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At least 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Space‐Based Observations for Understanding Changes in the Arctic‐Boreal Zone

A recent, interdisciplinary survey of more than 40 international remote sensing experts reviewed the strengths and limitations of current space-based observational capabilities of the Arctic Boreal Zone (ABZ) and made recommendations for improving upon these current capabilities (Duncan et al., 2019). General recommendations focused on the complementarity of sub-orbital and satellite observations, the need for measurement continuity, and the importance of stakeholder engagement. The development of a comprehensive and robust sub-orbital portion of an ABZ observing network can act to fill some temporal gaps in satellite coverage, provide detail unobtainable from space, and is necessary for validation and interpretation of satellite data. A priority across all types of observations is the continuation, enhancement, and/or creation of long-term, multi-satellite, climate-quality, and self-consistent data records of ABZ components, such as surface temperature, energy fluxes, or sea ice extent and volume, for improved determination of trends. Long-term passive satellite observations currently represent the only feasible option for monitoring change of the ABZ at broad spatial scales required to address pressing science challenges. Active sensors are particularly attractive for the ABZ as they do not depend on reflected sunlight and so join passive microwave sensors in having a significant advantage over passive visible and infrared sensors in the low-light conditions that are typical of the ABZ for several months of the year. Application of consistent retrieval algorithms to multiple data sets, as well as careful characterization of satellite instruments and their temporal evolution, helps to ensure data quality and consistency. Among the needs ranked as “Most Important” are those associated with gaining a process-based understanding of the ABZ carbon cycle and hydrologic cycle (which includes sea level rise) as they have the potential to affect a large portion of Earth’s population.

Remote sensing↗
NASA NTRS1999

Low Speed Analysis of Mission Adaptive Flaps on a High Speed Civil Transport Configuration

Thin-layer Navier-Stokes analyses were done on a high speed civil transport configuration with mission adaptive leading-edge flaps. The flow conditions simulated were Mach = 0.22 and Reynolds number of 4.27 million for angles-of-attack ranging from 0 to 18 degrees. Two turbulence closure models were used. Analyses were done exclusively with the Baldwin-Lomax turbulence model at low angle-of-attack conditions. At high angles-of-attack where considerable flow separation and vortices occurred the Spalart-Allmaras turbulence model was also considered. The effects of flow transition were studied. Predicted aerodynamic forces, moment, and pressure are compared to experimental data obtained in the 14- by 22-Foot Subsonic Tunnel at NASA Langley. The forces and moments correlated well with experimental data in terms of trends. Drag and pitching moment were consistently underpredicted. Predicted surface pressures compared well with experiment at low angles-of-attack. Above 10 angle-of-attack the pressure comparisons were not as favorable. The two turbulent models affected the pressures on the flap considerably and neither produced correct results at the high angles-of-attack.

Lessard, Victor R.↗
NASA NTRS1996

Measurements and Modeling of Soot Formation and Radiation in Microgravity Jet Diffusion Flames

This is a computational and experimental study for soot formation and radiative heat transfer in jet diffusion flames under normal gravity (1-g) and microgravity (0-g) conditions. Instantaneous soot volume fraction maps are measured using a full-field imaging absorption technique developed by the authors. A compact, self-contained drop rig is used for microgravity experiments in the 2.2-second drop tower facility at NASA Lewis Research Center. On modeling, we have coupled flame structure and soot formation models with detailed radiation transfer calculations. Favre-averaged boundary layer equations with a k-e-g turbulence model are used to predict the flow field, and a conserved scalar approach with an assumed Beta-pdf are used to predict gaseous species mole fraction. Scalar transport equations are used to describe soot volume fraction and number density distributions, with formation and oxidation terms modeled by one-step rate equations and thermophoretic effects included. An energy equation is included to couple flame structure and radiation analyses through iterations, neglecting turbulence-radiation interactions. The YIX solution for a finite cylindrical enclosure is used for radiative heat transfer calculations. The spectral absorption coefficient for soot aggregates is calculated from the Rayleigh solution using complex refractive index data from a Drude- Lorentz model. The exponential-wide-band model is used to calculate the spectral absorption coefficient for H20 and C02. It is shown that when compared to results from true spectral integration, the Rosseland mean absorption coefficient can provide reasonably accurate predictions for the type of flames studied. The soot formation model proposed by Moss, Syed, and Stewart seems to produce better fits to experimental data and more physically sound than the simpler model by Khan et al. Predicted soot volume fraction and temperature results agree well with published data for a normal gravity co-flow laminar flames and turbulent jet flames. Predicted soot volume fraction results also agree with our data for 1-g and 0-g laminar jet names as well as 1-g turbulent jet flames.

Ku, Jerry C.↗
NASA NTRS2001

Partial Pressures of Te2 and Thermodynamic Properties of Ga-Te System

The partial pressures of Te2 in equilibrium with Ga(1-x)Te(x) samples were measured by optical absorption technique from 450 to 1100 C for compositions, x, between 0.333 and 0.612. To establish the relationship between the partial pressure of Te, and the measured optical absorbance, the calibration runs of a pure Te sample were also conducted to determine the Beer's Law constants. The partial pressures of Te2 in equilibrium with the GaTe(s) and Ga2Te3(s)compounds, or the so-called three-phase curves, were established. These partial pressure data imply the existence of the Ga3Te4(s) compound. From the partial pressures of Te2 over the Ga-Te melts, partial molar enthalpy and entropy of mixing for Te were derived and they agree reasonable well with the published data. The activities of Te in the Ga-Te melts were also derived from the measured partial pressures of Te2. These data agree well with most of the previous results. The possible reason for the high activity of Te measured for x less than 0.60 is discussed.

Su, Ching-Hua↗
DOE OSTI2023

Utah FORGE: Optimization of a Plug-and-Perf Stimulation (Fervo Energy)

Information around the plug-and-perf treatment design at Utah FORGE by Fervo Energy. Objective and Purpose: - Develop a multistage hydraulic stimulation approach designed specifically to target the top three factors that control the technical and commercial viability of an EGS system: i) Achieving sufficient injectivity to support high cross-well flow rates ii) Distributing flow evenly across the wellbore and reservoir to maximize heat mining efficiency, ensure sustained heat transfer, and mitigate thermal breakthrough iii) Overcoming the effects of stress heterogeneity, stress shadowing, and variations in natural fracture properties during the stimulation treatment, leading to a more predictable stimulated reservoir volume and offset well placement - The following activities will be performed: i) Design, plan, and execute a multistage plug-and-perf stimulation treatment at a Fervo site with data acquisition and well testing activities aimed at addressing key technical aspects of the issues above ii) Perform data processing and interpretation of field results to translate the results form the Fervo site to a site-specific design at the Utah FORGE site iii) Design, plan, and execute a multistage plug-and-perf stimulation treatment design at the Utah FORGE site Methods and Approach: - Design a detailed data acquisition plan to maximize learning around: i) DFIT testing ii) Petrophysical logging, image logging iii) Permanent DAS/DTS fiber optic monitoring iv) Deep borehole microseismic monitoring v) Shallow borehole induced seismicity monitoring vi) Injection/production testing (RTA analysis, tracer testing) vii) Integrated numerical modeling and production forecasting

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

AI-Batt (Autonomous Identification of Battery Life Models) [SWR 21-36]

Autonomous Identification of Battery Life Models (AI-Batt) AI-Batt is a MATLAB code base for developing lifetime models for batteries from accelerated aging data. The code base provides many functions for processing, visualizing, and modeling battery aging data, making the data processing, exploration, and modeling workflow substantially faster. These tools are tailored for working with battery aging data sets, which usually consist of many separate time-series for each cell, with many test conditions and possible replicates at each condition, which makes it difficult to simply process or visualize the data set. Complex modeling tasks, such as cross-validation, sensitivity analysis, and uncertainty quantification have been implemented to enable thorough statistical investigation of model predictions. Additionally, several machine-learning algorithms are implemented to autonomously identify suitable models via symbolic regression. Data processing functions automatically cast data from the struct data type, which is commonly used to store experimental data, but is not an acceptable input for most algorithms, to the table data type, which can be easily used as input to any optimization algorithm. Also, the data can be separated into time-invariant and time-variant data tables, which is helpful for exploring the data set as well as developing separate models for time-variant and time-invariant aging mechanisms. For example, in aging tests with constant temperature, temperature is a time-invariant experimental condition. Visualization tools enable plotting of data, model fits, and model simulations possible with single-line function calls, empowering data exploration of complex data sets with both time-varying and time-invariant trends. Plots can be automatically generated for the whole data set, or separated by data group (groups of test replicates) or individual data series. Data points or data series can be automatically colored by the value of a variable with a variety of color maps, and model predictions can also be colored by the value of a fit statistic. Comparisons between data sets and the predictions/simulations of different models on the same data set can be easily plotted as well. Distributions of parameter values from bootstrap resampling can be plotted to visualize the reliability of parameter estimation, or determine any correlations between parameters. Modeling tools handle the complex task of creating and parsing symbolic equations for modeling battery lifetime. Equations are parsed to grab relevant data variables, parameter values, or specified sub-models for input into optimization, evaluation, or simulation functions. Models can be optimized locally (one set of parameters for each data series), bi-level (some parameters shared across the data set), or globally (single set of parameters for all data). Functions implementing symbolic regression algorithms help users to discover effective model equations, even in poorly sampled, high-dimensional data.

Smith, Kandler↗
DOE OSTI2021

Utah FORGE Well 16A(78)-32 Simplified Discrete Fracture Network Data

The FORGE team is making these fracture models available to researchers wanting a set of natural fractures in the FORGE reservoir for use in their own modeling work. They have been used to predict stimulation distances during hydraulic stimulation at the open toe section of well 16A(78)-32. This is a simplified DFN (discrete fracture network) dataset, that was generated using FracMan, for Utah FORGE well 16A(78)-32. A short, well-illustrated, report describing the data is also included in the provided archive file.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Automatic microseismic event picking via unsupervised machine learning

SUMMARY Effective and efficient arrival picking plays an important role in microseismic and earthquake data processing and imaging. Widely used short-term-average long-term-average ratio (STA/LTA) based arrival picking algorithms suffer from the sensitivity to moderate-to-strong random ambient noise. To make the state-of-the-art arrival picking approaches effective, microseismic data need to be first pre-processed, for example, removing sufficient amount of noise, and second analysed by arrival pickers. To conquer the noise issue in arrival picking for weak microseismic or earthquake event, I leverage the machine learning techniques to help recognizing seismic waveforms in microseismic or earthquake data. Because of the dependency of supervised machine learning algorithm on large volume of well-designed training data, I utilize an unsupervised machine learning algorithm to help cluster the time samples into two groups, that is, waveform points and non-waveform points. The fuzzy clustering algorithm has been demonstrated to be effective for such purpose. A group of synthetic, real microseismic and earthquake data sets with different levels of complexity show that the proposed method is much more robust than the state-of-the-art STA/LTA method in picking microseismic events, even in the case of moderately strong background noise.

Chen, Yangkang↗
DOE OSTI2023

Multiple incommensurate magnetic states in the kagome antiferromagnet Na 2 Mn 3 Cl 8

The kagome lattice can host exotic magnetic phases arising from frustrated and competing magnetic interactions. However, relatively few insulating kagome materials exhibit incommensurate magnetic ordering. Here, we present a study of the magnetic structures and interactions of antiferromagnetic Na 2 Mn 3 Cl 8 with an undistorted Mn 2+ kagome network. Using neutron-diffraction and bulk magnetic measurements, we show that Na 2 Mn 3 Cl 8 hosts two different incommensurate magnetic states, which develop at T N1 = 1.6 K and T N2 = 0.6 K. Magnetic Rietveld refinements indicate magnetic propagation vectors of the form q=(q x , q y , $\frac{3}{2}$), and our neutron-diffraction data can be well described by cycloidal magnetic structures. By optimizing exchange parameters against magnetic diffuse-scattering data, we show that the spin Hamiltonian contains ferromagnetic nearest-neighbor and antiferromagnetic third-neighbor Heisenberg interactions, with a significant contribution from long-ranged dipolar coupling. This experimentally determined interaction model is compared with density-functional-theory simulations. Using classical Monte Carlo simulations, we show that these competing interactions explain the experimental observation of multiple incommensurate magnetic phases and may stabilize multi-q states. Here, our results expand the known range of magnetic behavior on the kagome lattice.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Geostatistical Mapping of Salinity Conditioned on Borehole Logs, Montebello Oil Field, California

We present a geostatistics-based stochastic salinity estimation framework for the Montebello Oil Field that capitalizes on available total dissolved solids (TDS) data from groundwater samples as well as electrical resistivity (ER) data from borehole logging. Data from TDS samples (n = 4924) was coded into an indicator framework based on falling below four selected thresholds (500, 1000, 3000, and 10,000 mg/L). Collocated TDS-ER data from the surrounding groundwater basin were then employed to produce a kernel density estimator to establish conditional probabilities for ER data (n = 8 boreholes) falling below the selected TDS thresholds within the Montebello Oil Field area. Directional variograms were estimated from these indicator coded data, and 500 TDS realizations from conditional indicator simulation were generated for the subsurface region above the Montebello Oil Field reservoir. Simulations were summarized as 3D maps of median TDS, most likely salinity class, and probability for exceeding each of the specified TDS thresholds. Results suggested TDS was below 500 mg/L in most of the study area, with a trend toward higher values (500 to 1000 mg/L) to the southwest; consistent with the average regional groundwater flow direction. Discrete localized zones of TDS greater than 1000 mg/L were observed, with one of these zones in the greater than 10,000 mg/L range; however, these areas were not prevalent. The probabilistic approach used here is adaptable and is readily modified to include additional data and types and can be employed in time-lapse salinity modeling through Bayesian updating.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1975

NASA Earth Resources Survey Symposium. Volume 2-A: Special session presentations. Plenary summaries

Practical application of earth resources survey data is considered. The utilization and results of data from NASA programs involving LANDSAT, the Skylab Earth Resources Experiment Package, and aircraft, as well as other data acquisition programs are included. User services and requirements and applications in land use, agriculture, coastal zone management, and geology are among the topics covered. For Vol. 1A, see N76-17469.

Source record↗
NASA NTRS1976

Multivariate normality

Sets of experimentally determined or routinely observed data provide information about the past, present and, hopefully, future sets of similarly produced data. An infinite set of statistical models exists which may be used to describe the data sets. The normal distribution is one model. If it serves at all, it serves well. If a data set, or a transformation of the set, representative of a larger population can be described by the normal distribution, then valid statistical inferences can be drawn. There are several tests which may be applied to a data set to determine whether the univariate normal model adequately describes the set. The chi-square test based on Pearson's work in the late nineteenth and early twentieth centuries is often used. Like all tests, it has some weaknesses which are discussed in elementary texts. Extension of the chi-square test to the multivariate normal model is provided. Tables and graphs permit easier application of the test in the higher dimensions. Several examples, using recorded data, illustrate the procedures. Tests of maximum absolute differences, mean sum of squares of residuals, runs and changes of sign are included in these tests. Dimensions one through five with selected sample sizes 11 to 101 are used to illustrate the statistical tests developed.

Crutcher, H. L.↗
NASA NTRS1985

Global scale diagnoses of FGGE data

Descriptive global scale diagnoses of the First Global Atmospheric Research Experiment SOP-1 analyses were made and compared against controlled, real data integrations of the Goddard Laboratory of Atmospheric Science (GLAS) general circulation model (GCM) as well as other data sets. The effects of critical latitudes were studied; the influence of tropical wind data and latent heating upon the GLAS GCM was diagnosed; planetary wave structure on various time scales from the diurnal to the monthly was studied; and the GLAS analyses were compared with other analyses. Short term controlled GLAS GCM integrations show that: (1) the inclusion of tropical wind data in real data integrations has an important influence in the mid-latitude prediction in both hemispheres; and (2) the tropical divergent wind reacts almost immediately to alteration of the tropical latent heating. The presence or absence of zonally averaged easterlies depends strongly upon the presence of tropical latent heating.

Paegle, J.↗
NASA NTRS1985

A review of dynamic inflow and its effect on experimental correlations

A review is given of the relationship between experimental data and the development of modern dynamic-inflow theory. Some of the most interesting data, first presented 10 years ago at the Dynamic Specialist's Meeting, is now reviewed in light of the newer theories. These pure blade-flapping data correlate very well with analyses that include the new dynamic inflow theory, thus verifying the theory. Experimental data are also presented for damping with coupled inplane and body motions. Although inclusion of dynamic inflow is often required to correlate this coupled data, the data cannot be used to verify any particular dynamic inflow theory due to the uncertainties in modeling the inplane degree of freedom. For verification, pure flapping is required. However, the coupled data do show that inflow is often important in such computations.

Gaonkar, G. H.↗
NASA NTRS1987

Space Network mission support in the Space Station era

The Mission Model for user support and NASA's plans to provide the necessary support resources are discussed. Particular attention is given to considerations which imply operation of up to two additional Tracking and Data Relay Satellites (TDRS), as well as potential interoperability with data relay satellite systems planned for launch in the mid-1990s by the ESA and by the NASDA of Japan. NASA activities related to the development of an Advanced TDRS system for the support of missions flying in the 21st century are also discussed.

Harris, David W.↗
NASA NTRS1990

Interpolation schemes in the control of systems with unknown dynamics

Time-delay control for systems with unknown dynamics involves estimations. In its present form, these estimations include not only the interpolation of a time-varying function but also its derivative between data points. Presently, the control law is reformulated, taking into account the computation delay. A window-shifting scheme is then devised to view n data points as they are sampled in order to perform the function estimation. At each new sampling time, the window shifts to include the new data point as well as the last n-1 points. Several interpolation methods are considered. These methods use data points from a sampled function to construct a polynomial estimate of the function. The control system performance was experimentally tested using a servosystem. The results show that a Newtonian interpolation provided best results when the computation time was 0.4 times the sampling period.

Youcef-Toumi, K.↗
NASA NTRS1991

Seals Research at Texas A/M University

The Turbomachinery Laboratory at Texas A&M has been providing experimental data and computational codes for the design seals for many years. The program began with the development of a Halon based seal test rig. This facility provided information about the effective stiffness and damping in whirling seals. The Halon effectively simulated cryogenic fluids. Another test facility was developed (using air as the working fluid) where the stiffness and damping matrices can be determined. This data was used to develop bulk flow models of the seal's effect upon rotating machinery; in conjunction with this research, a bulk flow model for calculation of performance and rotordynamic coefficients of annular pressure seals of arbitrary non-uniform clearance for barotropic fluids such as LH2, LOX, LN2, and CH4 was developed. This program is very efficient (fast) and converges for very large eccentricities. Currently, work is being performed on a bulk flow analysis of the effects of the impeller-shroud interaction upon the stability of pumps. The data was used along with data from other researchers to develop an empirical leakage prediction code for MSFC. Presently, the flow field inside labyrinth and annular seals are being studied in detail. An advanced 3-D Doppler anemometer system is being used to measure the mean velocity and entire Reynolds stress tensor distribution throughout the seals. Concentric and statically eccentric seals were studied; presently, whirling seals are being studied. The data obtained are providing valuable information about the flow phenomena occurring inside the seals, as well as a data base for comparison with numerical predictions and for turbulence model development. A finite difference computer code was developed for solving the Reynolds averaged Navier Stokes equation inside labyrinth seals. A multi-scale k-epsilon turbulence model is currently being evaluated. A new seal geometry was designed and patented using a computer code. A large scale, 2-D seal flow visualization facility is also being developed.

Morrison, Gerald L.↗
NASA NTRS1992

The Dornier 328 Acoustic Test Cell (ATC) for interior noise tests and selected test results

To perform acoustic studies for achieving low noise levels for the Dornier 328, an acoustic test cell (ATC) of the Dornier 328 has been built. The ATC consists of a fuselage section, a realistic fuselage suspension system, and three exterior noise simulation rings. A complex digital 60 channel computer/amplifier noise generation system as well as multichannel digital data acquisition and evaluation system have been used. The noise control tests started with vibration measurements for supporting acoustic data interpretation. In addition, experiments have been carried out on dynamic vibration absorbers, the most important passive noise reduction measure for low frequency propeller noise. The design and arrangement of the current ATC are presented. Furthermore, exterior noise simulation as well as data acquisition are explained. The most promising results show noise reduction due to synchrophasing and dynamic vibration absorbers.

Hackstein, H. Josef↗