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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
DOE OSTI2020

Photo-z outlier self-calibration in weak lensing surveys

Calibrating photometric redshift errors in weak lensing surveys with external data is extremely challenging. In this work, we show that both Gaussian and outlier photo-z parameters can be self-calibrated from the data alone. This comes at no cost for the neutrino masses, curvature and dark energy equation of state w0, but with a 65% degradation when both w0 and wa are varied. We perform a realistic forecast for the Vera Rubin Observatory (VRO) Legacy Survey of Space and Time (LSST) 3× 2 analysis, combining cosmic shear, projected galaxy clustering and galaxy - galaxy lensing. We confirm the importance of marginalizing over photo-z outliers. We examine a subset of internal cross-correlations, dubbed "null correlations", which are usually ignored in 3× 2 analyses. Despite contributing only ~ 10% of the total signal-to-noise, these null correlations improve the constraints on photo-z parameters by up to an order of magnitude. Using the same galaxy sample as sources and lenses dramatically improves the photo-z uncertainties too. Together, these methods add robustness to any claim of detected new Physics, and reduce the statistical errors on cosmology by 15% and 10% respectively. Finally, including CMB lensing from an experiment like Simons Observatory or CMB-S4 improves the cosmological and photo-z posterior constraints by about 10%, and further improves the robustness to systematics. To give intuition on the Fisher forecasts, we examine in detail several toy models that explain the origin of the photo-z self-calibration. Our Fisher code LaSSI (Large-Scale Structure Information), which includes the effect of Gaussian and outlier photo-z, shear multiplicative bias, linear galaxy bias, and extensions to LCDM, is publicly available at \href{https://github.com/EmmanuelSchaan/LaSSI}{https://github.com/EmmanuelSchaan/LaSSI}.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Performance of the ATLAS forward proton Time-of-Flight detector in Run 2

We present performance studies of the Time-of-Flight (ToF) subdetector of the ATLAS Forward Proton (AFP) detector at the LHC. Efficiencies and resolutions are measured using high-statistics data samples collected at low and moderate pile-up in 2017, the first year when the detectors were installed on both sides of the interaction region. While low efficiencies are observed, of the order of a few percent, the resolutions of the two ToF detectors measured individually are 21 ps and 28 ps, yielding an expected resolution of the longitudinal position of the interaction, z vtx , in the central ATLAS detector of 5.3 ± 0.6 mm. This is in agreement with the observed width of the distribution of the difference between z vtx , measured independently by the central ATLAS tracker and by the ToF detector, of 6.0 ± 2.0 mm.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Uncertainty quantification in breakup reactions

Breakup reactions are one of the favored probes to study loosely bound nuclei, particularly those in the limit of stability forming a halo. In order to interpret such breakup experiments, the continuum discretized coupled channel method is typically used. In this study, the first Bayesian analysis of a breakup reaction model is performed. Herein we use a combination of statistical methods together with a three-body reaction model (the continuum discretized coupled channel method) to quantify the uncertainties on the breakup observables due to the parameters in the effective potential describing the loosely bound projectile of interest. The combination of tools we develop opens the path for a Bayesian analysis of not only breakup processes, but also a wide array of complex processes that require computationally intensive reaction models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

G-Mapper: Learning a Cover in the Mapper Construction

The Mapper algorithm is a visualization technique in topological data analysis (TDA) that outputs a graph reflecting the structure of a given dataset. However, the Mapper algorithm requires tuning several parameters in order to generate a “nice” Mapper graph. This paper focuses on selecting the cover parameter. We present an algorithm that optimizes the cover of a Mapper graph by splitting a cover repeatedly according to a statistical test for normality. Our algorithm is based on G-means clustering, which searches for the optimal number of clusters in 𝑘-means by iteratively applying the Anderson–Darling test. Our splitting procedure employs a Gaussian mixture model to carefully choose the cover according to the distribution of the given data. In conclusion, experiments for synthetic and real-world datasets demonstrate that our algorithm generates covers so that the Mapper graphs retain the essence of the datasets, while also running significantly faster than a previous iterative method.

G-means clustering↗
DOE OSTI2020

Methods for Explainable Artificial Intelligence

We explored ways of quantifying information in a neural network. This can be used to determine the right size of a network or to infer the way in which a network is processing information. The first year and a half was somewhat exploratory while the last half of the project focused on approaches that seemed to show the most promise. The introduce a new way of computing explainable artificial intelligence (XAI) saliency maps that is several orders of magnitude faster than methods with similar fidelity We call it FastCAM. The method works be combining a Class Activation Map (CAM) method such as GradCAM with a forward activation map computed with a statistic we call SMOE Scale. The addition of the forward activation maps to CAM methods seems to always improve their fidelity. At the same time, computational overhead is not increased by very much. While Gradients with SmoothGrad scores better on some fidelity measures, it is overall not as good and requires more than 1500 times to compute. We demonstrate two completed applications of FastCAM on tasks outside of the LDRD at LLNL. The source code for FastCAM is currently being implanted into Captum, the official XAI toolkit for the popular deep learning toolkit PyTorch. The LDRD currently has 13 publications released to the public. 10 of them are journal length.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Regridding uncertainty for statistical downscaling of solar radiation

Abstract. Initial steps in statistical downscaling involve being able to compare observed data from regional climate models (RCMs). This prediction requires (1) regridding RCM outputs from their native grids and at differing spatial resolutions to a common grid in order to be comparable to observed data and (2) bias correcting RCM data, for example via quantile mapping, for future modeling and analysis. The uncertainty associated with (1) is not always considered for downstream operations in (2). This work examines this uncertainty, which is not often made available to the user of a regridded data product. This analysis is applied to RCM solar radiation data from the NA-CORDEX (North American Coordinated Regional Climate Downscaling Experiment) data archive and observed data from the National Solar Radiation Database housed at the National Renewable Energy Lab. A case study of the mentioned methods over California is presented.

14 SOLAR ENERGY↗
NASA NTRS1984

Non-nulling seven-hole probes for high angle flow measurement

This paper illustrates a method for calibrating seven-hole probes to measure local total and static pressures and relative flow angles of up to 70 degrees in subsonic compressible flows. The method of Latin Squares was used to statistically sample a large and otherwise unmanageable data set, thereby reducing to a minimum the number of data points required to construct a polynomial curve fit to the data. Calibration produces three-variable third order polynomials which permit all of the desired flow properties to be found explicitly from probe measured pressures. This method determines the flow angles to within 2 degrees and Mach number to within 0.04 with 95 percent certainty.

Gerner, A. A.↗
NASA NTRS1990

A laboratory measurement of CCD photometric and dimensional stability

The sun exhibits periodic and quasi-periodic variability in its total luminosity, which provides information about its internal structure and dynamics. Variability ranges from a few minutes to many-year time scales, with amplitudes as small as a few ppm in the milliHz band. Extension of this analysis to a large sample of outer stars would be interesting: a panoramic detector such as a CCD could record many stars at once. To meet this objective, a ppm time-series differential precision is required. Laboratory CCD photometric measurements presented here are promising for such an instrument. Normalizing the response from a portion of the CCD area removes most of the individual-frame variability. When a trend attributed to a thermal transient in the CCD dewar is removed, the individual-frame photometric precision is about 0.0001, limited by photoelectron counting statistics. The time-series power spectrum is flat within the desired frequency domain. Analysis of the dimensional stability of the CCD within the same data set indicates better than ppm performance, when first-order bulk motion and magnification changes are removed.

Buffington, Andrew↗
NASA NTRS1990

A statistical study of merging galaxies: Theory and observations

A study of the expected frequency of merging galaxies is conducted, using the impulsive approximation. Results indicate that if we consider mergers involving galaxy pairs without halos in a single crossing time or orbital period, the expected frequency of mergers is two orders of magnitude below the observed value for the present epoch. If we consider mergers involving several orbital periods or crossing times, the expected frequency goes up by an order of magnitude. Preliminary calculation indicate that if we consider galaxy mergers between pairs with massive halos, the merger is very much hastened.

Chatterjee, Tapan K.↗
NASA NTRS1993

Multiple flow regimes in the Northern Hemisphere winter. I - Methodology and hemispheric regimes. II - Sectorial regimes and preferred transitions

Multivariate pdfs in the phase space of large-scale atmospheric motions are examined in order to identify recurrent and persistent flow patterns. The extent to which intraseasonal variablity can be described and understood in terms of multiple flow regimes is clarified. It is shown that the synoptically intriguing and statistically significant inhomogeneities exhibited by the 2D phase plane on the periphery of the distribution are due to the existence of persistent and recurrent anomaly patterns. It is argued that these inhomgeneities are obscured when PDFs are examined in a smaller-dimensional subspace than dynamically desired. A synoptic characterization of onsets and breaks for the flow regimes is given by compositing. In situ evolutions of anomaly patterns, slow westward shifts of high-latitude anomaly centers, and successive downstream increase of anomaly magnitudes are the typical signatures of such events.

Kimoto, Masahide↗
NASA NTRS1994

Goldstone radar contributions to Mars Pathfinder landing safety

Goldstar radar can provide topography 'profiles', statistical surface roughness, and radar images within a few degrees of the sub-Earth point. Goldstone/Very Large Array (VLA) bistatic radar observations can image the whole disk of Mars with integration times on the order of ten min before pixel smearing occurs. Data from all these radar techniques can be useful for observing the local surface conditions relating to landing safety issues for Mars Pathfinder.

Slade, Martin A.↗
NASA NTRS1999

Global-Scale Hydrology: Simple Characterization of Complex Simulation

Atmospheric general circulation models (AGCMS) are unique and valuable tools for the analysis of large-scale hydrology. AGCM simulations of climate provide tremendous amounts of hydrological data with a spatial and temporal coverage unmatched by observation systems. To the extent that the AGCM behaves realistically, these data can shed light on the nature of the real world's hydrological cycle. In the first part of the seminar, I will describe the hydrological cycle in a typical AGCM, with some emphasis on the validation of simulated precipitation against observations. The second part of the seminar will focus on a key goal in large-scale hydrology studies, namely the identification of simple, overarching controls on hydrological behavior hidden amidst the tremendous amounts of data produced by the highly complex AGCM parameterizations. In particular, I will show that a simple 50-year-old climatological relation (and a recent extension we made to it) successfully predicts, to first order, both the annual mean and the interannual variability of simulated evaporation and runoff fluxes. The seminar will conclude with an example of a practical application of global hydrology studies. The accurate prediction of weather statistics several months in advance would have tremendous societal benefits, and conventional wisdom today points at the use of coupled ocean-atmosphere-land models for such seasonal-to-interannual prediction. Understanding the hydrological cycle in AGCMs is critical to establishing the potential for such prediction. Our own studies show, among other things, that soil moisture retention can lead to significant precipitation predictability in many midlatitude and tropical regions.

Koster, Randal D.↗
NASA NTRS1997

Supervised Classification Techniques for Hyperspectral Data

The recent development of more sophisticated remote sensing systems enables the measurement of radiation in many mm-e spectral intervals than previous possible. An example of this technology is the AVIRIS system, which collects image data in 220 bands. The increased dimensionality of such hyperspectral data provides a challenge to the current techniques for analyzing such data. Human experience in three dimensional space tends to mislead one's intuition of geometrical and statistical properties in high dimensional space, properties which must guide our choices in the data analysis process. In this paper high dimensional space properties are mentioned with their implication for high dimensional data analysis in order to illuminate the next steps that need to be taken for the next generation of hyperspectral data classifiers.

Jimenez, Luis O.↗
NASA NTRS2003

Evolution of Galaxies and the Star Formation Rate in the Infrared

A central goal of extragalactic observational astronomy is to understand how normal galaxies evolve with redshift, and particularly when galaxies formed their stars. While optical and rest-frame UV observations have begun to address these issues, the interpretation of such data is particularly challenging because of the sensitivity to dust obscuration (at optical and UV wavelengths). The absorbed light is re-radiated at IR wavelengths, hence the optimal indicators of the star formation rate (SFR) is at a rest-frame wavelength of approx. 60 microns. The SIRTF mission will revolutionize the study of the global evolution of the SFR by providing mass-selected, complete samples of galaxies and far-IR estimators of the SFR. SIRTF will be two orders of magnitude more sensitive than previous IR space missions, and therefore will open up a completely new region of parameter space in sensitivity and angular resolution. This research program will study the SFR using statistical samples of galaxies in the local universe, at intermediate redshifts, and set the stage for continuing studies up to z = 5. The overall research program is divided into three main investigations: a Mid-IR Hubble Atlas and SFR estimators in the local universe, evolution of the SFR at 0 less than z less that 1 using pencil beam redshift surveys, and Galaxy formation and evolution at 1 less than z less than 5.

Pahre, Michael A.↗
NASA NTRS2004

Building Hybrid Rover Models for NASA: Lessons Learned

Particle filters have recently become popular for diagnosis and monitoring of hybrid systems. In this paper we describe our experiences using particle filters on a real diagnosis problem, the NASA Ames Research Center's K-9 rover. As well as the challenge of modelling the dynamics of the system, there are two major issues in applying a particle filter to such a model. The first is the asynchronous nature of the system-observations from different subsystems arrive at different rates, and occasionally out of order, leading to large amounts of uncertainty in the state of the system. The second issue is data interpretation. The particle filter produces a probability distribution over the state of the system, from which summary statistics that can be used for control or higher-level diagnosis must be extracted. We describe our approaches to both these problems, as well as other modelling issues that arose in this domain.

Willeke, Thomas↗
NASA NTRS2009

Measurement of Satellite Impact Test Fragments for Modeling Orbital Debris

There are over 13,000 pieces of catalogued objects 10cm and larger in orbit around Earth [ODQN, January 2009, p12]. More than 6000 of these objects are fragments from explosions and collisions. As the earth-orbiting object count increases, debris-generating collisions in the future become a statistical inevitability. To aid in understanding this collision risk, the NASA Orbital Debris Program Office has developed computer models that calculate quantity and orbits of debris both currently in orbit and in future epochs. In order to create a reasonable computer model of the orbital debris environment, it is important to understand the mechanics of creation of debris as a result of a collision. The measurement of the physical characteristics of debris resulting from ground-based, hypervelocity impact testing aids in understanding the sizes and shapes of debris produced from potential impacts in orbit. To advance the accuracy of fragment shape/size determination, the NASA Orbital Debris Program Office recently implemented a computerized measurement system. The goal of this system is to improve knowledge and understanding of the relation between commonly used dimensions and overall shape. The technique developed involves scanning a single fragment with a hand-held laser device, measuring its size properties using a sophisticated software tool, and creating a three-dimensional computer model to demonstrate how the object might appear in orbit. This information is used to aid optical techniques in shape determination. This more automated and repeatable method provides higher accuracy in the size and shape determination of debris.

Hill, Nicole M.↗
NASA NTRS2011

Multi-Axis Identifiability Using Single-Surface Parameter Estimation Maneuvers on the X-48B Blended Wing Body

The problem of parameter estimation on hybrid-wing-body type aircraft is complicated by the fact that many design candidates for such aircraft involve a large number of aero- dynamic control effectors that act in coplanar motion. This fact adds to the complexity already present in the parameter estimation problem for any aircraft with a closed-loop control system. Decorrelation of system inputs must be performed in order to ascertain individual surface derivatives with any sort of mathematical confidence. Non-standard control surface configurations, such as clamshell surfaces and drag-rudder modes, further complicate the modeling task. In this paper, asymmetric, single-surface maneuvers are used to excite multiple axes of aircraft motion simultaneously. Time history reconstructions of the moment coefficients computed by the solved regression models are then compared to each other in order to assess relative model accuracy. The reduced flight-test time required for inner surface parameter estimation using multi-axis methods was found to come at the cost of slightly reduced accuracy and statistical confidence for linear regression methods. Since the multi-axis maneuvers captured parameter estimates similar to both longitudinal and lateral-directional maneuvers combined, the number of test points required for the inner, aileron-like surfaces could in theory have been reduced by 50%. While trends were similar, however, individual parameters as estimated by a multi-axis model were typically different by an average absolute difference of roughly 15-20%, with decreased statistical significance, than those estimated by a single-axis model. The multi-axis model exhibited an increase in overall fit error of roughly 1-5% for the linear regression estimates with respect to the single-axis model, when applied to flight data designed for each, respectively.

Ratnayake, Nalin A.↗
DOE OSTI2022

Data-Driven Discovery of Active Nematic Hydrodynamics

Active nematics can be modeled using phenomenological continuum theories that account for the dynamics of the nematic director and fluid velocity through partial differential equations (PDEs). While these models provide a statistical description of the experiments, the relevant terms in the PDEs and their parameters are usually identified indirectly. We adapt a recently developed method to automatically identify optimal continuum models for active nematics directly from spatio-temporal data, via sparse regression of the coarse-grained fields onto generic low order PDEs. After extensive benchmarking, we apply the method to experiments with microtubule-based active nematics, finding a surprisingly minimal description of the system. Furthermore, our approach can be generalized to gain insights into active gels, microswimmers, and diverse other experimental active matter systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗