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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Dynamic Modeling Accuracy Dependence on Errors in Sensor Measurements, Mass Properties, and Aircraft Geometry

A nonlinear simulation of the NASA Generic Transport Model was used to investigate the effects of errors in sensor measurements, mass properties, and aircraft geometry on the accuracy of dynamic models identified from flight data. Measurements from a typical system identification maneuver were systematically and progressively deteriorated and then used to estimate stability and control derivatives within a Monte Carlo analysis. Based on the results, recommendations were provided for maximum allowable errors in sensor measurements, mass properties, and aircraft geometry to achieve desired levels of dynamic modeling accuracy. Results using other flight conditions, parameter estimation methods, and a full-scale F-16 nonlinear aircraft simulation were compared with these recommendations.

Grauer, Jared A.↗
DOE OSTI2020

Automatic Classification of Biological Targets in a Tidal Channel Using a Multibeam Sonar

Multibeam sonars are widely used for environmental monitoring of fauna at marine renewable energy sites. However, they can rapidly accrue vast volumes of data, which poses a challenge for data processing. Here, using data from a deployment in a tidal channel with peak currents of 1–2 m s –1 , we demonstrate the data-reduction benefits of real-time automatic classification of targets detected and tracked in multibeam sonar data. First, we evaluate classification capabilities for three machine learning algorithms: random forests, support vector machines, and k-nearest neighbors. For each algorithm, a hill-climbing search optimizes a set of hand-engineered attributes that describe tracked targets. Here, the random forest algorithm is found to be most effective—in postprocessing, discriminating between biological and nonbiological targets with a recall rate of 0.97 and a precision of 0.60. In addition, 89% of biological targets are correctly classified as either seals, diving birds, fish schools, or small targets. Model dependence on the volume of training data is evaluated. Second, a real-time implementation of the model is shown to distinguish between biological targets and nonbiological targets with nearly the same performance as in postprocessing. From this, we make general recommendations for implementing real-time classification of biological targets in multibeam sonar data and the transferability of trained models.

16 TIDAL AND WAVE POWER↗
NASA NTRS1992

Observational evidence for thin AGN disks

AGN spectrum and spectral features, polarization, inclination, and X-ray line and continuum reflection features are discussed in a critical way in order to determine the ones that are the least model-dependent. The sign and strength of absorption and emission edges are found to be model-dependent, and relativistic broadening and shifting makes them hard to detect. The presence or absence of the predicted Lyman edge polarization feature may be used as a decisive test for thin, bare AGN disks. Other good model-independent tests are several inclination-related line and continuum correlations in big AGN samples. It is shown that electron temperature near the surface of the disk can greatly exceed the disk equilibrium temperature, which causes deviations from LTE. This effect must be incorporated into realistic disk models.

Netzer, Hagai↗
NASA NTRS1984

A history dependent damage model for low cycle fatigue

This paper examines damage assessment and accumulation. A nonlinear damage postulate is advanced that embodies the dependence of the damage rate on cycle-dependent changes in the bulk microstructure and the surface topography. The postulate is analytically formulated in terms of the deformation history dependence of the bulk behavior. This formulation is used in conjunction with baseline data in accordance with the damage postulate to predict the low cycle fatigue resistance of OFE copper. Close comparison of the predictions with observed behavior suggests the postulate offers a viable basis for nonlinear damage analysis.

Leis, B. N.↗
DOE OSTI2024

Modeling Rate Dependent Volume Change in Porous Electrodes in Lithium-Ion Batteries

Automotive manufacturers are working to improve individual cell, module, and overall pack design by increasing the performance, range, and durability, while reducing cost. One key piece to consider during the design process is the active material volume change, its linkage to the particle, electrode, and cell level volume changes, and the interplay with structural components in the rechargeable energy storage system. As the time from initial design to manufacture of electric vehicles decreases, design work needs to move to the virtual domain; therefore, a need for coupled electrochemical-mechanical models that take into account the active material volume change and the rate dependence of this volume change need to be considered. In this study, we illustrated the applicability of a coupled electrochemical-mechanical battery model considering multiple representative particles to capture experimentally measured rate dependent reversible volume change at the cell level through the use of an electrochemical-mechanical battery model that couples the particle, electrode, and cell level volume changes. By employing this coupled approach, the importance of considering multiple active material particle sizes representative of the distribution is demonstrated. The non-uniformity in utilization between two different size particles as well as the significant spatial non-uniformity in the radial direction of the larger particles is the primary driver of the rate dependent characteristics of the volume change at the electrode and cell level.

Electrochemistry↗
DOE OSTI2022

Nonconventional NMR Spin-Coupling Constants in Oligosaccharide Conformational Modeling: Structural Dependencies Determined from Density Functional Theory Calculations

Nonconventional NMR spin-coupling constants were investigated to determine their potential as conformational constraints in MA’AT modeling of the O-glycosidic linkages of oligosaccharides. Four ( 1 J C1',H1' , 1 J C1',C2' , 2 J C1',H2' , and 2 J C2',H1' ) and eight ( 1 J C4,H4 , 1 J C3,C4 , 1 J C4,C5 , 2 J C3,H4 , 2 J C4,H3 , 2 J C5,H4 , 2 J C4,H5 , and 2 J C3,C5 ) spin-couplings in methyl β-d-galactopyranosyl-(1→4)-β-d-glucopyranoside (methyl β-lactoside) were calculated using density functional theory (DFT) to determine their dependencies on O-glycosidic linkage C–O torsion angles, $\phi$ and ψ, respectively. Long-range 4 J H1',H4 was also examined as a potential conformational constraint of either $\phi$ or ψ. Secondary effects of exocyclic (hydroxyl) C–O bond rotation within or proximal to these coupling pathways were investigated. Based on the findings of methyl β-lactoside, analogous J-couplings were studied in five additional two-bond O-glycosidic linkages [βGlcNAc-(1→4)-βMan, 2-deoxy-βGlc-(1→4)-βGlc, αMan-(1→3)-βMan, αMan-(1→2)-αMan, and βGlcNAc(1→2)-αMan] to determine whether the coupling behaviors observed in methyl β-lactoside were more broadly observed. Of the 13 nonconventional J-couplings studied, 7 exhibit properties that may be useful in future MA’AT modeling of O-glycosidic linkages, none of which involve coupling pathways that include the linkage C–O bonds. The findings also provide new insights into the general effects of exocyclic C–O bond conformation on the magnitude of experimental spin-couplings in saccharides and other hydroxyl-containing molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2004

Top-of-Atmosphere Shortwave Broadband Observed Radiance and Estimated Irradiance over Polar Regions from Clouds and the Earth's Radiant Energy System (CERES) Instruments on Terra

Empirical angular distribution models for estimating top-of-atmosphere shortwave irradiances from radiance measurements over permanent snow, fresh snow and sea ice are developed using CERES measurements on Terra. Permanent snow angular distribution models depend on cloud fraction, cloud optical thickness, and snow brightness. Fresh snow and sea ice angular distribution models depend on snow and sea ice fraction, cloud fraction, cloud optical thickness, and snow and ice brightness. These classifications lead to 10 scene types for permanent snow and 25 scene types for fresh snow and sea ice. The average radiance over clear-sky permanent snow is more isotropic with satellite viewing geometry than that over overcast permanent snow. On average, the albedo of clear-sky permanent snow varies from 0.65 to 0.68 for solar zenith angles between 60$logical and\circ$ and 80 deg, while the corresponding albedo of overcast scenes varies from 0.70 to 0.73. Clear-sky permanent snow albedos over Antarctica estimated from two independent angular distribution models are consistent to within 0.6%, on average. Despite significant variability in sea ice optical properties with season, the estimated mean relative albedo error is -1 % for very dark sea ice and 0.1% for very bright sea ice when albedos derived from different viewing angles are averaged. The estimated regional root-mean-square (RMS) relative albedo error is 5.6% and 2.6% when the sea ice angular distribution models are applied to a region that contains very dark and very bright sea ice, respectively. Similarly, the estimated relative albedo bias error for fresh snow is -0.1% for very dark snow.

Kato, S.↗
NASA NTRS1984

Stratospheric NO and NO2 profiles at sunset from analysis of high-resolution balloon-borne infrared solar absorption spectra obtained at 33 deg N and calculations with a time-dependent photochemical model

Simultaneous stratospheric vertical profiles of NO and NO2 at sunset were derived from an analysis of infrared solar absorption spectra recorded from a float altitude of 33 km with an interferometer system during a balloon flight. A nonlinear least squares procedure was used to analyze the spectral data in regions of absorption by NO and NO2 lines. Normalized factors, determined from calculations of time dependent altitude profiles with a detailed photochemical model, were included in the onion peeling analysis to correct for the rapid diurnal changes in NO and NO2 concentrations with time near sunset. The CO2 profile was also derived from the analysis and is reported.

Rinsland, C. P.↗
DOE OSTI2021

Differentiating Hund from Mott physics in a three-band Hubbard-Hund model: Temperature dependence of spectral, transport, and thermodynamic properties

We study the interplay between Mott physics, driven by Coulomb repulsion U, and Hund physics, driven by Hund's coupling J, for a minimal model for Hund metals, the orbital-symmetric three-band Hubbard-Hund model (3HHM) for a lattice filling of 1/3. Hund-correlated metals are characterized by spin-orbital separation (SOS), a Hund's-rule-induced two-stage Kondo-type screening process, in which spin screening occurs at much lower energy scales than orbital screening. By contrast, in Mott-correlated metals, lying close to the phase boundary of a metal-insulator transition, the SOS window becomes negligibly small and the Hubbard bands are well separated. Using dynamical mean-field theory and the numerical renormalization group as real-frequency impurity solver, we identify numerous fingerprints distinguishing Hundness from Mottness in the temperature dependence of various physical quantities. Furthermore, These include ARPES-type spectra, the local self-energy, static local orbital and spin susceptibilities, resistivity, thermopower, and lattice and impurity entropies. Our detailed description of the behavior of these quantities within the context of a simple model Hamiltonian will be helpful for distinguishing Hundness from Mottness in experimental and theoretical studies of real materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1992

A procedure for utilization of a damage-dependent constitutive model for laminated composites

Described here is the procedure for utilizing a damage constitutive model to predict progressive damage growth in laminated composites. In this model, the effects of the internal damage are represented by strain-like second order tensorial damage variables and enter the analysis through damage dependent ply level and laminate level constitutive equations. The growth of matrix cracks due to fatigue loading is predicted by an experimentally based damage evolutionary relationship. This model is incorporated into a computer code called FLAMSTR. This code is capable of predicting the constitutive response and matrix crack damage accumulation in fatigue loaded laminated composites. The structure and usage of FLAMSTR are presented along with sample input and output files to assist the code user. As an example problem, an analysis of crossply laminates subjected to two stage fatigue loading was conducted and the resulting damage accumulation and stress redistribution were examined to determine the effect of variations in fatigue load amplitude applied during the first stage of the load history. It was found that the model predicts a significant loading history effect on damage evolution.

Lo, David C.↗
DOE OSTI2021

Validation of a Pressure Dependent PBX 9501 Cookoff Model

A pressure dependent cookoff model for PBX 9501 was developed. This cookoff model was implemented in the finite element (FE) heat transfer code Aria and was used to simulate a set of cookoff experiments. This set is called the Large Scale Annular Cookoff (LSAC) experiments. Three dimensional and axisymmetric heat conduction FE models were implemented to simulate these experiments. The predictive ability of the PBX 9501 pressure dependent cookoff model was evaluated using Latin Hypercube sampling (LHS). Predictions of the thermal times to ignition and temperatures are compared with the experiments.

42 ENGINEERING↗
NASA NTRS2019

Parameters Inference and Model Reduction for the Single-Particle Model of Li Ion Cells

The Single-Particle Model (SPM) of Li ion cell is a computationally efficient model for simulating Li ion cell for weak to moderate currents. The model depends n a number of parameters describing the geometry and material properties of a cell components. In order to apply the model to simulating a cell, the best-fit parametric values have to be inferred from a constant discharge data. We report our efforts to determine the best-fit set for 18650 LP batteries. We found that rather than being best-fit by a particular point in the parametric space the data is fit equally well by an ensemble of points clustering about an effective multidimensional manifold in the parametric space. This property of the SPM is known to be shared by a multitude of the so-called "sloppy models" of complex systems, characterized by a few stiff directions in the parametric space, in which the predicted behavior varies significantly, and a number of sloppy directions in which the behavior doesn't change appreciably. Only the stiff parameters combinations are identifiable. Geometrical features of the BFM give insights to possible reduction of the SPM to a model having fewer sloppy parameters. We have constructed a hierarchy of such models. The fully reduced model depends on only stiff effective parameters which are identifiable and can be used for characterization of the battery's state of health.

Khasin, Michael↗
NASA NTRS1986

Time-dependent numerical modeling of dust halo formation at comets

The evolution of gas and dust distributions following a spatially and temporally localized comet outburst was calculated using a hybrid kinetic-hydrodynamic method. In the inner coma the time-dependent continuity, momentum, and energy equations of the dusty gas flow were solved simultaneously using 12 dust sizes. Beyond 300 km a three-dimensional kinetic model was used to calculate the trajectory of each individual dust grain. It was found that following the onset of the comet outburst a gas-dust blast wave propagates outward in the inner coma. About 15 minutes after the increased gas and dust production was initiated at the nucleus, a new equilibrium was reached in the inner coma. The most important feature of this new steady state was the significant increase of the dust terminal velocities. These higher terminal velocity values resulted in larger apex distances for dust particles emitted during the outburst. The dust particles spend a relatively long time near their apex points; therefore, the outburst generates long-lasting distinct dust envelopes in front of the regular dust coma.

Gombosi, T. I.↗
NASA NTRS1994

Abundance gradients in cooling flow clusters: Ginga Large Area Counters and Einstein Solid State Spectrometer spectra of A496, A1795, A2142, and A2199

We analyze the Ginga Large Area Counters (LAC) and Einstein Solid State Spectrometer (SSS) spectra of four cooling flow clusters, A496, A1795, A2142, and A2199, each of which shows firm evidence of a relatively cool component. The inclusion of such cool spectral components in joint fits of SSS and LAC data leads to somewhat higher global temperatures than are derived from the high-energy LAC data alone. We find little evidence of cool emission outside the SSS field of view. Metal abundances appear to be centrally enhanced in all four clusters, with varying degrees of model dependence and statistical significance: the evidence is statistically strongest for A496 and A2142, somewhat weaker for A2199 and weakest for A1795. We also explore the model dependence in the amount of cold, X-ray-absorbing matter discovered in these clusters by White et al.

White, Raymond E., III↗
DOE OSTI2023

Time-Dependent Boundary Modeling to Inform Design of SPARC Diagnostic and Actuators

The purpose of this work was to inform the design of diagnostic and actuator systems for a new experimental facility for Commonwealth Fusion Systems (CFS), called SPARC [Creely2020], using time-dependent plasma boundary simulations with the Scrape Off Layer Plasma Simulator (SOLPS) code [Wiesen2015]. The SPARC tokamak is a device that aims to demonstrate fusion energy production and high-field plasma operating scenarios. The developed technologies will be incorporated into a net-electricity pilot that will demonstrate approximately 200MW of electric power. A major difference from other private industry fusion companies is the use of a standard aspect ratio, but at a high magnetic field strength, which provides a well-established physics basis and a modest extrapolation to reactor operation. Time-dependent simulations were used to inform the design of main-chamber plasma facing components, which are protected by feedback control of the heat and particle loads during high power operation. The simulations provide the timescales and magnitudes of plasma and neutral particle response useful for determining the position and operation of diagnostics and actuators that will enable control. The plasma response and phase-space diagrams also provide input into advanced model-based control schemes, which are envisioned for later SPARC operation. Model-based control can reduce the risk of component failure, which would require expensive in-situ repairs and the associated delays, by predicting the system response to actuators over a short time-horizon.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

A substandard candle: the low-$$\nu $$ method at few-GeV neutrino energies

Abstract As accelerator-based neutrino oscillation experiments improve oscillation parameter constraints with more data, control over systematic uncertainties on the incoming neutrino flux and interaction models is increasingly important. The intense beams offered by modern experiments permit a variety of options to constrain the flux using in situ “standard candle” measurements. These standard candles must use very well understood interaction processes to avoid introducing additional interaction model dependence. One option often discussed in this context is the “low- $$\nu $$ ν ” method, which is designed to isolate neutrino interactions where there is low energy-transfer to the nucleus, such that the interaction cross section is expected to be approximately constant as a function of neutrino energy. The shape of the low-energy transfer event sample can then be used to extract the flux shape. Applications of the method at high neutrino energies (many tens of GeV) are well understood. However, the applicability of the method at the lower energies of current and future few-GeV accelerator neutrino experiments remains unclear due to the presence of nuclear and form-factor effects inherent in the interaction models.In this analysis we examine the prospects for improving constraints on the accelerator neutrino fluxes in situ with the low- $$\nu $$ ν method in an experiment-independent way, using (anti)neutrino interactions on argon and hydrocarbon targets from the GENIE, NEUT, NuWro and GiBUU event generators. We begin by investigating the extent to which deviations from the constant cross-section assumption are dependent on poorly understood aspects of the neutrino interaction model. We then assess whether a low energy-transfer event sample can be confidently identified using experimentally accessible observables. We finally consider how the practicalities of reconstructing the energy spectrum of interacting neutrinos in realistic detectors might further limit the utility of low- $$\nu $$ ν flux constraints. The results show that flux constraints from the low- $$\nu $$ ν method would be severely dependent on the interaction model assumptions used in an analysis of neutrinos with energies below 5 GeV, and anti-neutrinos below at least 15 GeV. The spread of model predictions show that a low- $$\nu $$ ν analysis is unlikely to offer much improvement on typical neutrino flux uncertainties, even with a perfect detector. Notably—running counter to the assumption inherent to the low- $$\nu $$ ν method—the model-dependence increases with decreasing energy transfer for experiments in the few-GeV region.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Trust-Based Detection and Mitigation of Cyber Attacks in Distributed Cooperative Control of Islanded AC Microgrids

In this study, we address the challenge of detecting and mitigating cyber attacks in the distributed cooperative control of islanded AC microgrids, with a particular focus on detecting False Data Injection Attacks (FDIAs), a significant threat to the Smart Grid (SG). The SG integrates traditional power systems with communication networks, creating a complex system with numerous vulnerable links, making it a prime target for cyber attacks. These attacks can lead to the disclosure of private data, control network failures, and even blackouts. Unlike machine learning-based approaches that require extensive datasets and mathematical models dependent on accurate system modeling, our method is free from such dependencies. To enhance the microgrid’s resilience against these threats, we propose a resilient control algorithm by introducing a novel trustworthiness parameter into the traditional cooperative control algorithm. Our method evaluates the trustworthiness of distributed energy resources (DERs) based on their voltage measurements and exchanged information, using Kullback-Leibler (KL) divergence to dynamically adjust control actions. We validated our approach through simulations on both the IEEE-34 bus feeder system with eight DERs and a larger microgrid with twenty-two DERs. The results demonstrated a detection accuracy of around 100%, with millisecond range mitigation time, ensuring rapid system recovery. Additionally, our method improved system stability by up to almost 100% under attack scenarios, showcasing its effectiveness in promptly detecting attacks and maintaining system resilience. These findings highlight the potential of our approach to enhance the security and stability of microgrid systems in the face of cyber threats.

Computer Science↗