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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Investigation of heat transport using directly driven gold spheres

Recently, heat transport was investigated using a directly driven beryllium sphere [Farmer et al., Phys. Plasmas 27, 082701 (2020)]. Models that overly restrict heat transport were rejected. This paper extends work to directly driven gold spheres where radiation loss is more important. Here, gold coated spheres are directly driven at the OMEGA laser facility at intensities of 5×10 14 W/cm 2 . Plasma conditions, laser coupling, and x-ray flux are all measured. Additionally, comparisons to 2D radiation-hydrodynamic simulations are performed. Simulations use three common heat transport models: local transport with flux limiters of f = 0.15 and f = 0.03, and the nonlocal Schurtz–Nicolai–Busquet (SNB) model. It is shown that both the SNB model and f = 0.15 match the measured plasma conditions with the SNB model better capturing the temporal evolution of electron temperature. The f = 0.03 model predicts too low of an electron density and too hot of a temperature. The measured scattered light is roughly 6% of the incident energy, the f = 0.15 and SNB models predict 0.5% uncoupled light, and f = 0.03, 38% uncoupled light. The x-ray fluxes in the f = 0.15 and SNB simulations rise too quickly and are just outside the measurement's error, while the x-ray flux in the f = 0.03 simulation is low by a factor of two-three. For these reasons, the f = 0.03 model is rejected.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Galaxy blending effects in deep imaging cosmic shear probes of cosmology

ABSTRACT Upcoming deep imaging surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time will be confronted with challenges that come with increased depth. One of the leading systematic errors in deep surveys is the blending of objects due to higher surface density in the more crowded images; a considerable fraction of the galaxies which we hope to use for cosmology analyses will overlap each other on the observed sky. In order to investigate these challenges, we emulate blending in a mock catalogue consisting of galaxies at a depth equivalent to 1.3 yr of the full 10-yr Rubin Observatory that includes effects due to weak lensing, ground-based seeing, and the uncertainties due to extraction of catalogues from imaging data. The emulated catalogue indicates that approximately 12 per cent of the observed galaxies are ‘unrecognized’ blends that contain two or more objects but are detected as one. Using the positions and shears of half a billion distant galaxies, we compute shear–shear correlation functions after selecting tomographic samples in terms of both spectroscopic and photometric redshift bins. We examine the sensitivity of the cosmological parameter estimation to unrecognized blending employing both jackknife and analytical Gaussian covariance estimators. An ∼0.025 decrease in the derived structure growth parameter S8 = σ8(Ωm/0.3)0.5 is seen due to unrecognized blending in both tomographies with a slight additional bias for the photo-z-based tomography. This bias is greater than the 2σ statistical error in measuring S8.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

A Dynamically-Reconfigurable Burst-Mode Link Using a Nanosecond Photonic Switch

Fast optical circuit switching has great potential to solve scaling issues with traditional packet-switch based networks and improve bandwidth and power efficiency in datacenter and high-performance computing applications. One difficultly in utilizing a fast optical switch is that the optical signal must be rapidly reacquired after each switching event so as to not significantly impact the overall throughput of the system. In this work we present a system-level integration of a nanosecond-scale $2 \times 2$ silicon photonic switch with a 25-Gbps burst-mode receiver that can lock in 31 ns. A novel FPGA-based control plane was used to generate test data, control the silicon photonic switch and burst-mode receiver, and measure bit errors at 12.5 and 20 Gbps. Error-free links (BER $< 10^{-12}$ ) with system-level reconfiguration times below 60 ns (at 20 Gbps) and 90 ns (at 12.5 Gbps) including bit- and frame-synchronization are demonstrated.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Melting point of group IV and V transition metal diborides

The environmental conical nozzle levitator system enables cooling trace experiments above 4000 K. These cooling trace experiments were used to determine the melting points through observation of thermal arrest of group IV and V transition metal diborides (TiB 2 , T m = 3313 ± 33 K; ZrB 2 , T m = 3404 ± 38 K; HfB 2 , T m = 3529 ± 33 K; and TaB 2 , T m = 3284 ± 10 K; note: mean ± 2 standard error). Temperature measurements were conducted utilizing dual single-color pyrometers at wavelengths of 0.9 and 0.65 µm. This system utilizes aerodynamic levitation and dual laser heating to achieve temperatures approaching 4000 K. The samples were synthesized from commercial powders using ceramic gel-casting to produce high-density spherical components. The measurements obtained were compared to previously reported melting temperature values and were generally found to be in agreement with most of the published values.

Materials science↗
DOE OSTI2024

Simulating Single Qubit Random

Single qubit RB is used to measure the error of gates via average gate fidelity. A single qubit RB program was made to calculate this. To filter out potential hardware issues, RB was executed through creating a simulator. Upon simulating both noisy and noise-less gates, we determined that there is a mix of both hardware and program issues.

Anguiano, Efren↗
DOE OSTI2024

Super Resolving Unrolled Neural Networks for Remote Sensing

In remote sensing systems, the capabilities of the system are constrained by the complex interactions between size, weight, and power (SWAP) of potential designs. In electro-optical (EO) systems, examples of these critical parameters include the system’s sensitivity and resolution. Those parameters can be increased by ever larger optical apertures and focal planes but at the cost of more SWAP. Multi-image super resolution (MISR) techniques allow resolution to be enhanced via computation rather than more sophisticated optical hardware. These algorithms combine multiple images together into a single, higher resolution image, trading temporal resolution and computation for spatial resolution. Fielded MISR techniques, such as Drizzle, can require several hundred images to create a single super resolved image, implying reduced temporal resolution, increased data acquisition load, and limiting mission applications. Iterative techniques, such as model-based image reconstruction and compressive sensing, have been shown to create super resolved images using fewer images than Drizzle. They do this by posing an optimization problem that balances accuracy between a highly accurate physical model and an image model. In the case of super resolution, the physical model is defined by the relation between low resolution input images and the desired high resolution output image. The image model encodes some assumptions about the super resolved image. These assumptions are meant to suppress reconstruction artifacts that arise due to deterministic physical model error, stochastic measurement noise, and potential undersampling. In practice, the performance of iterative methods are limited by imaging models compatible with optimization. Deep learning-based methods can effectively learn image models of arbitrary complexity, but lack the theoretical explainability and robustness of iterative techniques. Consensus equilibrium (CE) generalizes the iterative techniques beyond optimization, enabling blackbox algorithms such as traditional and neural image denoisers to be used as the image model. CE-based approaches retain much of the explainability and robustness of iterative techniques while allowing the expressiveness of machine learning image models to be used. Additionally, by unrolling iterations of CE with an embedded image denoiser, the image denoiser can be further trained and specialized to the specific application with potentially higher quality reconstructions. Under this project, we demonstrated the feasibility of training an unrolled neural network based upon CE. While we didn’t train one, we showed that the CE process is differentiable and its gradient can be tractably computed. We also explored the usage of a variants of CE akin to generative neural works. Most importantly, we applied the CE framework to a number of problems including non-blind deconvolution, upsampling, single-image super resolution, MISR, event-based sensing, and saturated deconvolution. Our MISR prototype creates high quality reconstructions with an order of magnitude fewer images than previous approaches and, critically, produces these reconstructions fast enough for practical usage.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

GLEAM: Galaxy Line Emission & Absorption Modeling

We present Galaxy Line Emission & Absorption Modeling (gleam), a Python tool for fitting Gaussian models to emission and absorption lines in large samples of 1D extragalactic spectra. gleam is tailored to work well in batch mode without much human interaction. With gleam, users can uniformly process a variety of spectra, including galaxies and active galactic nuclei, in a wide range of instrument setups and signal-to-noise regimes. gleam also takes advantage of multiprocessing capabilities to process spectra in parallel. With the goal of enabling reproducible workflows for its users, gleam employs a small number of input files, including a central, user-friendly configuration in which fitting constraints can be defined for groups of spectra and overrides can be specified for edge cases. For each spectrum, gleam produces a table containing measurements and error bars for the detected spectral lines and continuum and upper limits for nondetections. For visual inspection and publishing, gleam can also produce plots of the data with fitted lines overlaid. In the present paper, we describe gleam’s main features, the necessary inputs, expected outputs, and some example applications, including thorough tests on a large sample of optical/infrared multi-object spectroscopic observations and integral field spectroscopic data. gleam is developed as an open-source project hosted at https://github.com/multiwavelength/gleam and welcomes community contributions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Methods for Incorporating Model Uncertainty into Exoplanet Atmospheric Analysis

A key goal of exoplanet spectroscopy is to measure atmospheric properties, such as abundances of chemical species, in order to connect them to our understanding of atmospheric physics and planet formation. In this new era of high-quality JWST data, it is paramount that these measurement methods are robust. When comparing atmospheric models to observations, multiple candidate models may produce reasonable fits to the data. Typically, conclusions are reached by selecting the best-performing model according to some metric. This ignores model uncertainty in favor of specific model assumptions, potentially leading to measured atmospheric properties that are overconfident and/or incorrect. In this paper, we compare three ensemble methods for addressing model uncertainty by combining posterior distributions from multiple analyses: Bayesian model averaging, a variant of Bayesian model averaging using leave-one-out predictive densities, and stacking of predictive distributions. We demonstrate these methods by fitting the Hubble Space Telescope (HST) + Spitzer transmission spectrum of the hot Jupiter HD 209458b using models with different cloud and haze prescriptions. All of our ensemble methods lead to uncertainties on retrieved parameters that are larger but more realistic and consistent with physical and chemical expectations. Since they have not typically accounted for model uncertainty, uncertainties of retrieved parameters from HST spectra have likely been underreported. We recommend stacking as the most robust model combination method. Our methods can be used to combine results from independent retrieval codes and from different models within one code. They are also widely applicable to other exoplanet analysis processes, such as combining results from different data reductions.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1972

Emitter surface temperature distribution for a miniature thermionic diode

Brightness temperatures have been observed from five hohlraums equally spaced on a diameter of a 0.635 cm thermionic emitter surface. The hohlraums are 0.0381 cm in diameter and are 0.114 cm deep. The surface was mounted in a simulated diminiode geometry and was heated from the backside, according to the design, by electron bombardment. Several temperature observations were made at each hohlraum at four different levels of input power. Within experimental error no measurable temperature gradients across the emitter surface were observed at any input power level.

Lancashire, R. B.↗
NASA NTRS1973

Evaluate ERTS imagery for mapping and detection of changes of snowcover on land and on glaciers

The author has identified the following significant results. The standard error of measurement of snow covered areas in major drainage basins in the Cascade Range, Washington, using single measurements of ERTS-1 images, was found to range from 11% to 7% during a typical melt season, but was as high as 32% in midwinter. Many dangerous glacier situations in Alaska, Yukon, and British Columbia were observed on ERTS-1 imagery. Glacier dammed lakes in Alaska are being monitored by ERTS-1. Embayments in tidal glaciers show changes detectable by ERTS-1. Surges of Russell and Tweedsmuir Glaciers, now in progress, are clearly visible. The Tweedsmuir surge is likely to dam the large Alsek River by mid-November, producing major floods down-river next summer. An ERTS-1 image of the Pamir Mountains, Tadjik S.S.R., shows the surging Medvezhii (Bear) Glacier just after its surge of early summer which dammed the Abdukagor Valley creating a huge lake and later a flood in the populous Vanch River Valley. A map was compiled from an ERTS-1 image of the Lowell Glacier after its recent surge, compared with an earlier map compiled from pain-stakingly compiled from a mosaic of many aerial photographs, in a total elapsed time of 1.5 hours. This demonstrates the value of ERTS-1 for rapid mapping of large features.

Meier, M. F.↗
NASA NTRS1974

An elementary magnetic attitude control system

A three-axis closed-loop attitude-control system for earth-observatory momentum-bias spacecraft is proposed. A horizon scanner and magnetometer are employed to measure attitude errors; no yaw sensor is required. Appropriate control signals are generated and used to command variable-strength electromagnets, which interact with the geomagnetic field to reduce observed errors. This system provides for initial acquisition, precession control, nutation damping, and pitch-axis momentum control. All functions are performed autonomously - no ground-station interaction is required. Analytical expressions predicting system response are compared with numerical solutions of the governing equations, and with the results of the application of Floquet Theory.-

Stickler, A. C.↗
NASA NTRS1975

Error analysis of Dobson spectrophotometer measurements of the total ozone content

A study of techniques for measuring atmospheric ozone is reported. This study represents the second phase of a program designed to improve techniques for the measurement of atmospheric ozone. This phase of the program studied the sensitivity of Dobson direct sun measurements and the ozone amounts inferred from those measurements to variation in the atmospheric temperature profile. The study used the plane - parallel Monte-Carlo model developed and tested under the initial phase of this program, and a series of standard model atmospheres.

Holland, A. C.↗
NASA NTRS1975

GRAVSAT/GEOPAUSE covariance analysis including geopotential aliasing

A conventional covariance analysis for the GRAVSAT/GEOPAUSE mission is described in which the uncertainties of approximately 200 parameters, including the geopotential coefficients to degree and order 12, are estimated over three different tracking intervals. The estimated orbital uncertainties for both GRAVSAT and GEOPAUSE reach levels more accurate than presently available. The adjusted measurement bias errors approach the mission goal. Survey errors in the low centimeter range are achieved after ten days of tracking. The ability of the mission to obtain accuracies of geopotential terms to (12, 12) one to two orders of magnitude superior to present accuracy levels is clearly shown. A unique feature of this report is that the aliasing structure of this (12, 12) field is examined. It is shown that uncertainties for unadjusted terms to (12, 12) still exert a degrading effect upon the adjusted error of an arbitrarily selected term of lower degree and order. Finally, the distribution of the aliasing from the unestimated uncertainty of a particular high degree and order geopotential term upon the errors of all remaining adjusted terms is listed in detail.

Koch, D. W.↗