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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Follow-on cable coupling lightning test. Volume 3: Appendixes E and F

The following subject areas are covered: (1) Follow-on cable coupling lightning test swept continuous wave data plots, and (2) USBI cable coupling responses, EMA final test report (Lightning test results for the modified systems tunnel bonding on the Space Shuttle Solid Rocket Booster: tabulation of cable responses to threat level lightning testing; demonstration of linear extrapolation of swept continuous wave testing to NASA lightning specification).

Source record↗
NASA NTRS1993

Improved inhalation technology for setting safe exposure levels for workplace chemicals

Threshold Limit Values recommended as allowable air concentrations of a chemical in the workplace are often based upon a no-observable-effect-level (NOEL) determined by experimental inhalation studies using rodents. A 'safe level' for human exposure must then be estimated by the use of generalized safety factors in attempts to extrapolate from experimental rodents to man. The recent development of chemical-specific physiologically-based toxicokinetics makes use of measured physiological, biochemical, and metabolic parameters to construct a validated model that is able to 'scale-up' rodent response data to predict the behavior of the chemical in man. This procedure is made possible by recent advances in personal computer software and the emergence of appropriate biological data, and provides an analytical tool for much more reliable risk evaluation and airborne chemical exposure level setting for humans.

Stuart, Bruce O.↗
NASA NTRS2002

Architecture Studies Done for High-Rate Duplex Direct Data Distribution (D4) Services

A study was sponsored to investigate a set of end-to-end system concepts for implementing a high-rate duplex direct data distribution (D4) space-to-ground communications link. The NASA Glenn Research Center is investigating these systems (both commercial and Government) as a possible method of providing a D4 communications service between NASA spacecraft in low Earth orbit and the respective principal investigators using or monitoring instruments aboard these spacecraft. Candidate commercial services were assessed regarding their near-term potential to provide a D4 type of service. The candidates included K-band and V-band geostationary orbit and nongeostationary orbit satellite relay services and direct downlink (D3) services. Internet protocol (IP) networking technologies were evaluated to enable the user-directed distribution and delivery of science data. Four realistic, near-future concepts were analyzed: 1) A duplex direct link (uplink plus downlink communication paths) between a low-Earth-orbit spacecraft and a principal-investigator-based autonomous Earth station; 2) A space-based relay using a future K-band nongeosynchronous-orbit system to handle both the uplink and downlink communication paths; 3) A hybrid link using both direct and relay services to achieve full duplex capability; 4) A dual-mode concept consisting of both a duplex direct link and a space relay duplex link operating independently. The concepts were analyzed in terms of contact time between the NASA spacecraft and the communications service and the achievable data throughput. Throughput estimates for the D4 systems were based on the infusion of advanced communications technology products (single and multibeam K-band phased-arrays and digital modems) being developed by Glenn. Cost estimates were also performed using extrapolated information from both terrestrial and current satellite communications providers. The throughput and cost estimates were used to compare the concepts.

Source record↗
NASA NTRS2000

Timing Noise in SGR 1806-20

We have phase connected a sequence of Rossi X-ray Timing Explorer Proportional Counter Array observations of SGR 1806-20 covering 178 days. We find a simple secular spin-down model does not adequately fit the data. The period derivative varies gradually during the observations between 8.1 and 11.7 x 10(exp -11) s/s (approx. 40% larger than the long term trend), while the average burst rate as seen with the Burst and Transient Source Experiment drops throughout the time interval. The phase residuals show no evidence for periodicity, but more closely resemble timing noise as seen ill radio pulsars. The magnitude of the timing noise., however, is large relative to the noise level typically found in radio pulsars (Delta(sub 8) = 4.8; frequency derivative average power approx. = 8 X 10(exp -20) Hz/sq s). Combined with the noise levels measured for some AXPs. we find all magnetar candidates have A8 values larger than those expected from a simple extrapolation of the correlation found in radio pulsars. We find the timing noise ill SGR 1806-20 is greater than or equal to the levels found in some accreting systems (e.g., Vela X-1, 4U 1538-52 and 4U 1626-67). Alternatively, an orbital model with a period P(sub orb) = 733 days provides a statistically acceptable fit to the data. If the phase residuals are created by Doppler shifts from a gravitationally bound companion. then the allowed parameter space for the mass function (small) and orbital separation (large) rule out the possibility of accretion from the companion sufficient to power the persistent emission from the SGR.

Woods, Peter M.↗
NASA NTRS2001

Evolution, language and analogy in functional genomics

Almost a century ago, Wittgenstein pointed out that theory in science is intricately connected to language. This connection is not a frequent topic in the genomics literature. But a case can be made that functional genomics is today hindered by the paradoxes that Wittgenstein identified. If this is true, until these paradoxes are recognized and addressed, functional genomics will continue to be limited in its ability to extrapolate information from genomic sequences.

Evolution, Molecular↗
DOE OSTI2020

Data-Driven Constitutive Model for the Inelastic Response of Metals: Application to 316H Steel

Here, predictions of the mechanical response of structural elements are conditioned by the accuracy of constitutive models used at the engineering length-scale. In this regard, a prospect of mechanistic crystal-plasticity-based constitutive models is that they could be used for extrapolation beyond regimes in which they are calibrated. However, their use for assessing the performance of a component is computationally onerous. To address this limitation, a new approach is proposed whereby a surrogate constitutive model (SM) of the inelastic response of 316H steel is derived from a mechanistic crystal plasticity-based polycrystal model tracking the evolution of dislocation densities on all slip systems. The latter is used to generate a database of the expected plastic response and dislocation content evolution associated with several instances of creep loading. From the database, a SM is developed. It relies on the use of orthogonal polynomial regression to describe the evolution of the dislocation content. The SM is then validated against predictions of the dead load creep response given by the polycrystal model across a range of temperatures and stresses. When the SM is used to predict the response of 316H during complex non monotonic loading, extrapolating to new loading conditions, it is found that predictions compare particularly well against those from the physics-based polycrystal model.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Developing a robust strength model using physically-informed genetic programming

The strength of materials is influenced by a range of external conditions, such as temperature and deformation rate. Consequently, materials that demonstrate substantial variations in their mechanical behavior due to fluctuations in temperature and strain rate require complex strength models to accurately predict material performance in real-world applications. To predict such complex behavior, a robust and flexible strength model is necessary. In this work, we utilize genetic programming-based symbolic regression (GPSR) to develop data-driven strength models that accurately represent the measured stress–strain responses of tin across a wide range of strain, strain rate and temperature regimes. The GPSR models are constrained by physically-informed conditions, which leads to significant improvement in extrapolation. The best model is integrated into a multi-physics code to perform Taylor impact simulations, validating the model’s accuracy and robustness. In conclusion, the model predictions showed excellent agreement with experimental results, particularly when compared to predictions using traditional strength models.

Genetic programming↗
DOE OSTI2019

Investigation of the mechanical and microstructural evolution of a Cu based bulk metallic glass during ion irradiation

Ion irradiation and annealing experiments were performed on Cu 60 Zr 20 Hf 10 Ti 10 bulk metallic glass (BMG) specimens to investigate their irradiation- and temperature-induced microstructural and mechanical property evolution. For the ion irradiations, samples were exposed to 9 MeV Ni 3+ ions to a midrange (~1.2 μm depth) dose of 10 displacements per atom (dpa) at temperatures ranging from room temperature to 360 °C (the corresponding peak dose at ~2.8 μm depth was ~25 dpa). Bulk X-ray diffraction (XRD) and transmission electron microscopy (TEM) characterization revealed that the alloy did not crystallize during irradiation up to 290 °C but did partially crystallize at 360 °C. XRD analysis revealed that the crystallization which occurred in the sample irradiated at 360 °C was caused by thermal effects instead of irradiation displacement damage. Subsequent Rietveld refinement analysis of the XRD measurements revealed the presence of two distinct crystal phases, namely a CuTiZr hexagonal structure belonging to the P63/mmc space group and a CuTi tetragonal structure belonging to the P4/mmm space group. Nanoindentation experiments revealed that no pronounced hardness changes occurred in the specimens irradiated at room temperature and 290°C, although significant hardening was observed in the sample irradiated at 360 °C. The significant increase in the hardness at 360°C was ascribed to thermally induced partial crystallization of the alloy instead of the ion irradiation. In general, the results of the nanoindentation experiments and XRD characterization suggest that although the Cu BMG exhibits good stability during irradiation at temperatures up to 290 °C it is not suitable for irradiation environments where the temperature is 360 °C for extended periods of time. The Lam and Chong extrapolation method, which has been used to study the indentation size effect (ISE) in amorphous alloys, was employed to quantify how irradiation and temperature affect this type of behavior in the BMG. However, the poor linear fitting of the indentation hardness data by this model indicate that a new ISE model is likely needed to quantify indentation hardening in BMGs.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Learning two-phase microstructure evolution using neural operators and autoencoder architectures

Abstract Phase-field modeling is an effective but computationally expensive method for capturing the mesoscale morphological and microstructure evolution in materials. Hence, fast and generalizable surrogate models are needed to alleviate the cost of computationally taxing processes such as in optimization and design of materials. The intrinsic discontinuous nature of the physical phenomena incurred by the presence of sharp phase boundaries makes the training of the surrogate model cumbersome. We develop a framework that integrates a convolutional autoencoder architecture with a deep neural operator (DeepONet) to learn the dynamic evolution of a two-phase mixture and accelerate time-to-solution in predicting the microstructure evolution. We utilize the convolutional autoencoder to provide a compact representation of the microstructure data in a low-dimensional latent space. After DeepONet is trained in the latent space, it can be used to replace the high-fidelity phase-field numerical solver in interpolation tasks or to accelerate the numerical solver in extrapolation tasks.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Relativistic mean-field theories for neutron-star physics based on chiral effective field theory

We describe and implement a procedure for determining the couplings of a relativistic mean-field theory (RMFT) that is optimized for application to neutron star phenomenology. In the standard RMFT approach, the couplings are constrained by comparing the theory's predictions for symmetric matter at saturation density with measured nuclear properties. The theory is then applied to neutron stars which consist of neutron-rich matter at densities ranging up to several times saturation density, which allows for additional astrophysical constraints. In our approach, rather than using the RMFT to extrapolate from symmetric to neutron-rich matter and from finite-sized nuclei to uniform matter, we fit the RMFT to properties of uniform pure neutron matter obtained from chiral effective field theory. Chiral effective field theory incorporates the experimental data for nuclei in the framework of a controlled expansion for nuclear forces valid at nuclear densities and enables us to account for theoretical uncertainties when fitting the RMFT. We construct four simple RMFTs that span the uncertainties provided by chiral effective field theory for neutron matter, and are consistent with current astrophysical constraints on the equation of state. Lastly, our RMFTs can be used to model the properties of neutron-rich matter across the vast range of densities and temperatures encountered in neutron stars and their mergers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Effective Opacity of the Intergalactic Medium from Galaxy Spectra Analysis

We measure the effective opacity (τ{sub eff}) of the intergalactic medium from the composite spectra of 281 Lyman-break galaxies in the redshift range 2 ≲ z ≲ 3. Our spectra are taken from the COSMOS Lyα Mapping And Tomographic Observations survey derived from the Low Resolution Imaging Spectrometer on the W.M. Keck I telescope. We generate composite spectra in two redshift intervals and fit them with spectral energy distribution (SED) models composed of simple stellar populations. Extrapolating these SED models into the Lyα forest, we measure the effective Lyα opacity (τ{sub eff}) in the 2.02 ≤ z ≤ 2.44 range. At z = 2.22, we estimate τ{sub eff} =0.159±0.001 from a power-law fit to the data. These measurements are consistent with estimates from quasar analyses at z < 2.5 indicating that the systematic errors associated with normalizing quasar continua are not substantial. We provide a Gaussian processes model of our results and previous τ{sub eff} measurements that describes the steep redshift evolution in τ{sub eff} from z = 1.5–4.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1978

Formation of metallic LiH

It is shown that a metallic form of LiH may be produced at the relatively low transition pressure of 1.1 mbar. LiH may thus be applied to studies of insulator-metal transition at high pressure. Experimental data is used to calculate LiH transition parameters: first, Herzfeld's criterion (1927) is used to determine the volume at which metallic behavior begins, and second, pressure-volume measurements for estimating the pressure at which this volume is achieved are extrapolated. For comparison, the same volume-pressure calculation is performed for H2, and it is found that the metallization of LiH should occur more easily than that of H2.

Vaisnys, J. R.↗
NASA NTRS1991

Sensor fusion techniques for predicting thunderstorm evolution using lightning and radar networks

A pattern recognition scheme that is used to generate initial seeds or 'first guess' fields for clustering the discrete lightning discharges into storm cells is presented. The clustering process is critically dependent on the prior accuracy of the lightning location estimates. The generation of subsequent storm life-cycle time series (for extrapolation forecasting) also relies on the cluster analysis procedure assigning the correct number of lightning discharges (objects) to the proper storms (groups). The advantages and limitations of different clustering strategies for storm identification and tracking are examined. Storm identification with lightning data alone is compared to storm identification with radar alone, and some synergies for sensor fusion are explored.

Goodman, Steven J.↗
NASA NTRS1996

Baseline acoustic levels of the NASA Active Noise Control Fan rig

Extensive measurements of the spinning acoustic mode structure in the NASA 48 inch Active Noise Control Fan (ANCF) test rig have been taken. A continuously rotating microphone rake system with a least-squares data reduction technique was employed to measure these modes in the inlet and exhaust. Farfield directivity patterns in an anechoic environment were also measured at matched corrected rotor speeds. Several vane counts and spacings were tested over a range of rotor speeds. The Eversman finite element radiation code was run with the measured in-duct modes as input and the computed farfield results were compared to the experimentally measured directivity pattern. The experimental data show that inlet spinning mode measurements can be made very accurately. Exhaust mode measurements may have wake interference, but the least-squares reduction does a good job of rejecting the non-acoustic pressure. The Eversman radiation code accurately extrapolates the farfield levels and directivity pattern when all in-duct modes are included.

Sutliff, Daniel L.↗
NASA NTRS2008

Comparison of NTF Experimental Data with CFD Predictions from the Third AIAA CFD Drag Prediction Workshop

Recently acquired experimental data for the DLR-F6 wing-body transonic transport con figuration from the National Transonic Facility (NTF) are compared with the database of computational fluid dynamics (CFD) predictions generated for the Third AIAA CFD Drag Prediction Workshop (DPW-III). The NTF data were collected after the DPW-III, which was conducted with blind test cases. These data include both absolute drag levels and increments associated with this wing-body geometry. The baseline DLR-F6 wing-body geometry is also augmented with a side-of-body fairing which eliminates the flow separation in this juncture region. A comparison between computed and experimentally observed sizes of the side-of-body flow-separation bubble is included. The CFD results for the drag polars and separation bubble sizes are computed on grids which represent current engineering best practices for drag predictions. In addition to these data, a more rigorous attempt to predict absolute drag at the design point is provided. Here, a series of three grid densities are utilized to establish an asymptotic trend of computed drag with respect to grid convergence. This trend is then extrapolated to estimate a grid-converged absolute drag level.

Vassberg, John C.↗
NASA NTRS2014

Decomposition Technique for Remaining Useful Life Prediction

The prognostic tool disclosed here decomposes the problem of estimating the remaining useful life (RUL) of a component or sub-system into two separate regression problems: the feature-to-damage mapping and the operational conditions-to-damage-rate mapping. These maps are initially generated in off-line mode. One or more regression algorithms are used to generate each of these maps from measurements (and features derived from these), operational conditions, and ground truth information. This decomposition technique allows for the explicit quantification and management of different sources of uncertainty present in the process. Next, the maps are used in an on-line mode where run-time data (sensor measurements and operational conditions) are used in conjunction with the maps generated in off-line mode to estimate both current damage state as well as future damage accumulation. Remaining life is computed by subtracting the instance when the extrapolated damage reaches the failure threshold from the instance when the prediction is made.

Saha, Bhaskar↗
NASA NTRS2019

The NASA Orbital Debris Engineering Model 3.1: Development, Verification, and Validation

The NASA Orbital Debris Program Office has developed the Orbital Debris Engineering Model (ORDEM) primarily as a tool for spacecraft designers and other users to understand the long-term risk of collisions with orbital debris. The newest version, ORDEM 3.1, incorporates the latest and highest fidelity datasets available to build and validate representative orbital debris populations encompassing low Earth orbit (LEO) to geosynchronous orbit (GEO) altitudes for the years 2016-2050. ORDEM 3.1 models fluxes for object sizes > 10 μm within or transiting LEO and > 10 cm in GEO. The deterministic portion of the populations in ORDEM 3.1 is based on the U.S. Space Surveillance Network (SSN) catalog, which provides coverage down to approximately 10 cm in LEO and 1 m in GEO. Observational datasets from radar, in situ, and optical sources provide a foundation from which the model populations are statistically extrapolated to smaller sizes and orbit regions that are not well-covered by the SSN catalog, yet may pose the greatest threat to operational spacecraft. Objects in LEO ranging from approximately 5 mm to 10 cm are modeled using observational data from ground-based radar, namely the Haystack Ultrawideband Satellite Imaging Radar (HUSIR – formerly known as Haystack). The LEO population smaller than approximately 3 mm in size is characterized based on a reanalysis of in situ data from impacts to the windows and radiators of the U.S. Space Transportation System orbiter vehicle, i.e., the Space Shuttle. Data from impacts on the Hubble Space Telescope are also used to validate the sub-millimeter model populations in LEO. Debris in GEO with sizes ranging from 10 cm to 1 m is modeled using optical measurement data from the Michigan Orbital DEbris Survey Telescope (MODEST). Specific, major debris-producing events, including the Fengyun-1C, Iridium 33, and Cosmos 2251 debris clouds, and unique populations, such as sodium-potassium droplets, have been re-examined and are modeled and added to the ORDEM environment separately. The debris environment greater than 1 mm is forecast using NASA’s LEO-to- GEO ENvironment Debris model (LEGEND). Future explosions of intact objects and collisions involving objects greater than 10 cm are assessed statistically, and the NASA Standard Satellite Breakup Model is used to generate fragments from these events. Fragments smaller than 10 cm are further differentiated based on material density categories, i.e., high-, medium-, and low-density, to better characterize the potential debris risk posed to spacecraft. The future projection of the sub-millimeter environment is computed using a special small-particle degradation model where small particles are created from intact spacecraft and rocket bodies. This work discusses the development, features, and capabilities of the ORDEM 3.1 model; the ne new data analyses used to build the model populations; and sample verification and validation results.

Matney, M.↗
NASA NTRS2004

Physical Validation of TRMM TMI and PR Monthly Rain Products Over Oklahoma

The Tropical Rainfall Measuring Mission (TRMM) provides monthly rainfall estimates using data collected by the TRMM satellite. These estimates cover a substantial fraction of the earth's surface. The physical validation of TRMM estimates involves corroborating the accuracy of spaceborne estimates of areal rainfall by inferring errors and biases from ground-based rain estimates. The TRMM error budget consists of two major sources of error: retrieval and sampling. Sampling errors are intrinsic to the process of estimating monthly rainfall and occur because the satellite extrapolates monthly rainfall from a small subset of measurements collected only during satellite overpasses. Retrieval errors, on the other hand, are related to the process of collecting measurements while the satellite is overhead. One of the big challenges confronting the TRMM validation effort is how to best estimate these two main components of the TRMM error budget, which are not easily decoupled. This four-year study computed bulk sampling and retrieval errors for the TRMM microwave imager (TMI) and the precipitation radar (PR) by applying a technique that sub-samples gauge data at TRMM overpass times. Gridded monthly rain estimates are then computed from the monthly bulk statistics of the collected samples, providing a sensor-dependent gauge rain estimate that is assumed to include a TRMM equivalent sampling error. The sub-sampled gauge rain estimates are then used in conjunction with the monthly satellite and gauge (without sub- sampling) estimates to decouple retrieval and sampling errors. The computed mean sampling errors for the TMI and PR were 5.9% and 7.796, respectively, in good agreement with theoretical predictions. The PR year-to-year retrieval biases exceeded corresponding TMI biases, but it was found that these differences were partially due to negative TMI biases during cold months and positive TMI biases during warm months.

Fisher, Brad L.↗