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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Factors Influencing Pitot Probe Centerline Displacement in a Turbulent Supersonic Boundary Layer

When a total pressure probe is used for measuring flows with transverse total pressure gradients, a displacement of the effective center of the probe is observed (designated Delta). While this phenomenon is well documented in incompressible flow and supersonic laminar flow, there is insufficient information concerning supersonic turbulent flow. In this study, three NASA Lewis Research Center Supersonic Wind Tunnels (SWT's) were used to investigate pitot probe centerline displacement in supersonic turbulent boundary layers. The relationship between test conditions and pitot probe centerline displacement error was to be determined. For this investigation, ten circular probes with diameter-to-boundary layer ratios (D/delta) ranging from 0.015 to 0.256 were tested in the 10 ft x 10 ft SWT, the 15 cm x 15 cm SWT, and the 1 ft x 1 ft SWT. Reynolds numbers of 4.27 x 10(exp 6)/m, 6.00 x 10(exp 6)/in, 10.33 x 10(exp 6)/in, and 16.9 x 10(exp 6)/m were tested at nominal Mach numbers of 2.0 and 2.5. Boundary layer thicknesses for the three tunnels were approximately 200 mm, 13 mm, and 30 mm, respectively. Initial results indicate that boundary layer thickness, delta, and probe diameter, D/delta play a minimal role in pitot probe centerline offset error, Delta/D. It appears that the Mach gradient, dM/dy, is an important factor, though the exact relationship has not yet been determined. More data is needed to fill the map before a conclusion can be drawn with any certainty. This research provides valuable supersonic, turbulent boundary layer data from three supersonic wind tunnels with three very different boundary layers. It will prove a valuable stepping stone for future research into the factors influencing pitot probe centerline offset error.

Grosser, Wendy I.↗
DOE OSTI2024

Measure this, not that: Optimizing the cost and model-based information content of measurements

Model-based design of experiments (MBDoE) is a powerful framework for selecting and calibrating science-based mathematical models from data. Here, this work extends popular MBDoE workflows by proposing a convex mixed integer (non)linear programming (MINLP) to optimize the selection of measurements. The solver MindtPy is modified to support calculating the D-optimality objective and its gradient via an external package, scipy, using the grey-box module in Pyomo. The new approach is demonstrated in two case studies: estimating highly correlated kinetics from a batch reactor and estimating transport parameters in a large-scale rotary packed bed for CO 2 capture. Both case studies show how examining the Pareto optimal trade-offs between information content measured by A- and D-optimality versus measurement budget offers practical guidance for selecting measurements for scientific experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

GradeIT (Road Grade Inference Tool)

The National Renewable Energy Laboratory (NREL) has developed the Road Grade Inference Tool, "GradeIT". This tool is a modular Python package the leverages the United States Geological Survey’s (USGS) 1/3 arc-second Digital Elevation Model (DEM), an open and free public dataset. Roadway gradient (slope) has a strong influence on vehicle energy consumption behavior and longitudinal dynamics. Therefore, any tools, models, or analyses that consider vehicle energy consumption or driving profiles is incomplete without accurate elevation and grade information. Despite the acute need for this data, it is rarely collected alongside GPS (latitude and longitude) data, and tools to post-process GPS data to append elevation and grade are difficult to come by. GradeIT satisfies this significant need in the research community. Utilization of the USGS DEM makes the underlying data available to any potential user and ensures continuous data anywhere in the continental United States. The USGS DEM is a great resource; however, in order to be useful for automotive and traffic engineering applications, significant interpolation and filtering is required to achieve an accurate representation of gradient on the roadway. GradeIT employs a two-dimensional interpolation to approximate elevation at a point on the road from the nearest nodes in the DEM. Then, GradeIT applies multiple filtering techniques to smooth the elevation profile to a realistic road topology. Finally, road grade is derived from the elevation profile and returned as the primary output.

Holden, Jacob↗
DOE OSTI2023

Colloidal State Machines as Smart Tracers for Chemical Reactor Analysis

A widely utilized tool in reactor analysis is passive tracers that report the residence time distribution, allowing estimation of the conversion and other properties of the system. Recently, advances in microrobotics have introduced powered and functional entities with sizes comparable to some traditional tracers. This has motivated the concept of Smart Tracers that could record the local chemical concentrations, temperature, or other conditions as they progress through reactors. Herein, the design constraints and advantages of Smart Tracers by simulating their operation in a laminar flow reactor model conducting chemical reactions of various orders are analyzed. It is noted that far fewer particles are necessary to completely map even the most complex concentration gradients compared with their conventional counterparts. Design criteria explored herein include sampling frequency, memory storage capacity, and ensemble number necessary to achieve the required accuracy to inform a reactor model. Cases of severe particle diffusion and sensor noise appear to bind the functional upper limit of such probes and require consideration for future design. The results of the study provide a starting framework for applying the new technology of microrobotics to the broad and impactful set of problems classified as chemical reactor analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Stellar migration and chemical enrichment in the milky way disc: a hybrid model

ABSTRACT We develop a hybrid model of galactic chemical evolution that combines a multiring computation of chemical enrichment with a prescription for stellar migration and the vertical distribution of stellar populations informed by a cosmological hydrodynamic disc galaxy simulation. Our fiducial model adopts empirically motivated forms of the star formation law and star formation history, with a gradient in outflow mass loading tuned to reproduce the observed metallicity gradient. With this approach, the model reproduces many of the striking qualitative features of the Milky Way disc’s abundance structure: (i) the dependence of the [O/Fe]–[Fe/H] distribution on radius Rgal and mid-plane distance |z|; (ii) the changing shapes of the [O/H] and [Fe/H] distributions with Rgal and |z|; (iii) a broad distribution of [O/Fe] at sub-solar metallicity and changes in the [O/Fe] distribution with Rgal, |z|, and [Fe/H]; (iv) a tight correlation between [O/Fe] and stellar age for [O/Fe] > 0.1; (v) a population of young and intermediate-age α-enhanced stars caused by migration-induced variability in the Type Ia supernova rate; (vi) non-monotonic age–[O/H] and age–[Fe/H] relations, with large scatter and a median age of ∼4 Gyr near solar metallicity. Observationally motivated models with an enhanced star formation rate ∼2 Gyr ago improve agreement with the observed age–[Fe/H] and age–[O/H] relations, but worsen agreement with the observed age–[O/Fe] relation. None of our models predict an [O/Fe] distribution with the distinct bimodality seen in the observations, suggesting that more dramatic evolutionary pathways are required. All code and tables used for our models are publicly available through the Versatile Integrator for Chemical Evolution (VICE; https://pypi.org/project/vice).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Preliminary Primary System Thermal Fluids Analysis of a Horizontal Compact HTGR

The Horizontal Compact High Temperature Gas Reactor (HC-HTGR) is being designed by a multi-disciplinary team of nuclear, mechanical, and structural engineers, under the support of a DOE-NE Advanced Reactor Demonstration Program’s Advanced Reactor Concepts-20 (ARC-20) award. The objective of this ARC-20 project is to deliver a conceptual design for the proposed HC-HTGR in 3 years and support its commercialization as a safe, low-cost HTGR. Argonne National Laboratory (Argonne) is collaborating on the thermal hydraulic design and analysis of the HC-HTGR reactor pressure vessel internals. The scope of this work includes ensuring the reactor is able to maintain maximum core temperatures below designated safety thresholds during normal operation, shutdown, and accident conditions. This report documents the preliminary thermal hydraulic analysis of the HC-HTGR core design performed with a 1D fluid-3D solid coupled model built using the System Analysis Module (SAM). This assembly level model was utilized to inform the core assembly design, predict the temperature distribution in the peak power assembly including the peak fuel temperature, coolant channel outlet temperatures, and graphite temperature gradients. A key result of this analysis was the determination that the peak fuel temperature remains below the safety threshold of 1250°C. Additionally, this model was used to assess the assembly coolant channel and bypass flow mass flow rate distribution. Following the assembly level analysis, attention turned to the development of a full core reduced order model to be used to predict the core wide coolant flow distribution and to model certain operational and accidental transients.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1985

Improved satellite retrievals and mesoscale moisture variability

The investigations over the past year have led to the finalization of results from the study of mesoscale atmospheric parameters derived from the visible infrared spin scan radiometer (VISSR) atmospheric sounder (VAS). Soundings from several retrieval techniques for the 6 to 7 March 1982 special observation period were evaluated for mesoscale accuracy. Specific results and comparisons between data from a regression and two physical retrieval schemes are forthcoming in the Journal of Atmospheric and Oceanic Technology (JTech) this year. A generalization of these results is outlined. Large temperature and moisture biases existed in the VAS derived profiles, particularly in layers near inversions. Standard errors ranged from 1 to 3 C and 3 to 6 C for temperature and dewpoint, respectively. Parameters derived from VAS soundings (geopotential height, thickness, and precipitable water) often reflected the temperature and moisture profile biases. VAS derived mesoscale gradients were often weaker than those from corresponding rawinsonde data. Little improvement was made in defining the vertical structure of the atmosphere over the first guess information. VAS soundings were able to improve in the horizontal structure due to the high spatial resolution of the radiance data.

Jedlovec, G. J.↗
NASA NTRS2005

[Stellar Occultation Studies of Small Bodies in the Outer Solar System: Accomplishments, Status, and Plans]

Bodies residing in the outer solar system exhibit unique physical processes, and some of the lessons learned from them can be applied to understanding what occurred in the outer solar system during its formation and early evolution. Pluto, the largest known Kuiper Belt object (KBO), and its near twin Triton--an ex-KBO that has been captured by Neptune--have nitrogen atmospheres that are in vapor-pressure equilibrium with surface ice. These atmospheres are most sensitively probed from Earth by the technique of Stellar occultations, which can provide the temperature and pressure profiles of these atmospheres at a spatial resolution of a few kilometers. Recent results from occultations show that the surface pressure of Triton's atmosphere has been increasing and that the shape of the atmosphere deviates from its expected spherical figure. With the occultation technique we can also learn the sizes of smaller bodies that have formed in the outer solar system: Charon, the Centaurs, and KBOs. Our proposed program involves identifying occultation candidates, predicting occultations, observing occultations, analysis of the data, and synthesis of the occultation results with other data. The main goals for our proposed work are to (i) further observe occultations by Triton with the objectives of understanding its pressure changes, distortion, and enigmatic thermal structure (ii) determine whether the abrupt drop in Pluto's stellar occultation light curve is caused by a sharp thermal gradient near its surface or by atmospheric haze, (iii) further observations to characterize the potential collapse of Pluto's atmosphere as it recedes from the sun (information that should be of interest to the Pluto-Kuiper Express), ( iv ) determine Charon's radius more accurately than can be done with the mutual events to derive a better estimate of Charon's density, and ( v ) directly determine the size (and albedo) of Centaurs with the goal of more accurately estimating the sizes of KBOS.

Elliott, James↗
NASA NTRS2022

A Comprehensive Machine Learning Study to Classify Precipitation Type over Land from Global Precipitation Measurement Microwave Imager (GPM-GMI) Measurements

Precipitation type is a key parameter used for better retrieval of precipitation characteristics as well as to understand the cloud–convection–precipitation coupling processes. Ice crystals and water droplets inherently exhibit different characteristics in different precipitation regimes (e.g., convection, stratiform), which reflect on satellite remote sensing measurements that help us distinguish them. The Global Precipitation Measurement (GPM) Core Observatory’s microwave imager (GMI) and dual-frequency precipitation radar (DPR) together provide ample information on global precipitation characteristics. As an active sensor, the DPR provides an accurate precipitation type assignment, while passive sensors such as the GMI are traditionally only used for empirical understanding of precipitation regimes. Using collocated precipitation type flags from the DPR as the “truth”, this paper employs machine learning (ML) models to train and test the predictability and accuracy of using passive GMI-only observations together with ancillary information from a reanalysis and GMI surface emissivity retrieval products. Out of six ML models, four simple ones (support vector machine, neural network, random forest, and gradient boosting) and the 1-D convolutional neural network (CNN) model are identified to produce 90–94% prediction accuracy globally for five types of precipitation (convective, stratiform, mixture, no precipitation, and other precipitation), which is much more robust than previous similar effort. One novelty of this work is to introduce data augmentation (subsampling and bootstrapping) to handle extremely unbalanced samples in each category. A careful evaluation of the impact matrices demonstrates that the polarization difference (PD), brightness temperature (Tc) and surface emissivity at high-frequency channels dominate the decision process, which is consistent with the physical understanding of polarized microwave radiative transfer over different surface types, as well as in snow and liquid clouds with different microphysical properties. Furthermore, the view-angle dependency artifact that the DPR’s precipitation flag bears with does not propagate into the conical-viewing GMI retrievals. This work provides a new and promising way for future physics-based ML retrieval algorithm development.

machine learning/artificial intelligence↗
DOE OSTI2021

Steep sulfur gradient in CZTSSe solar cells by H 2 S-assisted rapid surface sulfurization

Sulfur/selenium grading is a widely used optimization strategy in kesterite thin-film solar cells to obtain a bandgap-graded absorber material and to optimize optical and electrical properties of the solar-cell device. In this work, we present a novel approach to introduce a [S]/([S] + [Se]) grading for Cu 2 ZnSn(S,Se) 4 solar cells. In contrast to commonly used methods with slow process dynamics, the presented approach aims to create a fast sulfurization reaction on the surface of pure selenide kesterite absorbers by using highly reactive H 2 S gas and high sulfurization temperatures in a rapid flash-type process. With a combination of X-ray photoelectron spectroscopy, X-ray emission spectroscopy, Raman spectroscopy, and Raman-shallow angle cross sections spectroscopy, we gain depth-varied information on the [S]/([S] + [Se]) ratio and discuss the impact of different process parameter variations on the material and device properties. The results demonstrate the potential of the developed process to generate a steep gradient of sulfur that is confined mainly to the surface region of the absorber film.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Colorado Elevation Gradient Snowmelt Manipulation Plant Phenology 2017-2018

This dataset includes observations of plant phenology at five locations along an elevation gradient in Crested Butte, Colorado. Observations occurred over the years 2017 and 2018. Observations taken in 2018 are associated with an experimental early snowmelt manipulation. The file PhenologyData_complete.txt contains raw data of phenology observations for each year, at each site, for each species within 1mX1m subplots. The file Phenology Data Package.docx contains information about sites, plots, and plant phenophases. These observations were taken to assess the temporal impact of early snowmelt perturbations on plant growth in the East River Valley. These data can be used to inform when and where plants may be using water resources throughout the season and how the phenology of plant communities in the watershed may respond to early snowmelt.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2015

Design of a Thermal Precipitator for the Characterization of Smoke Particles from Common Spacecraft Materials

A thermal precipitator (TP) was designed to collect smoke aerosol particles for microscopic analysis in fire characterization research. Information on particle morphology, size and agglomerate structure obtained from these tests supplements additional aerosol data collected. Modeling of the thermal precipitator throughout the design process was performed with the COMSOL Multiphysics finite element software package, including the Eulerian flow field and thermal gradients in the fluid. The COMSOL Particle Tracing Module was subsequently used to determine particle deposition. Modeling provided optimized design parameters such as geometry, flow rate and temperatures. The thermal precipitator was built and testing verified the performance of the first iteration of the device. The thermal precipitator was successfully operated and provided quality particle samples for microscopic analysis, which furthered the body of knowledge on smoke particulates. This information is a key element of smoke characterization and will be useful for future spacecraft fire detection research.

Smoke↗
NASA NTRS2014

Mass Dependency of Isotope Fractionation of Gases Under Thermal Gradient and Its Possible Implications for Planetary Atmosphere Escaping Process

Physical processes that unmix elements/isotopes of gas molecules involve phase changes, diffusion (chemical or thermal), effusion and gravitational settling. Some of those play significant roles for the evolution of chemical and isotopic compositions of gases in planetary bodies which lead to better understanding of surface paleoclimatic conditions, e.g. gas bubbles in Antarctic ice, and planetary evolution, e.g. the solar-wind erosion induced gas escaping from exosphere on terrestrial planets.. A mass dependent relationship is always expected for the kinetic isotope fractionations during these simple physical processes, according to the kinetic theory of gases by Chapman, Enskog and others [3-5]. For O-bearing (O16, -O17, -O18) molecules the alpha O-17/ alpha O-18 is expected at 0.5 to 0.515, and for S-bearing (S32,-S33. -S34, -S36) molecules, the alpha S-33/ αlpha S-34 is expected at 0.5 to 0.508, where alpha is the isotope fractionation factor associated with unmixing processes. Thus, one isotope pair is generally proxied to yield all the information for the physical history of the gases. However, we recently] reported the violation of mass law for isotope fractionation among isotope pairs of multiple isotope system during gas diffusion or convection under thermal gradient (Thermal Gradient Induced Non-Mass Dependent effect, TGI-NMD). The mechanism(s) that is responsible to such striking observation remains unanswered. In our past studies, we investigated polyatomic molecules, O2 and SF6, and we suggested that nuclear spin effect could be responsible to the observed NMD effect in a way of changing diffusion coefficients of certain molecules, owing to the fact of negligible delta S-36 anomaly for SF6.. On the other hand, our results also showed that for both diffusion and convection under thermal gradient, this NMD effect is increased by lower gas pressure, bigger temperature gradient and lower average temperature, which indicate that the nuclear spin effect may not be the significant contributor as the energies involved in the hyperfine effect are much smaller than those with molecular collisions, especially under convective conditions.

Sun, Tao↗
DOE OSTI2023

Ultrasonic measurement of temperature distributions in extreme environments: Electrical power plants testing in utility-scale steam generators

Thermal heterogeneities within energy conversion and storage, material processing, nuclear processes, aerospace, and military applications are often inaccessible to characterization by insertion sensors. When sensor deployment is possible, conventional pointwise temperature probes quickly degrade when inserted into harsh environments typical of such processes. We developed spatially-resolved ultrasonic thermometry to noninvasively measure the spatial distributions of thermal properties in such applications, even when sizable thermal gradients are present. Our method divides the path of ultrasonic propagation into segments bound by echogenic features, which create echoes in pulse-echo mode, encoding the information about interior temperature distributions. We use the acquired ultrasonic responses to estimate the internal temperature distributions by solving an inverse problem or concatenating segmental estimates. This work describes the implementation and industrial testing of the developed method at a coal-fired electrical power generation plant. We inserted an echogenically segmented Inconel 625 waveguide into the combustion zone of the utility-scale boiler and continuously acquired ultrasonic data while keeping sensitive components away from the damaging combustion environment. The accuracy of the time-dependent temperature distributions reconstructed from the ultrasonic measurements was comparable to that of thermocouples. The resiliency of ultrasonic thermometry to harsh combustion conditions was far superior to conventional insertion sensors. The measurements obtained during plant operation captured daily steam generation cycles in response to changing customer demand and intermittent contributions of renewable power sources to the power grid. These measurements have revealed new insights into the relationship between the dynamic power generation load and the conditions inside the steam generator. As a result, the successful industrial testing of spatially-resolved ultrasonic thermometry in solids indicates that the developed technology has matured to become an attractive alternative to conventional sensing in solving challenging problems of long-term thermal characterizations in extreme environments.

42 ENGINEERING↗
NASA NTRS1981

Determination of atmospheric properties for STS-1 aerothermodynamic investigations

A procedure for determining an approximation to the freestream atmospheric properties along the Shuttle entry trajectory is presented. Meteorological data as input is obtained by rawinsondes from surface to 70 km, and meteorological spheres from 60-90 km, launched from Hawaii and California. The Langley Atmospheric Information Retrieval System (LAIRS) developed to approximate the atmospheric freestream properties along the flight path, is outlined, noting temperature and wind data are interpolated in altitude, while gradients and diurnal and semidiurnal coefficients are taken from the COSPAR reference atmosphere. The data are input to a model to project temperature profiles for the Shuttle descent, and the input atmospheric parameters are listed. Efforts are continuing in order to correct discrepancies in the generated profiles for regions below 3 km.

Price, J. M.↗
NASA NTRS1983

Environmental data display

Methods for using a combination of computer-generated color graphics and image processing techniques to display a large data base of environment information are described. The data source can be either field data or mathematical models, reduced to summary statistics that characterize the data field as a whole. Sharp gradients are plotted into contour plots, which can also feature shades, degree of brightness, and saturation levels for fine-tuning the image. The basic concepts of digital image processing are reviewed, including location of the pixels, intensity mapping operations, pseudocolor enhancements, neighborhood averaging, and smoothing. Sample applications are presented in terms of emissions and air quality distributions over the south coast air basin of southern California.

Hussey, K. J.↗
NASA NTRS1987

Differential surface models for tactile perception of shape and on-line tracking of features

Tactile perception of shape involves an on-line controller and a shape perceptor. The purpose of the on-line controller is to maintain gliding or rolling contact with the surface, and collect information, or track specific features of the surface such as edges of a certain sharpness. The shape perceptor uses the information to perceive, estimate the parameters of, or recognize the shape. The differential surface model depends on the information collected and on the a priori information known about the robot and its physical parameters. These differential models are certain functionals that are projections of the dynamics of the robot onto the surface gradient or onto the tangent plane. A number of differential properties may be directly measured from present day tactile sensors. Others may have to be indirectly computed from measurements. Others may constitute design objectives for distributed tactile sensors of the future. A parameterization of the surface leads to linear and nonlinear sequential parameter estimation techniques for identification of the surface. Many interesting compromises between measurement and computation are possible.

Hemami, H.↗
NASA NTRS1992

A modified Eddington-Barbier relation in highly coherent resonance-line wings

It is shown that resonance-line wings are just as useful in inferring plane-parallel stellar chromospheric S sub L distributions as complete redistribution (CRD) profiles. Although coherent scattering effects at a given frequency tend to average depth-dependent parameters over a larger volume than in CRD, this effect can be offset by simply looking closer to line center, where the same depth-dependent information exists as in CRD, albeit somewhat more compressed in frequency space. For resonance lines with high excitation energies such as Ly-alpha, steep Planck function gradients can invalidate the modified Eddington-Barbier approach given, but this problem also exists in CRD.

Gayley, K. G.↗