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At least 55 records · Page 3

Electricity Baseline 2021

The Electricity Baseline (2021) is a regionalized life cycle inventory model of U.S. electricity generation, consumption, and distribution using standardized facility and generation data and was created using the ElectricityLCI v2 Python package (https://github.com/USEPA/ElectricityLCI/tree/v2.0). The Python package used the "ELCI_2021" model configuration to set the facility and generation data sources and years that were used to create this life cycle inventory, which were taken from publicly accessible datasets and automatically curated into a local data store. An archive of the data stores used in this model is available online: https://doi.org/10.18141/2569576. This model is presented in GreenDelta's openLCA schema v2 JSON-LD format (https://greendelta.github.io/olca-schema/).

Electricity; LCA; LCI; Life Cycle↗

Electricity Baseline 2020

The Electricity Baseline (2020) is a regionalized life cycle inventory model of U.S. electricity generation, consumption, and distribution using standardized facility and generation data and was created using the ElectricityLCI v2 Python package (https://github.com/USEPA/ElectricityLCI/tree/v2.0). The Python package used the "ELCI_2020" model configuration to set the facility and generation data sources and years that were used to create this life cycle inventory, which were taken from publicly accessible datasets and automatically curated into a local data store. An archive of the data stores used in this model is available online: https://doi.org/10.18141/2569605. This model is presented in GreenDelta's openLCA schema v2 JSON-LD format (https://greendelta.github.io/olca-schema/).

Electricity; LCA; LCI; data inventory↗

SLICE

For most of their lifetime, pebble-bed reactors (PBRs) operate at an equilibrium state in which the core is filled with fuel pebbles at various levels of burnup. A fuel pebble travels multiple times in so-called passes through the reactor before it reaches its target discharge burnup and is replaced with a fresh fuel pebble. Given the stochastic nature of the fuel pebble travel paths and consequently the individual fuel pebble histories, it is not possible with standard methods developed for traditional reactor concepts to calculate the fuel inventory in the reactor core. An iterative approach, the SCALE Leap-In method for Cores at Equilibrium (SLICE), was developed to generate region-average fuel inventory for a PBR. The SLICE code enables automatic generation of input files for the SCALE code system (https://www.ornl.gov/scale), management of the SCALE result files, and analysis of results.

Bostelmann, Friederike [Oak Ridge National Laborat↗

Landslide Susceptibility and Runout Assessment for the Arun Hydropower Cascade in Nepal Based on Multitemporal Landslide Inventory Developed Using Planet Imagery

The transboundary Pumqu/Arun River basin spreads across Nepal and Tibet. Nearly 95% of the basin lies in Tibet through which the Pumqu River flows forming the Arun River once it enters Nepal. The Arun River valley has about 3,163 MW in five large hydropower projects undergoing construction or planned for the future. Rainfall and earthquake-induced landslides, landslide dammed lakes and landslide-induced glacial lake outburst floods pose major risks to smooth operation of these projects. To safeguard upcoming hydropower projects, areas susceptible to landslides in the Arun River valley must be identified. We generated a multitemporal landslide inventory (2010-2020), modeled landslide susceptibility and runouts around the hydropower sites using Earth Observation (EO) techniques. We used high-resolution satellite imagery from Planet and open-source tool to establish a detailed and comprehensive multitemporal landslide inventory for the basin. The rigorous quality-controlled inventory represents yearly record of landslides from 2010 to 2020. To our knowledge this is one of the most comprehensive landslide inventories for the basin with yearly records of landslides.A data-driven approach was used to map areas susceptible to landslides within the Pumqu/Arun River basin. The multitemporal landslide inventory combined with other readily available EO-based variables were used to create a landslide susceptibility map. The highly susceptible areas delineated from the map was further used to characterize runouts near the hydropower sites. The susceptibility and runout analysis provide a valuable initial estimate of where landslides are likely to trigger and where the mobilized material is likely to end up.

Pukar Amatya↗

Development of a BlueCRAB/MELCOR Framework for Supporting Realistic Mechanistic Source Term Calculations in Microreactors

Efforts are currently underway to deploy microreactor modeling and simulation tools to better support vendors and regulatory authorities in submitting and reviewing licensing applications. In particular, the Nuclear Regulatory Commission is expected to rely on the Comprehensive Reactor Analysis Bundle (BlueCRAB) multiphysics toolset in performing design- and beyond-design-basis accident analyses. In addition, the Nuclear Regulatory Commission has been using the MELCOR code to estimate mechanistic source terms during accidents. As MELCOR relies on isotopic inventory and reactor temperature/power evolution profiles during accident conditions—all of which can theoretically be obtained from BlueCRAB—the ultimate goal of this activity is to establish a common BlueCRAB-MELCOR framework. However, prior to the present research, BlueCRAB had never been used to calculate such quantities of interest at the full-core level. While there are many Monte Carlo (MC) codes capable of computing such quantities of interest, they are unable to readily account for multiphysics feedback. BlueCRAB allows for the coupling of different physics codes together to perform multiphysics-informed calculations. Therefore, the purpose of this fiscal year 2023 work is to investigate the feasibility and challenges of performing such calculations within BlueCRAB so as to generate the data that MELCOR relies on. To demonstrate the methodology, the proposed workflow was applied to a prototypical heat pipe-cooled microreactor model. To predict isotopic concentrations (taking into account the ac- cumulation of fission products during operation), the necessary microscopic cross sections were generated via OpenMC and tabulated with respect to temperature and burnup. Next, a recently developed capability in Griffin (the reactor physics application in BlueCRAB) was used to convert the OpenMC output format into the ISOXML format used by Griffin. A multiphysics microscopic depletion calculation that involved performing a coupled full-core, heterogeneous neutron trans- port and thermal calculation at each depletion step was conducted to deplete the core to end of life (EOL) conditions so as to provide both isotopics and the initial condition for the transient calculation. Following a brief null-transient to verify that the initial condition had been properly restarted and was indeed in thermal equilibrium, a heat pipe failure transient was simulated. Thus, the entire workflow of using BlueCRAB to generate MELCOR inputs, from cross-section generation to producing isotopic inventory and power/temperature evolution profiles during transients, is demonstrated. This report also details the identified gaps in the workflow and how they were (for the most part) addressed. Future work should focus on directly including MEL- COR into the workflow by performing a MELCOR calculation using the BlueCRAB-generated input data. In addition, the heat pipe reactor design should be improved so as to reflect more prototypical burnup characteristics at EOL.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Multitemporal landslide inventory and susceptibility map for the Arun River Basin, Nepal

The transboundary Arun River Basin (ARB) spreads across Nepal and Tibet. Nearly 95% of the basin lies in Tibet through which the Pumqu River flows, forming the Arun River once it enters Nepal. The ARB has five large hydropower projects undergoing construction or planned for the future. Rainfall and earthquake-induced landslides, landslide dammed lakes and landslide-induced glacial lake outburst floods pose major risks to smooth operation of these projects. To safeguard upcoming hydropower projects, areas susceptible to landslides in the ARB must be identified. We used high-resolution satellite imagery and open-source tools to generate a multitemporal landslide inventory for the basin. The rigorously quality-controlled inventory represents a yearly record of landslides from 2011 to 2020. A data-driven approach was used to map areas susceptible to landslides within the ARB. The multitemporal landslide inventory combined with other readily available Earth observation-based variables were used to create a landslide susceptibility map. The susceptibility analysis provides a valuable initial estimate of where landslides are likely to initiate. These landslide products could form the basis of more comprehensive local studies to inform hydropower project development.

Arun River Basin↗

ISS Technology Demonstrations for Future Spaceflight Medical Systems

Throughout the history of human spaceflight, crewmembers have experienced various in-flight medical conditions including illness and injury. Planned missions to the Moon and Mars will require capabilities to maintain the health of future space travelers. Mass, power, and volume available in the vehicles and habitats for these missions will be severely constrained; resupply of resources will be limited or non-existent, as will opportunities for evacuation to Earth. Furthermore, ground-based support will be hampered by communication latencies and blackouts. These vehicle and mission constraints will necessitate a medical system that has been efficiently planned, providing on-board procedural guidance in addition to a variety of medical devices and consumable resources. Medical capabilities required for the diagnosis and treatment of potential medical conditions during future spaceflight missions may include real-time health monitoring, medical imaging, and biomarker analyses ( e.g., blood or urine). Terrestrial medicine shares these needs, thus many of these medical capabilities could likely be satisfied by Commercial-Off-The-Shelf (COTS) devices and methodologies; however, in some cases the unique space environment and increased mission duration will drive the need to modify technologies and the way care is provided. NASA’s Human Research Program (HRP) Exploration Medical Capability (ExMC) Element and Mars Campaign Office’s Exploration Medical Integrated Product Team (XMIPT) are working together to decrease medical risk during exploration missions. Flight-tested medical diagnostic and treatment technologies are necessary to effectively manage medical conditions relevant to exploration missions while meeting vehicle constraints, integrating with medical decision-support tools, and enabling increasingly Earth-independent operations. Several projects have leveraged the ISS as a testbed for exploration, including 1) i n- situ blood analysis, 2) medical inventory, 3) intravenous fluid generation, and 4) autonomous medical procedure guidance. Management of several in-flight medical conditions, such as bacterial and viral infections and acute radiation syndrome, is dramatically improved with ability to assess blood cell populations, electrolytes, and metabolites. I n December 2020 and January 2021 ExMC performed an ISS technology demonstration (Tech Demo) of the HemoCue® WBC DIFF analyzer (HemoCue, Brea, CA), a COTS device that was modified to enable functionality in a spaceflight environment. This Tech Demo marked the first time that hematology measurements were successfully performed real-time in microgravity. Also modified and demonstrated was the reusable Handheld Electrolytes and Lab Technology for Humans (rHEALTH) ONE analyzer (rHEALTH, Bedford, MA), which uses flow cytometry and sheath-based hydrodynamic focusing methodologies. The rHEALTH ONE ISS Tech Demo in May 2022 demonstrated test results obtained in-flight matched those on the ground. NASA currently relies on crew self-reporting to manage and maintain medical inventory on ISS.The ability to maintain an accurate inventory becomes more critical during long duration missions since the crew will need to be increasingly autonomous in finding and utilizing medical items, including those scenarios when alternative treatments need to be considered due to limited or no resupply. HRP’s Medical Consumables Tracking (MCT) project was developed by ZIN Technologies, Inc. (Cleveland, OH), and demonstrated real-time tracking of medical supplies aboard the ISS between December 2016 and July 2018. The MCT system design utilized Radio Frequency Identification Device (RFID) technology to perform automated inventory and was installed in the Crew Health Care System (CHeCS) Resupply Stowage Rack (RSR). The challenge of limited shelf life, exacerbated by the lack of resupply opportunities, affects a plethora of medical system components including consumables, pharmaceuticals, and intravenous (IV) fluid. In 2010, ExMC funded ZIN Technologies, Inc. (Cleveland, OH), to develop the Intravenous Fluid Generation (IVGEN) system. IV fluids were successfully generated with IVGEN using the potable water supply on ISS during ISS Expedition 23. The XMIPT is in the process of developing a miniaturized version of the original IVGEN hardware for a future Tech Demo aboard the ISS. Current ISS medical operations rely heavily on preflight training and real-time remote guidance, both of which become impractical or impossible for exploration missions. The primary goal of the Autonomous Medical Officer Support (AMOS) Software Tech Demos on ISS was to confirm telemedical proof-of-concept for autonomous medical imaging in an operational setting. This novel software tool shifts emphasis from preflight training and real-time remote guidance to in-flight just-in-time instruction, a new and necessary paradigm for crew medical autonomy. AMOS introduces a novel, streamlined skill management concept for exploration missions featuring comprehensive training and guidance modules for ultrasound examinations using the ISS Ultrasound 2 (a modified GE Vivid-q™; General Electric HealthCare, Chicago, IL). With no prior crew training or remote guidance, two Tech Demos on the ISS (April 2020 and June 2022) resulted in high quality, clinically useful image sets. We will provide a review of historical, current, and planned medical devices and technologies considered for inclusion within future spaceflight medical systems and summarize hardware development activities and medical device tech demos conducted on the ISS.

Astronaut health and performance↗

High bias machine learning for antineutrino-based safeguards for small reactors

The statistical methods used for antineutrino detection will need to be improved to effectively monitor the inventory of next-generation nuclear reactors. In this sensitivity study, we evaluate machine learning models compared to previously used statistical approaches to identify diversion scenarios in a simulated Advanced Fast Reactor (AFR)-100. A chi-square goodness-of-fit technique, which individually compares the simulated antineutrino yields to the expected antineutrino yield, resulted in precise but low diversion detection probability. Various support vector machine (SVM) models were applied with diverse training datasets to evaluate the robustness of the method towards unexpected or “unseen” diversion scenarios. Furthermore, our results indicate that while the SVM models significantly improved the detection probability of near-field antineutrino-based safeguards, up to a probability of ~0.04, for the simulated small reactor, the detection system still needs improvements to reach the 0.2 detection limit established by the International Atomic Energy Agency.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Radiological Safety Analysis Computer Program V 7.2

Users generates a fission product inventory from either reactor operating history or a nuclear criticality event. RSAC-7 models the effects of high-efficiency particulate air filters or other cleanup systems and calculates the decay and ingrowth during transport through processes, facilities, and the environment. Doses are calculated for inhalation, air immersion, ground surface, ingestion, and cloud gamma pathways. RSAC-7 is used as a tool to evaluate accident conditions in emergency response scenarios, radiological sabotage events, and safety basis accident consequences.

Jordan, RobertaA. [Idaho National Laboratory (INL)↗

Status Update on the High Precision Isotopic Measurements on High Burnup LWR Fuel in 2020

The US Department of Energy (DOE) Office of Nuclear Energy (NE) is currently investigating the feasibility of directly disposing dual-purpose (storage and transportation) canisters (DPCs) in a spent nuclear fuel (SNF) repository. Criticality during the repository performance period (10,000 years or more) is one of the major concerns related to direct disposal of DPCs, specifically as the system undergoes degradation in the repository environment and timeframe. Oak Ridge National Laboratory (ORNL) is developing an as-loaded criticality analysis methodology using full (actinides + fission products) burnup credit that exploits the inherent criticality margin associated with actual canister-specific loading configuration. Burnup credit criticality analysis requires validation of the depletion/decay codes used to generate the burned isotopic inventory of an assembly by comparing the code-predicted inventory with experimentally determined isotopic data. Currently, isotopic measurement data for boiling water reactors (BWR) SNF are limited, and additional measurements will be highly beneficial for BWR burnup credit analysis, which is essential to demonstrate disposability of BWR DPCs. Moreover, new pressurized water reactor (PWR) samples of isotopic measurements will expand the PWR sample population and consequently will greatly improve sample statistics. In turn, this will reduce uncertainty in the computational determination of the isotopic composition of commercial SNF and eliminate additional penalties currently used for lack of data. As part of the isotopic analysis task, eight diverse, high burnup (HBU) samples from several PWR rods are being dissolved and isotopically analyzed to provide high-quality measurement data for PWR SNF to reducing the uncertainties associated with PWR isotopic depletion validation. The isotopics of interest focus on nuclides important to burnup credit, shielding, and decay heat in PWR SNF. Additionally, eight high burnup BWR fuel samples from the Limerick nuclear power plant have been identified for measurement to support reducing uncertainties associated with BWR isotopic depletion validation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Flowsheet Evaluation of Dissolving Used Nuclear Fuel in PUREX Solvent

This study explores the potential benefit to the used nuclear fuel actinide recovery flowsheet of a process simplification and establish the experimental work needed to develop the simplified flowsheet. The simplification is based on replacing acid dissolution of used nuclear fuel with dissolution in the tri-butyl phosphate solvent used in the industrially mature Plutonium Uranium Reduction Extraction flowsheet. Though characterized by considerable uncertainty, simplified flowsheets appear feasible and potentially offer significant reductions in process complexity, nitrate inventory, secondary liquid effluent generation and plant footprint. Initial development of the technology should focus on key fission product and actinide dissolution as a function of process conditions and understanding the fundamental chemistry of tri-butyl phosphate solvent chemistry. Development of ancillary technologies for minor actinide separations and fuel pretreatment for tritium management is also recommended.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Valuing the Future Electric Grid: A Bid-Based Approach

Energy storage resources (ESRs) and other zero marginal cost (ZMC) resources have unique characteristics that are not fully captured in today’s electricity planning and operations modeling tools. Because the modeling assumptions used in these tools are simplified approximations of how operations and investment decisions occur in the real-world, accurately representing cost and operational characteristics are key for determining how these resources impact price formation. Questions such as—Where should we build new transmission? Will a small modular reactor earn enough revenue to participate in the future electric grid? Is retrofitting a coal plant with carbon capture technology economically feasible?—all require accurate electricity prices, which aren’t available from today’s electricity planning and operations modeling tools. As an example, production cost models (PCMs) are heavily utilized tools that determine the cost and reliability of the electric system. However, as PCMs were developed to help thermal generators manage their fuel inventories, production cost modeling is largely based on fuel prices. Because ESRs do not incur fuel costs, they are often modeled as ZMC resources. In reality, ESRs incur opportunity costs as well as technology-specific (degradation) costs that are non-trivial to calculate but are important for price formation. In this research, we identify options to incorporate more realistic opportunity and degradation costs in ESR bidding algorithms. Expanding available bidding assumptions allows energy system modelers to develop more accurate economic valuations for ESRs, leading to more accurate price formation from leading energy system modeling tools.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Radiological Safety Analysis Computer (RSAC) Program Version 7.4 Users’ Manual

The Radiological Safety Analysis Computer (RSAC) Program Version 7.4 (RSAC-7) is the newest version of the RSAC legacy code. RSAC-7 calculates the consequences of a release of radionuclides to the atmosphere. Users generates a fission product inventory from either reactor operating history or a nuclear criticality event. RSAC-7 models the effects of high-efficiency particulate air filters or other cleanup systems and calculates the decay and ingrowth during transport through processes, facilities, and the environment. Doses are calculated for inhalation, air immersion, ground surface, ingestion, and cloud gamma pathways. RSAC-7 is used as a tool to evaluate accident conditions in emergency response scenarios, radiological sabotage events, and safety basis accident consequences. This users’ manual contains the mathematical models and operating instructions for RSAC-7. Instructions, screens, and examples are provided to guide the user through the functions provided by RSAC-7. This program is designed for users who are familiar with radiological dose assessment methods.

73 - NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Large Area Crop Inventory Experiment (LACIE). Effect of sun angle and haze on generation of LANDSAT imagery

The author has identified the following significant results. When heavy haze was present over a nonvegetated scene, the mean radiance values for all MSS channels were lowered, with the greatest decrease occurring in channels 1 and 2. Over a vegetated scene, any apparent decrease in mean radiance values due to haze may be marked by an increase in mean radiance values which occurred as vegetation increased in vigor during its growth cycle. Mean radiance values for nonvegetated targets (except water) were closely correlated to the changes in sun elevation angle throughout the year. A sun angle correction to a fixed reference data appeared to offer the possibility of compensating for haze covered areas by predicting the mean radiance values which would be closely correlated to the normal sun declination curve.

Chesnutwood, C. M.↗

Comparative Techno-Economic Analysis of Available Feedstocks for High-Temperature Conversion: Whole Tree Thinnings and Mature Pine Residues

The techno-economic and life cycle implications of utilizing low-cost feedstocks in a high temperature conversion process are of great interest. Here, we investigate the conversion cost impacts of two underutilized feedstocks from the commercial pine industry: 13-year-old whole trees, representing trees removed for the purpose of precommercial thinning, and 23-year-old pine residues, representing a waste stream produced from the deconstruction of mature trees for other purposes. Experimental fast pyrolysis (FP) yields for each feedstock were adjusted to a catalytic fast pyrolysis (CFP) basis and used to estimate process economics by employing published correlations based on rigorous techno-economic modeling. These correlations were used in tandem with results from supply and preprocessing analyses to evaluate the field-to-fuel economics of each feedstock. A small difference in minimum fuel selling price (MFSP) was found between the conversion costs for the two feedstocks, with 23-year-old residues demonstrating a net benefit of $0.27 per gasoline gallon equivalent (GGE) compared to the 13- year-old whole tree thinnings, driven primarily by feedstock supply costs. This suggests that both whole tree thinnings and pine residues may be viable feedstock options for CFP conversion. Life cycle inventories (LCIs) were also generated for each case, enabling a field-to-fuel quantification of the cost and carbon cycle associated with each feedstock.

catalytic fast pyrolysis↗

Generative AI in Supply Chain Management: Applications, Challenges, and Future Directions

Supply chain management (SCM) is undergoing rapid transformation due to increasing global complexity, demand volatility, and operational disruptions. Generative Artificial Intelligence (GenAI) has emerged as a powerful paradigm capable of synthesizing data, simulating operational scenarios, and enabling adaptive decision-making across supply chain networks. This paper presents a survey of GenAI’s role in SCM, focusing on its applications in predictive analytics, autonomous logistics, and fraud detection. Unlike traditional AI systems that rely primarily on predictive analytics, GenAI models, including large language models, generative adversarial networks, and diffusion-based architectures, enable the creation of synthetic supply chain scenarios and autonomous optimization strategies. This survey provides (1) a taxonomy of GenAI techniques for supply chain applications, (2) a comparative analysis of generative AI approaches with traditional machine learning, reinforcement learning, and blockchain-based methods, and (3) a discussion of key challenges such as data privacy, interpretability, and integration with legacy enterprise systems. Furthermore, we outline open research problems and propose directions for future research toward autonomous, resilient, and sustainable AI-driven supply chains.

15 - GEOTHERMAL ENERGY↗

The Contaminant Footprint of Landed Spacecraft: Toward an Inventory and Modelling Framework

All spacecraft generate and carry contaminants, i.e., unwanted and potentially harmful material. When a spacecraft lands and operates in vacuum, as onto Earth’s Moon, it introduces contaminants into its environment that may compromise mission science objectives and engineering performance. Contamination may degrade sites of unique value to planetary science or in situ resource utilization. This presentation will identify and compare source terms and transport vectors for contaminants – in particular, organic material – generated by landed spacecraft. An integrated modeling framework for the organic contamination footprint of spacecraft missions will be described and presented.

Gas Dynamics↗

The Contaminant Footprint of Landed Spacecraft: Toward an Inventory and Modelling Framework

All spacecraft generate and carry contaminants, i.e., unwanted and potentially harmful material. When a spacecraft lands and operates in near-vacuum, as onto Earth’s Moon, it introduces contaminants into its environment that may compromise mission science objectives and engineering performance. Contamination of solar system bodies may irrevocably degrade targets of unique value to planetary scientists, for instance, as lunar landed spacecraft introduce propellant effluents into the otherwise pristine ice of the Moon’s permanently shadowed regions. NASA’s planetary protection discipline seeks to ensure that solar system bodies are not contaminated, for scientific purposes, by terrestrial material (i.e., forward contamination). This interest aligns with planetary science interest in mitigating the transport of terrestrial contaminants onto solar system bodies and in controlling types of contamination that could compromise the scientific value of samples or measurements. NASA, and other entities that practice planetary science, have compelling and multidisciplinary interests in the preservation of special regions and sampling sites of high scientific value – including lunar permanently shadowed regions (PSRs) – from inadvertent contamination by any spacecraft, and in understanding the contamination of such regions by all spacecraft. Organic molecular contamination here represents a primary threat. Organic molecules will be introduced to solar system bodies by nominal landed spacecraft and crew processes – including by the action of descent and ascent engines; natural materials outgassing; and crew environmental and life support system sources. Molecular contaminants can also travel in the free-molecular sense at global scale across near-vacuum bodies, including into regions where they may be permanently trapped. This presentation will address a high-level study to identify sources of contaminants – in particular, organic material – generated by landed spacecraft along with the transport vectors by which these contaminants can reach sites of scientific interest on bodies like the Moon. A vision for an integrated modeling framework for the organic contamination footprint of spacecraft missions, individually and collectively, will also be described and presented along with initial conclusions related to organic molecular transport.

Gas Dynamics↗