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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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141 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Computationally-Aided Design of a Small-Scale Radioactive Waste Glass Melter

To provide mission support to the Hanford Waste Immobilization and Treatment Plant for the vitrification of legacy nuclear tank waste, a reduced-scale vitrification pilot system is being designed to process simulated and actual radioactive tank wastes. The tank waste will be separated into high-level waste (HLW) and low-activity waste (LAW) fractions, where the majority by mass (~90%) is LAW and by activity (>95%) is HLW. The first tank waste to be processed at the WTP will be LAW. Since Hanford tank waste and the resultant melter feed compositions are known to vary widely, pilot-scale operations are essential to identify potential problems, provide needed data, confirm assumptions, and determine impacts to full-scale melters and off-gas systems from these different feeds. In addition, the reduced-scale melter system must be capable of quickly providing results to operations without the typically high costs of radioactive operations and provide an engineering platform in close proximity to local operations staff. The objective is to produce similar process conditions to those encountered in the full-scale LAW melters and minimize the volume of radioactive waste necessary for the evaluations. To this end, melter design features are being explored to increase production without significantly increasing surface area, melter glass volumes or compromising data quality. In support of these objectives, a set of computational fluid dynamic models have been developed to provide insight into the flow patterns within these small melters and evaluate design features to increase production without significantly increasing glass inventory. Computed velocities were evaluated at the interface between the cold cap and the molten glass pool and within the bulk glass pool. A method was developed to correlate results to an estimated melt rate and down-select design features that produce the highest gains.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Computationally-Aided Design of a Small-Scale Radioactive Waste Glass Melter

To provide mission support to the Hanford Waste Immobilization and Treatment Plant for the vitrification of legacy nuclear tank waste, a reduced-scale vitrification pilot system is being designed to process simulated and actual radioactive tank wastes. The tank waste will be separated into high-level waste (HLW) and low-activity waste (LAW) fractions, where the majority by mass (~90%) is LAW and by activity (>95%) is HLW. The first tank waste to be processed at the WTP will be LAW. Since Hanford tank waste and the resultant melter feed compositions are known to vary widely, pilot-scale operations are essential to identify potential problems, provide needed data, confirm assumptions, and determine impacts to full-scale melters and off-gas systems from these different feeds. In addition, the reduced-scale melter system must be capable of quickly providing results to operations without the typically high costs of radioactive operations and provide an engineering platform in close proximity to local operations staff. The objective is to produce similar process conditions to those encountered in the full-scale LAW melters and minimize the volume of radioactive waste necessary for the evaluations. To this end, melter design features are being explored to increase production without significantly increasing surface area, melter glass volumes or compromising data quality. In support of these objectives, a set of computational fluid dynamic models have been developed to provide insight into the flow patterns within these small melters and evaluate design features to increase production without significantly increasing glass inventory. Computed velocities were evaluated at the interface between the cold cap and the molten glass pool and within the bulk glass pool. A method was developed to correlate results to an estimated melt rate and down-select design features that produce the highest gains.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Technical Performance of Refractory Liners for Molten Chloride Salt Thermal Energy Storage Systems

A chloride-based molten-salt system that uses a ternary blend of MgCl2/KCl/NaCl is investigated to provide higher temperature thermal energy storage capability. Despite higher thermal stability, molten chlorides present several unique challenges, including the design of internal refractory-ceramic liners to prevent the corrosion and thermal stress of alloy tank shells. This work discusses issues and potential solutions related to containment of molten chloride salt, specifically the optimization of the refractory material at the molten salt interface (hot face). The down-selected hot face candidate limits permeation of salt through the material and forms a highly stable secondary surface phase in equilibrium with the molten salt. A mortar is created using the corrosion resistant hot face brick. Brick and mortar composite are subjected to mechanical stress/strain analysis, in order to calculate composite material properties and better inform thermomechanical models. The U.S. Department of Energy Generation 3 (DOE Gen3) program seeks to develop higher efficiency CSP plants that can provide cost-competitive, flexible power in the U.S. electric grid. The proposed Gen3 Liquid Pathway CSP plant closely resembles the configuration of current nitrate salt power towers with two-tank storage (Gen2). The differences between Gen2 and Gen3 include the types of compatible materials used in salt storage tank construction. Stainless steel loses strength at Gen3 temperatures, and although nickel superalloys would be capable of withstanding sustained high temperatures, these materials are prohibitively expensive at scale. Uninsulated tank shells also pose a significant risk as common steels are highly susceptible to chemical attack from molten chloride salt. To address these concerns, refractory-ceramic based containment materials are proposed to line the inside of the hot and cold storage tanks. In doing so, stainless or carbon steel shells may be used in construction depending on the level of insulation provided. The composition of the internal liner requires careful consideration to maximize the efficacy of multiple parameters including corrosion resistance, strength at operating temperature, durability, and cost. This is particularly true for the material at the interface with the salt, known as the "hot face", which is responsible for protecting the insulating layers between the tank shell and the hot face brick layer. The molten salt in this system is superheated over 300 °C above its freeze temperature. Therefore, unlike other industrial processes which use refractory-lined vessels, it is not expected that a freeze plane will develop in the hot face. Therefore, the hot face must be designed to withstand chemical corrosion and inhibit permeation of molten salt into the insulating layers. A down selection was performed to identify a hot face candidate best equipped to maintain thermal, mechanical, and chemical integrity when exposed to molten salt over extended periods of time. Long-duration chemical capability experiments were conducted with the down selected hot face refractory fully immersed in molten chloride salt for up to 3000 hours. The average salt penetration does not exceed 100 microns. When extrapolated to 20 and 30 years of continuous exposure, the expected salt penetration depth is approximately 2.0 mm and 2.9 mm, respectively. A magnesium-rich secondary phases develops at the salt/refractory interface. X-ray diffraction identifies the material as forsterite (Mg2SiO4), which is reported to form synthetically in molten chloride salt solutions. These results suggest the selected hot face will adequately inhibit salt permeation. While there is optimism that the hot face brick will inhibit salt permeation, mortar joints are typically the weakest point of a refractory brick liner. From a thermochemical perspective, differing thermal expansion coefficients may result in the mortar and brick to grow independent of each other, creating gaps through which molten salt can penetrate. To address this issue, NREL has developed an in-house mortar composed of the down selected hot face brick that has been shown to be compatible with the salt. Compressive stress/strain analyses have been performed on the brick/ mortar composites to generate stress/strain curves. Modulus of elasticity and Poisson's ratio of the composite may be calculated from the stress/strain curves, in order to provide more representative data to finite element mechanical models for accurate approximation of stress on the tank shell and the amount of thermal expansion expected within the tank liner.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2021

Elucidation of Aromatic Catabolic Pathways in White-Rot Fungi

This project aims to investigate the hypothesis that white-rot fungi can simultaneously depolymerize lignin extracellularly and catabolize depolymerization products intracellularly as carbon and energy sources. Evaluating this hypothesis will provide deeper understanding of the role of white-rot fungi in facilitating carbon sequestration in Nature. Additionally, identifying the most promising fungal strains for lignin turnover and catabolism will catalyze future efforts in genetic tool development to enable metabolic engineering in white-rot fungi for lignin bioconversion to bioproducts. Lignin is the second most abundant plant-based biopolymer on Earth and represents up to 40% of the energy density of lignocellulosic biomass. Even though lignin is a massive natural carbon and energy reservoir, only a small group of basidiomycete fungi, namely white-rot fungi (WRF), have evolved the ability to efficiently depolymerize and mineralize lignin to CO2 and H2O. Considerable research efforts have been undertaken to understand how WRF depolymerize lignin but the biochemical reactions that convert lignin into CO2 have been largely neglected. In fact, it is unclear if WRF intracellularly catabolize lignin-derived aromatic compounds to utilize them as a carbon and energy source, or rather if lignin is depolymerized and mineralized extracellularly merely to facilitate access to cellulose and hemicellulose for use as a primary carbon source. To date, we have employed 13C-isotope labeling, systems biology approaches, and in vitro enzyme assays to definitively demonstrate that two WRF, Trametes versicolor and Gelatoporia (Ceriporiopsis) subvermispora, funnel carbon from lignin-derived aromatic compounds into central carbon metabolism via intracellular catabolic pathways [1]. Specifically, 13C-isotopic labeling approaches showed that these WRF utilize poplar-derived aromatic compounds (e.g. 4-hydroxybenzoic acid (4-HBA)) as a carbon source. In silico genome analysis led us to hypothesize a complete catabolic pathway for 4-HBA and identify multiple homologous sequences for enzymes with putative oxidative decarboxylase, hydroxylase, and ring-opening dioxygenase activities, which are among the main biochemical reactions acting on aromatic compounds. Spatial and differential proteomic and metabolomic analyses supported the proposed catabolic pathways and showed alternative catabolic steps in T. versicolor that were not present in G. subvermispora. Based on the in silico, proteomics, and transcriptomics results, we down-selected enzymes for further in vitro characterization, and we have assigned a function to six fungal enzymes (including oxidative decarboxylases, hydroxylases, and ring-opening dioxygenases). Interestingly, even though we selected homologous enzyme pairs from both WRF with similar -omics trends, in a few cases only one of the studied fungi showed activity for the proposed substrate. Based on all the observations from this study [1], we hypothesized that 4-HBA preferentially undergoes oxidative decarboxylation to hydroquinone and subsequent hydroxylation to 1,2,4-benzenetriol in G. subvermispora before ring cleavage, whereas 4-HBA would preferentially undergo hydroxylation to protocatechuate and further oxidative decarboxylation to 1,2,4-benzenetriol in T. versicolor. Examining additional decarboxylases and hydroxylases as well as enzymes from other protein families that can perform the same or similar oxidative reactions, such as cytochromes P450 with aromatic hydroxylation activity, will also be key for elucidating enzyme preferences for specific substrates. Overall, this work forms the foundation of a new research area based on lignin catabolism by WRF, which could be further exploited to convert the undervalued biopolymer lignin into value-added compounds.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

PLN-6268 Yttrium Hydride Post Irradiation Examination Plan

The overarching goal of the Department of Energy Office of Nuclear Energy (DOE-NE) microreactor program is to develop technologies for the deployment of civilian microreactors by stakeholders1. Microreactors are expressed as advanced transportable nuclear reactors operating at low power (<20MWth) but high temperatures (>600°C), as well as plug-and-play and inherently safe designs. One prerequisite of a microreactor is the compactness, so that a truck can transport the reactor under safe conditions with the current road infrastructure1,2. The compactness of these reactors likely can be attainable by use of solid components for the essentials of the nuclear core, such as fuel, core heat removal components, reflectors, and moderators. Among these essentials, where fuel enrichment must remain < 20% to meet High Assay Low Enrichment Uranium criteria (HALEU), the largest contribution to the compactness is offered by use of solid moderators which benefit from light atomic weight elements, such as hydrogen, carbon, and beryllium2. Among these, hydrogen-bearing materials, such as metal hydrides, are superior to other options from the lowest critical mass standpoint. Noting that, factors other than critical mass should be considered for a specific reactor design. Yttrium- or zirconium-based metal hydrides have been down-selected due to their neutronic performance. In addition to the neutronic perspective, maintaining hydrogen within the metal hydride is important at the high operating temperatures proposed by advanced reactors. Yttrium hydride (YHx) is, therefore, a proposed moderator material that offers better hydrogen retention at higher operating temperatures than zirconium hydrides due to higher retention and thermal stability of hydrogen in the metal3. The irradiated materials properties of metal hydrides, in this case YHx, must be assessed for the qualification of these moderators. Material testing and inspection processes must illustrate that the effects of dimensional and property changes on thermophysical and mechanical properties do not cause any significant changes on the microreactor safety, and the moderating power is maintained within design limits. Thus, the effect of irradiation on the thermophysical and mechanical properties must be determined. This post-irradiation examination (PIE) plan specifically aims to determine these properties for YHx following Advanced Test Reactor (ATR) irradiation.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Contech to Accelerate Cleantech: Seeding Emerging Innovation Programs for Construction Productivity and Energy Efficiency Integration; Preprint

Investments in U.S.-based start-ups that focus on advanced building construction technologies to increase construction productivity (contech) surged to approximately $3.1 billion in 2018 (as per Crunchbase data). More recently, emerging programs by government funding agencies, philanthropic foundations, and venture capitalists have been instrumental in supporting contech start-ups for innovations that increase productivity of energy efficiency integration and accelerate clean energy technologies (cleantech) for the buildings sector. These programs include R&D support and funding mechanisms for contech and cleantech. Traditionally, contech and cleantech are considered as two different innovation ecosystems. To enhance and scale up energy efficiency in buildings, creative programs that bring together contech and cleantech are critical. This paper provides a landscape assessment of the "contech-for-cleantech" innovation ecosystem in the U.S. and its impact in accelerating technology readiness and the development pipeline of "contech-for-cleantech". Technologies highlighted are robotics for retrofits, prefabrication of energy-efficient products, and advanced manufacturing of low-carbon net-zero buildings construction. Programs discussed include those led by (1) government funding agencies: American-Made Challenges with prizes like E-ROBOT for retrofits with robotics, (2) philanthropic foundations: Wells Fargo Innovation Incubator (IN2) that includes focus on energy efficiency and prefabrication, and (3) venture capitalists: Shadow Ventures Green Building Accelerator program which provides funding support to start-ups with ambitious plans for decarbonizing the built environment. This paper will also expand upon robust processes and criteria involved in judging and down-selection of start-ups through vetting and feedback from national lab researchers and industry experts in both cleantech and contech.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Simulation and Optimization of Volatile Fatty Acid Upgrading Strategies for Sustainable Transportation Fuel Production

Underutilized wet waste is a promising feedstock for production of carbon-neutral or carbon-negative liquid transportation fuels. Arrested methanogenesis of wet wastes by microbes, which produces mixtures of C2-C8 carboxylic acids (volatile fatty acids, VFAs), is practiced industrially at a pilot scale and the VFA products can be catalytically upgraded to molecules suitable for use as transportation fuels (alcohols and alkanes) via sequential ketonization and hydrogenation, both steps of which have been demonstrated with high (>90%) yield at the lab scale. We present in this work a simulation-based decision-making framework which evaluates upgrading strategies of VFAs to alcohol- and hydrocarbon-based neat and blended diesel, jet, and gasoline fuels. The processes utilize sequential upgrading steps (ketonization and hydrogenation) accompanied by one distillation step (either separating VFAs before ketonization or alcohols after ketone hydrogenation) to form two liquid streams: a light alcohol stream best suited as a light-duty fuel and a heavy alcohol or hydrocarbon stream best suited as a diesel or jet fuel. Suitability of the liquid products as transportation fuels and maximum blending levels with petrofuels comes from simulation of critical fuel properties (boiling point, flash point, lower heating value, viscosity, melting point, water solubility, and cetane/octane number). Catalytic upgrading steps and fuel property mixing models used by the simulation are experimentally validated. We demonstrate the flexibility of the decision-making algorithm by evaluating processing scenarios for experimentally-observed VFA profiles with varied carbon chain length distributions. Processing scenarios are optimized for either maximum total renewable carbon utilization or production of heavy-duty (jet or diesel) fuels. We evaluate the economic viability and CO2 emissions of each proposed upgrading scenario using techno-economic and life cycle analyses. The decision-making framework developed in this work can also be used to down-select promising strategies for upgrading of other bio-based feedstocks to sustainable fuels and chemicals.

aviation fuel↗
DOE OSTI2020

Oxidation of Glycolate in the Defense Waste Processing Facility (DWPF) Recycle Collection Tank - 20305

The Savannah River Site's Defense Waste Processing Facility (DWPF) operations are being upgraded with the introduction of the Nitric-Glycolic Flowsheet. Glycolic acid has been shown superior to formic acid as the reducing acid used during chemical processing. The new flowsheet improves or maintains necessary parameters such as 1) reduction of mercury, 2) adjustment of feed rheology and 3) adjustment of melter oxidation/reduction potential. Further, the potential for catalytic hydrogen generation in DWPF processing is virtually eliminated. DWPF process condensates are collected and returned to the SRS Concentration, Storage and Transfer Facilities (CSTF). The Recycle Collection Tank (RCT) collects off-gas condensate during chemical processing, vitrification, and other unit operations performed in DWPF and is the singular return vessel delivering recycle effluent back to CSTF. Each batch of recycle may contain a small amount of glycolate from chemical processing and melter off-gas condensates. To avoid potential flammability issues due to thermolysis of glycolate in the CSTF, chemical oxidation within the RCT has been investigated as an option for mitigating the transfer of glycolate. Sodium permanganate has been down-selected as the best option for oxidation of glycolate. Testing was performed using both 2-L and 22-L reactors (16,800:1 and 1,530:1 scale by volume) with non-radioactive waste simulants to approximate the expected RCT compositions. RCT simulants were evaluated at various process pH and temperature conditions. Also, RCT operations, namely the sequence of addition of corrosion inhibitors (NaOH and NaNO{sub 2}) versus a permanganate strike, were evaluated. Glycolate was introduced via a sludge simulant to mimic both expected entrainment and abnormal process foam-over conditions - the range being between 68 and 5100 mg/kg glycolate. Glycolate destruction was monitored by ion chromatography (IC). The corresponding manganese behavior was monitored in real-time using in situ ultraviolet-visible (UV-Vis) spectroscopy. RCT glycolate content can be reduced to below the IC detection limit within 90 minutes for all concentrations investigated. Ion Chromatography analysis revealed that under alkaline conditions, glycolate is primarily oxidized to oxalate with no significant formation of CO{sub 2} or carbonate, and nitrite is not oxidized to nitrate. Initially, complete oxidation of organics species and nitrite was assumed. Determination of the mechanistic chemical reaction has allowed the required amount of permanganate to be more accurately predicted and the total addition to be significantly reduced. UV-Vis measurements reveal that permanganate (Mn{sup 7+}) is reduced to manganate (Mn{sup 6+}) in the RCT. The oxidant stoichiometry is defined by using the initial permanganate to glycolate (P/G) molar ratio. At low initial glycolate concentration (68 and 140 mg/kg), the minimum required initial permanganate to glycolate (P/G) molar ratio was found to be 5-6. With high initial glycolate concentrations (5100 mg/kg) a lower (P/G) molar ratio of ∼2.5 was needed. The final portion of this effort supporting the nitric/glycolic flowsheet will be to test actual (fully radioactive) RCT samples as per the above simulant tests. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Virtual and Augmented Realities to Support Development, Training, Deployment, and Operations of Remote Systems - 20516

Throughout the U.S. Department of Energy complex, there is a need to deploy new, unique equipment and systems for cleanup activities, waste processing, infrastructure repair, and decommissioning and demolition in radioactive and hazardous environments. The new equipment often consists of custom systems created by integrating and modifying commercial technologies. In addition, the systems are deployed in unique environments due to limited access, waste properties, and the presence of previously installed equipment or infrastructure that has been left in place. The deployment of custom systems that are 'turnkey' ready for first-time installation and application has its risks. Use of test platforms and mockups for cold (i.e., non-radioactive) testing is one method to mitigate that risk: however, full-scale test mockups for operations such as waste retrieval and tank inspection can be expensive and must be modified to incorporate the uniqueness of each application. An alternative to full-scale mockups is to use three-dimensional (3D) virtual environments and virtual reality (VR) technology to develop interactive virtual test beds. These can be used throughout the down-selection, development, system integration, operational planning, operator training, and mission execution phases of a task. Virtual test beds are readily reconfigured, can be used for multiple tasks, support multiple users in parallel, and can accommodate enhancements and changes not originally planned or conceived in the initial design. Virtual test beds also provide a platform for developing and testing augmented reality (AR) tools for improving operator efficiency. A VR experience has been generated for waste retrieval from a Hanford waste tank to present the potential applications of a virtual test bed. Features of the VR experience are presented, potential applications of VR and AR for remote applications are discussed, and development areas for improving future application are considered. (authors)

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

Generating An Advanced Cross-section Library For HTGR Pebble Bed Depletion Calculations Using Reduced-Order Model Generation Techniques

For code development, Advanced Reactor Technologies - Gas Cooled Reactors Program (ART-GCR) rely on a collaboration with the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, but the cross sections generation and the methodology definition is part of this program area goals. Based on previous studies in FY23, the size of microscopic cross section libraries increases rapidly with the number of tabulations, requiring significant amount of memory and drastically slowing down the Griffin calculations when evaluating cross sections via the multivariate linear interpolation approach. Rising to these challenges, this work investigates constructing Reduced-order Models (ROMs) for the multi-group microscopic cross sections to accelerate the cross section evaluation in Griffin. A database of multigroup cross sections is first collected considering all possible parameters that a designer could change for optimization. Down-selection of the ROM techniques afterward shows Deep Neural Network (DNN) as the best candidate when jointly consider memory efficiency, predictive accuracy, computational cost, scalability, flexibility and ease of implementation of the algorithms in comparison to the multidimensional interpolation. This work develops a specific interface that enables the cross section predictions using pre-trained DNN models into Griffin leveraging the existing ROM capabilities. DNNs have been trained for all isotopes for use in Griffin. Preliminary Griffin testing shows that DNNs exhibit exceptional predictive accuracy and the use of DNNs provides orders of magnitude improvement in memory efficiency compared to conventional interpolation techniques. With such ROM techniques, it holds great promise to further increase the fidelity of the Pebble Bed Reactor (PBR) simulation by increasing the number of tabulations/state variables during cross section evaluation, while maintaining the computational cost affordable in Griffin.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Reduce-Order Modeling of Multigroup Neutron Cross Sections for High-Temperature Gas-cooled Reactors

Deterministic neutronics calculations rely on multigroup neutron cross section libraries, which usually consists of a database of tabulated values, used to calculate the cross sections through multivariate linear interpolation. However, interpolation of the multidimensional cross section data becomes memory inefficient and time consuming as the number of tabulations increases, significantly slowing down the neutronics calculation, especially in the case of micro cross section libraries where every isotope (on the order of hundreds) has its own set of specific reactions and cross sections. To address this challenge, this work constructs efficient and robust reduced-order models (ROMs) of the multi-group cross sections to support the Griffin simulation of high-temperature gas-cooled reactors (HTGRs). The first part of the study investigates the linearity of the multi-group cross section data across isotopes, reaction types and energy groups on pre-generated datasets for the purpose of dimensionality reduction. Secondly, a down-selection of ROM techniques is presented on representative classical machine learning (ML) techniques, including variants of linear regression, kernel-based methods, tree-based algorithms, and artificial neural networks. The selection criteria jointly consider the memory efficiency, predictive accuracy, prediction speed, and scalability in comparison to the multidimensional interpolation. Among all the ML techniques, deep neural networks (DNNs) have proven to be the best selection with sufficient accuracy, high robustness, good memory efficiency, great scalability, and superior flexibility. DNNs for have been trained for all isotopes in this work and systematic Griffin testing is ongoing at this moment to ensure the feasibility of this ROM technique for cross section predictions.

42 - ENGINEERING↗
DOE OSTI2024

Reduced-Order Modeling of Multigroup Neutron Cross Sections for High-Temperature Gas-cooled Reactors

Abstract – Deterministic neutronics calculations rely on multigroup neutron cross section libraries, which consist of databases of tabulated values, used to calculate the neutron cross sections through multivariate linear interpolation. However, interpolation of the multidimensional cross section data becomes memory inefficient and time consuming as the number of tabulations increases, significantly slowing down the neutronics calculation, especially in the case of microscopic cross section libraries where every isotope (on the order of hundreds) has its own set of specific reactions and cross sections. In order to address this challenge, this work constructs efficient and robust reduced-order models (ROMs) of the multi-group cross sections to support the Griffin simulation of high-temperature gas-cooled reactors (HTGRs). The first part of the study investigates the linearity of the multigroup cross section data across isotopes, reaction types, and energy groups on pre-generated datasets for the purpose of dimensionality reduction. Secondly, a down-selection of ROM techniques is presented on representative classical machine learning (ML) techniques, including variants of linear regression, kernel-based methods, tree-based algorithms, and artificial neural networks. The selection criteria jointly consider the memory efficiency, predictive accuracy, prediction speed, and scalability in comparison to the multidimensional interpolation. Among all the ML techniques, deep neural networks (DNNs) have proven to be the best selection with sufficient accuracy, high robustness, good memory efficiency, great scalability, and superior flexibility. DNNs have been trained for all isotopes in this work and systematic Griffin testing is ongoing to ensure the feasibility of this ROM technique for predicting cross section and reducing memory requirements without a significant sacrifice in computational performance.

42 - ENGINEERING↗
DOE OSTI2024

Advanced Cross Section Library Generation using Reduced Order Models

Deterministic neutronics calculations rely on multigroup neutron cross section libraries, which consist of databases of tabulated values, used to calculate the neutron cross sections through multivariate linear interpolation. However, interpolation of the multidimensional cross section data becomes memory inefficient and time consuming as the number of tabulations increases, significantly slowing down the neutronics calculation, especially in the case of microscopic cross section libraries where every isotope (on the order of hundreds) has its own set of specific reactions and cross sections. In order to address this challenge, this work constructs efficient and robust reduced-order models (ROMs) of the multi-group cross sections to support the Griffin simulation of high-temperature gas-cooled reactors (HTGRs). The first part of the study investigates the linearity of the multigroup cross section data across isotopes, reaction types, and energy groups on pre-generated datasets for the purpose of dimensionality reduction. Secondly, a down-selection of ROM techniques is presented on representative classical machine learning (ML) techniques, including variants of linear regression, kernel-based methods, tree-based algorithms, and artificial neural networks. The selection criteria jointly consider the memory efficiency, predictive accuracy, prediction speed, and scalability in comparison to the multidimensional interpolation. Among all the ML techniques, deep neural networks (DNNs) have proven to be the best selection with sufficient accuracy, high robustness, good memory efficiency, great scalability, and superior flexibility. DNNs have been trained for all isotopes in this work and systematic Griffin testing is ongoing to ensure the feasibility of this ROM technique for predicting cross section and reducing memory requirements without a significant sacrifice in computational performance.

42 - ENGINEERING↗
DOE OSTI2026

Alternative Analysis and Prioritization of Department of Energy “TBD” Materials with No Identified Disposition Pathway

The Department of Energy (DOE) complex manages a significant inventory of excess nuclear materials for which disposition pathways have not been identified, commonly referred to as "To Be Determined" (TBD) items. The Disposition Pathways Program, initiated in FY2018, provides a standardized framework for identifying viable disposition pathways for these materials. In 2023, the program undertook a comprehensive review and systematic analysis of the remaining TBD material groups, updating the assessment from the 2020 TBD Study using the 2022 fiscal year-end Nuclear Material Inventory Assessment (NMIA) as the primary data source. This effort aimed to utilize quantitative analysis to down-select from a wide range of potential disposition options and prioritize the remaining pathways to facilitate informed, risk-based decision-making for future programmatic funding and execution. This paper details the alternative analysis methodology used for screening and prioritization, highlighting the key criteria, ranking process, and resultant recommendations. The study successfully narrowed fifty-two potential disposition options down to nineteen, providing a focused path forward for addressing a longstanding challenge within the DOE complex.

Ramsey, Catherine [Savannah River National Laborat↗
DOE OSTI2024

BioPhotovoltaics: New paradigm towards high-efficiency and high-stability cells

In this project, we demonstrated significant progress in the development of Bio-Photovoltaic (BioPV) technology, with a particular focus on the transition from the initial success with Artemisinin (ART) to the development of the E1 compound. This journey began with the exploration of less conformationally restricted analogs of ART, leading to the discovery of E1. The initial success in the first quarter with ART set a precedent for the project, guiding our approach in molecular selection and design. Our computational studies provided a solid rationale for selecting specific biomolecules, with density functional theory calculations revealing the potential of certain molecules to form beneficial interactions with perovskite. This was a crucial step in narrowing down the candidate molecules from a broader selection. Subsequently, our approach involved simplifying these molecules to refine their properties and enhance their performance in bioPV applications. The ART-MAPbI3 films, for example, showcased not only high carrier mobility and hydrophobicity but also a significant increase in PCE. The evolution from ART to E1 was marked by a thorough understanding of molecular interactions and their impact on the material’s performance. This progression, from the complexity of lead candidates to the modeling and testing of simplified compounds, has culminated in the development of next-generation biomolecules with vastly improved properties. The link between E1 and ART, through this enhanced understanding, has been compelling and instrumental in achieving the milestones set forth in our project. The success in material and device performance underscores the importance of fundamental molecular design parameters, pointing towards future potential in the field of bioPV technology.

14 SOLAR ENERGY↗