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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
NASA NTRS1974

Identification of Geostructures of the Continental Crust Particularly as They Relate to Mineral Resource Evaluation

The author has identified the following significant results. A pattern of very old geostructures was recognized, reflecting structures in the crust. This pattern is not peculiar to Alaska, but can be recognized throughout the northern cordillera. A new metallogenic hypothesis for Alaska was developed, based on the relationship of space image linears to known mineral deposits. Using image linear analysis, regional geologic features were also recognized; these features may be used to guide in the location of undiscovered oil and/or gas accumulations in northern Alaska. The effectiveness of ERTS data in enhancing medium and small scale mapping was demonstrated. ERTS data were also used to recognize and monitor the state of large scale vehicular scars on Arctic tundra.

Lathram, E. H.↗
NASA NTRS2003

WMAP Detection of Early Reionization

The Wilkinson Microwave Anisotropy Probe (WMAP) has mapped the full sky in Stokes I, Q, and U parameters at frequencies 23, 33, 41, 61, and 94 GHz. We detect correlations between the temperature and polarization maps significant at more than 10 standard deviations. The correlations are inconsistent with instrument noise and are significantly larger than the upper limits established for potential systenatic errors. The correlations are present in all WMAP frequency bands with similar amplitude from 23 to 94 GHz, and are consistent with a superposition of a CMB signal with a weak foreground. The fitted CMB component is robust against different data combinations and fitting techniques. On small angular scales the WMAP data show the temperature-polarization correlation expected from adiabatic density perturbations. The data for $\ell > 20$ agree well with the signal predicted solely from the temperature power spectra, with no additional free parameters. The existence of correlations on super-horizon scales provides significant support for inflationary cosmologies. We detect excess power on large angular scales compared to predictions based on the temperature power spectra alone. The excess power is well described by reionization at redshift $11 < z < 30$ at 95\% confidence. A model-independent fit to reionization optical depth yields results consistent with the best-fit $\Lambda$CDM model, with best fit value $\tau = 0.17 \pm 0.04$ at 68\% confidence, including systematic and foreground uncertainties. This value is larger than expected given the detection of a Gunn-Peterson trough in the absorption spectra of distant quasars, and implies that the universe has a complex ionization history. I will discuss the WMAP data and its implications for reionization in the early universe.

Kogut, A.↗
NASA NTRS2003

WMAP Detection of Early Reionization

The Wilkinson Microwave Anisotropy Probe (WMAP) has mapped the full sky in Stokes I, Q, and U parameters at frequencies 23, 33, 41, 61, and 94 GHz. We detect correlations between the temperature and polarization maps significant at more than 10 standard deviations. The correlations are inconsistent with instrument noise and are significantly larger than the upper limits established for potential systematic errors. The correlations are present in all WMAP frequency bands with similar amplitude from 23 to 94 GHz, and are consistent with a superposition of a CMB signal with a weak foreground. The fitted CMB component is robust against different data combinations and fitting techniques. On small angular scales the WMAP data show the temperature-polarization correlation expected from adiabatic density perturbations. The data for $\ell > 20$ agree well with the signal predicted solely from the temperature power spectra, with no additional free parameters. The existence of correlations on super-horizon scales provides significant support for inflationary cosmologies. We detect excess power on large angular scales compared to predictions based on the temperature power spectra alone. The excess power is well described by reionization at redshift $11 < z < 30$ at 95\% confidence. A model-independent fit to reionization optical depth yields results consistent with the best-fit $\Lambda$CDM model, with best fit value $\tau = 0.17 \pm 0.04$ at 68\% confidence, including systematic and foreground uncertainties. This trough in the absorption spectra of distant quasars, and implies that the universe has a complex ionization history. I will discuss the WMAP data and its implications for reionization in the early universe.

Kogut, A.↗
NASA NTRS2019

Small-Satellite Mission Failure Rates

The purpose of this report is to determine the failure rate of small-satellite missions launched between the years 2000 and 2016. This analysis considers the rates of both partial and total mission failure, as well as the failures attributable to failure of the launch vehicle. This study observed that between the years of 2000 to 2016, 41.3% of all small satellites launched failed or partially failed. Of these small satellite missions, 24.2% were total mission failures, another 11% were partial mission failures, and 6.1% were launch vehicle failures. The small satellite failure data reveals an increase in the failure rate as the yearly launch rate has increased. The period 2000 to 2008 averaged 15 launches per year, during which 28.6% of the small satellite missions failed or partially failed. The period from 2009 to 2016 averaged 48 launches per year, during which 42.6% of the small satellite missions failed or partially failed. The launch vehicle failure rate for both periods was the same at around 6.1%. The implication is that for modern small satellite missions, almost one out of every two small satellite missions will result in either a total or a partial mission failure. Counting the partial mission successes as “successful missions” reduces the failure rate, but only to 38.2% for the period 2009 to 2016.

Small Satellite↗
NASA NTRSDate not supplied

Numerical Simulation of No Vent Chill and Fill of a Large Liquid Hydrogen Tank

On orbit transfer of cryogenic liquids is necessary for many future space missions. The techniques required to transfer cryogens in micro gravity are quite different from ground system applications. In normal gravity, cryogenic tanks are usually filled from the bottom at nearly atmospheric pressure. The vapor generated due to heat transfer from warm tank walls, is allowed to vent from the top of the tank while the tank is being filled. If the normal gravity technique is used on orbit, the uncertainty of liquid and vapor distributions in unsettled condition may result in dumping of large amounts of liquid propellant overboard. The Vented Chill and No Vent Fill (VCNVF) process is a methodology [1] used to reduce propellant loss by holding the vent valve open during initial wall chilldown, preventing over-pressurization of the tank and stalling of the incoming flow, but closing the tank vent valve after chilling the tank wall sufficiently. An accurate simulation of no vent tank chill and fill is necessary to estimate the amount of propellant necessary to chill the tank, determine the maximum sustainable flowrate to fill the tank without stalling, and establish a timeline for the filling process. Numerical modeling of filling a cryogenic tank is complex because the flow is two-phase and the process involves both boiling and condensation with heat transfer between solid and fluid. In recent years, progress has been made to develop a numerical modeling technique [2,3,4] that has been verified by comparing with the test data from a small flight tank using liquid nitrogen [5]. The purpose of the present paper is to apply this technique in a larger tank with liquid hydrogen and compare with the test data of Chato [1]. The K-site Test Facility [1], shown in Figure 1, consists of a Test Tank, spray system, instrumentation, and the vacuum chamber. The test tank selected was ellipsoidal with an 87 inch major diameter and a 1.2 to 1 major to minor axis ratio. The two ends are joined by a short 1.5 inch cylindrical section. The tank is made of 2219 aluminum chemically milled to a nominal thickness of 0.087 inches. The tank weighs 329.25 pounds, and the tank volume is 175 ft 3 . The GFSSP model of the Test Tank is shown in Figure 2. Node 13 is a boundary node that represents the supply tank which is supplying liquid hydrogen at a given pressure and temperature. The total measured flowrate is evenly distributed through Branches 131 through 139. Nodes 1 through 9 represent the test tank and they are connected with metal solid nodes 14 through 22 through fluid-to-solid conductors that allow convective heat transfer between the solid and fluid nodes. The predicted tank pressure, filling rate, wall temperature and fluid temperature will be compared with test data.

Alok Majumdar↗
NASA NTRS1994

Analysis of small crack behavior for airframe applications

The small fatigue crack problem is critically reviewed from the perspective of airframe applications. Different types of small cracks-microstructural, mechanical, and chemical-are carefully defined and relevant mechanisms identified. Appropriate analysis techniques, including both rigorous scientific and practical engineering treatments, are briefly described. Important materials data issues are addressed, including increased scatter in small crack data and recommended small crack test methods. Key problems requiring further study are highlighted.

Mcclung, R. C.↗
NASA NTRS1975

Remote Sensing Application to Land Use Classification in a Rapidly Changing Agricultural/Urban Area: City of Virginia Beach, Virginia

Remote sensing data on computer-compatible tapes of LANDSAT 1 multispectral scanner imager were analyzed to generate a land use map of the City of Virginia Beach. All four bands were used in both the supervised and unsupervised approaches with the LAYSYS software system. Color IR imagery of a U-2 flight of the same area was also digitized and two sample areas were analyzed via the unsupervised approach. The relationships between the mapped land use and the soils of the area were investigated. A land use land cover map at a scale of 1:24,000 was obtained from the supervised analysis of LANDSAT 1 data. It was concluded that machine analysis of remote sensing data to produce land use maps was feasible; that the LAYSYS software system was usable for this purpose; and that the machine analysis was capable of extracting detailed information from the relatively small scale LANDSAT data in a much shorter time without compromising accuracy.

Odenyo, V. A. O.↗
NASA NTRS1975

A feasibility study for measuring stratospheric turbulence using metrac positioning system

The feasibility of obtaining measurements of Lagrangian turbulence at stratospheric altitudes is demonstrated by using the METRAC System to track constant-level balloons. The basis for current estimates of diffusion coefficients are reviewed and it is pointed out that insufficient data is available upon which to base reliable estimates of vertical diffusion coefficients. It is concluded that diffusion coefficients could be directly obtained from Lagrangian turbulence measurements. The METRAC balloon tracking system is shown to possess the necessary precision in order to resolve the response of constant-level balloons to turbulence at stratospheric altitudes. A small sample of data recorded from a tropospheric tetroon flight tracked by the METRAC System is analyzed to obtain estimates of small-scale three-dimensional diffusion coefficients. It is recommended that this technique be employed to establish a climatology of diffusion coefficients and to ascertain the variation of these coefficients with altitude, season, and latitude.

Gage, K. S.↗
DOE OSTI2022

Further improvement and evaluation of nudging in the E3SM Atmosphere Model version 1 (EAMv1): simulations of the mean climate, weather events, and anthropogenic aerosol effects

Abstract. A previous study on the use of nudging in E3SM Atmosphere Model version 1 (EAMv1) had an unresolved issue; i.e., a simulation nudged to EAMv1's own meteorology showed non-negligible deviations from the free-running baseline simulation over some of the subtropical marine stratocumulus and trade cumulus regions. Here, we demonstrate that the deviations can be substantially reduced by (1) changing where the nudging tendency is calculated in the time integration loop of a nudged EAM simulation so as to improve consistency with the free-running baseline and (2) increasing the frequency of the constraining data so as to better capture strong sub-diurnal variations. The fact that modification (2) improves the climate representativeness of the nudged simulations has motivated us to investigate whether the use of newer reanalysis products with higher data frequency can help improve nudged hindcast simulations by better capturing the observed weather events. To answer this question, we present simulations conducted at EAMv1's standard horizontal resolution (approximately 1∘) with nudging towards 6-hourly ERA-Interim reanalysis or 6-hourly, 3-hourly, or hourly ERA5 reanalysis. These simulations are evaluated against the climatology of free-running EAMv1 simulations as well as reanalyses, satellite retrievals, and in situ measurements from the Atmospheric Radiation Measurement user facility. For the 1∘ EAMv1 simulations, we recommend using the relocated nudging tendency calculation and the ERA5 reanalysis at 3-hourly or higher frequency. Simulations used for estimating the anthropogenic aerosol effects often use nudging to help discern signal from noise. The sensitivity of such estimates to the configuration of nudging is investigated in EAMv1, again using the standard 1∘ horizontal resolution. We find that, when estimating the global mean effects, the frequency of constraining data has relatively small impacts, while the choice of nudged variables can change the results substantially. The nudging of air temperature (in addition to horizontal winds) has two non-negligible effects. First, when the constraining data come from reanalysis, the nudging-induced mean bias correction can cause significant changes in the simulated clouds and hence substantially different estimates of the aerosol effects. The impact of the mean bias correction on ice cloud formation has been noted in previous studies and is also seen in EAMv1. For applications like ours, where the preferred configurations of nudging are those capable of providing results consistent with the multi-year free-running simulations, the consequence of the mean bias correction is undesirable. The second important impact of temperature nudging is a significant suppression of adjustments to aerosol forcing, which also causes changes in the estimated aerosol effects. This effect can be seen in simulations nudged to either reanalysis or EAM's own meteorology. These results suggest that nudging horizontal winds but not temperature is a better choice for estimating the anthropogenic aerosol effects.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1977

Review of current interest and research in water hyacinth-based wastewater treatment

The status of activity in the user community for water hyacinth-based wastewater treatment was evaluated. The principal technique used was that of interviewing people who either (1) were known to be engaged in hyacinth research or development or (2) had made inquiry to NASA about hyacinth systems. About 40 non-research organizations and a similar number of research organizations were contacted. As a result of the interviews and a review of the relevant literature, it was concluded that hyacinth systems have the potential for providing a lower cost way for small cities to meet increasingly stringent effluent requirements. A limited amount of full-scale demonstration of hyacinth systems has been carried out during the past two years, but the yield of design data has been small. Several organizations are currently planning construction of experimental full-scale hyacinth-based wastewater treatment systems during 1977-1978.

Markarian, R. K.↗
NASA NTRS2006

Estimation of Longitudinal Unsteady Aerodynamics of a Wing-Tail Combination From Wind Tunnel Data

This paper presents an initial step toward model identification from wind tunnel data for an airliner configuration. Two approaches to modeling a transport configuration are considered and applied to both steady and large-amplitude forced-oscillation wind tunnel data taken over a wide range of angles of attack. Only limited conclusions could be drawn from this initial data set. Although model estimated time histories of normal force and pitching moment agree reasonably well with the corresponding measured values, model damping parameters did not, for some cases, have values consistent with small amplitude oscillatory data. In addition, large parameter standard errors implied poor information content for model structure determination and parameter estimation. Further investigation of the modeling problem for more general aerodynamic models is recommended with close attention to experiment design for obtaining parameters with high accuracy.

Murphy, Patrick C.↗
NASA NTRSDate not supplied

Metabolic Vessel for Impedance Spectroscopy and Electrochemistry (MVISE): The Ground Mapping Unit for the Lunar Explorer Instrument for Space Biology Applications (LEIA)​

The BioSensor payload on the upcoming LEIA platform aboard a CLPS lander will carry yeast to the moon to study response to radiation and lunar gravity. The LEIA BioSensor is designed to monitor metabolic activity using absorbance in conjunction with alamarBlue for measuring colorimetric changes as proxy measurement for redox potential. The science data returned from small spacecraft mission modules like LEIA is limited as it relies solely on optical measurements, necessitating a corresponding ground mapping unit that is equipped with multiple electrochemical sensors for accurate mapping of the optical data and operates fully automatically. This technology development work discusses the extensive design and optimization efforts put into the ground mapping unit, MVISE. MVISE is a custom designed, 3D-printed vessel with an agitation system, with six different electrochemical sensor probes, and ports for sample collection and a pressure release valve. The sensors provide real-time data, with dry absorbance measurements aligning with LEIA flight hardware and wet measurements demonstrating invasive sensor design enabling a comparison between the two setups. The 3D printer resin was tested for mechanical robustness, biocompatibility, and resistance to autoclave sterilization. The inner walls were coated with food-grade epoxy, ensuring a smooth finish to prevent microbial lodging and dye staining. The MVISE has successfully passed a week-long leak test and is now undergoing active biology tests. The MVISE prototype will be prepared for radiation tests, with three identical units being tested for varying radiation levels and culture compositions at the NASA Space Radiation Laboratory in November 2024. The integrated sensor approach proposed in this work will enable the accurate mapping of the BioSentinel/LEIA optical flight data to six sensor parameters on the ground unit for better science data return and will enable the first effort to evaluate classical biochemical sensor measurements by comparing and contrasting their responses.

Chinmayee Govinda Raj↗
DOE OSTI2024

Data‐driven variational method for discrepancy modeling: Dynamics with small‐strain nonlinear elasticity and viscoelasticity

Abstract The effective inclusion of a priori knowledge when embedding known data in physics‐based models of dynamical systems can ensure that the reconstructed model respects physical principles, while simultaneously improving the accuracy of the solution in the previously unseen regions of state space. This paper presents a physics‐constrained data‐driven discrepancy modeling method that variationally embeds known data in the modeling framework. The hierarchical structure of the method yields fine scale variational equations that facilitate the derivation of residuals which are comprised of the first‐principles theory and sensor‐based data from the dynamical system. The embedding of the sensor data via residual terms leads to discrepancy‐informed closure models that yield a method which is driven not only by boundary and initial conditions, but also by measurements that are taken at only a few observation points in the target system. Specifically, the data‐embedding term serves as residual‐based least‐squares loss function, thus retaining variational consistency. Another important relation arises from the interpretation of the stabilization tensor as a kernel function, thereby incorporating a priori knowledge of the problem and adding computational intelligence to the modeling framework. Numerical test cases show that when known data is taken into account, the data driven variational (DDV) method can correctly predict the system response in the presence of several types of discrepancies. Specifically, the damped solution and correct energy time histories are recovered by including known data in the undamped situation. Morlet wavelet analyses reveal that the surrogate problem with embedded data recovers the fundamental frequency band of the target system. The enhanced stability and accuracy of the DDV method is manifested via reconstructed displacement and velocity fields that yield time histories of strain and kinetic energies which match the target systems. The proposed DDV method also serves as a procedure for restoring eigenvalues and eigenvectors of a deficient dynamical system when known data is taken into account, as shown in the numerical test cases presented here.

Masud, Arif↗
DOE OSTI2025

Harnessing distributed GPU computing for generalizable graph convolutional networks in power grid reliability assessments

Although machine learning (ML) has emerged as a powerful tool for rapidly assessing grid contingencies, prior studies have largely considered a static grid topology in their analyses. This limits their application, since they need to be re-trained for every new topology. Here, this paper explores the development of generalizable graph convolutional network (GCN) models by pre-training them across a range of grid topologies and contingency types. We found that a GCN model with auto-regressive moving average (ARMA) layers with a line graph representation of the grid offered the best predictive performance in predicting voltage magnitudes (VM) and voltage angles (VA). We introduced the concept of phantom nodes to consider disparate grid topologies with a varying number of nodes and lines. For pre-training the GCN ARMA model across a variety of topologies, distributed graphics processing unit (GPU) computing afforded us significant training scalability. The predictive performance of this model on grid topologies that were part of the training data is substantially better than the direct current (DC) approximation. Although direct application of the pre-trained model to topologies that are not part of the grid is not particularly satisfactory, fine-tuning with small amounts of data from a specific topology of interest significantly improves predictive performance. In general, this paper highlights the feasibility of training large-scale GNN models to assess the reliability of power grids by considering a wide variety of grid topologies and contingency types. With the advent of foundational models in ML and the exponential increase in GPU computing clusters, generalizable ML models will significantly enhance how utilities manage power systems and make decisions in real-time or near-real-time.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Streaming Compression of Scientific Data via Weak-SINDy

Here, in this paper, a streaming weak-SINDy algorithm is developed specifically for compressing streaming scientific data. The production of scientific data, either via simulation or experiments, is undergoing a stage of exponential growth, which makes data compression important and often necessary for storing and utilizing large scientific data sets. As opposed to classical “offline” compression algorithms that perform compression on a readily available data set, streaming compression algorithms compress data “online” while the data generated from simulation or experiments is still flowing through the system. This feature makes streaming compression algorithms well suited for scientific data compression, where storing the full data set offline is often infeasible. This work proposes a new streaming compression algorithm, streaming weak-SINDy, which takes advantage of the underlying data characteristics during compression. The streaming weak-SINDy algorithm constructs feature matrices and target vectors in the online stage via a streaming integration method in a memory efficient manner. The feature matrices and target vectors are then used in the offline stage to build a model through a regression process that aims to recover equations that govern the evolution of the data. For compressing high-dimensional streaming data, we adopt a streaming proper orthogonal decomposition (POD) process to reduce the data dimension and then use the streaming weak-SINDy algorithm to compress the temporal data of the POD expansion. We propose modifications to the streaming weak-SINDy algorithm to accommodate the dynamically updated POD basis. By combining the built model from the streaming weak-SINDy algorithm and a small amount of data samples, the full data flow could be reconstructed accurately at a low memory cost, as shown in the numerical tests.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1978

Data analysis of the LPSP experiment on OSO-8

The first and statistically most reliable step in the data analysis - the computation of the vertical phase lag between photospheric and chromospheric oscillations - was completed. Unfortunately, the error associated with this calculated phase lag is so great that the result has no physical significance. Since the subsequent data analysis that was originally planned would have much larger associated errors, it was concluded that the data available is insufficient to allow any meaningful results to be derived. Accordingly, the project was terminated. The reasons for the failure of the data are discussed. There are two basic reasons for this failure; (1) the very low signal to noise ratio of the raw data, and (1) the small statistical sample that resulted from the very small number of usable orbits. The final phase of data analysis is described. Finally, some comments and recommendations of a general nature are made concerning this entire contract effort. It is hoped that at least some lessons can be learned from this particular Guest Investigator project, so that future Guest Investigator programs can be pursued more effectively, and with less risk.

Frazier, E. N.↗
NASA NTRS1978

The dependence of the CO2 removal efficiency of LiOH on humidity and mesh size

The effect of humidity on the CO2 removal efficiency of small beds of anhydrous LiOH has been studied. Experimental data taken in this small bed system clearly show that there is an optimum humidity for beds loaded with LiOH from a single lot. The CO2 efficiency falls rapidly under dry conditions, but this behavior is approximately the same in all samples. The behavior of the bed under wet conditions is quite dependent on material size distribution. The presence of large particles in a sample can lead to rapid fall off in the CO2 efficiency as the humidity increases.

Davis, S. H.↗
NASA NTRS1990

A comparison of fatigue life prediction methodologies for rotorcraft

Because of the current U.S. Army requirement that all new rotorcraft be designed to a 'six nines' reliability on fatigue life, this study was undertaken to assess the accuracy of the current safe life philosophy using the nominal stress Palmgrem-Miner linear cumulative damage rule to predict the fatigue life of rotorcraft dynamic components. It has been shown that this methodology can predict fatigue lives that differ from test lives by more than two orders of magnitude. A further objective of this work was to compare the accuracy of this methodology to another safe life method called the local strain approach as well as to a method which predicts fatigue life based solely on crack growth data. Spectrum fatigue tests were run on notched (k(sub t) = 3.2) specimens made of 4340 steel using the Felix/28 tests fairly well, being slightly on the unconservative side of the test data. The crack growth method, which is based on 'small crack' crack growth data and a crack-closure model, also predicted the fatigue lives very well with the predicted lives being slightly longer that the mean test lives but within the experimental scatter band. The crack growth model was also able to predict the change in test lives produced by the rainflow reconstructed spectra.

Everett, R. A., Jr.↗