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At least 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Supply Chain Sustainability Analysis of Renewable Hydrocarbon Fuels via Indirect Liquefaction, Ex Situ Catalytic Fast Pyrolysis, Hydrothermal Liquefaction, Combined Algal Processing, and Biochemical Conversion: Update of the 2019 State-of-Technology Cases

This technical report describes the supply chain sustainability analysis (SCSAs) for the production of renewable hydrocarbon transportation fuels via a range of conversion technologies: (1) renewable high octane gasoline (HOG) via indirect liquefaction (IDL) of woody lignocellulosic biomass (note that the IDL pathway in this SCSA represents the syngas conversion design in the 2019 SOT); (2) renewable gasoline (RG) and diesel (RD) blendstocks via ex situ catalytic fast pyrolysis of woody lignocellulosic biomass; (3) RD via hydrothermal liquefaction (HTL) of wet sludge from a wastewater treatment plant; (4) renewable hydrocarbon fuels via biochemical conversion of herbaceous lignocellulosic biomass; (5) renewable diesel via HTL of a blend of algae and woody biomass; and (6) renewable diesel via combined algae processing (CAP). This technical report focuses on the environmental performance of these six biofuel production pathways in their 2019 SOT cases. The results of these renewable hydrocarbon fuel pathways in these SCSA analyses update those for the respective 2018 SOT cases. They also provide an opportunity to examine the impact of technology improvements in both biomass feedstock production and biofuel production that have been achieved in 2019 SOTs on the sustainability performance of these renewable transportation fuels, and they reflect updates to Argonne National Laboratory’s Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET®) model, which was released in October 2019. These GREET updates include the production of natural gas, electricity, and petroleum-based fuels that can influence biofuels’ supply chain greenhouse gas (GHG) (CO₂, CH₄, and N₂O) emissions, water consumption, and air pollutant emissions. GHG emissions, water consumption, and nitrogen oxides (NO x ) emissions are the main sustainability metrics assessed in this analysis. In this analysis, we define water consumption as the amount of water withdrawn from a freshwater source that is not returned (or returnable) to a freshwater source at the same level of quality. Life-cycle fossil energy consumption and net energy balance, which is the life-cycle fossil energy consumption deducted from the renewable biofuel energy produced, are also assessed.

09 BIOMASS FUELS↗
DOE OSTI2022

Roadmap for Deployment of Modularized Hydrothermal Liquefaction: Understanding the Impacts of Industry Learning, Optimal Plant Scale, and Delivery Costs on Biofuel Pricing

Hydrothermal liquefaction (HTL) is a promising technology for converting abundant organic wastes into fuels. Previous techno-economic analyses (TEAs) of HTL have been used to estimate the minimum fuel selling price (MFSP) of biofuel products, but these analyses often assume a bespoke plant design where each plant operates under unique process conditions and neglect transportation costs. However, transportation costs must be included in realistic TEAs, and further, a mass-produced fixed-scale modular plant design approach may be more effective than case-by-case plant design, provided that there is sufficient market capacity to benefit from modularization. This study estimates fuel price behavior in the presence of transportation costs and benefits stemming from modular plant design. This analysis indicates that a modular process capable of handling 60 dry tons per day (DTPD) is optimal, resulting in a ~25% reduction in MFSP (from $4.70/GGE, fully upgraded) at complete market feedstock utilization compared with case-by-case design. The associated cost reductions are attributable to learning benefits and modularization. Several HTL deployment “roadmaps” are then explored, with each roadmap consisting of different periods of case-by-case design followed by adoption of a modularized approach. A period of nonmodular industry growth up to market saturation of ~7% followed by implementation of modular plant design strikes a balance between the investment risk and learned cost reductions associated with modular plant design. However, if bespoke plants built during this period of nonmodular growth saturate more than 23% of available feedstock, learned cost reductions are significantly diminished. Here, this study points to the potential benefits of modularized and decentralized waste-to-energy processes when the modularization follows an optimal deployment strategy.

09 BIOMASS FUELS↗
DOE OSTI2025

A Scalable Gaussian Process Approach to Shear Mapping with MuyGPs

Analysis of cosmic shear is an integral part of understanding structure growth across cosmic time, which in turn provides us with information about the nature of dark energy. Conventional methods generate shear maps from which we can infer the matter distribution in the universe. Current methods (e.g., Kaiser–Squires inversion) for generating these maps, however, are tricky to implement and can introduce bias. Recent alternatives construct a spatial process prior for the lensing potential, which allows for inference of the convergence and shear parameters given lensing shear measurements. Realizing these spatial processes, however, scales cubically in the number of observations—an unacceptable expense as near-term surveys expect billions of correlated measurements. Therefore, we present a linearly scaling shear map construction alternative using a scalable Gaussian process prior called MuyGPs. MuyGPs avoids cubic scaling by conditioning interpolation on only nearest neighbors and fits hyperparameters using batched leave-one-out cross-validation. This work is the first step toward a full, scalable mass mapping method. We work in a simplified regime where we validate our method by interpolating and analyzing maps given noisy point-estimate data from all three shear fields, taken from a suite of N -body ray-tracing simulations. We also show that we can perform these operations at the scale of billions of galaxies on high-performance computing platforms.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Combustion in the ZrF 4 -Mg-Si and ZrF 4 -Al-Si systems for preparation of zirconium silicides

The exothermic reactions in the ZrF 4 –Mg-Si and ZrF 4 -Al-Si systems are investigated by a fast temperature recording (thermocouple) technique, differential scanning calorimetry (DSC), and thermogravimetric analysis (TGA). A quenching method is used to arrest the combustion process and conduct a layer-by-layer analysis of the products by x-ray diffraction (XRD) and electron microscopy. Two seemingly similar reactive systems exhibited considerably different combustion characteristics, composition, and morphology. Based on these investigations, we propose and discuss phase formation mechanisms at the early stages for each system. Three different pathways involving the reaction of ZrF 4 with other reagents and the Mg 2 Si intermediate are identified to occur in the ZrF 4 –Mg-Si system. Contrary to the complex mechanism in the ZrF 4 –Mg-Si system, the early stage of the combustion process for the ZrF 4 -Al-Si system involves the interaction of ZrF 4 with Al-Si eutectic melt. The exothermic reaction between reduced solid Zr and Si melt is the primary heat-generating step for both systems in spite of substantial differences in the early stages of the reactions. The silicon content in the reactive mixtures governs the phase composition of products. The ZrSi 2 phase, with a high growth rate, forms first on the Zr particle surfaces and then grows by a reactive diffusion mechanism. The ZrSi 2+ Zr reaction produces silicon-lean phases (e.g., ZrSi) when the silicon supply is limited. The combustion temperature also has a considerable influence on the phase compositions of the products. High combustion temperature in the ZrF 4 +2Mg+Si mixture enables the formation of multiphase products (α-ZrSi and β-ZrSi), whereas the relatively lower temperatures in the 3ZrF 4 +4Al+3Si mixture yields a single-phase α-ZrSi. As a result, lower combustion temperatures also make the ZrF 4 -Al-Si system more advantageous for the preparation of zirconium silicides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Numerical analysis of a time discretized method for nonlinear filtering problem with Lévy process observations

Abstract In this paper, we consider a nonlinear filtering model with observations driven by correlated Wiener processes and point processes. We first derive a Zakai equation whose solution is an unnormalized probability density function of the filter solution. Then, we apply a splitting-up technique to decompose the Zakai equation into three stochastic differential equations, based on which we construct a splitting-up approximate solution and prove its half-order convergence. Furthermore, we apply a finite difference method to construct a time semi-discrete approximate solution to the splitting-up system and prove its half-order convergence to the exact solution of the Zakai equation. Finally, we present some numerical experiments to demonstrate the theoretical analysis.

Mathematics↗
DOE OSTI2021

Individual Wave Detection and Tracking within a Rotating Detonation Engine through Computer Vision Object Detection applied to High-Speed Images

Known for their simplistic design and continuous detonation, rotating detonation engines (RDEs) constitute a majority of current pressure gain combustion (PGC) research efforts. Experimental RDE operation times have been continuously extended through the use of rig cooling techniques. As the window of observable behavior is expanded, and as the technology matures toward eventual integration within gas turbines, monitoring techniques must evolve to better match industrial diagnostics. High-speed image analysis techniques prove useful to capture and evaluate the unsteady detonation behavior within the RDE. Traditional image analysis techniques, however, require extensive processing times which prohibit simultaneous monitoring. To better address this problem, a computer vision object detection methodology is proposed to quickly detect individual detonation waves within a single down-axis image. Detonation waves are detected in individual images by the implemented computer vision method You Only Look Once (YOLO) object detection network. In order to detect detonation waves, the network must first be trained using RDE images of interest, for which each required phase of network development is outlined. Detection of waves is improved through proper treatment of the collected image set, variation of Intersection over Union (IoU) and confidence thresholding, and through a parametric study of annotation dimensions. Each detected wave is described by its location and rotational direction, and locations are tracked to calculate wave velocity across each frame, leading to a timestep resolution of 20 µs. Wave velocities are also calculated through a series of frames, leading to a suitable average velocity estimation using as few as 10 frames. Uncertainty analysis accounting for variation in camera framerate, pixel width and annotation centroid locations estimates a total uncertainty of ±4.3% for velocity calculations, using the smallest annotation boxes. This method offers great reductions in processing times, as a step toward real-time monitoring of detonation waves within an RDE. Improving on previous studies, this technique is impartial to wave modes not included in the original training set and calculates wave velocities independent of high-speed pressure data. The ability to isolate waves within predicted bounding boxes will likely facilitate analysis of pixel intensity variation as an estimation of wave strength in future work.

Johnson, Kristyn↗
DOE OSTI2021

Individual Wave Detection and Tracking within a Rotating Detonation Engine through Computer Vision Object Detection applied to High-Speed Images

Known for their simplistic design and continuous detonation, rotating detonation engines (RDEs) constitute a majority of current pressure gain combustion (PGC) research efforts. Experimental RDE operation times have been continuously extended through the use of rig cooling techniques. As the window of observable behavior is expanded, and as the technology matures toward eventual integration within gas turbines, monitoring techniques must evolve to better match industrial diagnostics. High-speed image analysis techniques prove useful to capture and evaluate the unsteady detonation behavior within the RDE. Traditional image analysis techniques, however, require extensive processing times which prohibit simultaneous monitoring. To better address this problem, a computer vision object detection methodology is proposed to quickly detect individual detonation waves within a single down-axis image. Detonation waves are detected in individual images by the implemented computer vision method You Only Look Once (YOLO) object detection network. In order to detect detonation waves, the network must first be trained using RDE images of interest, for which each required phase of network development is outlined. Detection of waves is improved through proper treatment of the collected image set, variation of Intersection over Union (IoU) and confidence thresholding, and through a parametric study of annotation dimensions. Each detected wave is described by its location and rotational direction, and locations are tracked to calculate wave velocity across each frame, leading to a timestep resolution of 20 µs. Wave velocities are also calculated through a series of frames, leading to a suitable average velocity estimation using as few as 10 frames. Uncertainty analysis accounting for variation in camera framerate, pixel width and annotation centroid locations estimates a total uncertainty of ±4.3% for velocity calculations, using the smallest annotation boxes. This method offers great reductions in processing times, as a step toward real-time monitoring of detonation waves within an RDE. Improving on previous studies, this technique is impartial to wave modes not included in the original training set and calculates wave velocities independent of high-speed pressure data. The ability to isolate waves within predicted bounding boxes will likely facilitate analysis of pixel intensity variation as an estimation of wave strength in future work.

Johnson, Kristyn↗
DOE OSTI2022

Geometrically necessary dislocation fingerprints of dislocation loop absorption at grain boundaries

Here we present a numerical methodology to compute the Nye-tensor fingerprints of dislocation loop absorption at grain boundaries (GBs) for comparison with TEM observations of irradiated polycrystals. Our approach links atomistic simulations of self-interstitial atom (SIA) prismatic loops gliding toward and interacting with GBs in body-centered cubic iron with experimentally extracted geometrically necessary dislocation (GND) maps to facilitate the interpretation of damage processes. The Nye-tensor analysis is strongly mesh-size dependent—corresponding to resolution-dependent TEM observations. The method computes GND fingerprints from discretized dislocation line segments extracted from molecular dynamics simulations of dislocation loops being absorbed at a GB. Specifically, we perform MD simulation of prismatic loops of two diameters and monitor the three stages of the absorption process: loop glide, the partial, and full absorption of the loops at a [1 0 0] symmetric tilt GB. These methods provide a framework for future investigations of the nature of defect absorption by grain boundaries under irradiation conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Community Resilience Indicator Analysis: Commonly Used Indicators from Peer-Reviewed Research (Updated for Research Published 2003-2021)

In 2017, FEMA’s National Integration Center (NIC) Technical Assistance (TA) Branch identified a need to establish a data-driven basis for prioritizing locations for TA investment and guiding local emergency management planning. To achieve this goal, FEMA tasked Argonne National Laboratory (Argonne) with identifying commonly used indicators of community resilience across the landscape of published peer-reviewed research. FEMA and Argonne completed the first Community Resilience Indicator Analysis (CRIA) in 2018 and repeated the process in 2022. The CRIA process begins with a literature review and cataloguing of published peer-reviewed assessment methodologies on social vulnerability and community resilience. The literature review findings are then filtered by inclusion criteria established by the CRIA research team to ensure the methodologies are: (1) Quantitative, (2) Data and methodology are publicly available, (3) Calculated at the county level or lower, (4) Examine generalized hazard risk (rather than a singular hazard), and (5) Focused on pre-disaster community conditions. After this, the research team identifies the commonly used indicators across these methodologies and selects the best data source for each indicator. Finally, the research team bins the data for visual display, conducts a correlation analysis and creates a composite index, the FEMA Community Resilience Index (FEMA CRI). In 2018, the CRIA identified eight resilience and vulnerability assessment methodologies and 20 commonly used indicators (indicators used in three or more of the eight methodologies). The FEMA CRI in 2018 was created from these 20 indicators and was produced for at the county level. The 2022 CRIA updated the literature review to expand the list of methodologies examined and followed the same process, resulting in an analysis of 14 methodologies published between 2003 and 2021 and 22 indicators identified as commonly used (indicators used in five or more of the 14 methodologies). In 2022, the research team produced the FEMA CRI at the county and the census tract levels. To make the CRIA data more accessible and more actionable, each individual indicator and the FEMA CRI is binned and included in FEMA’s Resilience Analysis and Planning Tool (RAPT). RAPT enables emergency managers and community partners to quickly visualize relative differences in potential resilience by county, tribe and census tract. By reviewing the data for each of these 22 indicators individually, emergency managers can gain insights for targeted outreach strategies, planning, mitigation investments and response and recovery operations. Communities, regional governments and others can use this data to better understand potential challenges to resilience. As the social science field of examining and validating indicators of resilience evolves, FEMA will update RAPT to provide emergency managers and community partners with additional data and tools to inform planning, mitigation, response and recovery. It is important to understand that the role of the emergency manager is not to change or to “improve” the data, but to plan appropriately for the community characteristics reflected in the data. These datasets are community characteristics that researchers have identified as important considerations for resilience. For example, people with disabilities may have greater challenges to be resilient to disasters. If a community has a high population of people with disabilities, the emergency manager(s) may need to create tailored preparedness outreach programs and strategies to ensure those residents have support if evacuation is necessary. Rather than label these indicators as an absolute measure of resilience, FEMA considers “potential challenges to resilience” a better frame to understand these indicators. Everyone is vulnerable to disasters. While scholars theorize that certain characteristics may make an individual or a household more socially vulnerable, the data does not reflect measures that individuals and/or communities have taken to address potential challenges, such as emergency management planning and outreach or household preparedness measures. To aid emergency managers in understanding how to use these indicators, calling them potential challenges to resilience supports a more positive and strategic application of the data in all phases of emergency management.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Safety Analysis for the Versatile Test Reactor Conceptual Design

Safety analysis simulations have been carried out using the SAS4A/SASSYS-1 safety analysis code system to update the baseline set of results for the Versatile Test Reactor conceptual design. Results from a previous revision of this work provided input for the Conceptual Safety Design Report summarizing the overall safety basis for the VTR. This work will also support future analyses that will be required for Chapter 13, “Accident Analysis,” of a preliminary safety analysis report. A number of transients have been evaluated based on categories of postulated accident sequences suggested for consideration in NUREG-1537. Ultimately, the full spectrum of event initiators and subsequent accident sequences will be defined through a probabilistic risk assessment of the plant design following the implementation of the Licensing Modernization Project guidelines as described in the VTR Safety Design Strategy. Since that process is ongoing, the present analysis addresses several transients that are expected to be bounding accident scenarios that represent the three key ways to perturb a reactor: through changes to the core inlet temperature, mass flow rate, or reactivity. These correspond to a loss of heat sink (LOHS), loss of flow (LOF) or station blackout (SBO), and transient overpower (TOP), respectively. Both Protected and Unprotected versions of these transients have been evaluated, along with additional transients that include transient overpower with one stuck rod, pump coast-down failures, seismic events, and overcooling events. At the current stage of design, transient simulation results for the Versatile Test Reactor indicate that large safety margins exist for many event initiators. However, several “enabling” assumptions have been made, in terms of both design features and design limits, in order to perform the analyses; and these assumptions will need to be revised as the design matures. In addition, a larger spectrum of events needs to be evaluated as part of the on-going probabilistic risk assessment process.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Operability and control in process intensification and modular design: Challenges and opportunities

Abstract In this article, the importance of considering operability and control criteria in the analysis and design of intensified and modular processes is discussed. We first analyze the impact on operability of key factors including: (i) degrees of freedom, (ii) process constraints, (iii) numbering up vs. scaling up, and (iv) dynamic/periodic operation. Comparative examples are presented to showcase the pros and cons in intensified/modular systems vs. their conventional counterparts from operability and control aspects. Then we look into metrics and tools to address these challenges such as: (i) flexibility analysis, (ii) operability‐based design, and (iii) advanced model‐based control. Considering different conceptual design stages as synthesis intensification, steady‐state design, and dynamic operational optimization, we highlight the need to incorporate different levels of operability considerations. Future research opportunities and perspectives are also identified, particularly emphasizing the importance of a holistic strategy for integrated design, operability, and control of intensified and modular process systems.

Pistikopoulos, Efstratios N.↗
DOE OSTI2021

Home Energy Professionals Certifications ISO/IEC 17024: 2021 Policies and Procedures Manual

The U.S. Department of Energy (DOE) enlisted its National Renewable Energy Laboratory (NREL) to coordinate the development of a framework for new certifications in the weatherization and home performance industry. The Home Energy Professional certifications support DOE's Weatherization Assistance Program (WAP) and the broader residential home performance industry through the credentialing process of defined job task analysis for energy auditors and quality control inspectors. The HEP certifications are not intended to supplant or infringe upon any existing industry-recognized credentials, however, the WAP and the home performance industry have utilized the advanced HEP certifications to promote quality work and standardized job task analysis since 2010. On an ongoing basis, NREL brings industry practitioners and subject matter experts together to develop, review, and revise the certification schemes in accordance with the International Organization for Standardization (ISO)/International Electrotechnical Commission (IEC) 17024 standard, "Conformity assessment - General requirements for bodies operating certification of persons" (ISO/IEC 17024). This handbook covers the policies and procedures for the process of developing, maintaining, and validating the certification schemes. Each policy and procedure includes the relevant ISO/IEC 17024 section at the beginning.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

MSD CoP Webinar: "Advances in MSD-LIVE to Support the MSD Community of Practice"

Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org). Advances in MSD-LIVE to Support the MSD Community of Practice Presenters: Casey Burleyson and Zoe Guillen (Pacific Northwest National Laboratory) Abstract: The MultiSector Dynamics Living, Intuitive, Value-adding, Environment (MSD-LIVE; msdlive.org) is a cloud-based data management system and advanced computing platform that enables MSD researchers to document and archive their data, run their models and analysis tools, and share their data, software, and workflows within the MSD Community of Practice. Recently, several high-profile datasets have attracted many new users to MSD-LIVE. This webinar has two goals: 1) To refamiliarize the MSD community and new users with the components of the platform (e.g., the data repository, model training notebooks, and data dashboards) and to highlight examples of how these components are advancing MSD science and 2) To demonstrate new features in v3 of the platform, released in late 2025. The main new feature in v3 is the ability to interactively explore data in MSD-LIVE without downloading it. MSD-LIVE users can now click a button in our data repository and launch a blank Jupyter notebook with access to the underlying data on AWS. Users can use the notebook to write analysis, visualization, or subsetting routines that process the data directly on the AWS cloud. We also added a GitHub integration feature that allows users to share analysis or visualization code they develop with the community of MSD-LIVE users. The webinar will wrap up with a look at what's coming next for MSD-LIVE in 2026. Moderator: Patrick M. Reed (MSD CoP Facilitation Team) This webinar was held on: May 12th, 2026 from 1-2 PM EST.

Open Science↗
DOE OSTI2022

Disentangling direct from indirect relationships in association networks

Networks are vital tools for understanding and modeling interactions in complex systems in science and engineering, and direct and indirect interactions are pervasive in all types of networks. However, quantitatively disentangling direct and indirect relationships in networks remains a formidable task. Here, we present a framework, called iDIRECT (Inference of Direct and Indirect Relationships with Effective Copula-based Transitivity), for quantitatively inferring direct dependencies in association networks. Using copula-based transitivity, iDIRECT eliminates/ameliorates several challenging mathematical problems, including ill-conditioning, self-looping, and interaction strength overflow. With simulation data as benchmark examples, iDIRECT showed high prediction accuracies. Application of iDIRECT to reconstruct gene regulatory networks in Escherichia coli also revealed considerably higher prediction power than the best-performing approaches in the DREAM5 (Dialogue on Reverse Engineering Assessment and Methods project, #5) Network Inference Challenge. In addition, applying iDIRECT to highly diverse grassland soil microbial communities in response to climate warming showed that the iDIRECT-processed networks were significantly different from the original networks, with considerably fewer nodes, links, and connectivity, but higher relative modularity. Further analysis revealed that the iDIRECT-processed network was more complex under warming than the control and more robust to both random and target species removal ( P < 0.001). As a general approach, iDIRECT has great advantages for network inference, and it should be widely applicable to infer direct relationships in association networks across diverse disciplines in science and engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Circular Reprocessing of Thermoset Polyurethane Foams

Thermoset polyurethane (PU) foams are widely used in industrial applications, but they cannot be recycled by conventional melt reprocessing because of their cross-linked structures. The introduction of carbamate exchange catalysts converts thermoset PU into covalent adaptable networks (CANs), which are amenable to reprocessing at elevated temperatures. However, this approach has produced solid PU films, which have fewer uses and lower commercial demand. In this work, simultaneous reprocessing and refoaming of thermoset PU foams is demonstrated by leveraging the melt-processability of PU CANs and allowing cell growth by gas generation in a twin-screw extruder. The optimal operating temperature of the refoaming process is determined through chemical, thermal, and structural analysis of PU foam extrudates. The foam-to-foam extrusion process produces controllable, continuous, and uniform foam structures, as characterized by cell diameter and cell number density. Low-density PU foams are obtained through a process simulating injection molding. The compression properties of reprocessed PU foam are compared with as-synthesized PU foam to demonstrate efficacy of the refoaming processes. These results demonstrate that PU foams can be prepared through recycling while maintaining microstructural and chemical integrity. In the future, this strategy may be applied to thermoset PU foams of various chemical compositions and shows promise for scalability.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Fabrication of UN-Mo CERMET Nuclear Fuel Using Advanced Manufacturing Techniques

Ceramic-metallic nuclear fuels are a candidate fuel for nuclear thermal propulsion systems due to their high heat transport properties, which are necessary in very high-temperature environments. The conventional fabrication of uranium nitride–molybdenum fuel has been thoroughly studied in the past, but modern manufacturing techniques have presented a unique opportunity for further development within this field. This work demonstrates the use of advanced manufacturing techniques to produce nuclear fuel pellets composed of uranium nitride microspheres encased in a molybdenum matrix. Binder jetting is used to print molybdenum disks that are filled with uranium nitride microspheres and afterward sintered using spark plasma sintering. Two fuel pellets were fabricated to demonstrate the methodology and to provide a baseline analysis of the effects of temperature and pressure processing conditions. Characterization of the sintered fuel pellets includes detailed microstructural analysis and thermal conductivity measurements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Recycling of a post-industrial printed multilayer plastic film containing polyurethane inks by solvent-targeted recovery and precipitation

The recently reported Solvent-Targeted Recovery And Precipitation (STRAP) strategy is used to deconstruct multilayer plastic packaging films into their constituent resins by selective polymer dissolution. To broaden the applicability of STRAP, we demonstrate the process with a flexible post-industrial printed multilayer plastic film used for food packaging. The material was a reverse printed film composed of polyethylene (PE), ethylene vinyl alcohol (EVOH), polyethylene terephthalate (PET), and polyurethane (PU)-based inks. Removal of all colors was observed with biomass-derived gamma-valerolactone (GVL) and the recovered polymers possessed comparable properties to the corresponding virgin resins. A technoeconomic analysis indicates that this STRAP process could be economically feasible at a processing capacity of 6,000 tons per year. Furthermore, the production of plastic films with materials recovered by this STRAP process can have a lower climate change impact than the production of films from virgin polymers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Consequence Analysis of Residual Water in a Storage Canister - 20484

Recent observations from projects sponsored under the DOE-Nuclear Energy Spent Fuel and Waste Disposition campaign show that residual free water, well above the 0.4 gm-moles that correspond to a 3 torr rebound pressure after a 30-minute hold following prototypic drying, may remain within SNF canisters used for long-term dry storage. Specifically, experimental observations in an Integrated Research Project showed subzero temperatures and a local pocket of frozen water in a mockup fuel assembly subjected to an industry practiced drying process. In gas sampling and analysis from the High Burnup (HBU) Demonstration project, using a fully loaded and dried SNF canister, indicated presence of 100 g of residual water had remained in the canister. The effects of residual water in terms of potential adverse impacts on the condition of the SNF and the canister internals during long-term dry storage has been rigorously evaluated to address inadvertent residual water contents. The impact of residual water on the fuel and canister internals, with a focus on the oxidation of the cladding and of postulated exposed (breached-clad) fuel, were evaluated using an integrated set of time-dependent environmental conditions with semi-empirical materials oxidation models. An 'integration model,' with coupled sub-models, developed and previously used by the Center for Nuclear Waste Regulatory Analysis (CNWRA), was applied and expanded with improved sub-models for water radiolysis, and for cladding and fuel oxidations. Cladding oxidation models for various alloys were developed using the rate constants for various cladding alloys in the dry storage temperature range. A burnup-dependent fuel oxidation model was developed; it accounted for inhibition effect of fission products on fuel oxidation rates. The potential for extension of the initial breach flaw (1 mm hole) was evaluated by two separate mechanics criteria. In the first case, a critical cladding strain criterion was used. In the second case, a critical stress intensity was used to evaluate stability of a planar axial flaw postulate. A failure condition exists when a sufficient amount of fuel oxidation (at the postulated breached-clad location) causes fuel pellet swelling to load the cladding to meet a mechanics criterion for flaw extension. The integration model's results provide the following insights. The radiolysis-generated oxygen is consumed with a partitioning between the cladding and the fuel. The extent of cladding oxidation is no more than 2 μm additional consumption of the cladding metal even with 10 moles of residual water, indicating that changes in cladding conditions due to water are expected to be negligible. The conditions for cladding failure (breach opening size extension) directly correlates with the extent of fuel oxidation. Fuel oxidation significant to extend the breach could occur even with 5.5 moles of residual water. The results indicate that fuel oxidation vis-a-vis cladding oxidation is more likely under a higher radiation field, i.e., when radiolytic decomposition of the residual water occurs in few years compared to several decades, and that the conditions to cause failure are increased with fuel and cladding temperatures approaching the peak storage temperature limit of 400 deg. C. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗