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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 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Planck 2015 Constraints on the Nonflat ΦCDM Inflation Model

We perform Markov chain Monte Carlo analyses to put constraints on the nonflat ΦCDM inflation model using Planck 2015 cosmic microwave background (CMB) anisotropy data and baryon acoustic oscillation distance measurements. The ΦCDM model is a consistent dynamical dark energy model in which the currently accelerating cosmological expansion is powered by a scalar field Φ slowly rolling down an inverse power-law potential energy density. We also use a physically consistent power spectrum for energy density inhomogeneities in this nonflat model. We find that, like the closed-ΛCDM and closed-XCDM models, the closed-ΦCDM model provides a better fit to the lower multipole region of the CMB temperature anisotropy data compared to that provided by the tilted flat-ΛCDM model. Also, like the other closed models, this model reduces the tension between the Planck and the weak lensing σ 8 constraints. Furthermore, the higher multipole region of the CMB temperature anisotropy data are better fit by the tilted flat-Λ model than by the closed models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Registration and fusion of large-scale melt pool temperature and morphology monitoring data demonstrated for surface topography prediction in LPBF

In-situ monitoring technologies for laser powder bed fusion (LPBF) additive manufacturing often face one key challenge, extracting the ultrafast melt pool (MP) signatures for understanding the localized part properties. Further, the spatial information of each monitored MP signature is essential for correlating the MP – part property. This spatial information is often unavailable especially from commercial LPBF printers. Many MP monitoring methods have been reported and utilized. However, very few of these have the MP’s spatial information. To overcome this challenge, in this work we report a method for spatially registering the key MP signatures (MP intensity, temperature, and area) to the monitored print parts. The MP signatures are obtained from our coaxial high-speed single-camera based two-wavelength imaging pyrometry (STWIP) system and the MP spatial information is obtained from an off-axis camera system. A machine learning aided image analysis method is employed to retrieve the spatial distribution of MPs within the corresponding part’s coordinates system. Then, the MP signature maps (MPSMs) are reconstructed by mapping the STWIP measured MP signatures to the registered MP coordinates. Further, a long short-term memory (LSTM) neural network is developed for estimating the layer surface topography from the registered MPSMs. The obtained results indicate that the layer surface topography can be more accurately estimated by using MP temperature signature rather than MP intensity and/or area signatures as in common practice. Finally, our developed methods for MP monitoring, registration, and MP-surface topography prediction offer advanced capabilities for the online detection of process anomalies and part defects.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Dielectric Properties of Water Ice, the Ice Ih/XI Phase Transition, and an Assessment of Density Functional Theory

The dielectric properties of the hydrogen disordered hexagonal phase (Ih) of water ice have been computed using density functional theory (DFT) based Monte Carlo simulations in the isobaric–isothermal ensemble. Temperature dependent data yield a fit for the Curie–Weiss law of the system and hence a prediction of the temperature of the phase transition from the Ih phase to the hydrogen ordered ice XI phase. Direct simulations around the phase transition temperature confirm and refine the predicted phase transition temperatures and provide data for further properties, such as the linear thermal expansion coefficient. Results have been obtained with both hybrid and semilocal density functionals, which yields insight in the performance of the electronic structure method. In particular, the hybrid functional yields significantly more realistic dielectric constants than the semilocal variant, namely ε ≈ 116 as opposed to ε ≈ 151 at 273 K (ε experiment = 95). This can be attributed to the tendency of semilocal functionals to be biased to configurations with a large dipole moment, and their overestimation of the dipole moments of these configurations. This is also reflected in the estimates of the Ih/XI transition temperature, which is 70–80 and 90–100 K for the hybrid and semilocal functional respectively. Finally, DFT based sampling of the millions of configurations necessary for this work has been enabled by a Tree Monte Carlo algorithm, designed for massively parallel computers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

A data-driven approach for retrieving temperatures and abundances in brown dwarf atmospheres

Brown dwarf spectra contain a wealth of information about their molecular abundances, temperature structure, and gravity. We present a new data driven retrieval approach, previously used in planetary atmosphere studies, to extract the molecular abundances and temperature structure from brown dwarf spectra. The approach makes few a priori physical assumptions about the state of the atmosphere. The feasibility of the approach is first demonstrated on a synthetic brown dwarf spectrum. Given typical spectral resolutions, wavelength coverage, and noise, property precisions of tens of percent can be obtained for the molecular abundances and tens to hundreds of K on the temperature profile. The technique is then applied to the well-studied brown dwarf, Gl 570D. From this spectral retrieval, the spectroscopic radius is constrained to be 0.75-0.83 R {sub J}, log (g) to be 5.13-5.46, and T {sub eff} to be between 804 and 849 K. Estimates for the range of abundances and allowed temperature profiles are also derived. The results from our retrieval approach are in agreement with the self-consistent grid modeling results of Saumon et al. This new approach will allow us to address issues of compositional differences between brown dwarfs and possibly their formation environments, disequilibrium chemistry, and missing physics in current grid modeling approaches as well as a many other issues.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1984

Initialization of a mesoscale model for April 10, 1979, using alternative data sources

A 35 km grid limited area mesoscale model was initialized with high density SESAME radiosonde data and high density TIROS-N satellite temperature profiles for April 10, 1979. These data sources were used individually and with low level wind fields constructed from surface wind observations. The primary objective was to examine the use of satellite temperature data for initializing a mesoscale model by comparing the forecast results with similar experiments employing radiosonde data. The impact of observed low level winds on the model forecasts was also investigated with experiments varying the method of insertion. All forecasts were compared with each other and with mesoscale observations for precipitation, mass and wind structure. Several forecasts produced convective precipitation systems with characteristics satisfying criteria for a mesoscale convective complex. High density satellite temperature data and balanced winds can be used in a mesoscale model to produce forecasts which verify favorably with observations.

Kalb, M. W.↗
DOE OSTI2013

Elaboration of the α-model derived from the BCS theory of superconductivity

The single-band α-model of superconductivity (Padamsee et al 1973 J. Low Temp. Phys. 12 387) is a popular model that was adapted from the single-band Bardeen–Cooper–Schrieffer (BCS) theory of superconductivity mainly to allow fits to electronic heat capacity versus temperature T data that deviate from the BCS prediction. The model assumes that the normalized superconducting order parameter Δ(T)/Δ(0) and therefore the normalized London penetration depth λL(T)/λL(0) are the same as in BCS theory, calculated using the BCS value αBCS ≈ 1.764 of α ≡ Δ(0)/kBTc, where kB is The single-band α-model of superconductivity (Padamsee et al 1973 J. Low Temp. Phys. 12 387) is a popular model that was adapted from the single-band Bardeen–Cooper–Schrieffer (BCS) theory of superconductivity mainly to allow fits to electronic heat capacity versus temperature T data that deviate from the BCS prediction. The model assumes that the normalized superconducting order parameter Δ(T)/Δ(0) and therefore the normalized London penetration depth λL(T)/λL(0) are the same as in BCS theory, calculated using the BCS value αBCS ≈ 1.764 of α ≡ Δ(0)/kBTc, where kB is Boltzmann's constant and Tc is the superconducting transition temperature. On the other hand, to calculate the electronic free energy, entropy, heat capacity and thermodynamic critical field versus T, the α-model takes α to be an adjustable parameter. Here we write the BCS equations and limiting behaviors for the superconducting state thermodynamic properties explicitly in terms of α, as needed for calculations within the α-model, and present plots of the results versus T and α that are compared with the respective BCS predictions. Mechanisms such as gap anisotropy and strong coupling that can cause deviations of the thermodynamics from the BCS predictions, especially the heat capacity jump at Tc, are considered. Extensions of the α-model that have appeared in the literature, such as the two-band model, are also discussed. Tables of values of Δ(T)/Δ(0), the normalized London parameter Λ(T)/Λ(0) and λL(T)/λL(0) calculated from the BCS theory using α = αBCS are provided, which are the same in the α-model by assumption. Tables of values of the entropy, heat capacity and thermodynamic critical field versus T for seven values of α, including αBCS, are also presented.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Estimating Electron Temperature and Density Using Van Allen Probe Data: Typical Behavior of Energetic Electrons in the Inner Magnetosphere

Abstract The Earth's inner magnetosphere contains multiple electron populations influenced by different factors. The cold electrons of the plasmasphere, warm plasma that contributes to the ring current, and the relativistic plasma of the radiation belts often seem to behave independently. Using omni‐directional flux and energy measurements from the HOPE and Magnetic Electron Ion Spectrometer instruments aboard the Van Allen Probes, we provide a detailed density and temperature description of the inner magnetosphere, offering a comprehensive statistical analysis of the entire Van Allen Probe era. While number density and temperature data at geosynchronous orbit are available, this study focuses on the warm plasma in the inner magnetosphere . Values of density and temperature are extracted by fitting energy and phase space density to obtain the distribution function. The fitted distributions are related to the zeroth and second moments to estimate the number density and temperature. Analysis has indicated that a two Maxwellian fit is sufficient over a wide range of and that there are two independent plasma populations. The more energetic population has a median number density of approximately and a temperature of around 130 keV, with a temperature peak observed between L * = 4 and L * = 4.5. This population is relatively uniform in magnetic local time (MLT). In contrast, the less energetic warm electron population has a median number density of about and a temperature of 7.4 keV. Strong statistical trends in density and temperature across both L * and MLT are presented, along with potential sources driving these variations.

58 GEOSCIENCES↗
NASA NTRS1986

Initialization of a mesoscale model with satellite derived temperature profiles

The abilities of rawinsonde data and Tiros-N satellite derived temperature profile data to depict mesoscale precipitation accumulation are evaluated. Four mesoscale simulations using combinations of temperature, low-level wind, and low-level wind initialization were performed with the limited area mesoscale prediction system (LAMPS) model. Comparisons of the simulations with operational LFM forecast accumulations reveal that the LAMPS model simulations provide a better depiction of the observed precipitation accumulation than the LFM forecasts, and the satellite temperature profiles produce better mesoscale precipitation accumulation forecasts than the rawinsonde temperature data.

Kalb, Michael W.↗
DOE OSTI2015

Measurements of E-mode polarization and temperature-E-MODE correlation in the cosmic microwave background from 100 square degrees of SPTPOL data

We present measurements of E-mode polarization and temperature-E-mode correlation in the cosmic microwave background using data from the first season of observations with SPTpol, the polarization-sensitive receiver currently installed on the South Pole Telescope (SPT). The observations used in this work cover 100 deg{sup 2} of sky with arcminute resolution at 150 GHz. We report the E-mode angular auto-power spectrum (EE) and the temperature-E-mode angular cross-power spectrum (TE) over the multipole range 500 < ℓ ≤ 5000. These power spectra improve on previous measurements in the high-ℓ (small-scale) regime. We fit the combination of the SPTpol power spectra, data from Planck, and previous SPT measurements with a six-parameter ΛCDM cosmological model. We find that the best-fit parameters are consistent with previous results. The improvement in high-ℓ sensitivity over previous measurements leads to a significant improvement in the limit on polarized point-source power: after masking sources brighter than 50 mJy in unpolarized flux at 150 GHz, we find a 95% confidence upper limit on unclustered point-source power in the EE spectrum of D{sub ℓ}=ℓ(ℓ+1)C{sub ℓ}/2π<0.40 μK{sup 2} at ℓ=3000, indicating that future EE measurements will not be limited by power from unclustered point sources in the multipole range ℓ<3600, and possibly much higher in ℓ.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRSDate not supplied

Evaluation of Climate Fingerprinting Sounder Product (ClimFiSP) Air Temperature and H2O Trends

Climate fingerprinting Sounder Product (ClimFiSP) provides gridded (0.5x0.5) daily skin temperature, surface emissivity, air temperature, water vapor, trace gases, and cloud properties, which derived from IR hyper-spectral radiance measured by AIRS on Aqua and CrIS on SNPP and JPSS series. In this work, the ClimFiSP daily air temperature and H2O were retrieved on 98 pressure levels by applying the spectral fingerprint algorithm on 0.5x0.5 gridded daily mean radiances from Climate Hyperspectral Infrared Radiance Product (CHIRP). CHIRP is a stable climate-quality radiance time series spanning AIRS and CrIS. The air temperature and H2O monthly data and trends were calculated from the more than two decades long CHIRP AIRS data. Troposphere warming and stratosphere cooling can be seen in both ClimFiSP and ERA5 air temperature data. The ClimFiSP air temperature trends are also compared with the MW sounding air temperature trends to validate the ClimFiSP air temperature results. The H2O trends on upper troposphere are evaluated by comparing with the ERA5 H2O trends, and results show a reasonable agreement with two sets of results. The ClimFiSP algorithm provides a unique and fast way to retrieve the spatial-temporal change in climate variables from the corresponding change in radiances, gridded at the same spatial-temporal scale. This greatly facilitates the procession of long-term climate data records.

ClimFiSP↗
DOE OSTI2020

Imaging of Calibrated Defects in Additively Manufactured Materials: Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components

Additive manufacturing (AM, or 3D printing) for commercial nuclear energy applications is an emerging method for cost-efficient manufacturing aimed at replacing aging nuclear reactor parts and reducing costs for new construction. Known material flaws in AM include low-density regions consisting of non-sintered powder, which have to be detected to ensure the safety of long-term performance nuclear reactor components. Currently, limited options are available for nondestructive evaluation (NDE), either during or post manufacturing. As a solution to NDE of AM, we are developing pulsed thermal imaging which is non-contact, one-sided, and scalable to arbitrary size and shape of the AM parts. Pulsed thermography (PT) system utilizes a high intensity flash lamp to rapidly heat surface of sample, and a high sensitivity fast-frame megapixel infrared (IR) camera to capture data of surface temperature variations. The acquired data cube consists of a stack of surface temperature images taken at different times. Information about material internal defects is extracted by analyzing the data cube. This report provides results of preliminary performance evaluation of pulsed thermal imaging capability in detection of imprinted flaws in AM metallic structures. The flaws were introduced into AM parts as imprinted hemispherical low density regions, consisting of trapped un-sintered metallic powder. Specimens for developed for this study consisted of AM stainless steel 316 and Inconel 718 plates. The diameters of imprinted defects varied from 1mm to 8mm, and their depths below the plate flat surface varied between 1mm and 6mm. Pulsed thermal tomography (PTT) processes the measured data cube to obtain 3D reconstructions of material effusivity using a unique inversion algorithm developed at Argonne. PTT has been previously used in imaging of similar size flat bottom hole (FBH) simulated defects in stainless steel 316 and Inconel 718 specimens. In the study involving AM specimens, PTT imaging results have shown that 1mm-diameter defects located 1mm and 2mm below the surface of specimens were detectable. Larger size defects were detectable at greater depth. We also explored an alternative approach to detection of material flaws in PT data cube, which is using neural learning-based approach to blind source separation. Detection of small material defects requires finding features in the data cube which have signal contrast levels approaching sensitivity limit of IR camera. In this study, an optimized Neural Learning based Blind Source Separation (NLBSS) algorithm, including Principal Component Analysis (PCA), and Independent Component Analysis (ICA) is demonstrated to automatically extract principal temporal and spatial features of thermography frames to enhance flaw detection. By using the NLBSS algorithm, material internal defects can be automatically detected. Furthermore, this processing approach compensates for experimental thermal imaging artifacts, such as noise and uneven heating. By merging artificial intelligence with phtotothermics, the NDE system detects internal calibrated defects of various sizes and depths in AM nuclear-grade metallic alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Utah FORGE: Slide-Hold-Slide Experiments on Gneiss at Increased Temperature

Included are data from triaxial, single-inclined-fracture friction experiments. The experiments were performed with slide-hold-slide protocol on Utah FORGE gneiss at increased temperature. With a ~10 MPa normal stress, temperatures vary between experiments from room temperature up to 163 Celsius. Hold times vary during experiment from ~10^1 to ~10^5 seconds. Measured are the frictional response upon reactivation after a hold period, active acoustic data (P-wave velocity and amplitude) and passive acoustic data (acoustic emission occurrence and amplitude). There are two types of datafiles: (1) Datafiles containing the friction data, including the temperature and the active acoustic data measured during the experiment (AEXX_Gneiss_Vp_mixref4). The underscore _Vp means that it includes the Vp or P-wave velocity data, with _mixref meaning that we use a mixed reference point for calculating the P-wave velocity. And (2) the datafiles containing the passive acoustics data, a catalog of the acoustic emissions (AE's) measured during the experiment (AEcatalog_AEXX_runX), where AEXX matches the experiment number and runX denotes which part of the experiment the data was collected, matching the times where active acoustic data was collected. AE catalogs are split in two parts when the file size exceeds 1 GB to aid download/opening times.

15 GEOTHERMAL ENERGY↗
NASA NTRS1981

Correlation of spacecraft passive microwave system data with soil moisture indices (API)

Electrical scanning microwave radiometer brightness temperature, meteorological data, climatological data, and winter wheat crop information were used to estimate that soil moisture content in the Great Plains region. Results over the predominant winter wheat areas indicate that the best potential to infer soil moisture occurs during fall and spring. These periods encompass the growth stages when soil moisture is most important to winter wheat yield. Other significant results are reported.

Blanchard, B. J.↗
DOE OSTI2014

Small Specimen Data from a High Temperature HFIR Irradiation Experiment

The HTV capsule is a High Flux Isotope Reactor (HFIR) target-rod capsule designed to operate at very high temperatures. The graphite containing section of the capsule (in core) is approximately 18 inches (457.2 mm) long and is separated into eight temperature zones. The specimen diameters within each zone are set to achieve the desired gas gap and hence design temperature (900 C, 1200 C or 1500 C). The capsule has five zones containing 0.400 inch (10.16 mm) diameter specimens, two zones containing 0.350 inch (8.89 mm) diameter specimens and one zone containing 0.300 inch (7.62 mm) diameter specimens. The zones have been distributed within the experiment to optimize the gamma heating from the HFIR core as well as minimize the axial heat flow in the capsule. Consequently, there are two 900 C zones, three 1200 C zones, and three 1500 C zones within the HTV capsule. Each zone contains nine specimens 0.210 0.002 inches (5.334 mm) in length. The capsule will be irradiated to a peak dose of 3.17 displacements per atom. The HTV specimens include samples of the following graphite grades: SGL Carbon s NBG-17 and NBG-18, GrafTech s PCEA, Toyo Tanso s IG-110, Mersen s 2114 and the reference grade H-451 (SGL Carbon). As part of the pre-irradiation program the specimens were characterized using ASTM Standards C559 for bulk density, and ASTM C769 for approximate Young s modulus from the sonic velocity. The probe frequency used for the determination of time of flight of the ultrasonic signal was 2.25 MHz. Marked volume (specimen diameter) effects were noted for both bulk density (increased with increasing specimen volume or diameter) and Dynamic Young s modulus (decreased with increasing specimen volume or diameter). These trends are extended by adding the property vs. diameter data for unirradiated AGC-1 creep specimens (nominally 12.5 mm-diameter x 25.4 mm-length). The relatively large reduction in Dynamic Young s Modulus was surprising given the trend for increasing density with increasing volume. The graphite-filler particle size was noted to be influential in the volume dependency data, with finer grained graphites showing the least specimen volume/diameter effect. Here the volume dependency trends are discussed in terms of the graphite s filler-particle size and texture.

graphite↗
DOE OSTI2016

Equation of state for QCD at finite temperature and density. Resummation versus lattice data

The perturbative series for finite-temperature field theories has very poor convergence properties and one needs a way to reorganize it. In this talk, I review two ways of reorganizing the perturbative series for field theories at finite temperature and chemical potential, namely hard-thermal-loop perturbation theory (HTLpt) and dimensional reduction (DR). I will present results for the pressure, trace anomaly, speed of sound, and the quark susceptibilities from a 3-loop HTLpt calculation and for the quark susceptibilities using DR at four loops. A careful comparison with available lattice data shows good agreement for a number of physical quantities.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗