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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Neutron-induced fission fragment angular distributions, anisotropy, and linear momentum transfer measured with the NIFFTE fission time projection chamber

The Neutron Induced Fission Fragment Tracking Experiment (NIFFTE) collaboration has performed measurements with a fission time projection chamber (fissionTPC) to study the fission process by reconstructing full three-dimensional tracks of fission fragments and other ionizing radiation. The amount of linear momentum imparted to the fissioning nucleus by the incident neutron can be inferred by measuring the opening angle between the fission fragments. Using this measured linear momentum, fission fragment angular distributions can be converted to the center-of-mass frame for anisotropy measurements. Angular anisotropy is an important experimental observable for understanding the quantum mechanical state of the fissioning nucleus and vital to determining detection efficiency for cross section measurements. Neutron linear momentum transfer to fissioning 235 U, 238 U, and 239Pu and fission fragment angular anisotropy of 235 U and 238 U as a function of neutron energies in the range 130 keV–250 MeV are presented.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2005

Observation of an Aligned Gas - Solid "Eutectic" during Controlled Directional Solidification Aboard the International Space Station - Comparison with Ground-based Studies

Direct observation of the controlled melting and solidification of succinonitrile was conducted in the glovebox facility of the International Space Station (ISS). The experimental samples were prepared on ground by filling glass tubes, 1 cm ID and approximately 30 cm in length, with pure succinonitrile (SCN) in an atmosphere of nitrogen at 450 millibar pressure for eventual processing in the Pore Formation and Mobility Investigation (PFMI) apparatus in the glovebox facility (GBX) on board the ISS. Real time visualization during controlled directional melt back of the sample showed nitrogen bubbles emerging from the interface and moving through the liquid up the imposed temperature gradient. Over a period of time these bubbles disappear by dissolving into the melt. Translation is stopped after melting back of about 9 cm of the sample, with an equilibrium solid-liquid interface established. During controlled re-solidification, aligned tubes of gas were seen growing perpendicular to the planar solid/liquid interface, inferring that the nitrogen previously dissolved into the liquid SCN was now coming out at the solid/liquid interface and forming the little studied liquid = solid + gas eutectic-type reaction. The observed structure is evaluated in terms of spacing dimensions, interface undercooling, and mechanisms for spacing adjustments. Finally, the significance of processing in a microgravity environment is ascertained in view of ground-based results.

Grugel, R. N.↗
DOE OSTI2021

Particle image velocimetry analysis with simultaneous uncertainty quantification using Bayesian neural networks

Particle image velocimetry (PIV) is an effective tool in experimental fluid mechanics for extracting flow fields from images. Recently, convolutional neural networks (CNNs) have been used to perform PIV analysis with accuracy on par with classical methods. Here we extend the use of CNNs to analyze PIV data while providing simultaneous uncertainty quantification on the inferred flow field. The method we apply in this paper is a Bayesian convolutional neural network (BCNN) which learns distributions of the CNN weights through variational Bayes. In order to demonstrate the utility of BCNNs for the PIV task, we compare the performance of three distinct BCNN models with simple architectures. The first network estimates flow velocity from image interrogation regions only. Our second model learns to infer velocity from both the image interrogation regions and interrogation region cross-correlation maps. Finally, our best performing network infers velocities from interrogation region cross-correlation maps only. We find that BCNNs using interrogation region cross-correlation maps as inputs perform better than those using interrogation windows only as inputs and discuss reasons why this may be the case. Additionally, we test the best performing BCNN on a full synthetic test image pair and a real image pair from the 1st International PIV Challenge. We show that ~98% of true particle displacements from the full synthetic image pair can be captured within the BCNN's 95% confidence intervals, and that the BCNN's performance on the real image pair is quantitatively similar to that of algorithms tested in the 1st International PIV Challenge. Finally, we show that BCNNs can be generalized to be used with multi-pass PIV algorithms with a moderate loss in accuracy, which may be overcome by future work on finetuning and training schemes. So to our knowledge, this is the first use of Bayesian neural networks to perform PIV.

47 OTHER INSTRUMENTATION↗
NASA NTRS1974

Progress in gamma ray burst astronomy

Spectral observations on nine of the eleven known cosmic gamma ray bursts detected from IMP-7 from late 1972 through 1973 are reported. All nine events were found to have average spectra ranging from 100 to 1100 keV. The hypothesis of a single greater than 100 keV average event spectrum for all gamma ray bursts (inferred from IMP-6 observations) was investigated. In addition to the mutual consistency of these 14 IMP events, all independently reported average event spectra fit the IMP-7 common spectrum. This observed lack of variability of the average event spectrum suggests that the production mechanism is tied to more rigidly fixed source parameters than most celestial or solar hard X-ray phenomena. Other characteristics of gamma ray bursts events, are discussed: a high-energy spectral tail with power-law index -2.5, a rising size spectrum from the earlier event rate, and a hint of clustering of event occurrence in time.

Cline, T. L.↗
NASA NTRS1988

Turbulent magnetohydrodynamic density fluctuations

A spectral-method numerical code is used to compute mass-density fluctuation spectra in turbulent magnetofluids. The computations are used to test and extend the analytical theory of density variations in slightly compressible magnetofluids given by Montgomery, et al. (1987) and used to infer inertial-range density-fluctuation spectra for the nearby interstellar medium and solar wind. A local equation of state is assumed, relating density to pressure. Constant, scalar resistivities and viscosities are used. In the limit of low Mach numbers and high mechanical-to-magnetic pressure ratios, the fit of the computations to the analytical theory is seen to be close.

Shebalin, John V.↗
NASA NTRS1991

Voyager 2 electron observations in the magnetosphere of Neptune

This paper describes electron data obtained during the Neptune encounter by the Voyager 2 plasma science experiment. The densities and temperatures of low-energy (10-5950 eV) electrons and the electrostatic potential of the spacecraft near Neptune are derived. The data indicate that the escape of charged particles from Triton and the local ionization of atoms in the neutral torus originating from Triton are the major plasma sources. It is inferred that this neutral torus of hydrogen atoms has a density of about 300/cu cm and an inner boundary at 8 R(N). The data near Neptune exhibit signatures suggesting that both precipitation into Neptune's atmosphere and ring absorption are important plasma loss mechanisms. Plasma transport in the magnetosphere appears to be very fast; the diffusion coefficient is 1 x 10 exp -7 L exp 3 R(N) exp 2/sec.

Zhang, Ming↗
NASA NTRS1995

Emplacement of Xenolith Nodules in the Kaupulehu Lava Flow, Hualalai Volcano, Hawaii

The basaltic Kaupulehu 1800-1801 lava flow of Hualalai Volcano, Hawaii contains abundant ultramafic xenoliths. Many of these xenoliths occur as bedded layers of semi-rounded nodules, each thinly coated with a veneer (typically 1 mm thick) of lava. The nodule beds are analogous to cobble deposits of fluvial sedimentary systems. Although several mechanisms have been proposed for the formation of the nodule beds, it was found that, at more than one locality, the nodule beds are overbank levee deposits. The geological occurrence of the nodules, certain diagnostic aspects of the flow morphology and consideration of the inferred emplacement process indicate that the Kaupulehu flow had an exceptionally low viscosity on eruption and that the flow of the lava stream was extremely rapid, with flow velocities of at least 10 m/s (more than 40 km/h. This flow is the youngest on Hualalai Volcano and future eruptions of a similar type would pose considerable hazard to life as well as property.

Guest, J. E.↗
NASA NTRS2008

Development of Time-Distance Helioseismology Data Analysis Pipeline for SDO/HMI

The Helioseismic and Magnetic Imager of SDO will provide uninterrupted 4k x 4k-pixel Doppler-shift images of the Sun with approximately 40 sec cadence. These data will have a unique potential for advancing local helioseismic diagnostics of the Sun's interior structure and dynamics. They will help to understand the basic mechanisms of solar activity and develop predictive capabilities for NASA's Living with a Star program. Because of the tremendous amount of data the HMI team is developing a data analysis pipeline, which will provide maps of subsurface flows and sound-speed distributions inferred form the Doppler data by the time-distance technique. We discuss the development plan, methods, and algorithms, and present the status of the pipeline, testing results and examples of the data products.

DuVall, T. L., Jr.↗
NASA NTRS2026

Thermochemically-Closed Sonic-Flow Inversion for Enthalpy and Temperature in Multispecies Arc-Jet Flows

A thermochemically-closed sonic-flow inversion framework (TSIF) is developed to infer bulk enthalpy and total temperature upstream of a choked nozzle in arc-jet flows. The formulation recasts a pressure-rise total enthalpy quantification technique as an inverse problem in characteristic-velocity c * space using measured mass flow rate, upstream total pressure, gas composition, and nozzle throat geometry as inputs. Unlike calorimetric energy-balance approaches or optical diagnostics, the method relies primarily on routinely measured facility quantities combined with explicit thermochemical closure. Thermochemical states are obtained using NASA’s open-source Chemical Equilibrium with Applications (CEA) code, enabling construction of a chemistry-consistent relation between characteristic velocity, total enthalpy, and total temperature under equilibrium or frozen assumptions. A discharge coefficient is self-calibrated using cold-flow (arc-off) operation data and applied to hot-flow (arc-on) measurements, enabling upstream losses to be accounted for without empirical correlations. The framework is applied to air, N 2 , and CO 2 –N 2 arc-jet flows and demonstrates expected trends for the inferred thermochemical states as function of arc power, specific energy input, mass-flow, heater configuration, and test gas. In the air limit, under equilibrium assumptions, the method recovers the classical high-enthalpy asymptotic correlation of Winovich with a mean residual of 4.4%, demonstrating compatibility with established sonic-flow scaling, while extending applicability to arbitrary multi-species mixtures and non-equilibrium chemistry. The framework provides a mixture-flexible methodology for determining bulk thermochemical states in modern arc-jet environments using routine facility pressure, mass-flow, gas-composition, and nozzle-geometry information together with a cold-flow calibration.

stagnation heat flux↗
DOE OSTI2021

Utilizing computer vision and artificial intelligence algorithms to predict and design the mechanical compression response of direct ink write 3D printed foam replacement structures

Additive Manufacturing (AM) of porous polymeric materials, such as foams, recently became a topic of intensive research due their unique combination of low density, impressive mechanical properties, and stress dissipation capabilities. Conventional methods for fabricating foams rely on complex and stochastic processes, making it challenging to achieve precise architectural control of structured porosity. In contrast, AM provides access to a wide range of printable materials, where precise spatial control over structured porosity can be modulated during the fabrication process enabling the production of foam replacement structures (FRS). Current approaches for designing FRS are based on intuitive understanding of their properties or an extensive number of finite element method (FEM) simulations. These approaches, however, are computationally expensive and time consuming. As such, in this work, we present a novel methodology for determining the mechanical compression response of direct ink write (DIW) 3D printed FRS using a simple cross-sectional image. By obtaining measurement data for a relatively small number of samples, an artificial neural network (ANN) was trained, and a computer vision algorithm was used to make inferences about foam compression characteristics from a single cross-sectional image. Finally, a genetic algorithm (GA) was used to solve the inverse design problem, generating the AM printing parameters that an engineer should use to achieve a desired compression response from a DIW printed FRS. The methods developed herein present an avenue for entirely autonomous design and analysis of additively manufactured structures using artificial intelligence.

36 MATERIALS SCIENCE↗
DOE OSTI2024

AEPF: Attention-Enabled Point Fusion for 3D Object Detection

Current state-of-the-art (SOTA) LiDAR-only detectors perform well for 3D object detection tasks, but point cloud data are typically sparse and lacks semantic information. Detailed semantic information obtained from camera images can be added with existing LiDAR-based detectors to create a robust 3D detection pipeline. With two different data types, a major challenge in developing multi-modal sensor fusion networks is to achieve effective data fusion while managing computational resources. With separate 2D and 3D feature extraction backbones, feature fusion can become more challenging as these modes generate different gradients, leading to gradient conflicts and suboptimal convergence during network optimization. To this end, we propose a 3D object detection method, Attention-Enabled Point Fusion (AEPF). AEPF uses images and voxelized point cloud data as inputs and estimates the 3D bounding boxes of object locations as outputs. An attention mechanism is introduced to an existing feature fusion strategy to improve 3D detection accuracy and two variants are proposed. These two variants, AEPF-Small and AEPF-Large, address different needs. AEPF-Small, with a lightweight attention module and fewer parameters, offers fast inference. AEPF-Large, with a more complex attention module and increased parameters, provides higher accuracy than baseline models. Experimental results on the KITTI validation set show that AEPF-Small maintains SOTA 3D detection accuracy while inferencing at higher speeds. AEPF-Large achieves mean average precision scores of 91.13, 79.06, and 76.15 for the car class’s easy, medium, and hard targets, respectively, in the KITTI validation set. Results from ablation experiments are also presented to support the choice of model architecture.

Chemistry↗
NASA NTRS1977

Mesoscale cloud phenomena observed by LANDSAT

Examples of certain mesoscale cloud features - jet cirrus, eddies/vortices, cloud banding, and wave clouds - were collected from LANDSAT imagery and placed into Mason's four groups of causes of cloud formation based on the mechanism of vertical motion which produces condensation. These groups are as follows: (1) layer clouds formed by widespread regular ascent; (2) layer clouds caused by irregular stirring motions; (3) convective clouds; and (4) clouds formed by orographic disturbances. These mechanisms explain general cloud formation. Once formed, other forces may play a role in the deformation of a cloud or cloud mass into unusual and unique meso- and microscale patterns. Each example presented is followed by a brief discussion describing the synoptic situation, and some inference into the formation and occurrence of the more salient features. No major attempt was made to discuss in detail the meteorological and topographic interplay producing these mesoscale features.

Ormsby, J. P.↗
NASA NTRS1977

Electrostatic emissions between electron gyroharmonics in the outer magnetosphere

A scheme was constructed and a theoretical model was developed to classify electrostatic emissions. All of the emissions appear to be generated by the same basic mechanism: an unstable electron plasma distribution consisting of cold electrons (less than 100 eV) and hot loss cone electrons (about 1 keV). Each emission class is associated with a particular range of model parameters; the wide band electric field data can thus be used to infer the density and temperature of the cold plasma component. The model predicts that gyroharmonic emissions near the plasma frequency require large cold plasma densities.

Hubbard, R. F.↗
NASA NTRS1978

Electrostatic emissions between electron gyroharmonics in the outer magnetosphere

Electrostatic emissions are often observed by spacecraft in the outer magnetosphere at frequencies between low electron gyroharmonics. The emissions include the well-known odd half-harmonic emissions as well as weaker emissions which occur near the electron plasma frequency. A scheme is constructed for classifying the emissions, and it is shown that a theoretical model which has been previously used to explain '3/2' emissions can be extended to the other classes of emissions. All of the emissions therefore appear to be generated by the same basic mechanism: an unstable electron plasma distribution consisting of cold electrons (below 100 eV) and hot loss cone electrons (about 1 keV). Each emission class is associated with a particular range of model parameters; the wide-band electric field data can thus be used to infer the density and temperature of the cold plasma component. The model predicts that gyroharmonic emissions near the plasma frequency require large cold plasma densities.

Hubbard, R. F.↗
NASA NTRS1981

On the growth of turbulent regions in laminar boundary layers

Turbulent spots evolving in a laminar boundary layer on a nominally zero pressure gradient flat plate are investigated. The plate is towed through an 18 m water channel, using a carriage that rides on a continuously replenished oil film giving a vibrationless tow. Turbulent spots are initiated using a solenoid valve that ejects a small amount of fluid through a minute hole on the working surface. A novel visualization technique that utilizes fluorescent dye excited by a sheet of laser light is employed. Some new aspects of the growth and entrainment of turbulent spots, especially with regard to lateral growth, are inferred from the present experiments. To supplement the information on lateral spreading, a turbulent wedge created by placing a roughness element in the laminar boundary layer is also studied both visually and with probe measurements. The present results show that, in addition to entrainment, another mechanism is needed to explain the lateral growth characteristics of a turbulent region in a laminar boundary layer. This mechanism, termed growth by destabilization, appears to be a result of the turbulence destabilizing the unstable laminar boundary layer in its vicinity. To further understand the growth mechanisms, the turbulence in the spot is modulated using drag-reducing additives and salinity stratification.

Gad-El-hak, M.↗
NASA NTRS2002

Upper Temperature Limit of Environmental Barrier Coatings Based on Mullite and BSAS

Current state-of-the-art environmental barrier coatings (EBCs) for Si-based ceramics consist of three layers: a silicon bond coat, an intermediate mullite (3Al2O3-2SiO2) or mullite + BSAS (1-xBaO-xSrO-Al2O3-2SiO2) layer, and a BSAS top coat. Areas of concern for long-term durability are environmental durability, chemical compatibility, silica volatility, phase stability, and thermal conductivity. Variants of this family of EBCs were applied to monolithic SiC and melt infiltrated SiC/SiC composites. Reaction between BSAS and silica results in low melting (approx. 1300 C) glasses at T > 1400 C, which can cause the spallation of the EBC. At temperatures greater than 1400 C, the BSAS top coat also degrades by formation of a porous structure, and it suffers significant recession via silica volatilization in water vapor-containing atmospheres. All of these degradation mechanisms can be EBC life-limiting factors. BSAS undergoes a very sluggish phase transformation (hexagonal celsian to monoclinic celsian), the implications of which are not fully understood at this point. There was evidence of rapid sintering at temperatures as low as 1300 C, as inferred from the sharp increase in thermal conductivity.

Lee, Kang N.↗
NASA NTRS2000

Trapped Energetic Electrons in the Magnetosphere of Ganymede

On May 7, 1997, the Galileo orbiter flew through the magnetosphere of Ganymede and crossed flux tubes connected at both ends to the satellite. Energetic electrons, observed during this encounter by means of the Energetic Particle Detector on board Galileo, showed double loss cones and "butterfly" type pitch angle distributions, as has been noted in past publications. In addition, as the spacecraft flew toward Ganymede, both the shape and magnitude of the spectrum changed. The intensities decreased, with the greatest depletion observed at the lowest energies, and the monotonic slope characteristic of the Jovian environment was replaced by a rollover of the spectrum at the low-energy end. The spectra lead us to infer a strongly energy-dependent injection efficiency into the trapping region. As on previous encounters, the pitch angle distributions confirmed the position of the magnetopause as indicated by the magnetometer measurements, but the spectra remained Jovian until the trapping region was reached. Various physical mechanisms capable of generating the observed spectra and pitch angle distributions, including downstream reconnection insertion followed by magnetic gradient drift and absorption of the lowest-energy electrons by Ganymede and injection from Jovian flux tubes upstream are assessed.

Eviatar, Aharon↗
NASA NTRS2004

Open Platform for Limit Protection with Carefree Maneuver Applications

This Open Platform for Limit Protection guides the open design of maneuver limit protection systems in general, and manned, rotorcraft, aerospace applications in particular. The platform uses three stages of limit protection modules: limit cue creation, limit cue arbitration, and control system interface. A common set of limit cue modules provides commands that can include constraints, alerts, transfer functions, and friction. An arbitration module selects the "best" limit protection cues and distributes them to the most appropriate control path interface. This platform adopts a holistic approach to limit protection whereby it considers all potential interface points, including the pilot's visual, aural, and tactile displays; and automatic command restraint shaping for autonomous limit protection. For each functional module, this thesis guides the control system designer through the design choices and information interfaces among the modules. Limit cue module design choices include type of prediction, prediction mechanism, method of critical control calculation, and type of limit cue. Special consideration is given to the nature of the limit, particularly the level of knowledge about it, and the ramifications for limit protection design, especially with respect to intelligent control methods such as fuzzy inference systems and neural networks.

Jeram, Geoffrey J.↗