Kc values tailored to crop production in the water-stressed Maipo River Valley over consecutive growing seasons from 2019 to 2022. Two distinct approaches were implemented, each relying on remotely-sensed NASA Earth observation datasets. The first method estimated Kc values based on the linear relationship with the Normalized Difference Vegetation Index (NDVI) obtained from either Terra Moderate Resolution Imaging Spectroradiometer (MODIS) or Landsat 8 Operational Land Imager (OLI) surface reflectance. The second technique leveraged information from the ISS Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) by computing the ratio between actual crop evapotranspiration and potential evapotranspiration. The former approach best captured vegetation signals of annual crops while the latter appeared best suited for perennials. Overall, this study provides a strong basis and novel way to accurately estimate Kc using remote sensing, with the potential for improved irrigation management and reduction in water consumption.

Rishudh Thadur↗

NASA NTRSDate not supplied

Formation of Tropopause Cirrus clouds by Typhoon-induced gravity waves during the Asian Summer Monsoon: A Case Study from the BATAL 2017 Campaign

Cirrus clouds in the Tropical Tropopause Layer (TTL) have a net warming impact on Earth’s climate and they regulate the amount of water vapor entering the lower stratosphere through dehydration process near the cold-point tropopause. During the Boreal summer, Asian Summer Monsoon (ASM) is an important source of cirrus clouds and humidity in the TTL owing to frequent deep convection. However, better representation of convection and TTL cirrus clouds in global climate models is needed for accurate assessment of their response to changing climate. In this study, we investigate the mechanisms involved in the formation of a tropopause cirrus cloud layer observed during the Balloon measurement campaigns of the Asian Tropopause Aerosol Layer (BATAL) over Hyderabad (17.47 °N, 78.58 °E), India on 23 August 2017. A subvisible cirrus cloud layer (optical thickness ~0.025) was detected by a backscatter sonde (COBALD) onboard a balloon near the cold-point tropopause (CPT, temperature~ -86.4 ° C, altitude~17.9 km) which was later confirmed by the CATS lidar on the ISS. Simultaneous measurements from an optical particle counter (Boulder Counter) revealed the presence of ice crystals smaller than 50 microns in this layer. The formation mechanism responsible for this tropopause cirrus is investigated using a technique combining three-dimensional back-trajectories, satellite observations, and ERA5 reanalysis data. Satellite observations revealed that the overshooting convection associated with a category-3 typhoon Hato, which hit Macau and Hong Kong on 23 August 2017 injected ice into the lower stratosphere. This caused a hydration patch that followed the ASM anticyclone subsequently moving towards Hyderabad. The presence of tropopause cirrus cloud layers in the cold temperature anomalies and updrafts along the back-trajectories indicated towards the role of typhoon-induced gravity waves in their formation. This case study highlights the role of typhoons in influencing the formation of tropopause cirrus clouds through stratospheric hydration and gravity waves in the ASM anticyclone.

Amit Kumar Pandit↗

NASA NTRSDate not supplied

Evaluation of TAO Observation System on ENSO Predictions from the GMAO S2S Forecast System

Since the early 1990’s, the Tropical Atmosphere Ocean (TAO) mooring array has been instrumental for observing Kelvin and Rossby wave propagation which is key for El Nino/Southern Oscillation (ENSO) prediction. However, recent funding and programmatical issues have highlighted the need to rigorously assess the impact of the TAO observing system on ENSO predictions. Therefore, we evaluate the TAO using data assimilation observation denial experiments (also known as Observing System Evaluation or OSE experiments). This presentation will evaluate the TAO observing impact on both reanalyses and prediction of the big 2015 El Nino. We have completed reanalyses for July 2014-Dec 2015 for both the CONTROL experiment (that assimilates all available data) and the NOTAO experiment (that is identical to the CONTROL but withholds all TAO observations) using the best available NASA GEOS-S2S V3 seasonal prediction system. Validation of these reanalyses shows that TAO assimilation generally improves comparisons of temperature and salinity versus gridded in situ observations. Temperature is universally improved above the thermocline near the equator, but the biggest improvement is found in the eastern Pacific, just below the thermocline, where the variation of the thermocline defines ENSO events. In addition, a surprising result is that even with relatively few observations, salinity is improved throughout the equatorial region except near 120oW near the surface. ENSO forecasts were performed that were initialized from these CONTROL and NOTAO reanalyses. For the 9-month forecasts which were initialized in January, July, and October 2015, the NINO3.4 SST shows that the CONTROL forecasts are warmer and closer to observations than the NOTAO forecasts. We will show that upwelling and shoaling of the mixed layer amplifies the ENSO signal due to TAO assimilation. Prior to (after) April 2015, this upwelling is caused by relatively stronger Rossby (Kelvin) waves in the CONTROL than in the NOTAO experiments.

E. Hackert↗

DOE OSTI2023

Geographically Dependent Sustainability Indicators for Comparison of Conventional Vegetable Production to Controlled-Environment Agriculture

Many food system lifecycle analyses distill agricultural production and supply chain impacts into single-value sustainability metrics for various food categories. These studies provide an overview of the food supply system that highlight striking results such as the GHG impacts of meat production. The supply chain impacts of vegetable production occupy the middle ground; higher than average food loss and waste, lower than average overall energy use, etc. However, aggregated results obscure the sustainability implications of the location of food production, especially for vegetables. Moreover, the increasing instability of food production systems are not captured, as illustrated by a recent Washington Post article. According to a UC Merced study conducted for the state, California farmers left nearly 400,000 acres of agricultural land unplanted last year because of a lack of water. The result, the study found, was a direct economic cost to farmers of $1.1 billion and the loss of nearly 9,000 agricultural jobs. (The Washington Post, March 21, 2022.) Previous work quantified the food-energy-water nexus implications of transitioning vegetable production from large, centralized agricultural operations to smaller distributed production in controlled-environment farms (CEA). The importance of location-specific data is especially evident for water use. Water impacts of the food system are primarily local to the region where food is produced, water impacts vary significantly between locations, and water stress is a major concern in locations that currently host large agricultural operations. Location-specific data is needed to accurately assess the water impacts of transitioning to CEA. The location of farms in relation to consumers impacts transportation energy use, food loss and waste, and requirements for food processing (e.g., to reduce weight, preserve foods for long storage, and package foods to reduce damage and loss) Reducing transport is particularly relevant for agricultural products that could be grown in CEAs (fruits, vegetables, protein). Access to nutritious food is not evenly distributed in the population. Remote communities, communities in harsh environments, and economically-disadvantaged communities often have poor access to healthy foods. CEA is ideally suited to these environments. However, the energy and water use of CEA, while in many respects lower overall than conventional supply chains, are concentrated within communities and could have significant local impacts. This paper reports on development of sustainability metrics that seek to capture the tradeoffs between the current supply chain and a CEA supply chain for vegetables; focusing on the location-dependent implications of water use, the transition from largely fossil fuel based energy use to electricity, and the food access, resilience and wellbeing implications of urban versus rural food production.

controlled-environment agriculture↗

DOE OSTI2024

Application of Banking Scoring and Rating for Coherent Risk Measures in Electricity Systems ABSCORES

This project developed a framework for asset and system risk management that can be incorporated into current electricity system operations to improve economic efficiency and establish an Electric Assets Risk Bureau. We leveraged scoring and ratings from banking and financial institutions alongside current optimization methods in dispatching power systems to help system operators and electricity markets schedule resources. This approach is based on the observation that there are major discrepancies between the power scheduled by a system operator and the actual power generated/consumed. These discrepancies—exacerbated by unplanned contingencies (e.g., natural disasters)—are caused by multiple factors, including the different financial, environmental and risk preferences of power producers, consumers, and aggregators. We developed a framework that counteracts two failures in electricity system operations: imperfect information and missing markets for products. The technical approach included five tasks. Tasks 1 and 2 supported the development of risk scores at the asset level with historical data collected for this project. Tasks 3, 4, and 5 incorporated scoring into decision-making at the system level. The proposed effort achieved PERFORM's Program Objectives because the proposed outputs and algorithms do not exist in the electricity industry and are an innovative approach to managing risk. Since the acknowledged need to better assess and act upon risk profiles for grid assets has not been met by the industry, this project will also impact ARPA-E's Mission Areas, including improving energy efficiency and giving the U.S. a technological lead in advanced energy technologies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Using Calibrated Sodium Data for Preliminary Validation of the SRT Code for Advanced Reactors

Various types of non-light water reactors are currently engaged in the U.S. licensing process. Because of inherent differences compared with well-established large light water reactors, appropriate assessment tools are needed. Specifically, source term analysis, which determines environmental dose impacts from potential accident scenarios, is a crucial part of design and licensing. The U.S. Nuclear Regulatory Commission has emphasized the importance of mechanistic source term analysis for advanced reactor deployments. To align with these needs, Argonne National Laboratory has developed the Simplified Radionuclide Transport (SRT) source term analysis code for metal fuel Sodium-cooled Fast Reactors (SFRs) and microreactors. SRT conducts time-dependent radionuclide transport and retention in SFRs for core and ex-core radionuclide source accident sequences. The main objective of SRT is to provide rapid sensitivity and uncertainty analyses, incorporating parametric uncertainties and summarizing probabilistic results. As part of the code validation process, a study focused on the bubble scrubbing module was performed using an experiment recently carried out by the University of Wisconsin-Madison. Based on the analysis, the modeling approach in SRT provides accurate results for small and large aerosols, while slight underprediction of radionuclide aerosol removal are observed for medium sized aerosols. However, the deviation is minor, considering the highly uncertain phenomenon and range of results, and is in the conservative direction. In addition, uncertainty information derived from the experiments is further implemented, reflecting the actual span of parameters, which leads to enhanced agreement with code predictions. The results demonstrate that SRT provides reasonable predictions for the bubble scrubbing process in sodium pool.

Kam, Dong Hoon↗

DOE OSTI2025

Development and Validation of Two-Phase Flow Models in MOOSE and Application to Molten Salt Reactors

Two-phase flow in Molten Salt Reactors (MSRs) is important as it impacts reactivity evolution, reactor transient response, and the removal of species dissolved in the molten salt through gas phase transfer. Therefore, accurately predicting the gas distribution and the associated liquid-gas interface area in MSRs is essential for their design and operation. Recently, we integrated a new two-phase model into Idaho National Laboratory (INL)’s Multiphysics Object-Oriented Simulation Environment (MOOSE): a multi-D generalization of a mixture drift-flux model. It provides greater computational efficiency, which is typically preferred for modeling reactor transients. However, the mixture model’s accuracy in capturing void distribution and interfacial area in MSRs still needs to be assessed. This article begins with a description of the mathematical framework for the two-phase model implemented in MOOSE. It then presents validation of these models against relevant experimental data. Finally, the model is applied to the Molten Salt Reactor Experiment case study, analyzing various operational conditions such as different rates of fission product volatilization and diverse cover gas entrainment scenarios at the reactor pump. The article concludes by assessing the suitability of the mixture drift-flux model for capturing the two-phase flow dynamics critical to MSR operations

42 - ENGINEERING↗

DOE OSTI2025

Development and Validation of Two-Phase Flow Models in MOOSE for Molten Salt Reactor Application

Two-phase flow in Molten Salt Reactors (MSRs) is important as it impacts reactivity evolution, reactor transient response, and the removal of species dissolved in the molten salt through gas phase transfer. Therefore, accurately predicting the gas distribution and the associated liquid-gas interface area in MSRs is essential for their design and operation. Recently, we integrated two new models into Idaho National Laboratory (INL)’s Multiphysics Object-Oriented Simulation Environment (MOOSE): a multi-D generalization of a mixture drift-flux model and a Euler-Euler model. The Euler-Euler model offers higher fidelity, while the mixture drift-flux model provides greater computational efficiency, which is typically preferred for modeling reactor transients. However, the mixture model's accuracy in capturing void distribution and interfacial area in MSRs still needs to be assessed. This article begins with a description of the mathematical framework for the two-phase models implemented in MOOSE. It then presents validation of these models against relevant experimental data. Finally, both models are applied to the Molten Salt Reactor Experiment case study, analyzing various operational conditions such as different rates of fission product volatilization and diverse cover gas entrainment scenarios at the reactor pump. The article concludes by assessing the suitability of both models for capturing the two-phase flow dynamics critical to MSR operations.

42 - ENGINEERING↗

DOE OSTI2025

Development and Validation of Two-Phase Flow Models in MOOSE and Application to Molten Salt Reactors

Two-phase flow in Molten Salt Reactors (MSRs) is important as it impacts reactivity evolution, reactor transient response, and the removal of species dissolved in the molten salt through gas phase transfer. Therefore, accurately predicting the gas distribution and the associated liquid-gas interface area in MSRs is essential for their design and operation. Recently, we integrated two new models into Idaho National Laboratory (INL)’s Multiphysics Object-Oriented Simulation Environment (MOOSE): a multi-D generalization of a mixture drift-flux model and a Euler-Euler model. The Euler-Euler model offers higher fidelity, while the mixture drift-flux model provides greater computational efficiency, which is typically preferred for modeling reactor transients. However, the mixture model's accuracy in capturing void distribution and interfacial area in MSRs still needs to be assessed. This article begins with a description of the mathematical framework for the two-phase models implemented in MOOSE. It then presents validation of these models against relevant experimental data. Finally, both models are applied to the Molten Salt Reactor Experiment case study, analyzing various operational conditions such as different rates of fission product volatilization and diverse cover gas entrainment scenarios at the reactor pump. The article concludes by assessing the suitability of both models for capturing the two-phase flow dynamics critical to MSR operations.

42 - ENGINEERING↗

DOE OSTI2024

Technical Information Needs and Regulatory Considerations for Front-End Transportation Activities of HALEU Fuel Feed Material

This report fulfills task order number 31310022F0033 Task 1 Assessment of technical information needs and considerations for front-end transportation activities for HALEU fuel feed material. This assessment primarily focuses on the transportation outlook and packaging requirements for transporting high-assay low-enriched uranium (HALEU) fuel feed material. The regulatory framework is described in section 3.0. In section 4.0 the specific issues associated with reviewing HALEU feed material packages are discussed. The rest of the report discusses the need for new packages and Department of Energy progress on HALEU production. Through this evaluation it is shown that the 5% enrichment barrier between low-enriched uranium and HALEU is a significant challenge to transportation packaging. However, there are licensed designs and concepts that can be used to transport HALEU feedstock. No significant issues were identified through the HALEU range up to 20% enriched.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗