Ru-Catalyzed Polyethylene Hydrogenolysis under Quasi-Supercritical Conditions
Not Available
catalytic polyolefin conversion↗
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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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A conditional latent autoregressive recurrent model for generation and forecasting of beam dynamics in particle accelerators
Not Available
97 MATHEMATICS AND COMPUTING↗
Demonstration and Evaluation of Explainable and Trustworthy Predictive Technology for Condition-based Maintenance
The domestic nuclear power plant (NPP) fleet has historically relied on labor-intensive and time-consuming predictive maintenance (PdM) programs, thus driving up operation and maintenance (O&M) costs to achieve high-capacity factors. Artificial intelligence (AI) and machine-learning (ML) can help simplify complex problems such as diagnosing equipment degradation to enable more effective decision-making efforts. The benefits of AI will be felt through more efficient plant O&M, improved work processes, and better integration of people and technology. Together, these benefits hold the promise to make nuclear power more sustainable by reducing O&M costs while improving employee engagement. While AI and ML technologies hold significant promise for the nuclear industry, there are challenges or barriers to their adoption. Explainability and trustworthiness of AI are two salient challenges that need to be addressed for wider deployment of these technologies in NPPs. This research focuses specifically on addressing the explainability and trustworthiness of AI technologies to advance the human, technical, and organization (HTO) readiness levels in adopting a risk-informed PdM strategy at commercial NPPs. In addition, this approach can be adapted to enhance the acceptability of AI in other nuclear applications with a few application-specific modifications. The technical approach ensuring wider adoption of AI technologies was developed by Idaho National Laboratory (INL)—in collaboration with Public Service Enterprise Group (PSEG), Nuclear, LLC—by utilizing the circulating water system (CWS) at two PSEG-owned plant sites for demonstration. Focused user studies were performed in collaboration with subject matter experts (SMEs) from PSEG and other nuclear domains to enhance human and organization readiness by building trust in AI-informed technologies. VIsualization for PrEdictive maintenance Recommendation (VIPER)—a Battelle Energy Alliance, LLC, copyrighted software—was developed and expanded to provide a user-centric visualization by incorporating inputs from the collaborating utility, human factors engineering guidelines, and data analysts. The VIPER software enables users, who may be unfamiliar with ML in general, to be interactively engaged by asking technical questions about PdM, work orders, diagnosis results and their confidence levels, the kind of data being used, and the types of ML algorithms employed. This interactive engagement enhances explainability and builds trust. One of the enabling accomplishments was the integration of large language models (LLMs), both text-based and vision-based, in the VIPER software.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Nucleation and Growth of Blue Phase 3D Cubic Structure Under Continuously Changing Curved Boundary Conditions
The blue phase of liquid crystals (BPLCs) with a cubic lattice of disclination lines and 3D nanostructure enables the modulation of photonic bandgap thus casting them in the category of photonic crystals. Its unique nature promises applications in display technologies, electro‐optics, and sensors. To integrate these ordered materials into wearable devices a fundamental understanding of curvature, and spatial confinement is necessary. Although continuous confinement in flat geometries have been studied, confining curvature has shown to induce strong destabilization effects on the cubic structure and formation of topological defects, thereby deteriorating their optical performance. Moreover, limitations in controlling the curvature of droplets further hinder studies of nucleation and growth of BPLCs. Here, to address these challenges, micro‐scale patterned surfaces of concentric cylinders are exploited to systematically control curvatures. The impact of curvature on the confined BPLCs is revealed in terms of phase transition temperature, nucleation and growth, morphology, as well as phase transformation. This research offers valuable insights into the stability, and structural characteristics of BPLCs in adaptive photonic devices, paving the way for future advancements in flexible displays, sensors, and other technologies leveraging liquid crystal (LC) materials.
3D Cubic Structure↗
Deformation Behaviors in Single BCC‐Phase Refractory Multi‐Principal Element Alloys under Dynamic Conditions
The mechanical behavior and microstructural evolution of a BCC-phase NbTaTiV refractory multi-principal element alloy (RMPEA) is studied over a wide range of strain rates (10 −3 to 10 3 s −1 ) and temperatures (room temperature to 850 °C). The mechanical property of present RMPEA shows less strain-rate dependence and strong resistance to softening at high temperatures. Under high strain-rate loading, the formation of thin type-I twins is observed, which could lead to an increase in strain-hardening rates. However, this hardening mechanism competes with adiabatic heating effects, resulting in the deterrence of strain-hardening behaviors. In contrast, substantial strain-hardening occurs at cryogenic temperatures due to the formation of twins, which act as stronger barriers to dislocation motion and interact with each other. To further understand the different strain-hardening behaviors, density functional theory (DFT) calculations predict relatively low stacking fault energies and high twinning stress for the NbTaTiV RMPEA.
36 MATERIALS SCIENCE↗
Tropical Forest Soil Microbiome Modulates Leaf Heat Tolerance More Strongly Under Warming Than Ambient Conditions
ABSTRACT It is unclear how plants respond to increasing temperatures. Leaf heat tolerance (LHT) is often at its upper limit in tropical forests, suggesting that climate change might negatively impact these forests. We hypothesized that intraspecific variation in LHT might be associated with changes in the soil microbiome, which might also respond to climate. We hypothesized that warming would increase LHT through changes in the soil microbiome: we combined an in situ tropical warming experiment with a shade house experiment in Puerto Rico. The shade house experiment consisted of growing seedlings of Guarea guidonia , a dominant forest species, under different soil microbiome treatments (reduced arbuscular mycorrhizal fungi, reduced plant pathogens, reduced microbes, and unaltered) and soil inoculum from the field experiment. Heat tolerance was determined using chlorophyll fluorescence ( F V /F m ) on individual seedlings in the field and on groups of seedlings (per pot) in the shade house. We sequenced soil fungal DNA to analyze the impacts of the treatments on the soil microbiome. In the field, seedlings from ambient temperature plots showed higher F V /F m values under high temperatures (0.648 at 46°C and 0.067 at 52°C) than seedlings from the warming plots (0.535 at 46°C and 0.031 at 52°C). In the shade house, the soil microbiome treatments significantly influenced the fungal community composition and LHT ( T crit and F V /F m ). Reduction in fungal pathogen abundance and diversity altered F V /F m before T 50 for seedlings grown with soil inoculum from the warming plots but after T 50 for seedlings grown with soil inoculum from the ambient plots. Our findings emphasize that the soil microbiome plays an important role in modulating the impacts of climate change on plants. Understanding and harnessing this relationship might be vital for mitigating the effects of warming on forests, emphasizing the need for further research on microbial responses to climate change.
Hernandes Villani, Gabriela [Department of Plant B↗
Mechanical and poroelastic behavior of porous tuff under drained and undrained conditions
A series of drained and undrained water-saturated constant mean-stress tests were performed to investigate the strength, elasticity, and poroelastic response of a water-saturated high porosity nonwelded tuff. Drained strengths are found to increase with increasing effective confining pressures. Elastic moduli increase with increasing mean stress. Undrained strengths are small due to development of high pore pressures that generate low effective confining pressures. Skempton’s values are pressure dependent and appear to reflect the onset of inelastic deformation. Permeabilities decrease after deformation from ~ 10 –14 to ~ 10 –16 m 2 and are a function of the applied confining pressure. Deformation is dominated by pore collapse, compaction, and intense microfracturing, with the undrained tests favoring microfracture-dominant deformation and the drained tests favoring compaction-dominant deformation. These property determinations and observations are used to develop/parameterize physics-based models for underground explosives testing.
58 GEOSCIENCES↗
On Master-Length Scale Formulations for Stable Conditions in Turbulence Closure Models
Three formulations of the turbulence-length scales used in numerical modelling of atmospheric flows are compared. The comparison is made using the Mellor–Yamada–Nakanishi–Niino turbulence closure model within the stable boundary layer local similarity framework. With an appropriate choice of model constants, the model predictions are barely discernible and compare well with the empirical data obtained from the SHEBA campaign.
54 ENVIRONMENTAL SCIENCES↗
Initial Conditions of Planet Formation: Time Constraints from Small Bodies and the Lifetime of Reservoirs in the Solar Protoplanetary Disk
This review explores the timescales of the initial phase of planet formation, from nebular dust (CAIs and chondrules) to planetesimal accretion and differentiation, using evidence from meteorite research. Aluminium-Mg systematics of CAIs indicate either an extended period of CAI formation (∼0.3 Ma) or an initial 26 Al heterogeneity, with evidence supporting a homogeneous 26 Al abundance in the protoplanetary disk. Thermal and aqueous alteration on the parent body can disturb the U-Pb and Al-Mg chronometers in chondrules. Focusing on relatively robust isochron data from plagioclase of pristine (types ≤3.05) chondrites indicates a shift in chondrule formation locations, moving from the inner to the outer disk over time. Ages of basaltic achondrites show that silicate differentiation on small bodies was well underway within the first few million years (Ma) of our solar system. Their age record, however, reveals inconsistencies between different chronometers, partly caused by (i) secondary disturbances due to thermal metamorphism, aqueous alteration, or impacts, (ii) the presence of xenolithic minerals, and (iii) potentially variable initial 26 Al abundances due to disturbances at the mineral scale. Nucleosynthetic isotope data indicate that parent bodies of iron and stony meteorites formed in two distinct regions within the protoplanetary disk: the inner, non-carbonaceous (NC) and the outer, carbonaceous (CC) region. Based on Hf-W chronometry it has been demonstrated that NC and CC parent bodies of magmatic iron meteorites segregated their cores within ∼1–3 Ma after CAI formation, implying that parent body accretion occurred within <1 Ma in both reservoirs. Combining accretion ages with nucleosynthetic data further reveals that, at first order, NC and CC reservoirs in the solar protoplanetary disk were established within 1 Ma and existed over several Ma with limited exchange between them. In the CR chondrite accretion region of the disk, planetary bodies formed over at least 3 Ma, while in most other regions, formation spanned at least 1 Ma, with minimal changes in nucleosynthetic isotope compositions. Aerodynamical size sorting of dust likely introduced or amplified some of these variations.
26Al distribution↗
Challenges in developing materials for microreactors: A case-study of yttrium dihydride in extreme conditions
Not Available
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Active learning for the design of polycrystalline textures using conditional normalizing flows
Generative modeling has opened new avenues for solving previously intractable materials design problems. However, these new opportunities are accompanied by a drastic increase in the required amount of training data. This is in stark juxtaposition to the high expense and difficulty in curating such large materials datasets. In this work, we propose a novel framework for integrating generative models within an active learning loop. Further, this enables the training of generative models with datasets significantly smaller than what has previously been demonstrated, providing a direct route for their application in data constrained environments. The functionality of this framework is then demonstrated by addressing the challenge of designing polycrystalline textures associated with target anisotropic mechanical properties. The developed protocol exhibited a cost reduction between 14 to 18 times over a randomly sampled experimental design.
36 MATERIALS SCIENCE↗
Impact of salinity on morphology, growth, and pigment profiles of Scenedesmus obliquus HTB1 under ambient air and elevated CO 2 (10 %) conditions
Certain microalgal species, such as Scenedesmus obliquus strain HTB1, thrive under high CO 2 concentrations, making them promising for carbon sequestration to mitigate climate change. Isolated from the Baltimore Inner Harbor, HTB1 grows faster with 10 % CO 2 than with ambient air. To investigate its responses to salinity and elevated CO 2 , two experiments were conducted. In the first, HTB1 was cultured at seven different salinities (0, 17.5, 20, 22.5, 25, 27.5, and 30 ppt) (parts per thousand) under ambient air. Higher salinity caused cell shrinkage, color changes from green to pale white, reduced pigments like zeaxanthin, lutein, and chlorophyll b, but increased canthaxanthin. Growth declined significantly above 22.5 ppt. The second experiment compared HTB1's response to salinity (0, 10, 20 ppt) under air and 10 % CO 2 . Cultures under 10 % CO 2 showed minimal color changes, while those under air shifted from green to brown, with salinity having less inhibitory effects on growth under elevated CO 2 . Interestingly, lutein and canthaxanthin levels rose with salinity in 10 % CO 2 . These findings indicate that elevated CO 2 mitigates salt stress in HTB1, reducing its impact on growth and promoting adaptive pigment changes. This study sheds light on how salinity and CO 2 interact to influence HTB1's morphology, growth, and pigment composition, enhancing our understanding of its resilience and potential applications.
20 FOSSIL-FUELED POWER PLANTS↗
High-burnup boiling water reactor steady-state operating conditions and fuel performance analysis
The primary operational costs for existing nuclear reactors are plant operation costs, maintenance costs, and fuel costs, all of which are influenced by the materials used and the design of the reactor core. Optimizing core design parameters—including burnup limits and enrichment levels—can lengthen cycles, reduce outages, reduce reload batch fractions and spent fuel storage requirements, and lower maintenance and operating expenses, thereby enhancing economic viability. Furthermore, developing higher-fidelity tools to simulate these parameters enables better identification of the available margin, improves overall plant safety, and improves the understanding a given plant’s responses to accident scenarios. Here, in the US, much of the research and development focus has traditionally been on pressurized water reactors (PWRs), but boiling water reactors (BWRs) comprise approximately one-third of the US reactor fleet. Modeling and simulation advances for BWRs and PWRs—particularly those achieved through the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program—are crucial to the long-term viability of the light–water reactor industry. A key research area of the high burnup and increased enriched fuel initiative is focused on addressing issues related to postulated loss-of-coolant accident (LOCA) scenarios. NEAMS has dedicated significant effort to enhancing tools to better support BWRs. A current focus is showcasing the BWR framework for high-burnup LOCA analysis. This high-fidelity steady-state analysis is a first step toward demonstrating a best-estimate, pin-by-pin high-burnup BWR LOCA analysis to assess full-core cladding rupture behavior for a representative BWR. The objective of this effort is to provide a modeling capability that will help elucidate and provide a best-estimate evaluation for cladding rupture susceptibility in BWRs. This modeling capability could then be used to prevent and/or mitigate cladding ruptures in postulated accident scenarios without penalizing operational parameters. Additionally, the results of this work will help identify strategies for finding additional margins or potentially limiting cladding ruptures through core design optimizations to enable more efficient core designs.
Capps, Nathan [Oak Ridge National Laboratory (ORNL↗
The role of interface boundary conditions and sampling strategies for Schwarz-based coupling of projection-based reduced order models
Not Available
Wentland, Christopher R.↗