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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Notch Sensitivity of Woven Ceramic Matrix Composites Under Tensile Loading: An Experimental, Analytical, and Finite Element Study

The stress concentrations associated with circular notches and subjected to uniform tensile loading in woven ceramic matrix composites (CMCs) have been investigated for high-efficient turbine engine applications. The CMC's were composed of Nicalon silicon carbide woven fabric in SiNC matrix manufactured through polymer impregnation process (PIP). Several combinations of hole diameter/plate width ratios and ply orientations were considered in this study. In the first part, the stress concentrations were calculated measuring strain distributions surrounding the hole using strain gages at different locations of the specimens during the initial portion of the stress-strain curve before any microdamage developed. The stress concentration was also calculated analytically using Lekhnitskii's solution for orthotropic plates. A finite-width correction factor for anisotropic and orthotropic composite plate was considered. The stress distributions surrounding the circular hole of a CMC's plate were further studied using finite element analysis. Both solid and shell elements were considered. The experimental results were compared with both the analytical and finite element solutions. Extensive optical and scanning electron microscopic examinations were carried out for identifying the fracture behavior and failure mechanisms of both the notched and notched specimens. The stress concentration factors (SCF) determined by analytical method overpredicted the experimental results. But the numerical solution underpredicted the experimental SCF. Stress concentration factors are shown to increase with enlarged hole size and the effects of ply orientations on stress concentration factors are observed to be negligible. In all the cases, the crack initiated at the notch edge and propagated along the width towards the edge of the specimens.

Haque, A.↗
NASA NTRS1984

A comparison of experimental and theoretical results for leakage, pressure distribution, and rotordynamic coefficients for annular gas seals

The importance of seal behavior in rotordynamics is discussed and current annular seal theory is reviewed. A Nelson's analytical-computational method for determining rotordynamic coefficients for this type of compressible-flow seal is outlined. Various means for the experimental identification of the dynamic coefficients are given, and the method employed at the Texas A and M University (TAMU) test facility is explained. The TAMU test apparatus is described, and the test procedures are discussed. Experimental results, including leakage, entrance-loss coefficients, pressure distributions, and rotordynamic coefficients for a smooth and a honeycomb constant-clearance seal are presented and compared to theoretical results from Nelson's analysis. The results for both seals show little sensitivity to the running speed over the test range. Agreement between test results and theory for leakage through the seal is satisfactory. Test results for direct stiffness show a greater sensitivity to fluid pre-rotation than predicted. Results also indicate that the deliberately roughened surface of the honeycomb seal provides improved stability versus the smooth seal.

Nicks, C. O.↗
DOE OSTI2021

Structural Changes during the Growth of Atomically Precise Metal Oxido Nanoclusters from Combined Pair Distribution Function and Small-Angle X-ray Scattering Analysis

The combination of in situ pair distribution function (PDF) analysis and small-angle X-ray scattering (SAXS) enables analysis of the formation mechanism of metal oxido nanoclusters and cluster–solvent interactions as they take place. Herein, we demonstrate the method for the formation of clusters with a [Bi 38 O 45 ] core. Upon dissolution of crystalline [Bi 6 O 5 (OH) 3 (NO 3 ) 5 ]∙3 H 2 O in DMSO, an intermediate rapidly forms, which slowly grows to stable [Bi 38 O 45 ] clusters. To identify the intermediate, we developed an automated modeling method, where smaller [Bi x O y ] structures based on the [Bi 38 O 45 ] framework are tested against the data. [Bi 22 O 26 ] was identified as the main intermediate species, illustrating how combined PDF and SAXS analysis is a powerful tool to gain insight into nucleation on an atomic scale. PDF also provides information on the interaction between nanoclusters and solvent, which is shown to depend on the nature of the ligands on the cluster surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1990

Probabilistic analysis of a materially nonlinear structure

A probabilistic finite element program is used to perform probabilistic analysis of a materially nonlinear structure. The program used in this study is NESSUS (Numerical Evaluation of Stochastic Structure Under Stress), under development at Southwest Research Institute. The cumulative distribution function (CDF) of the radial stress of a thick-walled cylinder under internal pressure is computed and compared with the analytical solution. In addition, sensitivity factors showing the relative importance of the input random variables are calculated. Significant plasticity is present in this problem and has a pronounced effect on the probabilistic results. The random input variables are the material yield stress and internal pressure with Weibull and normal distributions, respectively. The results verify the ability of NESSUS to compute the CDF and sensitivity factors of a materially nonlinear structure. In addition, the ability of the Advanced Mean Value (AMV) procedure to assess the probabilistic behavior of structures which exhibit a highly nonlinear response is shown. Thus, the AMV procedure can be applied with confidence to other structures which exhibit nonlinear behavior.

Millwater, H. R.↗
NASA NTRS1996

Discrete Deterministic and Stochastic Petri Nets

Petri nets augmented with timing specifications gained a wide acceptance in the area of performance and reliability evaluation of complex systems exhibiting concurrency, synchronization, and conflicts. The state space of time-extended Petri nets is mapped onto its basic underlying stochastic process, which can be shown to be Markovian under the assumption of exponentially distributed firing times. The integration of exponentially and non-exponentially distributed timing is still one of the major problems for the analysis and was first attacked for continuous time Petri nets at the cost of structural or analytical restrictions. We propose a discrete deterministic and stochastic Petri net (DDSPN) formalism with no imposed structural or analytical restrictions where transitions can fire either in zero time or according to arbitrary firing times that can be represented as the time to absorption in a finite absorbing discrete time Markov chain (DTMC). Exponentially distributed firing times are then approximated arbitrarily well by geometric distributions. Deterministic firing times are a special case of the geometric distribution. The underlying stochastic process of a DDSPN is then also a DTMC, from which the transient and stationary solution can be obtained by standard techniques. A comprehensive algorithm and some state space reduction techniques for the analysis of DDSPNs are presented comprising the automatic detection of conflicts and confusions, which removes a major obstacle for the analysis of discrete time models.

MATHEMATICAL MODELS↗
NASA NTRS2004

Guaranteed spatial initialization of distributed spacecraft formations

In a precious paper the authors developed a formation initialization (FI) algorithm for a deep space, N-spacecraft formation. It was demonstrated analytically that this FI contribution of this paper is to extend this planar guarantee to deep space formations with arbitrary initial conditions. As part of the guarantee of initialization, a bound on the time-to-initialize is obtained. The guaranteed FI algorithm is then demonstrated for a two-spacecraft formation with realistic deep space mission constraints (e.g. limited field-of-view relative sensors and attitude constraints). The two-spacecraft scenario is challenging in that it has the least relative sensor field-of-view overlap. Finally, for this scenario, the distribution of time-to-initialize is characterized through a 150,000-case Monte Carlo analysis.

initialization↗
NASA NTRS1984

Software reliability: Additional investigations into modeling with replicated experiments

The effects of programmer experience level, different program usage distributions, and programming languages are explored. All these factors affect performance, and some tentative relational hypotheses are presented. An analytic framework for replicated and non-replicated (traditional) software experiments is presented. A method of obtaining an upper bound on the error rate of the next error is proposed. The method was validated empirically by comparing forecasts with actual data. In all 14 cases the bound exceeded the observed parameter, albeit somewhat conservatively. Two other forecasting methods are proposed and compared to observed results. Although demonstrated relative to this framework that stages are neither independent nor exponentially distributed, empirical estimates show that the exponential assumption is nearly valid for all but the extreme tails of the distribution. Except for the dependence in the stage probabilities, Cox's model approximates to a degree what is being observed.

Nagel, P. M.↗
NASA NTRS1992

An analytic model of the neutral cloud evolution in the earth's atmosphere

An analytic model for the expansion of a chemically reacting gas in the upper atmosphere is discussed. The spatial-temporal distribution of released particles in the initial regime is described on the basis of self-similar solutions of Euler's equations. In the case of transition to the diffusion regime an approximate solution of the kinetic equation with the collision integral in the form of BGK is performed. Gravitation and the atmospheric inhomogeneity are taken into account, The diffusion regime is described by an analytic solution of the diffusion equation in an exponential atmosphere taking account of possible losses of the gas due to chemical reactions. Some peculiarities of the expansion of various gases as well as the possibility of applying the model for describing ionospheric 'holes' are discussed.

Bruskin, L. G.↗
NASA NTRS2003

Individual Aerosol Particles from Biomass Burning in Southern Africa: Compositions and Size Distributions of Carbonaceous Particles - 1

Individual aerosol particles in smoke plumes from biomass fires and in regional hazes in southern Africa were studied using analytical transmission electron microscopy (TEM), which allowed detailed characterization of carbonaceous particle types in smoke and determination of changes in particle properties and concentrations during smoke aging. Based on composition, morphology, and microstructure, three distinct types of carbonaceous particles were present in the smoke: organic particles with inorganic (K-salt) inclusions, tar ball particles, and soot. The relative number concentrations of organic particles were largest in young smoke, whereas tar balls were dominant in a slightly aged (1 hour) smoke from a smoldering fire. Flaming fires emitted relatively more soot particles than smoldering fires, but soot was a minor constituent of all studied plumes. Further aging caused the accumulation of sulfate on organic and soot particles, as indicated by the large number of internally mixed organic/sulfate and soot/sulfate particles in the regional haze. Externally mixed ammonium sulfate particles dominated in the boundary layer hazes, whereas organic/sulfate particles were the most abundant type in the upper hazes. Apparently, elevated haze layers were more strongly affected by biomass smoke than those within the boundary layer. Based on size distributions and the observed patterns of internal mixing, we hypothesize that organic and soot particles are the cloud-nucleating constituents of biomass smoke aerosols. Sea-salt particles dominated in the samples taken in stratus clouds over the Atlantic Ocean, off the coast of Namibia, whereas a distinct haze layer above the clouds consisted of aged biomass smoke particles.

Posfai, Mihaly↗
NASA NTRS2000

A polymer, random walk model for the size-distribution of large DNA fragments after high linear energy transfer radiation

DNA double-strand breaks (DSBs) produced by densely ionizing radiation are not located randomly in the genome: recent data indicate DSB clustering along chromosomes. Stochastic DSB clustering at large scales, from > 100 Mbp down to < 0.01 Mbp, is modeled using computer simulations and analytic equations. A random-walk, coarse-grained polymer model for chromatin is combined with a simple track structure model in Monte Carlo software called DNAbreak and is applied to data on alpha-particle irradiation of V-79 cells. The chromatin model neglects molecular details but systematically incorporates an increase in average spatial separation between two DNA loci as the number of base-pairs between the loci increases. Fragment-size distributions obtained using DNAbreak match data on large fragments about as well as distributions previously obtained with a less mechanistic approach. Dose-response relations, linear at small doses of high linear energy transfer (LET) radiation, are obtained. They are found to be non-linear when the dose becomes so large that there is a significant probability of overlapping or close juxtaposition, along one chromosome, for different DSB clusters from different tracks. The non-linearity is more evident for large fragments than for small. The DNAbreak results furnish an example of the RLC (randomly located clusters) analytic formalism, which generalizes the broken-stick fragment-size distribution of the random-breakage model that is often applied to low-LET data.

DNA/radiation effects↗
DOE OSTI2020

Chapter 7: Predictive Analytics in Future Power Systems: A Panorama and State-of-the-Art of Deep Learning Applications

The challenges surrounding the optimal operation of power systems are growing in various dimensions, due in part to increasingly distributed energy resources and a progression towards large-scale transportation electrification. Currently, the increasing uncertainties associated with both renewable energy generation and demand are largely being managed by increasing operational reserves - potentially at the cost of suboptimal economic conditions - in order to maintain the reliability of the system. This chapter looks at the big picture role of forecasting in power systems from generation to consumption and provides a comprehensive review of traditional approaches for forecasting generation and load in various contexts. This chapter then takes a deep dive into the state-of-the-art machine learning and deep learning approaches for power systems forecasting. Furthermore, a case study of multi-time-horizon solar irradiance forecasting using deep learning is discussed in detail. Smart grids form the backbone of the future interdependent networks. For addressing the challenges associated with the operations of smart grid, development and wide adoption of machine learning and deep learning algorithms capable of producing better forecasting accuracies is urgently needed. Along with exploring the implementation and benefits of these approaches, this chapter also considers the strengths and limitations of deep learning algorithms for power systems forecasting applications. This chapter, thus, provides a panoramic view of state-of-the-art of predictive analytics in power systems in the context of future smart grid operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1990

Analytical solutions with Generalized Impedance Boundary Conditions (GIBC)

The diffraction by a material discontinuity in a thick dielectric/ferrite layer is considered by modeling the layer as a distributed current sheet obeying generalized sheet transition conditions (GSTC's). The sheet currents are then formulated and solved via the standard dual integral equation approach. This yields the diffracted field in terms of unknown constants which underscore the non-uniqueness of the GSTC current sheet representation. The constants are dependent on the geometry and properties of the discontinuity and are determined by enforcing field continuity across the material junction. This requires the field internal to the slab which are determined from the external ones via analytic continuity. Results are given which validate the solution and demonstrate the importance of the constants.

Ricoy, Mark A.↗
NASA NTRS2014

Shielding Characteristics Using an Ultrasonic Configurable Fan Artificial Noise Source to Generate Modes - Experimental Measurements and Analytical Predictions

An Ultrasonic Configurable Fan Artificial Noise Source (UCFANS) was designed, built, and tested in support of the NASA Langley Research Center's 14x22 wind tunnel test of the Hybrid Wing Body (HWB) full 3-D 5.8% scale model. The UCFANS is a 5.8% rapid prototype scale model of a high-bypass turbofan engine that can generate the tonal signature of proposed engines using artificial sources (no flow). The purpose of the program was to provide an estimate of the acoustic shielding benefits possible from mounting an engine on the upper surface of a wing; a flat plate model was used as the shielding surface. Simple analytical simulations were used to preview the radiation patterns - Fresnel knife-edge diffraction was coupled with a dense phased array of point sources to compute shielded and unshielded sound pressure distributions for potential test geometries and excitation modes. Contour plots of sound pressure levels, and integrated power levels, from nacelle alone and shielded configurations for both the experimental measurements and the analytical predictions are presented in this paper.

Artifical Noise↗
DOE OSTI2022

Vapor-Phase Aggregation of Cerium Oxide Nanoparticles in a Rapidly Cooling Plasma

Local conditions, such as temperature and oxygen availability, have a pronounced effect on the formation and evolution of fallout following a nuclear explosion. While the behavior of nuclear-relevant materials such as uranium has begun to be explored under a wider range of environments, little is known about the behavior of plutonium. Here, using cerium as a surrogate, we track the vapor-phase aggregation of cerium oxide nanoparticles created in a plasma flow reactor under conditions of controlled temperature at two different oxygen fugacities. In situ optical emission spectroscopy is used to measure the variations in the spectral intensity of atomic and molecular species with temperature and oxygen content. We find that the relative rate of gas-phase oxidation of cerium is highly dependent on both temperature and local redox conditions within the flow reactor, to the extent that doubling the oxygen availability effectively doubles the amount of vapor-phase cerium monoxide at high temperatures (>2000 K). Condensed cerium oxide nanoparticles are also collected and analyzed ex situ via transmission electron microscopy and grazing-incidence small-angle X-ray scattering to determine their elemental composition, crystal structure, and size distribution. The size and morphology of the condensed nanoparticles are independent of local redox conditions, forming the same crystal type with the same size distribution regardless of oxygen availability. Postcondensation particle evolution, however, is found to be predominantly driven by temperature, with the average particle size increasing as particles cool and subsequently aggregate. These results expand our understanding of the chemical and physical behavior of refractory oxides that form during the early stages of fallout formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Sensitivity evaluation of the Kudryavtsev permafrost model

Modeling is an important way to assess current and future permafrost spatial distribution and dynamics, especially in data poor areas like the Arctic region. Here, we evaluate a physics-based analytical model, Kudryavtsev's active layer model, which is widely used because it has relatively few data requirements. This model was recently incorporated into a component modeling toolbox, allowing for coupled modeling of permafrost and geomorphic processes over geological timescales. However, systematic quantitative assessment of the influence of its controlling parameters on permafrost temperature and active layer thickness predictions has not been undertaken before. In this work, we investigate the sensitivity of the Kudryavtsev's active layer model by Monte Carlo simulations to generate probability distributions for input parameters and compare predictions with a comprehensive benchmark dataset of in-situ permafrost observations over entire Alaska. Predicted permafrost surface temperature is highly dependent on mean annual air temperature (r = 0.78 on average), annual temperature amplitude (–0.41), and winter-averaged snow thickness (0.30). Uncertainty of predicted permafrost temperature is relatively small (RMSE = 1 °C), when air temperature and snow depth are well constrained. Similarly, RMSE between simulated and observed ALT at stations is ~0.08 m. However, under given air temperature and snow conditions, soil water content bias can significantly affect modeled active layer thickness (RMSE = 0.1 m or 40% of the observed active layer thickness). If soil water content has a large bias, improvements in other parameters may not significantly improve the active layer predictions of the Kudryavtsev's model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

TCF-20-20213: Advanced Power Distribution Sensing and Communications through the Cable TV Broadband Network (Final Report. Period of Performance: June 2020 to June 2022)

To enable the rapid, widespread commercial availability of secondary distribution grid voltage and phase angle data, the DOE OE Technology Commercialization Fund (TCF) project: 1) created a new American National Standard for next-generation grid power quality sensing and communications, 2) created a new prototype broadband-based standard-compliant grid power sensing system for use by utilities and others, and 3) improved by several orders of magnitude the spatiotemporal scale of the in-progress DOE CESER project: Situational Awareness of Grid Anomalies (SAGA) for Visual Analytics.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1987

Gravitational lensing by an ensemble of isothermal galaxies

Calculation of 28,000 models of gravitational lensing of a distant quasar by an ensemble of randomly placed galaxies, each having a singular isothermal mass distribuiton, is reported. The average surface mass density was 0.2 of the critical value in all models. It is found that the surface mass density averaged over the area of the smallest circle that encompasses the multiple images is 0.82, only slightly smaller than expected from a simple analytical model of Turner et al. (1984). The probability of getting multiple images is also as large as expected analytically. Gravitational lensing is dominated by the matter in the beam; i.e., by the beam convergence. The cases where the multiple imaging is due to asymmetry in mass distribution (i.e., due to shear) are very rare. Therefore, the observed gravitational-lens candidates for which no lensing object has been detected between the images cannot be a result of asymmetric mass distribution outside the images, at least in a model with randomly distributed galaxies. A surprisingly large number of large separations between the multiple images is found: up to 25 percent of multiple images have their angular separation 2 to 4 times larger than expected in a simple analytical model.

Katz, Neal↗