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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 163 records · Page 9

Visualizing Flutter Mechanism as Traveling Wave Through Animation of Simulation Results for the Semi-Span Super-Sonic Transport Wind-Tunnel Model

It has long been recognized that frequency and phasing of structural modes in the presence of airflow play a fundamental role in the occurrence of flutter. Animation of simulation results for the long, slender Semi-Span Super-Sonic Transport (S4T) wind-tunnel model demonstrates that, for the case of mass-ballasted nacelles, the flutter mode can be described as a traveling wave propagating downstream. Such a characterization provides certain insights, such as (1) describing the means by which energy is transferred from the airflow to the structure, (2) identifying airspeed as an upper limit for speed of wave propagation, (3) providing an interpretation for a companion mode that coalesces in frequency with the flutter mode but becomes very well damped, (4) providing an explanation for bursts of response to uniform turbulence, and (5) providing an explanation for loss of low frequency (lead) phase margin with increases in dynamic pressure (at constant Mach number) for feedback systems that use sensors located upstream from active control surfaces. Results from simulation animation, simplified modeling, and wind-tunnel testing are presented for comparison. The simulation animation was generated using double time-integration in Simulink of vertical accelerometer signals distributed over wing and fuselage, along with time histories for actuated control surfaces. Crossing points for a zero-elevation reference plane were tracked along a network of lines connecting the accelerometer locations. Accelerometer signals were used in preference to modal displacement state variables in anticipation that the technique could be used to animate motion of the actual wind-tunnel model using data acquired during testing. Double integration of wind-tunnel accelerometer signals introduced severe drift even with removal of both position and rate biases such that the technique does not currently work. Using wind-tunnel data to drive a Kalman filter based upon fitting coefficients to analytical mode shapes might provide a better means to animate the wind tunnel data.

Christhilf, David M.

Decayheatml

This code is designed to predict and analyze the decay heat generated in molten salt reactors (MSRs) using a hybrid approach that combines machine learning and segmented polynomial fitting. The accurate prediction of decay heat is essential for reactor safety and the optimization of spent fuel storage. The code operates through several key components: 1) Data Architecture: It incorporates a modular data architecture that handles various MSR-specific operational parameters such as power density, humidity content, and air ingress. These parameters are sampled using Sobol sequences to ensure comprehensive coverage of operational uncertainties. 2) Machine Learning Framework: The code employs a diverse set of machine learning models, including polynomial regression, decision trees, random forests, gradient boosting, support vector regression, k-nearest neighbors, multi-layer perceptrons, and symbolic regression. These models are trained to predict decay heat over a wide temporal range, from immediate shutdown up to 10,000 years. 3) Region-Optimized Training: The temporal domain is divided into multiple regions, each modeled separately to capture distinct decay heat characteristics across different time scales. This approach significantly improves the accuracy and interpretability of predictions. 4) Segmented Polynomial Interpretation (SPI): The SPI method translates machine learning predictions into piecewise polynomial equations. These equations are physically interpretable and can be directly integrated into existing engineering workflows and safety analyses. 5) Front-End Interfaces: The code includes both a Jupyter notebook interface for research development and a Streamlit web application for operational deployment. These interfaces allow users to interactively explore decay heat predictions, adjust operational parameters, and visualize results in real-time. 6) Applications: The framework supports various applications, including safety system validation and spent fuel container optimization. It enables real-time evaluation of worst-case decay heat scenarios, informing the design of passive safety systems and optimizing container designs for long-term storage. Overall, this code provides a robust, accurate, and user-friendly tool for predicting decay heat in MSRs, enhancing reactor safety, and optimizing spent fuel management.

Retamales, Mauricio Eduardo Tano [Idaho National L

Kansas environmental and resource study: A Great Plains model

The author has identified the following significant results. Improvement in the land use classification accuracy of ERTS-1 MSS multi-images over Kansas can be made using two distances between neighboring grey tone N-tuples instead of one distance. Much more information is contained texturally than spectrally on the Kansas image. Ground truth measurements indicate that reflectance ratios of the 545 and 655 nm wavebands provide an index of plant development and possibly physiological stress. Preliminary analysis of MSS 4 and 5 channels substantiate the ground truth interpretation. Results of the land use mapping experiment indicate that ERTS-1 imagery has major potential in regionalization. The ways in which land is utilized within these regions may then be studied more effectively than if no adequate regionalization is available. A model for estimating wheat yield per acre has been applied to acreage estimates derived from ERTS-1 imagery to project the 1973 wheat yields for a ten county area in southwest Kansas. The results are within 3% of the preharvest estimates for the same area prepared by the USDA. Visual identification of winter wheat is readily achieved by using a temporal sequence of images. Identification can be improve by stratifying the project area into subregions having more or less homogeneous agricultural practices and crop mixes.

Haralick, R. M.

Scattering of infrared radiation by dust in NGC 7023 and NGC 2023

The contribution of scattered light to the total nebular emission is determined on the basis of linear polarization measurements at 1.25, 1.65, and 2.2 microns of the visual reflection nebulae NGC 7023 and NGC 2023. The percentage polarization of NGC 7023 slowly increases from 0.3 to 1 micron, with peak polarizations of up to 26 percent at 1.25 micron, then rapidly decreases, with values of 4-7 percent at 2.2 microns. This is interpreted as implying that scattered starlight contributes most to the SW emission, while unpolarized emission from small grains or large molecules dominates at longer wavelengths. IR polarization and surface brightness measurements are combined to derive the intensity of scattered light, which is then compared with scattering models. While the near-IR emission of both NGC 2023 and NGC 7023 is dominated by small-grain or large-molecule emission, IR scattered light plays a larger role in NGC 2023 than in NGC 7023.

Sellgren, K.

Interpretation of HCMM images: A regional study

Potential users of HCMM data, especially those with only a cursory background in thermal remote sensing are familiarized with the kinds of information contained in the images that can be extracted with some reliability solely from inspection of such standard products as those generated at NASA/GSFC and now achieved in the National Space Science Data Center. Visual analysis of photoimagery is prone to various misimpressions and outright errors brought on by unawareness of the influence of physical factors as well as by sometimes misleading tonal patterns introduced during photoprocessing. The quantitative approach, which relies on computer processing of digital HCMM data, field measurements, and integration of rigorous mathematical models, can usually be used to identify, compensate for, or correct the contributions from at least some of the natural factors and those associated with photoprocessing. Color composite, day-IR, night-IR and visible images of California and Nevada are examined.

Source record

Graphical Language for Data Processing

A graphical language for processing data allows processing elements to be connected with virtual wires that represent data flows between processing modules. The processing of complex data, such as lidar data, requires many different algorithms to be applied. The purpose of this innovation is to automate the processing of complex data, such as LIDAR, without the need for complex scripting and programming languages. The system consists of a set of user-interface components that allow the user to drag and drop various algorithmic and processing components onto a process graph. By working graphically, the user can completely visualize the process flow and create complex diagrams. This innovation supports the nesting of graphs, such that a graph can be included in another graph as a single step for processing. In addition to the user interface components, the system includes a set of .NET classes that represent the graph internally. These classes provide the internal system representation of the graphical user interface. The system includes a graph execution component that reads the internal representation of the graph (as described above) and executes that graph. The execution of the graph follows the interpreted model of execution in that each node is traversed and executed from the original internal representation. In addition, there are components that allow external code elements, such as algorithms, to be easily integrated into the system, thus making the system infinitely expandable.

Alphonso, Keith

Modeling the Jovian aurora

The Jovian aurora is the most powerful aurora in the solar system, over 100 times more powerful than the Earth's aurora. These magnificent visual displays can provide important information about the planetary magnetosphere which is responsible for the acceleration of energetic particles that produce aurora at any planet. Similarities and differences in planetary auroral emissions are thus a viable means of classifying and studying both comparative atmospheric and magnetospheric processes. For instance, at Earth the solar wind is the primary source of auroral power while at Jupiter it is conjectured that the rotation of the planet is the major source of magnetospheric and auroral power. The purpose of this IR project was to develop a model: (1) for use in interpreting the existing set of multispectral observations of Jupiter's aurora; and (2) to design new experiments based on the findings to improve understanding of the underlying auroral processes.

Waite, J. Hunter, Jr.

Models for quasi-periodic electric fields and associated electron precipitation in the auroral zone

Quasi-periodic electric fields observed in the nighttime auroral oval and in the polar cleft had periods of between 0.5 and 3 s and amplitudes from 2 to 30 mV/m and exhibited left-hand and right-hand elliptical polarization. The events in the auroral oval were associated with substorms and visual auroral activity, and the spectral and polarization properties of the observed fields suggest that they represented the electric components of Pc 1 or Pi 1 micropulsations. One possibility is that the micropulsations result from Birkeland current chopping by an unstable double layer located at an altitude of approximately one earth radius. In this interpretation, the double layer is assumed to accelerate the observed electrons, the electron flux variations being due either to the inherent variations of the double layer or to its interaction with the micropulsations.

Petelski, E. F.

Measurements of field-aligned currents in a multiple auroral arc system

A rocket-borne experiment to study the currents associated with a system of multiple auroral arcs was conducted at Poker Flat, Alaska, at 1122 UT on Feb. 2, 1972. The magnetic field in the vicinity of the auroral system was measured with a cesium vector magnetometer. Possible configurations were inferred by constructing model current systems that reproduced the magnetic field variations measured along the flight path. The data are interpreted in terms of a model current system consisting of two eastward electrojets and one westward electrojet and three pairs of oppositely directed Birkeland sheet currents, all lying in a plane approximately parallel to the auroral arcs. Sheet thicknesses ranged from 20 to 60 km and current densities from 10 to 45 microampere/sq m; the electrojet currents ranged from 1000 to 2000 A. A possible alternate model consisted of four pairs of sheets whose thicknesses range from 10 to 40 km with current densities from 10 to 90 microampere/sq m. There was quite good agreement between the locations of the visual arcs and the upward current sheets. The overall current configuration is discussed in view of the theoretical models constructed by Atkinson and Sato and Holzer and of other observations.

Sesiano, J.

Visual scanning behavior and pilot workload

Sophisticated man machine interaction often requires the human operator to perform a stereotyped scan of various instruments in order to monitor and/or control a system. For situations in which this type of stereotyped behavior exists, such as certain phases of instrument flight, scan pattern was shown to be altered by the imposition of simultaneous verbal tasks. A study designed to examine the relationship between pilot visual scan of instruments and mental workload is described. It was found that a verbal loading task of varying difficulty causes pilots to stare at the primary instrument as the difficulty increases and to shed looks at instruments of less importance. The verbal loading task also affected the rank ordering of scanning sequences. By examining the behavior of pilots with widely varying skill levels, it was suggested that these effects occur most strongly at lower skill levels and are less apparent at high skill levels. A graphical interpretation of the hypothetical relationship between skill, workload, and performance is introduced and modelling results are presented to support this interpretation.

Tole, J. R.

Partial resolution of sources of n-alkanes in the saline portion of the Parachute Creek Member, Green River Formation (Piceance Creek Basin, Colorado)

Systematic variations in the 13C contents of individual extractable n-alkanes (C16-C29) can be modelled quantitatively and interpreted as indicating contributions from at least five distinct sources. These appear to be cyanobacterial (C16-C18, delta 13C = -37% vs PDB), phytoplanktonic (C16-C23, delta = -32%), chemoautotrophic bacterial (C20-C29, delta = -38%), phytoplanktonic or heterotrophic bacterial (C20-C29, delta = -30%), and vascular plants (C23-C29, delta = -29%). Hydrous pyrolysis of related kerogens yields large quantities of additional n-alkanes with different and much more uniform delta values. The latter materials are apparently derived from the thermolysis of aliphatic biopolymers whose presence in the Green River Oil Shale has been recognized visually.

Non-NASA Center

Physical interpretation and application of principles of ultrasonic nondestructive evaluation of high-performance materials

An ultrasonic measurement system employed in the experimental interrogation of the anisotropic properties (through the measurement of the elastic stiffness constants) of the uniaxial graphite-epoxy composites is presented. The continuing effort for the development of improved visualization techniques for physical parameters is discussed. The background is set for the understanding and visualization of the relationship between the phase and energy/group velocity for propagation in high-performance anisotropic materials by investigating the general requirements imposed by the classical wave equation. The consequences are considered when the physical parameters of the anisotropic material are inserted into the classical wave equation by a linear elastic model. The relationship is described between the phase velocity and the energy/group velocity three dimensional surfaces through graphical techniques.

Miller, James G.

An uncertainty visualization framework for large-scale cardiovascular flow simulations: A case study on aortic stenosis

We present a generalizable uncertainty quantification (UQ) and visualization framework for lattice Boltzmann method simulations of high Reynolds number vascular flows, demonstrated on a patient-specific stenosed aorta. The framework combines EasyVVUQ for parameter sampling with large-eddy simulation turbulence modeling in HemeLB, and executes ensembles on the Frontier exascale supercomputer. Spatially resolved metrics, including entropy and isosurface-crossing probability, are used to map uncertainty in pressure and wall shear stress fields directly onto vascular geometries. Two sources of model variability are examined: inlet peak velocity and the Smagorinsky constant. Inlet velocity variation produces high uncertainty downstream of the stenosis where turbulence develops, while upstream regions remain stable. Smagorinsky constant variation has little effect on the large-scale pressure field but increases WSS uncertainty in localized high-shear regions. In both cases, the stenotic throat manifests low entropy, indicative of robust identification of elevated WSS. By linking quantitative UQ measures to three-dimensional anatomy, the framework improves interpretability over conventional 1D UQ plots and supports clinically relevant decision-making, with broad applicability to vascular flow problems requiring both accuracy and spatial insight.

Hemodynamics

Reliable and Efficient Machine Learning (Final Technical Report)

Modern scientific experiments generate massive amounts of data at a pace much faster than humans can manually analyze. While machine learning has revolutionized commercial data analysis (such as recommending movies or recognizing faces), applying these tools to complex scientific discovery is challenging because scientific answers must be precise, interpretable, and adhere to physical laws. The research under this project aims to develop new mathematical tools and computer algorithms specifically designed for scientific applications. Major progress has been made in automatically cleaning and deconstructing messy experimental data, analyzing the visual information of physical phenomena, determining the underlying physical variables, and providing rig orous mathematical analysis of interesting algorithms and concepts widely used in machine learning. This project addressed the critical gap between our ability to generate massive scientific data and our ability to extract interpretable information from it. We established mathematical foundations for Scientific Machine Learning (SciML) aimed at effective data analytics and automated discovery. Our work focused on three core objectives: (1) developing reliable feature extraction methods for dynamic high-dimensional data, (2) establishing mathematical foundations for discovering dynamics via neural networks, and (3) creating rigorous optimization techniques for these models. Key outcomes come from two fronts. On the practical side, they include the development of algorithms that significantly enhance the extraction of signals from field data, as well as the capability to handle situations that exhibit smooth variations or physical stretching due to temperature changes. They also include the creation of an automated framework for discovering fundamental state variables from raw experimental data, demonstrating the ability to identify intrinsic physical dimensions without prior knowledge of the governing laws. On the theoretical front, the research results in theoretical advances in Optimal Transport, a widely used notion in SciML, specifically regarding functions with fixed-size nodal sets, provide sharp bounds relevant to uncertainty quantification. Meanwhile, the outcomes also include the establishment of convergence theories for nonlocal gradient descent methods, enabling robust optimization with noisy data in high-dimensional settings commonly encountered in scientific modeling. The project also helps creating opportunities to train the next generation of researchers, equipping them with the necessary technical skills for today’s workplace and preparing them for future advances.

97 MATHEMATICS AND COMPUTING

A Finite Element Method for Compressible and Turbulent Multiphase Flow Instabilities with Heat Transfer

We present a new finite element framework for modeling compressible, turbulent multiphase flows with heat transfer. For two-fluid systems with a free surface, the Volume of Fluid (VOF) method is implemented without the need for interface reconstruction, while turbulence is resolved using a dynamic Vreman large eddy simulation (LES) model. Unlike most two-phase VOF studies, which neglect heat transfer, the present approach incorporates energy transport equations within the VOF formulation to account for heat exchange, an effect particularly important in turbulent flows. Conjugate heat transfer is often challenging in finite volume methods, which require explicit specification of heat fluxes at the solid–fluid interface, limiting accuracy and predictive capability. By contrast, the finite element formulation does not require heat flux inputs, allowing more accurate and robust simulation of heat transfer between solids and fluids. The method is demonstrated through three representative cases. First, a two-fluid instability with a single-mode perturbation is simulated and validated against analytical growth rates. Second, conjugate heat transfer is examined in a high-temperature flow over a cold metal cylinder, with validation performed both quantitatively—via pressure coefficient comparisons with experimental data—and qualitatively using vector field topology. Finally, compressible spray injection and breakup are modeled, demonstrating the ability of the framework to capture interfacial dynamics and atomization under turbulent, high-speed conditions. In the compressible spray injection and breakup case, the results indicate that the finite element formulation achieved higher predictive accuracy and robustness than the finite-volume method. With the same mesh resolution, the FEM reduced the root mean square error (RMSE) and mean absolute percentage error (MAPE) from 6.96 mm and 26.0% (for the FVM) to 4.85 mm and 12.7%, respectively, demonstrating improved accuracy and robustness in capturing interfacial dynamics and heat transfer. The study also introduced vector field topology to visualize and interpret coherent flow structures and instabilities, offering insights beyond conventional scalar-field analyses.

97 MATHEMATICS AND COMPUTING

Constraining Stellar Photospheres as an Essential Step for Transmission Spectroscopy of Small Exoplanets

Transiting exoplanets offer a unique opportunity to study the atmospheres of terrestrial worlds in other systems in the coming decade. By absorbing and scattering starlight, exoplanet atmospheres produce spectroscopic transit depth variations that allow us to probe their physical structures and chemical compositions. These same variations, however, can be introduced by the photospheric heterogeneity of the host star (i.e., the transit light source effect). Recent modeling efforts and increasingly precise observations are revealing that our understanding of transmission1spectra of the smallest transiting exoplanets will likely be limited by our knowledge of host star photospheres. Here we outline promising scientific opportunities for the next decade that can provide useful constraints on stellar photospheres and inform interpretations of transmission spectra of the smallest(R < 4R) exoplanets. We identify and discuss four primary opportunities: (1) refining stellar magnetic active region properties through exoplanet crossing events; (2) spectral decomposition of active exoplanet host stars; (3) joint retrievals of stellar photospheric and planetary atmospheric properties with studies of transmission spectra; and (4) continued visual transmission spectroscopy studies to complement longer-wavelength studies from JWST. In this context, we make four recommendations to the Astro2020 Decadal Survey Committee:(1) identify the transit light source (TLS) effect as a challenge to precise exoplanet transmission spectroscopy and an opportunity ripe for scientific advancement in the coming decade; (2) include characterization of host star photospheric heterogeneity as part of a comprehensive research strategy for studying transiting exoplanets; (3) support the construction of ground-based extremely large telescopes (ELTs); (4) support multi-disciplinary research teams that bring together the heliophysics, stellar physics, and exoplanet communities to further exploit transiting exoplanets as spatial probes of stellar photospheres; and (5) support visual transmission spectroscopy efforts as complements to longer-wavelength observational campaigns with JWST.

Rackham, Benjamin V.

Spatial and Temporal Signatures of Flux Transfer Events in Global Simulations of Magnetopause Dynamics

Flux transfer events (FTEs) were originally identified by transient bipolar variations of the magnetic field component normal to the nominal magnetopause centered on enhancements in the total magnetic field strength. Recent Cluster and THEMIS multi-point measurements provided a wide range of signatures that are interpreted as evidence for FTE passage (e.g., crater FTE's, traveling magnetic erosion regions). We use the global magnetohydrodynamic (MHD) code BATS-R-US developed at the University of Michigan to model the global three-dimensional structure and temporal evolution of FTEs during multi-spacecraft magnetopause crossing events. Comparison of observed and simulated signatures and sensitivity analysis of the results to the probe location will be presented. We will demonstrate a variety of observable signatures in magnetic field profile that depend on space probe location with respect to the FTE passage. The global structure of FTEs will be illustrated using advanced visualization tools developed at the Community Coordinated Modeling Center

Kuznetsova, Maria M.

Constraining Stellar Photospheres as an Essential Step for Transmission Spectroscopy of Small Exoplanets

Transiting exoplanets offer a unique opportunity to study the atmospheres of terrestrial worlds in other systems in the coming decade. By absorbing and scattering starlight, exoplanet atmospheres produce spectroscopic transit depth variations that allow us to probe their physical structures and chemical compositions. These same variations, however, can be introduced by the photospheric heterogeneity of the host star (i.e., the transit light source effect). Recent modeling efforts and increasingly precise observations are revealing that our understanding of transmission spectra of the smallest transiting exoplanets will likely be limited by our knowledge of host star photospheres. Here we outline promising scientific opportunities for the next decade that can provide useful constraints on stellar photospheres and inform interpretations of transmission spectra of the smallest (R < 4R ) exoplanets. We identify and discuss four primary opportunities: (1) refining stellar magnetic active region properties through exoplanet crossing events; (2) spectral decomposition of active exoplanet host stars; (3) joint retrievals of stellar photospheric and planetary atmospheric properties with studies of transmission spectra; and (4) continued visual transmission spectroscopy studies to complement longer-wavelength studies from JWST. In this context, we make four recommendations to the Astro2020 Decadal Survey Committee: (1) identify the transit light source (TLS) effect as a challenge to precise exoplanet transmission spectroscopy and an opportunity ripe for scientific advancement in the coming decade; (2) include characterization of host star photospheric heterogeneity as part of a comprehensive research strategy for studying transiting exoplanets; (3) support the construction of ground-based extremely large telescopes (ELTs); (4) support multi-disciplinary research teams that bring together the heliophysics, stellar physics, and exoplanet communities to further exploit transiting exoplanets as spatial probes of stellar photospheres; and (5) support visual transmission spectroscopy efforts as complements to longer-wavelength observational campaigns with JWST.

Benjamin V. Rackham