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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Recovered supernova Ia rate from simulated LSST images

Aims.TheVera C. RubinObservatory’s Legacy Survey of Space and Time (LSST) will revolutionize time-domain astronomy by detecting millions of different transients. In particular, it is expected to increase the number of known type Ia supernovae (SN Ia) by a factor of 100 compared to existing samples up to redshift ∼1.2. Such a high number of events will dramatically reduce statistical uncertainties in the analysis of the properties and rates of these objects. However, the impact of all other sources of uncertainty on the measurement of the SN Ia rate must still be evaluated. The comprehension and reduction of such uncertainties will be fundamental both for cosmology and stellar evolution studies, as measuring the SN Ia rate can put constraints on the evolutionary scenarios of different SN Ia progenitors. Methods.We used simulated data from the Dark Energy Science Collaboration (DESC) Data Challenge 2 (DC2) and LSST Data Preview 0 to measure the SN Ia rate on a 15 deg 2 region of the “wide-fast-deep” area. We selected a sample of SN candidates detected in difference images, associated them to the host galaxy with a specially developed algorithm, and retrieved their photometric redshifts. We then tested different light-curve classification methods, with and without redshift priors (albeit ignoring contamination from other transients, as DC2 contains only SN Ia). We discuss how the distribution in redshift measured for the SN candidates changes according to the selected host galaxy and redshift estimate. Results.We measured the SN Ia rate, analyzing the impact of uncertainties due to photometric redshift, host-galaxy association and classification on the distribution in redshift of the starting sample. We find that we are missing 17% of the SN Ia, on average, with respect to the simulated sample. As 10% of the mismatch is due to the uncertainty on the photometric redshift alone (which also affects classification when used as a prior), we conclude that this parameter is the major source of uncertainty. We discuss possible reduction of the errors in the measurement of the SN Ia rate, including synergies with other surveys, which may help us to use the rate to discriminate different progenitor models.

Astronomy & Astrophysics↗
NASA NTRS2023

Users' Guide to Vinci: Personal Computer Software for Planning Image-based Measurements in Wind Tunnels

Vinci is software that can be used to plan image-based measurements in wind tunnels. It allows the user to plan the placement of cameras and the choice of lenses well in advance of a test, thereby reducing the set-up time and cost when tunnel occupancy begins. It can also be used post-test to display data (pressure-sensitive paint, particle image velocimetry, model deformation) in context with the test article. Vinci is self-contained and runs on personal computers under Windows operating systems. No other software is required. Test articles are represented by CFD-like surface grids that may be read from an external file or created within the program as a combination of simple geometric shapes. The user controls the position and orientation of the test article through a Graphical User Interface (GUI) and may add many additional objects, including tunnel walls and windows, a wide variety of simple geometric shapes, mirrors, lamps, and laser sheets. The application computes simulated images from up to 40 cameras. Images are based on pinhole projection. Each camera is defined by the sensor size and the focal length of the lens. All camera parameters, including position and point angles, are controlled through the GUI. Simulated images are displayed in a window of the GUI and may be saved as bitmaps.

Users’ Guide, Image Planning, Wind Tunnels, Softwa↗
NASA NTRS1982

Finding the lost river gas field - Lineament density analysis in hydrocarbon exploration

A comparative trial analysis of lineament density in 1:500,000 Landsat and 1:48,000 aerial Landsat-simulator images of a gas-field region in West Virginia is presented. The high-contrast, band 4, 5, 7 color composite Landsat image was interpreted independently by two analysts. The slightly different lineament maps were evaluated in terms of lineament-density variation in 10 x 10-km areas, and the resulting areal-variation maps are found to be statistically equivalent. High lineament density is shown to be associated with productive gas wells. Comparison of ground-based substructural contour maps and lineament-density analyses of the Landsat-simulator images reveals good correlation between density maxima or isopleths and substructural features associated with hydrocarbon formations. A hydrocarbon-exploration strategy using both Landsat and aerial images is proposed.

Lang, H. R.↗
DOE OSTI2023

Dark Energy Survey Year 3 results: magnification modelling and impact on cosmological constraints from galaxy clustering and galaxy–galaxy lensing

We study the effect of magnification in the Dark Energy Survey Year 3 analysis of galaxy clustering and galaxy–galaxy lensing, using two different lens samples: a sample of luminous red galaxies, redMaGiC, and a sample with a redshift-dependent magnitude limit, MagLim. We account for the effect of magnification on both the flux and size selection of galaxies, accounting for systematic effects using the Balrog image simulations. We estimate the impact of magnification on the galaxy clustering and galaxy–galaxy lensing cosmology analysis, finding it to be a significant systematic for the MagLim sample. We show cosmological constraints from the galaxy clustering autocorrelation and galaxy–galaxy lensing signal with different magnifications priors, finding broad consistency in cosmological parameters in ΛCDM and wCDM. However, when magnification bias amplitude is allowed to be free, we find the two-point correlation functions prefer a different amplitude to the fiducial input derived from the image simulations. We validate the magnification analysis by comparing the cross-clustering between lens bins with the prediction from the baseline analysis, which uses only the autocorrelation of the lens bins, indicating that systematics other than magnification may be the cause of the discrepancy. We show that adding the cross-clustering between lens redshift bins to the fit significantly improves the constraints on lens magnification parameters and allows uninformative priors to be used on magnification coefficients, without any loss of constraining power or prior volume concerns.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Prospects for Cherenkov Telescope Array Observations of the Young Supernova Remnant RX J1713.7−3946

We perform simulations for future Cherenkov Telescope Array (CTA) observations of RX J1713.7−3946, a young supernova remnant (SNR) and one of the brightest sources ever discovered in very high energy (VHE) gamma rays. Special attention is paid to exploring possible spatial (anti)correlations of gamma rays with emission at other wavelengths, in particular X-rays and CO/H i emission. We present a series of simulated images of RX J1713.7−3946 for CTA based on a set of observationally motivated models for the gamma-ray emission. In these models, VHE gamma rays produced by high-energy electrons are assumed to trace the nonthermal X-ray emission observed by XMM-Newton , whereas those originating from relativistic protons delineate the local gas distributions. The local atomic and molecular gas distributions are deduced by the NANTEN team from CO and H i observations. Our primary goal is to show how one can distinguish the emission mechanism(s) of the gamma rays (i.e., hadronic versus leptonic, or a mixture of the two) through information provided by their spatial distribution, spectra, and time variation. This work is the first attempt to quantitatively evaluate the capabilities of CTA to achieve various proposed scientific goals by observing this important cosmic particle accelerator.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Optimal 1D Ly α forest power spectrum estimation – III. DESI early data

ABSTRACT The 1D power spectrum P1D of the Ly α forest provides important information about cosmological and astrophysical parameters, including constraints on warm dark matter models, the sum of the masses of the three neutrino species, and the thermal state of the intergalactic medium. We present the first measurement of P1D with the quadratic maximum likelihood estimator (QMLE) from the Dark Energy Spectroscopic Instrument (DESI) survey early data sample. This early sample of 54 600 quasars is already comparable in size to the largest previous studies, and we conduct a thorough investigation of numerous instrumental and analysis systematic errors to evaluate their impact on DESI data with QMLE. We demonstrate the excellent performance of the spectroscopic pipeline noise estimation and the impressive accuracy of the spectrograph resolution matrix with 2D image simulations of raw DESI images that we processed with the DESI spectroscopic pipeline. We also study metal line contamination and noise calibration systematics with quasar spectra on the red side of the Ly α emission line. In a companion paper, we present a similar analysis based on the Fast Fourier Transform estimate of the power spectrum. We conclude with a comparison of these two approaches and discuss the key sources of systematic error that we need to address with the upcoming DESI Year 1 analysis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

In-cylinder spray evolution in a motored central-injection gasoline engine: Imaging and simulating the effects of flash-boiling and intake crossflow

Accurate predictions of fuel spray behavior and mixture formation in simulations of direct-injection spark-ignition (DISI) engines are fundamental to ensure proper description of all subsequent processes including ignition, combustion, and emissions. In this work, the spray evolution in a single-cylinder optical DISI engine was studied experimentally and numerically with the goal of enabling predictive computational fluid dynamics (CFD) modeling of in-cylinder sprays. The authors explored a wide range of operating conditions characterized by several fuel injection temperatures and engine speeds, using a well-characterized nine-component gasoline surrogate known as PACE-20. The effect of flash boiling and intake crossflow on the spray is discussed, with a focus on evaluating the ability of the spray models to capture highly transient spray behavior. In the experiments, the fuel temperature was varied between 20°C and 80°C, allowing for non-flash- to flash-boiling transition to emerge with enhanced flashing intensity at the highest temperatures. Spray collapse resulted in vapor-rich regions, owing to the locally lower inertia of the fluid. Varying the engine speed from 650 to 1950 rpm promoted increasingly more turbulent in-cylinder crossflow which interacted with the spray during the injection event and resulted in enhanced spray dispersion. The CFD model was able to capture the spray morphology transition at different fuel temperatures and engine speeds adequately. Further, it is shown that the spray breakup model could capture the transitional spray behavior induced by flash boiling atomization and intake flow via proper initialization of the spray cone angle and calibration of the spray models’ constants.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Testing the LSST Difference Image Analysis Pipeline Using Synthetic Source Injection Analysis

Abstract We evaluate the performance of the Legacy Survey of Space and Time Science Pipelines Difference Image Analysis (DIA) on simulated images. By adding synthetic sources to galaxies on images, we trace the recovery of injected synthetic sources to evaluate the pipeline on images from the Dark Energy Science Collaboration Data Challenge 2. The pipeline performs well, with efficiency and flux accuracy consistent with the signal-to-noise ratio of the input images. We explore different spatial degrees of freedom for the Alard–Lupton polynomial-Gaussian image subtraction kernel and analyze for trade-offs in efficiency versus artifact rate. Increasing the kernel spatial degrees of freedom reduces the artifact rate without loss of efficiency. The flux measurements with different kernel spatial degrees of freedom are consistent. We also here provide a set of DIA flags that substantially filter out artifacts from the DIA source table. We explore the morphology and possible origins of the observed remaining subtraction artifacts and suggest that given the complexity of these artifact origins, a convolution kernel with a set of flexible bases with spatial variation may be needed to yield further improvements.

Liu, S. (ORCID:0000000244612143)↗
NASA NTRS1997

Recovery of motion parameters from distortions in scanned images

Scanned images, such as those produced by the scanning-laser ophthalmoscope (SLO), show distortions when there is target motion. This is because pixels corresponding to different image regions are acquired sequentially, and so, in essence, are slices of different snapshots. While these distortions create problems for image registration algorithms, they are potentially useful for recovering target motion parameters at temporal frequencies above the frame rate. Stetter, Sendtner and Timberlake measured large distortions in SLO images to recover the time course of rapid horizontal saccadic eye movements. Here, this work is extended with the goal of automatically recovering small eye movements in two dimensions. Eye position during the frame interval is modeled using a low dimensional parametric description, which in turn is used to generate predicted distortions of a reference template. The input image is then registered to the distorted template using normalized cross correlation. The motion parameters are then varied, and the correlation recomputed, to find the motion which maximizes the peak value of the correlation. The location and value of the correlation maximum are determined with sub-pixel precision using biquadratic interpolation, yielding eye position resolution better than 1 arc minute. This method of motion parameter estimation is tested using actual SLO images as well as simulated images. Motion parameter estimation might also be applied to individual video lines in order to reduce pipeline delays for a near real-time system.

Mulligan, Jeffrey B.↗