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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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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Topological Hall Effect Anisotropy in Kagome Bilayer Metal Fe 3 Sn 2

Kagome lattice materials attract growing interest for their topological properties and flat-bands in electronic structure. We present comprehensive study on the anisotropy and out-of-plane electric transport in Fe 3 Sn 2 , a metal with bilayer of Fe kagome planes and with massive Dirac fermions that features high-temperature non-collinear magnetic structure and magnetic skyrmions. For the electrical current path along the c-axis, in micron-size crystals, we found a large topological Hall effect (THE) over a wide temperature range down to spin-glass state. Twofold and fourfold angular magnetoresistance are observed for different magnetic phases, reflecting the competition of magnetic interactions and magnetic anisotropy in kagome lattice that preserve robust topological Hall effect for inter kagomebilayer currents. This information provides new insight into the anisotropy in Fe 3 Sn 2 , of interest in skyrmionicbubble application-related micron-size devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1986

Geochemical characters and tectonic evolution of the Chitradurga schist belt: An Archaean suture (?) of the Dharwar Craton, India

The Chitradurga schist belt extending for about 450 km in a NS direction and 2-50 km across, is one of the most prominent Archean (2.6 b.y.) tectonic features of the Indian Precambrian terrain, comprising about 2 to 10 km thick sequence of volcano sedimentary rocks. The basal unit of this belt is composed of an orthoquartzite-carbonate facies, unlike many other contemporary greentone belts of the Gondwana land which begin with a basal mafic-ultramafic sequence. Eighty percent of the belt is made up of detrital and chemogenic sediments, their succession commencing with a poorly preserved quartz pebble basal conglomerate and current bedded quartzites which, in turn, rest on tonalitic gneisses, the latter having been further remobilized with along the schist belt. Deposition of current bedded matue arenites indicte the existence of platformal conditions near the shore line. Polymictic graywacke conglomerates, graywackes, shales, phyllites, carbonates, BIFs (oxide, carbonate and sulfide) BMF's (Banded Maganese Formations) and cherts thus constitute the main sedimentary rocks of the belt. The polymicitic conglomerates contain debris of rocks of older greenstone sequences, as well as an abundant measure of folded quartzites, BIF's and gneissic fragments which represent earlier orogenies.

Naqvi, S. M.↗
NASA NTRS2009

Spinoff 2009

Topics covered include: Image-Capture Devices Extend Medicine's Reach; Medical Devices Assess, Treat Balance Disorders; NASA Bioreactors Advance Disease Treatments; Robotics Algorithms Provide Nutritional Guidelines; "Anti-Gravity" Treadmills Speed Rehabilitation; Crew Management Processes Revitalize Patient Care; Hubble Systems Optimize Hospital Schedules; Web-based Programs Assess Cognitive Fitness; Electrolyte Concentrates Treat Dehydration; Tools Lighten Designs, Maintain Structural Integrity; Insulating Foams Save Money, Increase Safety; Polyimide Resins Resist Extreme Temperatures; Sensors Locate Radio Interference; Surface Operations Systems Improve Airport Efficiency; Nontoxic Resins Advance Aerospace Manufacturing; Sensors Provide Early Warning of Biological Threats; Robot Saves Soldier's Lives Overseas (MarcBot); Apollo-Era Life Raft Saves Hundreds of Sailors; Circuits Enhance Scientific Instruments and Safety Devices; Tough Textiles Protect Payloads and Public Safety Officers; Forecasting Tools Point to Fishing Hotspots; Air Purifiers Eliminate Pathogens, Preserve Food; Fabrics Protect Sensitive Skin from UV Rays; Phase Change Fabrics Control Temperature; Tiny Devices Project Sharp, Colorful Images; Star-Mapping Tools Enable Tracking of Endangered Animals; Nanofiber Filters Eliminate Contaminants; Modeling Innovations Advance Wind Energy Industry; Thermal Insulation Strips Conserve Energy; Satellite Respondent Buoys Identify Ocean Debris; Mobile Instruments Measure Atmospheric Pollutants; Cloud Imagers Offer New Details on Earth's Health; Antennas Lower Cost of Satellite Access; Feature Detection Systems Enhance Satellite Imagery; Chlorophyll Meters Aid Plant Nutrient Management; Telemetry Boards Interpret Rocket, Airplane Engine Data; Programs Automate Complex Operations Monitoring; Software Tools Streamline Project Management; Modeling Languages Refine Vehicle Design; Radio Relays Improve Wireless Products; Advanced Sensors Boost Optical Communication, Imaging; Tensile Fabrics Enhance Architecture Around the World; Robust Light Filters Support Powerful Imaging Devices; Thermoelectric Devices Cool, Power Electronics; Innovative Tools Advance Revolutionary Weld Technique; Methods Reduce Cost, Enhance Quality of Nanotubes; Gauging Systems Monitor Cryogenic Liquids; Voltage Sensors Monitor Harmful Static; and Compact Instruments Measure Heat Potential.

Source record↗
NASA NTRS2021

Empirical Constraints on Progressive Shock Metamorphism of Magnetite from the Siljan Impact Structure, Sweden

Little is known about the microstructural behavior of magnetite during hypervelocity impact events, even though it is a widespread accessory mineral and important magnetic carrier in terrestrial and extraterrestrial rocks. We report systematic electron backscatter diffraction crystallographic analysis of shock features in magnetite, from a transect across the 52-km diameter ~380 Ma Siljan impact structure in Sweden. Magnetite grains in granitoid samples contain brittle fracturing, crystal-plasticity, and lamellar twins. Deformation twins along {111} with shear direction of <112> are consistent with spinel-law twins. Inferred bulk shock pressures for investigated samples, as constrained by planar deformation features (PDFs) in quartz and shock twins in zircon, range from 0–20 GPa; onset of shock-induced twinning in magnetite is observed at >5 GPa. These results highlight the utility of magnetite to record shock deformation in rocks that experience shock pressures >5 GPa, which may be useful in quartz-poor samples. Despite significant hydrothermal alteration, and variable transformation of host magnetite to hematite, shock effects are preserved, demonstrating that magnetite is a reliable mineral for preserving shock deformation over geologic time.

magnetite↗
DOE OSTI2022

Advanced modeling and simulation of research reactors using dynamic mode decomposition

Full text of publication follows. Due to the ever-increasing safety requirements, the current trend of nuclear reactor analysis is shifting towards high-fidelity multi-physics models, which have a very high computational cost and modelling complexity. As the cost of even a single model run makes it impossible to analyse the behaviour and performance of these models on large-scale commercial plants, it has become even more significant to provide suitable benchmarks to validate and test them extensively. In this sense, research reactors offer a promising solution for the initial validation of high-fidelity models, as they are significantly smaller than commercial reactors and their characteristics are well known. In particular, the reactors of the TRIGA family have been used to assess and validate models and methods for Generation-IV designs, as they have some similar features (such as the dominance of natural convection as cooling mechanism and the difficulties in performing sub-channel analysis using standard codes). Still, the computational requirements of high-fidelity models make them unsuitable for real-time analysis, even following their assessment on research reactors. In this sense, Model Order Reduction (MOR) techniques give an additional strategy to reduce the computational cost of high-fidelity models (whilst preserving sufficient accuracy). In particular, this work focuses on Dynamic Mode Decomposition (DMD), a non-intrusive MOR technique that aims at representing models with explicit temporal dynamics by extracting the time-varying characteristics and the governing structures based only on a set of available data, thus without needing any underlying knowledge of the governing equations. In addition, DMD also computes a low-dimensional surrogate of the dynamic matrix of the system, making it suited for stability analysis and real-time evaluations. This work focuses on the application and validation of the DMD method on the Computational Fluid-Dynamics (CFD) model TRIGA Mark II reactor, also discussing in detail the potentiality of this algorithm as an advanced modelling tool for nuclear reactor analysis. (author)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Library of Advanced Materials for Engineering (LAMÉ) 5.2

Accurate and efficient constitutive modeling remains a cornerstone issue for solid mechanics analysis. Over the years, the LAMÉ advanced material model library has grown to address this challenge by implementing models capable of describing material systems spanning soft polymers to stiff ceramics including both isotropic and anisotropic responses. Inelastic behaviors including (visco)plasticity, damage, and fracture have all incorporated for use in various analyses. This multitude of options and flexibility, however, comes at the cost of many capabilities, features, and responses and the ensuing complexity in the resulting implementation. Therefore, to enhance confidence and enable the utilization of the LAMÉ library in application, this effort seeks to document and verify the various models in the LAMÉ library. Specifically, the broader strategy, organization, and interface of the library itself is first presented. The physical theory, numerical implementation, and user guide for a large set of models is then discussed. Importantly, a number of verification tests are performed with each model to not only have confidence in the model itself but also highlight some important response characteristics and features that may be of interest to end-users. Finally, in looking ahead to the future, approaches to add material models to this library and further expand the capabilities are presented.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Linkages Between Mineral Element Composition of Soils and Sediments With Hyporheic Zone Dissolved Organic Matter Chemistry Across the Contiguous United States

The hyporheic zone is a hotspot for biogeochemical cycling where interactions with mineral metals preserve the release and biodegradation of organic matter (OM). A small fraction of OM can still be exchanged between localized sediments and the overlying water column, and recent evidence suggests there exists a longitudinal structuring in sediment dissolved OM (DOM) chemistry across the continental United States (CONUS). In this study, we tested a hypothesis that water extractable sediment DOM chemistry could be explained by sediment metal contents and integrative watershed scale features at the CONUS scale. Crowdsourced samples were characterized for high resolution mass spectrometry and coupled with sediment metals determined via x-ray fluorescence as well as with land cover and soil elemental information obtained from national databases. Our results highlight weak relationships between DOM chemistry and elemental composition at the CONUS scale indicating limited transferability of organo-metal linkages into multi-scale hydrobiogeochemical models.

58 GEOSCIENCES↗
NASA NTRSDate not supplied

Real Time Nitrogen Monitoring and Quality Control System for NASA Astromaterials Collection

The Nitrogen system is a vital utility supporting the curation office within NASA's Astromaterials Re-search and Exploration Science (ARES) Division at the Johnson Space center (JSC). Since the Apollo samples were returned in 1969. It has played an essential role in preserving NASA’s astromaterial collections (now nine collections) by maintaining contamination-free, controlled environments required for long term curation and advanced scientific research. To meet the stringent purity requirements for contamination control, high purity modified Grade C Liquid Nitrogen (LN2) is delivered weekly by an industrial gas vendor to a 15,000-gallon tank located outside at NASA JSC near the ARES facility. This nitrogen is vital for creating an inert atmosphere to store the collection in, ensuring they are continuously shielded from contaminants and alterations through a constant N2purge. For most of the past 65 years deliveries of LN2 have required a CoA (Certificate of Analysis) prior to delivery. If those were not available, then LN2 deliver were sent to third-party laboratories for verification, creating an operational bottleneck and quality gap. To address this challenge and maintain rigorous quality control, NASA JSC Infrastructure and Astromaterials Acquisition & Curation Office initiated the development of an on-site Analytical Gas Sampling (AGS) Laboratory. Designed to streamline quality verification if a CoA unavailable, the AGS lab was constructed by a subcontractor in Newton, NJ. After a successful factory acceptance test conducted by the NASA ARES Infrastructure team, the lab was trans-ported to NASA JSC, where it was anchored and integrated into the site’s nitrogen pressure system using stainless steel, oxygen-cleaned tubing. The ARES nitrogen system was modified to provide parallel flows to the AGS lab for quality control and to the astromaterials collection labs for maintaining an inert environment. The AGS lab features two operational modes: (1)Primary: Gaseous Nitrogen (GN2) Quality Monitoring –The AGS system continuously samples the site’s GN2 supply every 15 minutes to ensure compliance with required purity levels. (2) Secondary: LN2 Quality Verification when a comprehensive CoA is not available, a cryogenic vaporizer converts LN2 to GN2, which is then analyzed for impurities: H₂, Ar, O₂, CO, CO₂, H₂O, and total hydrocarbons (THC). By significantly enhancing on-site analytical capabilities, the AGS lab eliminates reliance on external testing, ensures uninterrupted quality monitoring of the nitrogen pressure system, and reinforces NASA’s commitment to preserving pristine astromaterials under the highest standards of curation and research integrity.

glove box↗
NASA NTRS2003

Impact Craters of Venus with D Greater Than 5 km Classified Based on Degree of Preservation of the Associated Radar-Dark Deposits

This is a further continuation of work, which studied craters greater than or equal to 30 km in diameter. That work subdivided craters based on character of the associated radar dark deposits. It was suggested and then confirmed that the most pristine deposits of that sort are radar-dark parabolas. Non-parabolic radar-dark halos represent the next stage of the deposit evolution and then with time they disappear. So presence and character of crater-associated dark deposit can be used for estimates of the crater age and then for dating other features. Previous work classified craters into: 1) craters with dark parabola (DP), 2) with clear dark halo (CH), 3) with faint halo (FH) and 4) with no dark halo (NH). It was found that abundances of craters superposed on regional plains (whose mean age is close to the planet mean surface age T) and belonging to DP, CH, FH and NH classes were correspondingly 15, 30, 30 and 25%. From that it was concluded that DP craters are not older than 0.1-0.15T; CH craters formed during the time interval from approx. 0.5T until 0.1-0.15T ago, and the FH and NH craters formed prior to approx. 0.5T ago. It was shown that the DP, CH, FH and NH percentages show only slight apparent dependence on the crater geographic latitudes and no noticeable dependence on the crater size. The present study analyzes a much larger population (all D greater than or equal to 5 km craters) to investigate better the latitude effect and to study if within this larger crater population the size effect exists.

Basilevsky, A. T.↗
DOE OSTI2025

Cognitive IoT and Edge Computing for Intrusion Detection with Federated TinyML

Internet of Things (IoT) and Edge Computing (EC) are rapidly becoming an integral part of the modern society. By 2030, there is estimated to be over 40 billion active and connected IoT devices [1]. This rapid progress also comes with a significant implication on cybersecurity. Back-end infrastructure and systems have a much broader attack than they did previously due to vulnerable IoT/EC devices being connected to wireless networks. This expanding attack surface is a growing concern because IoT/EC are increasingly being used in critical systems such as power grids, health care, and smart homes. To effectively address a problem of this scale, cognitive cyber methods—which can autonomously detect and react to cyber attacks as they develop—are needed. To address this, we bring Artificial Intelligence (AI) and Machine Learning (ML) to IoT/EC devices, using tinyML to monitor voluminous IoT data against cyber threats, and using Federated Learning (FL) to share local detection knowledge across the system while preserving privacy. We propose a novel three-layer architecture: (1) an IoT layer for tinyML-based inference, (2) an edge layer for ML model training, and (3) a cloud layer for FL operations. Using the publicly available 11-class N-BaIoT dataset [2], we demonstrate that this architecture mitigates resource constraints at the IoT layer while improving detection accuracy over standard two-layer designs. An outlier-resistant scaler, feature reduction, and quantization enable the tinyML model to maintain detection accuracy with a reduced model size. Additionally, federated learning that only utilizes the intersection (across heterogenous devices) of the reduced feature set achieves superior detection accuracy compared to locally trained models.

Li, Mingyan [ORNL] (ORCID:0009000569532640)↗
DOE OSTI2022

Library of Advanced Materials for Engineering ((LAMÉ) 5.6

Accurate and efficient constitutive modeling remains a cornerstone issue for solid mechanics analysis. Over the years, the LAMÉ advanced material model library has grown to address this challenge by implementing models capable of describing material systems spanning soft polymers to stiff ceramics including both isotropic and anisotropic responses. Inelastic behaviors including (visco)plasticity, damage, and fracture have all incorporated for use in various analyses. This multitude of options and flexibility, however, comes at the cost of many capabilities, features, and responses and the ensuing complexity in the resulting implementation. Therefore, to enhance confidence and enable the utilization of the LAMÉ library in application, this effort seeks to document and verify the various models in the LAMÉ library. Specifically, the broader strategy, organization, and interface of the library itself is first presented. The physical theory, numerical implementation, and user guide for a large set of models is then discussed. Importantly, a number of verification tests are performed with each model to not only have confidence in the model itself but also highlight some important response characteristics and features that may be of interest to end-users. Finally, in looking ahead to the future, approaches to add material models to this library and further expand the capabilities are presented.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The impact of capillary heterogeneity on CO 2 flow and trapping across scales

Capillary heterogeneity has been identified over the last decade as a key control on subsurface CO 2 flow behavior during geological CO 2 sequestration. These heterogeneities can be formed in all sedimentary rocks, ranging from slight variations in the sand grain sizes to extensive sequences of interbedded sands, shales, and limestones. Capillary heterogeneity has been largely, although not entirely, overlooked in subsurface flow modeling because it is assumed to only directly influence fluid redistribution over scales of centimeters to meters. However, even small-scale fluid movements can result in dramatic impacts on the mobility and trapping of the CO 2 over kilometers. Therefore, neglecting capillary heterogeneity at multiple scales could potentially lead to errors in modeling and predicting field-scale plume migration. In this review paper, we aim to provide a consistent overview to (1) establish that capillary heterogeneity can have a major impact on CO 2 plume migration, (2) establish the respective length scales at which capillary heterogeneity matters, and (3) provide guidance for numerical modeling. This review covers pertinent literature and extracts key observations from the core to the field scales. Experimental studies have shown that millimeter-decimeter scale capillary heterogeneity can cause the so-called capillary heterogeneity trapping in addition to pore-scale residual trapping. Even at such a small scale, capillary heterogeneity can already lead to complex upscaled constitutive relationships, such as flow-rate dependent and anisotropic relative permeability, which affects field-scale CO 2 migration even when field-scale heterogeneities are present. Under gravity-dominated flow regimes, centimeter-meter scale capillary heterogeneity can entrap a significant amount of CO 2 at field scale, not just after imbibition but also during drainage. In certain cases, the presence of capillary heterogeneity can even completely stop the vertical movement of the CO 2 plume, hence greatly reducing leakage risks. At meter-kilometer scale, the influence of capillary heterogeneity is more pronounced and can hinder or redirect CO 2 migration in both lateral and vertical directions. The impact of capillary heterogeneity across multiple spatial scales poses a great challenge in modeling CO 2 migration at field scale, because it is practically impossible to build a field-scale earth model with grid blocks at millimeter scale. We recommend a hierarchical modeling approach to address this challenge. At field scale, earth models are built to capture geological features and heterogeneities in high but still practical grid resolutions. For each facies or rock type of the field-scale model, high- resolution meter-scale “conceptual” models are built with millimeter-scale grid blocks to capture representative fine-scale bedding geometries and heterogeneities in various environments of deposition, bridging the gap from subcore scale to the size of a field-scale simulation grid block. Upscaling is then used to preserve the smaller-scale flow dynamics of various rock types in field-scale simulations. Here, future work is needed to (1) refine, improve, and validate the hierarchical modeling approach; (2) build libraries of fine-scale bedding models for facies in various environments of deposition; (3) quantify multiscale capillary heterogeneity effects under subsurface uncertainties; (4) gain learning from different storage formations; and (5) establish best practices that balance accuracy and computational speed.

Capillary heterogeneity↗
NASA NTRS1994

A stochastic precipitation disaggregation scheme for GCM applications

In the surface hydrologic parameterization of general circulation models (GCMs), it is commonly assumed that the precipitation processes are homogeneous over a GCM grid square and that the precipitation intensity is uniformly distributed. Based on evidence that the spatial distribution of precipitation within a GCM grid square is crucial for the land surface hydrology parameterization, a few researchers have explored the impacts of assuming that the precipitation is exponentially distributed. This paper explores the suitability of the aforementioned assumptions. First, a statistical analysis is conducted of historical precipitation data for three GCM grids in different regions of the United States. The analysis suggests that neither the uniform nor the exponential distribution assumption may be suitable at the GCM grid scale and, that instead, the spatial variability in precipitation is characterized by statistical patterns that are inhomogeneous. These patterns vary from grid to grid and are induced by the interaction between atmospheric conditions and various land surface characteristics, such as topographical features, surface properties, etc. Within the same grid square, however, the statistical patterns are generally constant from year to year. Based on this analysis, a computationally viable (i.e., usable with GCMs) stochastic precipitation disaggregation scheme that utilizes these stable statistical patterns is proposed. The method was used to generate spatially distributed hourly rainfall for a summer season in the southwestern region of the continental United States. Analysis of the results shows that the methodology preserves the seasonal characteristics of spatial variability in precipitation that is observed in the long-term historical data.

Gao, Xiaogang↗
DOE OSTI2026

A strong and ductile Super Kovar alloy via fully coherent nanoprecipitates

Emerging high-precision technologies demand materials with exceptional dimensional stability and mechanical robustness, as even microscopic thermomechanical deformation can cause functional failure. However, a fundamental trilemma exists: High strength, ductility, and low thermal expansion are mutually exclusive, as strengthening-induced lattice distortions compromise the spin-lattice coupling, which is essential for low thermal expansion. Here, we overcome this trilemma by designing “Super Kovar,” an Fe-Ni-Co-Al-Ta alloy, featuring fully coherent nanoprecipitates. It unifies a 1.0-gigapascal ultimate tensile strength and ∼39% elongation with a Kovar-grade thermal expansion of 3.81 × 10−6 K−1 (100 to 410 K). The key is a dense dispersion of L12 nanoprecipitates that form an almost strain-free coherent interface with the ferromagnetic matrix. Beyond providing precipitation strengthening, these coherent interfaces suppress intrinsic phonons of nanoprecipitates via elastic coupling while avoiding magnetic domain pinning to preserve the Invar effect of the matrix. This reduces the thermal expansion of the precipitates by 56% and achieves a fourfold enhancement in the strength-ductility product, establishing a paradigm for dimensionally stable, ultrastrong alloys.

Yu, Chengyi [University of Science and Technology ↗
DOE OSTI2022

Automated Control for Nuclear Thermal Propulsion Start-Up using MOOSE-based Applications

This report presents a Griffin/Bison/RELAP-7 numerical model of a prototypical NTP system that features fuel assemblies arranged in rings, and which was designed to simulate rapid startup transients. The physics modeled include full-core neutronics, assembly-wise heat conduction, and conjugate heat transfer, with the balance of plant mainly imposed through boundary conditions. In addition, various forms of automated reactivity control were deployed by using the MOOSE to autonomously drive the model and simulate the reactor transitioning from assumed initial conditions to nominal power in a fraction of a minute. To generate the cross-sections of the neutronics model, and in an effort to simultaneously account for the tremendous axial temperature gradients in the reactor and to limit the number of state points required for cross-section generation, the average component temperatures and hydrogen densities in the cooling channels were correlated to the average fuel and moderator temperatures, and fixed axial profiles were derived for nominal conditions and then used during the transient. With this approximation, a tractable cross-section library tabulated with fuel/moderator temperatures and CD angles was generated using Serpent. The full-core SPH correction procedure and the CD decusping technology in Griffin, respectively, ensure preservation of the multiplication factor and reaction rates at state points, along with a reasonably accurate reactivity worth between tabulated CD angles, despite using a coarse mesh. Feedback from other physics was calculated by modeling one representative fuel assembly per ring, along with the corresponding fuel and moderator cooling channels. To limit power overshoots during startup, another layer of multiphysics coupling was added to the model in order to automatically control the drums. Two different technologies presented herein showed outstanding performance in this regard: (1) a novel hybrid PID controller based on both power and reactivity signals, and (2) a PGC that relies on kinetics parameters and reactivity coefficients to predict future behavior and adjust the desired signal accordingly. A challenging benchmark was devised, featuring a power demand curve that exponentially increases by a factor of 500 within 30 seconds, then levels out after that. Both control approaches create a simulated power curve that closely follows the power demand curve and limits power overshoots to 1% or less. While the former approach requires more tuning of the internal parameters, the latter requires additional knowledge of the reactivity feedback coefficients and rates of change of the corresponding variables, including fuel and moderator temperature, which could be difficult to dynamically measure for a real NTP system. Fortunately, some inaccuracy in these quantities will not drastically degrade the PGC performance. Subsequently, a more realistic startup sequence was considered, in which the mass flow rate and outlet pressures are ramped up to model bootstrap and thrust build-up phases prior to reaching steady-state conditions, demonstrating the ability of the hybrid PID and PGCs to handle such transients, with both types of controllers exhibiting very similar behavior. Nevertheless, a significant chamber temperature overshoot was observed, caused by the demanded power signal and assumed mass flow rate. This issue could be mitigated by deploying a reactor controller that follows the chamber temperature signal and actuates both the control valves and drums (rather than using a power signal based solely on the drums to control reactivity). Enhancement of the hydrogen fluid properties available in MOOSE, as well as a better understanding of prototypical initial conditions, are also needed to further enhance this startup model. Finally, a study was performed to model decay heat post-shutdown, and to prepare for extending this model to predict shutdown behavior and post-shutdown pulsed cooling requirements.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

An Open-source Llm Enhanced-tool Specialized In Helping Moose Related Problems And Tasks

MOOSEenger is an open-source, terminal-first chat application for the MOOSE ecosystem that couples specialized parsing of MOOSE documentation and “.i” input files with retrieval-augmented generation to deliver grounded answers about multiphysics modeling and workflows. It includes dedicated readers for MOOSE-style HTML and a pyhit-based parser that uses the MOOSE syntax tree to preserve block structure and attach retrieval metadata. A data-ingestion pipeline performs semantic chunking into atomic facts and stores them hierarchically in a local Chroma vector database that maintains parent–child relationships across documents; the system can ingest directories, individual files, and single-page web content, and it provides CRUD operations (insert, update, delete) to manage the corpus. At query time, relevant chunks are embedded, retrieved, and fused into the model context, with interactive features such as token streaming, persistent chat history, and dynamic RAG (retrieval triggered by user input or intermediate model output). Deployment is flexible: MOOSEenger runs with local Ollama models or remote Hugging Face/OpenAI backends—typically coordinating generation, lightweight tagging/summarization, and embeddings across three models—and it also supports a server mode and integration with the VS Code Continue interface.

Li, Mengnan [Idaho National Laboratory (INL), Idah↗
NASA NTRS1991

Styles of crater gradation in Southern Ismenius Lacus, Mars

Preserved morphology around selected impact craters together with results from study of long term gradational evolution are used to assess processes responsible for crater modification in southern Ismenius Lacus. Results are compared with the gradational styles of selected terrestrial craters. Although most craters in the region display complex primary morphologies, some first order comparisons with the gradational styles around simple terrestrial craters may be valid. Nearly complete high resolution coverage provides a basis for studying morphologic features at scales comparable to those observed in LANDSAT TM images of terrestrial craters. It is concluded that the relative importance of gradational processes differs around the terrestrial and Martian craters considered here: Martian rimless morphologies are produced by mass wasting, eolian deposition/erosion, and limited fluvial incisement resulting in downwasting and significant backwasting of crater walls.

Grant, J. A.↗
NASA NTRS2014

Conservation of Mass and Preservation of Positivity with Ensemble-Type Kalman Filter Algorithms

This paper considers the incorporation of constraints to enforce physically based conservation laws in the ensemble Kalman filter. In particular, constraints are used to ensure that the ensemble members and the ensemble mean conserve mass and remain nonnegative through measurement updates. In certain situations filtering algorithms such as the ensemble Kalman filter (EnKF) and ensemble transform Kalman filter (ETKF) yield updated ensembles that conserve mass but are negative, even though the actual states must be nonnegative. In such situations if negative values are set to zero, or a log transform is introduced, the total mass will not be conserved. In this study, mass and positivity are both preserved by formulating the filter update as a set of quadratic programming problems that incorporate non-negativity constraints. Simple numerical experiments indicate that this approach can have a significant positive impact on the posterior ensemble distribution, giving results that are more physically plausible both for individual ensemble members and for the ensemble mean. In two examples, an update that includes a non-negativity constraint is able to properly describe the transport of a sharp feature (e.g., a triangle or cone). A number of implementation questions still need to be addressed, particularly the need to develop a computationally efficient quadratic programming update for large ensemble.

EnKF↗