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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

The influence of autocorrelation in signature extraction - An example from a geobotanical investigation of Cotter Basin, Montana

The presence of positive serial correlation (autocorrelation) in remotely sensed data results in an underestimate of the variance-covariance matrix when calculated using contiguous pixels. This underestimate produces an inflation in F statistics. For a set of Thematic Mapper Simulator data (TMS), used to test the ability to discriminate a known geobotanical anomaly from its background, the inflation in F statistics related to serial correlation is between 7 and 70 times. This means that significance tests of means of the spectal bands initially appear to suggest that the anomalous site is very different in spectral reflectance and emittance from its background sites. However, this difference often disappears and is always dramatically reduced when compared to frequency distributions of test statistics produced by the comparison of simulated training sets possessing equal means, but which are composed of autocorrelated observations.

Labovitz, M. L.↗
DOE OSTI2016

Precision comparison of the power spectrum in the EFTofLSS with simulations

We study the prediction of the dark matter power spectrum at two-loop order in the Effective Field Theory of Large Scale Structures (EFTofLSS) using high precision numerical simulations. In our universe, short distance non-linear fluctuations, not under perturbative control, affect long distance fluctuations through an effective stress tensor that needs to be parametrized in terms of counterterms that are functions of the long distance fluctuating fields. We find that at two-loop order it is necessary to include three counterterms: a linear term in the overdensity, δ, a quadratic term, δ{sup 2}, and a higher derivative term, ∂{sup 2}δ. After the inclusion of these three terms, the EFTofLSS at two-loop order matches simulation data up to k ≅ 0.34 h Mpc{sup −1} at redshift z = 0, up to k ≅ 0.55 h Mpc{sup −1} at z = 1, and up to k ≅ 1.1 h Mpc{sup −1} at z = 2. At these wavenumbers, the cosmic variance of the simulation is at least as small as 10{sup −3}, providing for the first time a high precision comparison between theory and data. The actual reach of the theory is affected by theoretical uncertainties associated to not having included higher order terms in perturbation theory, for which we provide an estimate, and by potentially overfitting the data, which we also try to address. Since in the EFTofLSS the coupling constants associated with the counterterms are unknown functions of time, we show how a simple parametrization gives a sensible description of their time-dependence. Overall, the k -reach of the EFTofLSS is much larger than previous analytical techniques, showing that the amount of cosmological information amenable to high-precision analytical control might be much larger than previously believed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2013

A Virtual Aluminum Reduction Cell

The most important component in the aluminum industry is the aluminum reduction cell; it has received considerable interests and resources to conduct research to improve its productivity and energy efficiency. Currently, we focus on the integration of numerical simulation data and virtual reality technology to create a scientifically and practically realistic virtual aluminum reduction cell by presenting complex cell structures and physical–chemical phenomena. The multiphysical field simulation models were first built and solved in ANSYS software (ANSYS Inc., Canonsburg, PA, USA). Then, the methodology of combining the simulation results with virtual reality was introduced, and a virtual aluminum reduction cell was created. Our demonstration showed that a computer-based world could be created in which people who are not analysis experts can see the detailed cell structure in a context that they can understand easily. With the application of the virtual aluminum reduction cell, even people who are familiar with aluminum reduction cell operations can gain insights that make it possible to understand the root causes of observed problems and plan design changes in much less time.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Crystal plasticity model of BCC metals from large-scale MD simulations

Accurate crystal plasticity models that faithfully capture the behavior of single crystals under a wide range of loading conditions, such as loading direction, strain rate, and temperature, are still lacking. Here we introduce a novel approach in which a crystal plasticity (CP) model is informed directly from and calibrated to large-scale quantum-accurate MD simulations in which single crystal BCC Ta serves as a testbed material. By analyzing our large set of MD simulations several key insights are obtained leading us to modify constitutive assumptions in order to address deficiencies of existing CP models. Importantly, we observe that the standard notion of fixed slip systems – pairs of slip directions and slip planes – is inadequate for describing high-rate plasticity in BCC tantalum at room temperature. Instead, pencil glide defined as dislocation motion in the maximum resolved shear stress planes (MRSSP) of each Burgers vector is fully consistent with our MD simulation data while providing significant simplifications of the constitutive relations. Herein, our resulting new CP model closely matches the behavior of single crystals observed in high-rate MD simulations while being fully consistent with lower rate experimental results.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A systematic feature extraction and selection framework for data-driven whole-building automated fault detection and diagnostics in commercial buildings

In data-driven automated fault detection and diagnostics (AFDD) modeling for building energy systems, feature engineering is a critical process of extracting information from high-dimensional and noisy sensor measurement and turning it into informative and representative inputs or features for data-driven modeling. However, few studies specifically discuss the feature engineering, especially the interactions between feature extraction and feature selection in whole-building AFDD. We developed a systematic feature extraction and selection framework for whole-building AFDD. In this framework, features are aggressively extracted from raw sensor data using statistical feature extraction techniques with various window sizes and statistics. With many features extracted, a hybrid feature selection algorithm that combines the filter and wrapper method then selects the best feature set. The framework considers diversity in the duration of fault behavior among fault types in whole-building AFDD, thus achieving high model generalization. We implemented our developed framework in a virtual testbed calibrated with measured data from Oak Ridge National Laboratory's Flexible Research Platform designed to mimic the operation of a typical small commercial building. The AFDD model is trained by the simulation data generated from the virtual testbed. The results show that (1) the developed framework improves the generalization of the AFDD model by 10.7% compared with literature-reported feature extraction and selection methods and (2) features with diverse window sizes and statistics are selected, providing insight into physical systems beyond the current understanding of buildings and faults and improving the detection and diagnostics of multiple fault types.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

A 'nu' look at gravitational waves: the black hole birth rate from neutrinos combined with the merger rate from LIGO

We make projections for measuring the black hole birth rate from the diffuse supernova neutrino background (DSNB) by future neutrino experiments, and constrain the black hole merger fraction ε, when combined with information on the black hole merger rate from gravitational wave experiments such as LIGO. The DSNB originates from neutrinos emitted by all the supernovae in the Universe, and is expected to be made up of two components: neutrinos from neutron-star-forming supernovae, and a sub-dominant component at higher energies from black-hole-forming 'unnovae'. We perform a Markov Chain Monte Carlo analysis of simulated data of the DSNB in an experiment similar to Hyper-Kamiokande, focusing on this second component. Since all knowledge of the neutrino emission from unnovae comes from simulations of collapsing stars, we choose two sets of priors: one where the unnovae are well-understood and one where their neutrino emission is poorly known. By combining the black hole birth rate from the DSNB with projected measurements of the black hole merger rate from LIGO, we show that the fraction of black holes which lead to binary mergers observed today ε could be constrained to be within the range 2 ⋅ 10{sup −4} ≤ ε ≤ 3 ⋅ 10{sup −2} at 3 σ confidence, after ten years of running an experiment like Hyper-Kamiokande.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Neural networks for large eddy simulations of wall-bounded turbulence: numerical experiments and challenges

Here, we examine the application of neural network-based methods to improve the accuracy of large eddy simulations of incompressible turbulent flows. The networks are trained to learn a mapping between flow features and the subgrid scales, and applied locally and instantaneously—in the same way as traditional physics-based subgrid closures. Models that use only the local resolved strain rate are poorly correlated with the actual subgrid forces obtained from filtering direct numerical simulation data. We see that highly accurate models in a priori testing are inaccurate in forward calculations, owing to the preponderance of numerical errors in implicitly filtered large eddy simulations. A network that accounts for the discretization errors is trained and found to be unstable in a posteriori testing. We identify a number of challenges that the approach faces, including a distribution shift that affects networks that fail to account for numerical errors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Chimera F-Series Gravitational Wave Emission Sourced from Matter and Neutrino Anisotropy

This dataset contains gravitational wave data sourced from the the time-dependent fluid quadrupole motion as well as neutrino anisotropy, in the Chimera F-Series two-dimensional core collapse supernova simulations. Data from two models initiated from two different progenitors are presented: F15.78 and F15.79. Please see the README for more information about the data structure and progenitors.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

The Preliminary Validation and Verification of GSM

The Generalized Spallation Model, or GSM, simulates hadron-nucleus and nucleus-nucleus collisions at intermediate to high incident energies. It is recommended that use of GSM be limited to interactions for particles and nuclei with kinetic energies greater than ~ 100 MeV, up to ~ 1 T eV/A. GSM was developed to investigate the deprecation of the Los Alamos Quark-Gluon String Model (LAQGSM), as implemented in the event generator LAQGSM03.03. The deprecation of LAQGSM will allow for a simplification of the high energy physics models utilized within the Monte Carlo N-Particle® (MCNP®) transport code1 . MCNP applies simulated data from the Cascade Exciton Model (CEM), as implemented in the CEM03.03 event generator, and the LAQGSM event generator for most high energy reactions, by default, for its simulations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Electric Field Calculation of Coherent Synchrotron Radiation via the Jefimenko Equation

The electric field of coherent synchrotron radiation (CSR) from an electron beam was investigated by employing an alternate formulation of the Maxwell equation, i.e., the Jefimenko field equation where the electric field depends only on the retarded charge density and retarded current density as described by McDonald1 . From this approach, a simple program is developed in python to calculate the electric field from CSR particle-in-cell(PIC) simulation data. For the CSR problem it is intended that the results of this calculation will be used to assist in the diagnosis of discrepancies found during previous PIC simulation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

A Machine Learns to Predict the Stability of Highly Diverse Multi-planetary Systems

Machine learning has proven to be an invaluable tool for characterizing the stability of planets in simplified planetary systems. In this work, we investigate the performance of a machine learning classifier on tightlypacked systems containing a rich diversity of planets, from Earths to Jupiters. Using information derived from short numerical simulations about a planet’s early orbital evolution and its relationship with the most massive planets in the system, we train a random forest classifier to predict instability with a > 88 percent accuracy. Our classifier relies on relative planet masses and the standard deviation of eccentricity for much of its predictive power. Most misclassified planets lie along a multi-dimensional boundary between stable and unstable planets, indicating that their early orbital evolution is ambiguous. The major reason for misclassification in this work is timescale: because our classifier uses information from only the first 137 years of simulation data, it is blind to late time interactions that cause or prevent instability. Machine learning methods like those utilized in this work provide powerful tools to complement numerical simulations across a wide range of planetary architectures.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1984

A comparative evaluation of simulated SPOT, Thematic Mapper, and simulated Thematic Mapper data in a western ecozone

Spectral information content was quantitatively measured for simulated SPOT, Thematic Mapper, and simulated Thematic Mapper data acquired over Santa Cruz County, California. Two techniques were employed: spectral separability summarized through optimal wave band evaluation, and histogram cluster analysis. Using data from the three sources it is shown that three spectral bands can provide separability nearly as high as six bands provide, if the three bands are optimally chosen for the cover type. Analysis of the Santa Cruz scene emphasizes the importance of TM bands 1 and 5 in particular. The three bands of the SPOT scanner are shown to provide sufficient separability for cover types within the study area. The higher spatial resolution data (20 meters) provided by SPOT contain more distinct distributions than data from the other sources studied. Techniques should be developed to exploit this additional information.

Buis, J. S.↗
NASA NTRS2001

Global Lidar Measurements of Clouds and Aerosols from Space Using the Geoscience Laser Altimeter System (GLAS)

The Geoscience Laser Altimeter System (GLAS) is scheduled for launch on the ICESat satellite as part of the NASA EOS mission in 2002. GLAS will be used to perform high resolution surface altimetry and will also provide a continuously operating atmospheric lidar to profile clouds, aerosols, and the planetary boundary layer with horizontal and vertical resolution of 175 and 76.8 m, respectively. GLAS is the first active satellite atmospheric profiler to provide global coverage. Data products include direct measurements of the heights of aerosol and cloud layers, and the optical depth of transmissive layers. In this poster we provide an overview of the GLAS atmospheric data products, present a simulated GLAS data set, and show results from the simulated data set using the GLAS data processing algorithm. Optical results from the ER-2 Cloud Physics Lidar (CPL), which uses many of the same processing algorithms as GLAS, show algorithm performance with real atmospheric conditions during the Southern African Regional Science Initiative (SAFARI 2000).

Hlavka, Dennis L.↗
DOE OSTI2020

The Analog Front-end for the LGAD Based Precision Timing Application in CMS ETL

The analog front-end for the Low Gain Avalanche Detector (LGAD) based precision timing application in the CMS Endcap Timing Layer (ETL) has been prototyped in a 65 nm CMOS mini-ASIC named ETROC0. Serving as the very first prototype of ETL readout chip (ETROC), ETROC0 aims to study and demonstrate the performance of the analog frontend, with the goal to achieve 40 to 50 ps time resolution per hit with LGAD (therefore reach about 30ps per track with two detector-layer hits per track). ETROC0 consists of preamplifier and discriminator stages, which amplifies the LGAD signal and generates digital pulses containing time of arrival and time over threshold information. This paper will focus on the design considerations that lead to the ETROC front-end architecture choice, the key design features of the building blocks, the methodology of using the LGAD simulation data to evaluate and optimize the front-end design. The ETROC0 prototype chips have been extensively tested using charge injection and the measured performance agrees well with simulation. The initial beam test results are also presented, with time resolution of around 33 ps observed from the preamplifier waveform analysis and around 41 ps from the discriminator pulses analysis. A subset of ETROC0 chips have also been tested to a total ionizing dose of 100 MRad with X-ray and no performance degradation been observed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1978

Discrete event simulation and the resultant data storage system response in the operational mission environment of Jupiter-Saturn /Voyager/ spacecraft

The Data Storage Subsystem Simulator (DSSSIM) simulating (by ground software) occurrence of discrete events in the Voyager mission is described. Functional requirements for Data Storage Subsystems (DSS) simulation are discussed, and discrete event simulation/DSSSIM processing is covered. Four types of outputs associated with a typical DSSSIM run are presented, and DSSSIM limitations and constraints are outlined.

Mukhopadhyay, A. K.↗
DOE OSTI2018

Theoretical prediction of crystallization kinetics of a supercooled Lennard-Jones fluid

The first order curvature correction to the crystal-liquid interfacial free energy is calculated using a theoretical model based on the interfacial excess thermodynamic properties. The correction parameter (δ), which is analogous to the Tolman length at a liquid-vapor interface, is found to be 0.48 ± 0.05 for a Lennard-Jones (LJ) fluid. We show that this curvature correction is crucial in predicting the nucleation barrier when the size of the crystal nucleus is small. The thermodynamic driving force (Δμ) corresponding to available simulated nucleation conditions is also calculated by combining the simulated data with a classical density functional theory. In this study, we show that the classical nucleation theory is capable of predicting the nucleation barrier with excellent agreement to the simulated results when the curvature correction to the interfacial free energy is accounted for.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

From Images to Dark Matter: End-to-end Inference of Substructure from Hundreds of Strong Gravitational Lenses

Abstract Constraining the distribution of small-scale structure in our universe allows us to probe alternatives to the cold dark matter paradigm. Strong gravitational lensing offers a unique window into small dark matter halos (<10 10 M ⊙ ) because these halos impart a gravitational lensing signal even if they do not host luminous galaxies. We create large data sets of strong lensing images with realistic low-mass halos, Hubble Space Telescope (HST) observational effects, and galaxy light from HST’s COSMOS field. Using a simulation-based inference pipeline, we train a neural posterior estimator of the subhalo mass function (SHMF) and place constraints on populations of lenses generated using a separate set of galaxy sources. We find that by combining our network with a hierarchical inference framework, we can both reliably infer the SHMF across a variety of configurations and scale efficiently to populations with hundreds of lenses. By conducting precise inference on large and complex simulated data sets, our method lays a foundation for extracting dark matter constraints from the next generation of wide-field optical imaging surveys.

79 ASTRONOMY AND ASTROPHYSICS↗