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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Spitzer secondary eclipses of the dense, modestly-irradiated, giant exoplanet HAT-P-20b using pixel-level decorrelation

HAT-P-20b is a giant metal-rich exoplanet orbiting a metal-rich star. We analyze two secondary eclipses of the planet in each of the 3.6 and 4.5 μm bands of Warm Spitzer. We have developed a simple, powerful, and radically different method to correct the intra-pixel effect for Warm Spitzer data, which we call pixel-level decorrelation (PLD). PLD corrects the intra-pixel effect very effectively, but without explicitly using—or even measuring—the fluctuations in the apparent position of the stellar image. We illustrate and validate PLD using synthetic and real data and comparing the results to previous analyses. PLD can significantly reduce or eliminate red noise in Spitzer secondary eclipse photometry, even for eclipses that have proven to be intractable using other methods. Our successful PLD analysis of four HAT-P-20b eclipses shows a best-fit blackbody temperature of 1134 ± 29 K, indicating inefficient longitudinal transfer of heat, but lacking evidence for strong molecular absorption. We find sufficient evidence for variability in the 4.5 μm band that the eclipses should be monitored at that wavelength by Spitzer, and this planet should be a high priority for James Webb Space Telescope spectroscopy. All four eclipses occur about 35 minutes after orbital phase 0.5, indicating a slightly eccentric orbit. A joint fit of the eclipse and transit times with extant RV data yields ecosω=0.01352{sub −0.00057}{sup +0.00054} and establishes the small eccentricity of the orbit to high statistical confidence. HAT-P-20b is another excellent candidate for orbital evolution via Kozai migration or other three-body mechanisms.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2015

Estimates of Power Plant NOx Emissions and Lifetimes from OMI NO2 Satellite Retrievals

Isolated power plants with well characterized emissions serve as an ideal test case of methods to estimate emissions using satellite data. In this study we evaluate the Exponentially-Modified Gaussian (EMG) method and the box model method based on mass balance for estimating known NOx emissions from satellite retrievals made by the Ozone Monitoring Instrument (OMI). We consider 29 power plants in the USA which have large NOx plumes that do not overlap with other sources and which have emissions data from the Continuous Emission Monitoring System (CEMS). This enables us to identify constraints required by the methods, such as which wind data to use and how to calculate background values. We found that the lifetimes estimated by the methods are too short to be representative of the chemical lifetime. Instead, we introduce a separate lifetime parameter to account for the discrepancy between estimates using real data and those that theory would predict. In terms of emissions, the EMG method required averages from multiple years to give accurate results, whereas the box model method gave accurate results for individual ozone seasons.

Emissions inventory↗
DOE OSTI2016

Evaluation of wetland methane emissions across North America using atmospheric data and inverse modeling

Existing estimates of methane (CH 4 ) fluxes from North American wetlands vary widely in both magnitude and distribution. In light of these differences, this study uses atmospheric CH 4 observations from the US and Canada to analyze seven different bottom-up, wetland CH 4 estimates reported in a recent model comparison project. We first use synthetic data to explore whether wetland CH 4 fluxes are detectable at atmospheric observation sites. We find that the observation network can detect aggregate wetland fluxes from both eastern and western Canada but generally not from the US. Based upon these results, we then use real data and inverse modeling results to analyze the magnitude, seasonality, and spatial distribution of each model estimate. The magnitude of Canadian fluxes in many models is larger than indicated by atmospheric observations. Many models predict a seasonality that is narrower than implied by inverse modeling results, possibly indicating an oversensitivity to air or soil temperatures. The LPJ-Bern and SDGVM models have a geographic distribution that is most consistent with atmospheric observations, depending upon the region and season. Lastly, these models utilize land cover maps or dynamic modeling to estimate wetland coverage while most other models rely primarily on remote sensing inundation data.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

High-resolution processing of long-pulse-lidar data

The purpose of this work is to demonstrate the performance of the Fourier-deconvolution technique developed to improve the resolution of the long-pulse coherent lidar power profile, and to take into account the multiplicative fluctuations. The behavior of the error due to the power fluctuations and a method to reduce it are analyzed theoretically and simulated numerically. A processing of real data obtained from the National Oceanic and Atmospheric Administration (NOAA) ground-based Doppler lidar is also presented. Similar problems were investigated using a different approach based on introducing a correction function to the lidar equation.

Gurdev, L. L.↗
DOE OSTI2022

Discovering Ca II absorption lines with a neural network

Quasar absorption line analysis is critical for studying gas and dust components and their physical and chemical properties as well as the evolution and formation of galaxies in the early universe. Calcium II (Ca II ) absorbers, which are one of the dustiest absorbers and are located at lower redshifts than most other absorbers, are especially valuable when studying physical processes and conditions in recent galaxies. However, the number of known quasar Ca II absorbers is relatively low due to the difficulty of detecting them with traditional methods. In this work, we developed an accurate and quick approach to search for Ca II absorption lines using deep learning. In our deep learning model, a convolutional neural network, tuned using simulated data, is used for the classification task. The simulated training data are generated by inserting artificial Ca II absorption lines into original quasar spectra from the Sloan Digital Sky Survey (SDSS), while an existing Ca II catalogue is adopted as the test set. The resulting model achieves an accuracy of 96 per cent on the real data in the test set. Our solution runs thousands of times faster than traditional methods, taking a fraction of a second to analyse thousands of quasars, while traditional methods may take days to weeks. The trained neural network is applied to quasar spectra from SDSS’s DR7 and DR12 and discovered 399 new quasar Ca II absorbers. In addition, we confirmed 409 known quasar Ca II absorbers identified previously by other research groups through traditional methods.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Model-Based Iterative Reconstruction of Magnetization Using Vector Field Electron Tomography

Vector field electron tomography (VFET) is extensively used for three-dimensional (3-D) imaging of magnetic materials at nanometer resolutions. The conventional approach is to reconstruct and visualize the magnetic vector potential or the magnetic field associated with the sample. There is a lack of algorithms capable of reconstructing the 3-D distribution of magnetization from VFET data. Unlike magnetic vector potential and magnetic field, magnetization is a fundamental physical property of the sample that does not extend beyond the dimensions of the sample. We present a model-based iterative reconstruction algorithm (MBIR) that reconstructs the magnetization by minimizing a cost function consisting of a forward model term and a prior model term. The forward model uses the physics of imaging to model the VFET data as a function of the magnetization, and the prior model enforces sparsity in the magnetization reconstruction. We then formulate an optimization algorithm based on the theory of alternate direction method of multipliers to minimize the resulting MBIR cost function. In conclusion, using simulated and real data, we show that our algorithm accurately reconstructs both the magnetization and the magnetic vector potential.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A review of NEST models for liquid xenon and an exhaustive comparison with other approaches

This paper discusses the microphysical simulation of interactions in liquid xenon, the active detector medium in many leading rare-event searches for new physics, and describes experimental observables useful for understanding detector performance. The scintillation and ionization yield distributions for signal and background are presented using the Noble Element Simulation Technique (NEST), a toolkit based on experimental data and simple empirical formulas, which mimic previous microphysics modeling but are guided by data. The NEST models for light and charge production as a function of the particle type, energy, and electric field are reviewed, along with models for energy resolution and final pulse areas. NEST is compared with other models or sets of models and validated against real data, with several specific examples drawn from XENON, ZEPLIN, LUX, LZ, PandaX, and table-top experiments used for calibrations.

WIMPs↗
NASA NTRS1979

The use of satellite estimates of rainfall in the initialization of a mesoscale hurricane model

The use of rainfall rate data obtained from satellites to improve the initial specification of the hurricane circulation is discussed with particular reference to the techniques for incorporating rainfall data into high-resolution hurricane models. The variation of latent heating in a numerical model of a steady state tropical cyclone is considered to ascertain what features of the storm motion can be deduced from a given field of latent heat release. A real-data example involving a mesoscale model for hurricane Eloise (1975) has demonstrated that satellite measurements of rainfall may be beneficial to numerical hurricane prediction.

Fiorino, M.↗
DOE OSTI2024

Integrating Multi-Source Data for Bi-Level Traffic Simulator Calibration: A Literature Review and Highway Case Study

Traffic simulation serves as a powerful tool for pre-evaluating policies and technologies. In this context, simulation-based Dynamic traffic assignment (DTA) models are capable of capturing traffic dynamics. They are well-known as critical tools in controlling and predicting traffic situations. The reliability of simulation results heavily depends on the calibration process. Most studies in the literature formulate and calibrate simulators based on a single source of collected data or multiple data sets with the same spatiotemporal characteristics. However, in practice, traffic data is collected by various tools with usually different spatial and temporal resolutions. This study introduces a novel approach to taking into account diverse input data from a variety of sources. An iterative bi-level solution is proposed. to equally treat traffic flow and speed data. The upper level solves flow calibration with the exact solution method, and the lower level calibrates the speed with the simultaneous perturbation stochastic approximation (SPSA) algorithm. Subsequently, the effectiveness of the proposed model is investigated using data from a six-mile section of Nashville's I-24 highway in Tennessee. The results demonstrate that our proposed model creates an effective feedback loop between the optimizer and the simulator for calibrating flow and speed to reduce the error between simulated and real data.

42 ENGINEERING↗
NASA NTRS2004

Wavefront Sensing using a Multi-Object Spectrograph (NIRSpec)

An analysis is presented that illustrates how the JWST fine-phasing process can be carried out using NIRSpec data collected at the science focal plane. The analysis is based on a multi-plane diffraction model which properly accounts for the microshutter diffractive element placed at the first relay position of the spectrograph. Wavefront sensing results are presented based on both simulated as well as real data collected from the NASA Goddard Microshutter Testbed.

Dean, Bruce↗
NASA NTRS2014

Optimizing Vetoes for Gravitational-wave Transient Searches

Interferometric gravitational-wave detectors like LIGO, GEO600 and Virgo record a surplus of information above and beyond possible gravitational-wave events. These auxiliary channels capture information about the state of the detector and its surroundings which can be used to infer potential terrestrial noise sources of some gravitational-wave-like events. We present an algorithm addressing the ordering (or equivalently optimizing) of such information from auxiliary systems in gravitational-wave detectors to establish veto conditions in searches for gravitational-wave transients. The procedure was used to identify vetoes for searches for unmodelled transients by the LIGO and Virgo collaborations during their science runs from 2005 through 2007. In this work we present the details of the algorithm; we also use a limited amount of data from LIGO's past runs in order to examine the method, compare it with other methods, and identify its potential to characterize the instruments themselves. We examine the dependence of Receiver Operating Characteristic curves on the various parameters of the veto method and the implementation on real data. We find that the method robustly determines important auxiliary channels, ordering them by the apparent strength of their correlations to the gravitational-wave channel. This list can substantially reduce the background of noise events in the gravitational-wave data. In this way it can identify the source of glitches in the detector as well as assist in establishing confidence in the detection of gravitational-wave transients.

Transient↗
DOE OSTI2014

New methods for indexing multi-lattice diffraction data

A new indexing method is presented which is capable of indexing multiple crystal lattices from narrow wedges of data. The efficacy of this method is demonstrated with both semi-synthetic multi-lattice data and real multi-lattice data recorded from microcrystals of ∼1 µm in size. A new indexing method is presented which is capable of indexing multiple crystal lattices from narrow wedges of diffraction data. The method takes advantage of a simplification of Fourier transform-based methods that is applicable when the unit-cell dimensions are known a priori. The efficacy of this method is demonstrated with both semi-synthetic multi-lattice data and real multi-lattice data recorded from crystals of ∼1 µm in size, where it is shown that up to six lattices can be successfully indexed and subsequently integrated from a 1° wedge of data. Analysis is presented which shows that improvements in data-quality indicators can be obtained through accurate identification and rejection of overlapping reflections prior to scaling.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Conformal Hierarchical Simulation-Based Inference with Local Validity

Trustworthy and interpretable uncertainty quantification is a long-standing challenge in artificial intelligence. Simulation-based inference (SBI) comprises a broad swath of approaches for estimating latent parameters with uncertainties. Although flexible neural density estimators in SBI can be remark- ably expressive capturing highly structured, high-dimensional posteriors their credible regions can be badly mis-calibrated and are often only accompanied by heuristic coverage checks. We present the first SBI framework that delivers finite-sample local valid coverage guarantees that hold in the neighborhood of each observation. Our framework can couple any off-the-shelf hierarchical SBI engine with a confor- mal Bayesian post-processing step that operates on the posterior predictive density. A kernel-weighted conformity score adapts the conformal quantile to the local geometry of the data, yielding prediction sets that are simultaneously (i) marginally calibrated, (ii) locally valid, and (iii) hierarchical, handling global and observation-specific parameters in a single pass. Through experiments on synthetic data and benchmarks from neuroscience and physics, we show that our approach attains 1 − α coverage, where prior SBI methods under- or over-cover. Our approach also maintains a competitive, credible set size with minimal computational overhead. Finally, our approach can be used to make predictions on real data and give valid credible regions modulo weight-initialization-based model mis-specification.

Trivedi, Shubhendu [Fermilab]↗
DOE OSTI2017

Wayne—A Simulator for HST WFC3 IR Grism Spectroscopy

Wayne is an algorithm that simulates Hubble Space Telescope Wide Field Camera 3 (WFC3) grism spectroscopic frames, including sources of noise and systematics. It can simulate both staring and spatial scan modes, and observations such as the transit and the eclipse of an exoplanet. Unlike many other instrument simulators, the focus of Wayne is on creating frames with realistic systematics in order to test the effectiveness of different data analysis methods in a variety of different scenarios. This approach is critical for method validation and optimizing observing strategies. In this paper we describe the implementation of Wayne for WFC3 in the near-infrared channel with the G102 and G141 grisms. We compare the simulations to real data obtained for the exoplanet HD 209458b, to verify the accuracy of the simulation. The software is now available as open source at https://github.com/ucl-exoplanets/wayne.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2001

Reply to "Comment on the Paper ''On the Determination of Electron Polytrope Indices Within Coronal Mass Ejections in the Solar Wind'"'

We strongly disagree with the essence of the Osherovich (hereafter Osherovich) comment on one of our papers. The following paragraphs provide the basis of our disagreement and elaborate on why we believe that none of the concluding statements in his Comment are true. Our most important point is that one can apply the model developed by Osherovich and colleagues to real data obtained at a single point in space to determine the polytropic index within magnetic clouds if and only if the highly idealized assumptions of that model conform to physical reality. There is good reason to believe that those assumptions do not provide an accurate physical description of real magnetic clouds in the spherically expanding solar wind.

Gosling, J. T.↗
DOE OSTI2021

Real-Time XFEL Data Analysis at SLAC and NERSC: a Trial Run of Nascent Exascale Experimental Data Analysis

X-ray scattering experiments using Free Electron Lasers (XFELs) are a powerful tool to determine the molecular structure and function of unknown samples (such as COVID-19 viral proteins). XFEL experiments are a challenge to computing in two ways: i) due to the high cost of running XFELs, a fast turnaround time from data acquisition to data analysis is essential to make informed decisions on experimental protocols; ii) data collection rates are growing exponentially, requiring new scalable algorithms. Here we report our experiences analyzing data from two experiments at the Linac Coherent Light Source (LCLS) during September 2020. Raw data were analyzed on NERSC's Cori XC40 system, using the Superfacility paradigm: our workflow automatically moves raw data between LCLS and NERSC, where it is analyzed using the software package CCTBX. We achieved real time data analysis with a turnaround time from data acquisition to full molecular reconstruction in as little as 10 min -- sufficient time for the experiment's operators to make informed decisions. By hosting the data analysis on Cori, and by automating LCLS-NERSC interoperability, we achieved a data analysis rate which matches the data acquisition rate. Furthermore, completing data analysis with 10 mins is a first for XFEL experiments and an important milestone if we are to keep up with data collection trends.

Blaschke, Johannes P.↗
DOE OSTI2021

Time-temperature-superposition analysis of diverse datasets by the minimum-arclength method: long-term prediction with uncertainty margins

In a recent publication, we carried out an extensive analysis of an unsupervised method of determining optimum shift factors in time-temperature-superposition of accelerated-aging data that involves minimizing the vertical arclength to obtain the master curve. For synthetic Arrhenius data with a variety of noise distributions, the work showed that, in conjunction with bootstrap-resampling, the method can produce reliable estimates of the mean activation energy along with uncertainty quantification. Here, we apply the above method to six different datasets taken from the published literature and demonstrate accurate prediction of mean activation energy from the data as-is without the need for any pre-processing or fitting. We also compare uncertainty margins computed by second-order bootstrap with that by linear regression theory and show that the former appears to provide consistent margins in the presence of common noise types in real data, including intra-isotherm measurement-errors, sample-to-sample variations, and intrinsic deviation from perfect Arrhenius behavior.

36 MATERIALS SCIENCE↗