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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Space Mathematics: A Resource for Secondary School Teachers

A collection of mathematical problems related to NASA space science projects is presented. In developing the examples and problems, attention was given to preserving the authenticity and significance of the original setting while keeping the level of mathematics within the secondary school curriculum. Computation and measurement, algebra, geometry, probability and statistics, exponential and logarithmic functions, trigonometry, matrix algebra, conic sections, and calculus are among the areas addressed.

Kastner, Bernice↗
NASA NTRS2024

Tracing Presolar Grain Populations Through Matrix Alteration Histories

Primitive meteorites preserve remnants of evolved stars as presolar grains, from asymptotic and red giant branch stars, novae and supernovae. These grains retain records of the formation mechanisms of the stellar environment from which they condensed, as well as physical and chemical processes in the interstellar medium (ISM), solar nebula and the parent bodies in which they are found. Consequently, their study can refine our understanding of the solar system and external stellar and planetary systems. However, presolar grains and their records can be altered, re-equilibrated with the surrounding matrix, and eventually lost through aqueous and thermal processing on the meteorite parent body. NanoSIMS is the most rapid and effective method for in situ identification of presolar grains via their highly anomalous isotopic ratios. Previous studies have measured variations in presolar grain populations between different matrix regions within the same meteorite thin section. However, most of these studies do not identify if there are any ties between these variations in presolar grain populations and the chemical and mineralogical differences in measured matrix regions. Therefore, the goal of this study is to determine if there is measurable variations in the degree of alteration of different matrix regions within the same thin section, and if mineralogical and chemical changes in matrix regions can be used as indicators for presolar grain preservation. Such a correlation could improve the efficiency of presolar grain identification during searches across large surface areas. To do this, we carried out coordinated scanning electron microscope (SEM) and NanoSIMS analyses, using a new SEM method which measures the ppm concentration of 100 nm to 5 μm sized Mg-, S-, Al-, C- and Ca-rich matrix grains.

presolar grains↗
DOE OSTI2022

Radiation-Generating Device Safety Self-Study [Slides]

Self-study slides are included for the following modules: RGD Safety Course Presentation, Radiation Detection, Biological Effects, RGDs, Radiation Protection Principles, Production of X-Rays, Protective Measures, and Responsibilities for X-Ray Safety.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
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↗
DOE OSTI2024

Achieving a near-ideal silicon crystal neutron interferometer using submicrometer fabrication techniques

Perfect-crystal neutron interferometry, which is analogous to Mach-Zehnder interferometry, uses Bragg diffraction to form interfering neutron paths. The measured phase shifts can be used to probe many types of interactions whether it be nuclear, electromagnetic, gravitational, or topological in nature. For a perfect-crystal interferometer to preserve coherence, the crystal must possess a high degree of dimensional tolerance as well as being relatively defect-free with minimal internal stresses. In the past, perfect-crystal neutron interferometers have been produced by a two-step process. First, a resin diamond wheel would be used to remove excess material and shape the interferometer. Afterword, the crystal would be etched to remove surface defects and elevate strains. This process has had limitations in terms of repeatability and in maximizing the final contrast, or fringe visibility, of the interferometer. We have tested various fabrication and post-fabrication techniques on a single perfect-crystal neutron interferometer and measured the interferometer's performance at each step. Here we report a robust, nonetching fabrication process with high final contrast. For the interferometer used in this work, we achieved contrasts of greater than 90% several times and ultimately finished with an interferometer that has 92% contrast and a uniform phase distribution. Published by the American Physical Society 2024

Huber, M. G. (ORCID:0000000237958445)↗
DOE OSTI2024

Uncertainty-Aware, Structure-Preserving Machine Learning Approach for Domain Shift Detection From Nonlinear Dynamic Responses of Structural Systems

Complex structural systems deployed for aerospace, civil, or mechanical applications must operate reliably under varying operational conditions. Structural health monitoring (SHM) systems help ensure the reliability of these systems by providing continuous monitoring of the state of the structure. SHM relies on synthesizing measured data with a predictive model to make informed decisions about structural states. However, these models—which may be thought of as a form of a digital twin—need to be updated continuously as structural changes (e.g., due to damage) arise. We propose an uncertainty-aware machine learning model that enforces distance preservation of the original input state space and then encodes a distance-aware mechanism via a Gaussian process (GP) kernel. The proposed approach leverages the spectral-normalized neural GP algorithm to combine the flexibility of neural networks with the advantages of GP, subjected to structure-preserving constraints, to produce an uncertainty-aware model. This model is used to detect domain shift due to structural changes that cannot be observed directly because they may be spatially isolated (e.g., inside a joint or localized damage). This work leverages detection theory to detect domain shift systematically given statistical features of the prediction variance produced by the model. The proposed approach is demonstrated on a nonlinear structure being subjected to damage conditions. In conclusion, it is shown that the proposed approach is able to rely on distances of the transformed input state space to predict increased variance in shifted domains while being robust to normative changes.

Algorithms↗
DOE OSTI2020

Nematic transitions in iron pnictide superconductors imaged with a quantum gas

The Scanning Quantum Cryogenic Atom Microscope (SQCRAMscope) uses an atomic Bose–Einstein condensate to measure magnetic fields emanating from solid-state samples. The quantum sensor does so with unprecedented d.c. sensitivity at micrometre resolution, from room to cryogenic temperatures. An additional advantage of the SQCRAMscope is the preservation of optical access to the sample so that magnetometry imaging of, for example, electron transport may be performed in concert with other imaging techniques. Here, we apply this multimodal imaging capability to the study of nematicity in iron pnictide high-temperature superconductors, where the relationship between electronic and structural symmetry breaking resulting in a nematic phase is under debate. We combine the SQCRAMscope with an in situ microscope that measures optical birefringence near the surface. This enables simultaneous and spatially resolved detection of both bulk and near-surface manifestations of nematicity via transport and structural deformation channels, respectively. By performing local measurements of emergent resistivity anisotropy in iron pnictides, we observe sharp, nearly concurrent transport and structural transitions. More broadly, these measurements demonstrate the SQCRAMscope’s ability to reveal important insights into the physics of complex quantum materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Enabling ambient stability and quantum integration of organometallic magnonic ferrimagnets via atomic layer encapsulation

Magnons, the quanta of spin waves in magnetic materials, are promising for hybrid quantum systems by bridging electromagnetic and spin degrees of freedom. The organometallic ferrimagnet vanadium tetracyanoethylene (V[TCNE] x , x ≈ 2) is especially well-suited for quantum magnonics due to its low Gilbert damping and substrate versatility. However, its rapid chemical degradation in ambient conditions hinders practical applications. Incumbent encapsulation methods provide some protection, but are bulky, obscure intrinsic properties of V[TCNE] x , introduce thermal stress at cryogenic temperatures, and complicate microwave device integration. Here, we demonstrate that ultrathin alumina films deposited via low-temperature atomic layer deposition effectively protect V[TCNE] x by preserving its magnetic and magnonic properties following ambient exposure. The sub-100 nm transparent films also enable advanced spectroscopy, magnetometry, and cavity magnonic measurements that reveal the intrinsic properties of V[TCNE] x . This encapsulation strategy advances molecule-based quantum information science by providing a robust route toward scalable, monolithic integration in hybrid quantum technologies.

magnetic materials↗
NASA NTRS1986

Capacitive Gauge Measures Film Thickness

Rugged capacitive transducer measures thickness of film of liquid flowing over wind-tunnel model or other object. Transducer mounted flush with surface of model to preserve model outline, thus minimally disturbing wind-tunnel and film flows. Additional uses include thickness control of paint or nonmetallic solid films.

Seegmiller, H. L.↗
DOE OSTI2023

Organizational System Resilience to Disinformation: A Viable Systems Model Exploration

This paper explores the utility of organizational system modeling frameworks to provide valuable insight into information flows within organizations and subsequently the opportunities for increasing resilience against disinformation campaigns targeting the system's ability to utilize information within its decision making. Disinformation is a growing challenge for many organizations and in recent years has created delay in decision making. Here the paper has utilized the viable systems model (VSM) to characterize organizational systems and used this approach to outline potential subsystem requirements to promote resilience of the system. The results of this paper can support the development of simulations and models considering the human elements within the system as well as support the development of quantitative measures of resilience.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2020

Brachiopod δ 34 S CAS microanalyses indicate a dynamic, climate-influenced Permo-Carboniferous sulfur cycle

Early isotopic studies of sulfate in carbonate minerals (carbonate associated sulfate; CAS) suggested that carbonates can provide a reliable, well-dated archive of the marine sulfur cycle through time. However, subsequent research has shown that diagenetic alteration can impose highly heterogeneous CAS sulfur isotopic compositions (δ 34 S CAS ) among different carbonate phases within sediments. Such alteration necessitates targeted sampling of well-preserved, primary carbonate phases. Here, we present a new record of Carboniferous and Early Permian brachiopod δ 34 S CAS generated from over 130 measurements of microsampled brachiopod shells. Our record refines existing brachiopod δ 34 S CAS records and confirms a large, ~6.5‰ δ 34 S CAS decrease in the Early Carboniferous. Importantly, the record also features a novel 3–5‰ increase in δ 34 S CAS near the Serpukhovian-Bashkirian boundary (323.4 Ma) that coincides with carbonate δ 13 C and δ 18 O increases. Variability in δ 34 S CAS is minor both within (≤0.3‰) and among (≤2‰) individual co-depositional brachiopod specimens. A taxon-specific δ 34 S CAS offset is present one species (Composita subtilita) that also exhibits a δ 13 C offset, supporting the existence of biological “vital effects” on δ 34 S CAS . Geologic evidence and mathematical modeling of the Permo-Carboniferous carbon and sulfur cycles suggest that changes in the burial ratio of organic carbon to pyrite sulfur (R C:S ) are insufficient to explain the observed mid-Carboniferous δ 34 S CAS record. We find that changes in the 34 S depletion of pyrite relative to seawater sulfate ( 34 ε) or in the δ 34 S of the input to the ocean (δ 34 S in ) are also needed. Large additions of O 2 from organic carbon burial during the Permo-Carboniferous cannot be entirely compensated for with sulfur cycle changes; lower than modern late Visean pO 2 and/or additional O 2 sinks are needed to keep pO 2 at plausible levels. Based on the geologic context surrounding our record's mid-Carboniferous δ 34 S CAS increase, we advocate for simultaneous changes in pyrite burial, 34 ε, and δ 34 S in , driven by sea level or tectonically induced changes in environments of sulfur burial, as a viable mechanism to produce rapid seawater δ 34 S changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Selecting representative geological realizations to model subsurface CO 2 storage under uncertainty

Carbon capture and storage (CCS) is one of the quickest and most effective solutions for reducing carbon emissions. The majority of subsurface storage occurs in saline aquifers, for which geological information is lacking which in turn results in geological uncertainty. To evaluate uncertainty in CO 2 injection projections, the use of multiple geological realizations (GRs) has been practiced very commonly. In this approach, hundreds or thousands of high-resolution GRs is used that quickly becomes computationally expensive. This issue can be addressed with representative geological realizations (RGRs) that preserve the uncertainty domain of the ensemble GRs. Here, in this study, we propose the use of unsupervised machine learning (UML) frameworks, including dissimilarity measurement, dimensionality reduction, clustering and sampling algorithms ta select a predetermined number of RGRs. We compare the simulation outputs of the RGR sets and the ensemble using the Kolmogorov–Smirnov (KS) test to select the best UML. The UML frameworks and their associated selection processes are evaluated using a saline aquifer with a single CO 2 injection well and 200 GRs with varying uncertain petrophysical characteristics. The best UML framework is selected to use only 5% of the GRs while maintaining the uncertainty domain of the ensemble GRs. In addition, the best UML framework is tested using a saline aquifer with three CO 2 injection wells and varied GRs. The results show that our proposed UML framework can be used to choose RGRs, capturing the whole uncertainty domain. Our approach leads to a significant reduction in the computational cost associated with scenario testing, decision-making, and development planning for CO 2 storage sites under geological uncertainty.

58 GEOSCIENCES↗
DOE OSTI2026

Magneto-optical Kerr effect in an A-type antiferromagnet

Magneto-optic Kerr effect (MOKE) is a powerful probe of broken time-reversal symmetry (T$${{\mathcal{T}}}$$), typically used to study ferromagnets. While MOKE has been observed in some antiferromagnets (AFMs) with vanishing magnetization, it is often associated with structures whose symmetry is lower than basic collinear, bipartite order. In contrast, theory predicts a mechanism for MOKE intrinsic to all AFMs of A-type, i.e. layered AFMs in which ferromagnetic layers are antiferromagnetically aligned. Here we report the experimental confirmation of this mechanism in a bulk AFM. We achieve this by measuring the imaginary component of MOKE as a function of photon energy in MnBi2Te4, an A-type AFM where T$${{\mathcal{T}}}$$ is preserved in combination with a translation, and comparing the experimental results with model calculations. Our model suggests that observable MOKE should be expected in all collinear A-type AFMs with out-of-plane spin order, thus enabling optical detection of AFM domains and expanding the scope of MOKE to few-layer AFMs.

Sunko, Veronika↗
DOE OSTI2022

Structural heterogeneity in non-crystalline Te x Se1−x thin films

Rapid crystallization behavior of amorphous TexSe1−x thin films limits the use of these alloys as coatings and in optoelectronic devices. Understanding the short- and medium-range ordering of the amorphous structure and the fundamental physics governing the crystallization of the films is crucial. Although the lack of long range crystalline order restricts the characterization of the amorphous films, electron microscopy offers a way to extract information about the nanoscale ordering. In this paper, the local ordering of amorphous TexSe1−x thin films with x=0.22, 0.61, 0.70, 0.90, and 1 grown by thermal evaporation is investigated using radial distribution function (RDF) and fluctuation electron microscopy (FEM) analysis. RDF results show that the nearest-neighbor distances of selenium (Se) and tellurium (Te) in their crystalline structure are preserved, and their bond lengths increase with the addition of Te. Density functional theory (DFT) calculations predict structures with interatomic distances similar to those measured experimentally. Additionally, fluctuations in atomic coordination are analyzed. Medium range order (MRO) analysis obtained from FEM and DFT calculations suggests that there are at least two populations within the chain network structure, which are close to the Se–Se and Te–Te intrachain distances. For the binary alloy with x > 0.61, TexSe1−x, Te–Te like populations increase and Te fragments might form, suggesting that the glass forming ability decreases rapidly.

Sari, Bengisu (ORCID:0000000244217098)↗
DOE OSTI2020

SnowPac : a multiscale cubic B-spline wavelet compressor for astronomical images

ABSTRACT As more advanced and complex survey telescopes are developed, the size and scale of data being captured grows at increasing rates. Across various domains, data compression through wavelets has enabled the reduction of data size and increase in computation efficiency. In this paper, we provide qualitative and quantitative tests of a new wavelet-based image compression method compared against the current standard for astronomical images. The analysis is improved by making use of state-of-the-art object detection systems to accurately measure the impact of the compression. We find that a combination of lossy wavelet-based methods, efficient quantization, and lossless dictionary compressors can preserve up to 98 per cent of astronomical objects at a 10:1 compression ratio. This significant reduction in file size also preserves astronomical object properties better than existing methods. These methods help further reduce future workloads for image-heavy processing pipelines.

Pulido, Jesus↗
DOE OSTI2026

Technical Report for Bayesian Optimization and Reinforcement Learning for Beam Polarization Increase in the BNL Hadron Injectors

This project developed and evaluated physics-informed Bayesian learning and machine learning (ML)-based optimization methods for improving beam polarization preservation in the BNL hadron injector chain. The work focused on uncertainty-aware digital twin modeling, Bayesian calibration of accelerator simulations using beam measurements, and data-efficient optimization strategies including Bayesian optimization and reinforcement learning. These methods were applied to injector tuning and RF control problems in realistic accelerator settings to support improved operational robustness and readiness for RHIC operations and future Electron–Ion Collider facilities. No subject inventions were disclosed under this award.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Solar-Tracker Diffuse-Response Algorithm for Balancing Energy Gain and Mechanical Wear in Photovoltaic Systems

Single-axis solar tracking maximizes photovoltaic energy production under clear-sky conditions; however, its effectiveness decreases under cloudy and overcast skies, where diffuse irradiance dominates and the optimal module orientation changes. Conventional tracking algorithms either neglect sky conditions or rely on simplified diffuse-response strategies that may trigger frequent tracker repositioning under variable cloud cover, leading to increased mechanical wear with marginal energy gains. This work proposes an enhanced diffuse-response tracking algorithm that explicitly accounts for both the intensity and temporal persistence of cloudiness. By requiring overcast conditions to persist for a minimum duration before reorienting the tracker to a diffuse-stow position, the proposed approach reduces unnecessary movements while preserving the benefits of diffuse-response operation. The algorithm is evaluated through numerical simulations based on historical meteorological data and validated using field measurements on monofacial and bifacial photovoltaic strings. The results show that the proposed strategy reduces excess tracker movement from 114% to 0.16% while maintaining nearly the same energy yield. Compared to a conventional diffuse-response algorithm, the associated energy reduction is minimal (≈0.17%) relative to the ≈0.37% yield gain observed at the studied location. These findings demonstrate that incorporating cloudiness duration enables a practical compromise between energy performance and tracker durability, particularly for monofacial photovoltaic systems.

14 SOLAR ENERGY↗
DOE OSTI2024

Vegetation Warming Experiment: Thaw Depth and dGPS locations, Barrow, Alaska, 2018

Thaw depth measurements within and around warming chambers, and at ambient plots. Measurements were taken at the start and end of chamber deployment, and two intermediate times during the 2018 growth season. dGPS measurements of chamber and ambient plot locations. This dataset contains one kmz, two xlsx, and three csv files where the xlsx files have been preserved as csvs for preservation. These data were collected as part of a series of single-season warming experiments on tundra vegetation on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. A different plant species was targeted each year, over four experimental years from 2017–2021. Each year, five warming chambers and paired ambient control plots were deployed from around the time of snowmelt in mid-June through to mid-September. Average seasonal warming of 3-4°C was achieved using Zero Power Warming (ZPW) chambers (Lewin et al, 2017).The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗