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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Milky Way mass with K giants and BHB stars using LAMOST, SDSS/SEGUE, and Gaia : 3D spherical Jeans equation and tracer mass estimator

ABSTRACT We measure the enclosed Milky Way mass profile to Galactocentric distances of ∼70 and ∼50 kpc using the smooth, diffuse stellar halo samples of Bird et al. The samples are Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) and Sloan Digital Sky Survey/Sloan Extension for Galactic Understanding and Exploration (SDSS/SEGUE) K giants (KG) and SDSS/SEGUE blue horizontal branch (BHB) stars with accurate metallicities. The 3D kinematics are available through LAMOST and SDSS/SEGUE distances and radial velocities and Gaia DR2 proper motions. Two methods are used to estimate the enclosed mass: 3D spherical Jeans equation and Evans et al. tracer mass estimator (TME). We remove substructure via the Xue et al. method based on integrals of motion. We evaluate the uncertainties on our estimates due to random sampling noise, systematic distance errors, the adopted density profile, and non-virialization and non-spherical effects of the halo. The tracer density profile remains a limiting systematic in our mass estimates, although within these limits we find reasonable agreement across the different samples and the methods applied. Out to ∼70 and ∼50 kpc, the Jeans method yields total enclosed masses of 4.3 ± 0.95 (random) ±0.6 (systematic) × 1011 M⊙ and 4.1 ± 1.2 (random) ±0.6 (systematic) × 1011 M⊙ for the KG and BHB stars, respectively. For the KG and BHB samples, we find a dark matter virial mass of $M_{200}=0.55^{+0.15}_{-0.11}$ (random) ±0.083 (systematic) × 1012 M⊙ and $M_{200}=1.00^{+0.67}_{-0.33}$ (random) ±0.15 (systematic) × 1012 M⊙, respectively.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Grover-QAOA for 3-SAT: quadratic speedup, fair-sampling, and parameter clustering

Abstract The SAT problem is a prototypical NP-complete problem of fundamental importance in computational complexity theory with many applications in science and engineering; as such, it has long served as an essential benchmark for classical and quantum algorithms. This study shows numerical evidence for a quadratic speedup of the Grover Quantum Approximate Optimization Algorithm (G-QAOA) over random sampling for finding all solutions to 3-SAT (All-SAT) and Max-SAT problems. G-QAOA is less resource-intensive and more adaptable for these problems than Grover’s algorithm, and it surpasses conventional QAOA in its ability to sample all solutions. We show these benefits by classical simulations of many-round G-QAOA on thousands of random 3-SAT instances. We also observe G-QAOA advantages on the IonQ Aria quantum computer for small instances, finding that current hardware suffices to determine and sample all solutions. Interestingly, a single-angle-pair constraint that uses the same pair of angles at each G-QAOA round greatly reduces the classical computational overhead of optimizing the G-QAOA angles while preserving its quadratic speedup. We also find parameter clustering of the angles. The single-angle-pair protocol and parameter clustering significantly reduce obstacles to classical optimization of the G-QAOA angles.

Zhang, Zewen (ORCID:000000032258613X)↗
NASA NTRS1984

Structure of nonevaporating sprays - Measurements and predictions

Structure measurements were completed within the dilute portion of axisymmetric nonevaporating sprays (SMD of 30 and 87 microns) injected into a still air environment, including: mean and fluctuating gas velocities and Reynolds stress using laser-Doppler anemometry; mean liquid fluxes using isokinetic sampling; drop sizes using slide impaction; and drop sizes and velocities using multiflash photography. The new measurements were used to evaluate three representative models of sprays: (1) a locally homogeneous flow (LHF) model, where slip between the phases was neglected; (2) a deterministic separated flow (DSF) model, where slip was considered but effects of drop interaction with turbulent fluctuations were ignored; and (3) a stochastic separated flow (SSF) model, where effects of both interphase slip and turbulent fluctuations were considered using random sampling for turbulence properties in conjunction with random-walk computations for drop motion. The LHF and DSF models were unsatisfactory for present test conditions-both underestimating flow widths and the rate of spread of drops. In contrast, the SSF model provided reasonably accurate predictions, including effects of enhanced spreading rates of sprays due to drop dispersion by turbulence, with all empirical parameters fixed from earlier work.

Solomon, A. S. P.↗
DOE OSTI2021

Power Grid Reliability Estimation via Adaptive Importance Sampling

Electricity production currently generates approximately 25% of greenhouse gas emissions in the USA. Thus, increasing the amount of renewable energy is a key step to carbon neutrality. However, integrating a large amount of fluctuating renewable generation is a significant challenge for power grid operating and planning. Grid reliability, i.e., an ability to meet operational constraints under power fluctuations, is probably the most important of them. In this letter, we propose computationally efficient and accurate methods to estimate the probability of line overflow, i.e., reliability constraints violation, under a known distribution of renewable energy generation. To this end, we investigate an importance sampling approach, a flexible extension of Monte-Carlo methods, which adaptively changes the sampling distribution to generate more samples near the reliability boundary. The approach allows to estimate overload probability in real-time based only on a few dozens of random samples, compared to thousands required by the plain Monte-Carlo. Our study focuses on high voltage direct current power transmission grids with linear reliability constraints on power injections and line currents. Herein, we propose a novel theoretically justified physics-informed adaptive importance sampling algorithm and compare its performance to state-of-the-art methods on multiple IEEE power grid test cases.

power system faults↗
DOE OSTI2025

Curiosity driven exploration to optimize structure–property learning in microscopy

Rapidly determining structure–property correlations in materials is an important challenge in better understanding fundamental mechanisms and greatly assists in materials design. In microscopy, imaging data provides a direct measurement of the local structure, while spectroscopic measurements provide relevant functional property information. Deep kernel active learning approaches have been utilized to rapidly map local structure to functional properties in microscopy experiments, but are computationally expensive for multi-dimensional and correlated output spaces. Here, we present an alternative lightweight curiosity algorithm which actively samples regions with unexplored structure–property relations, utilizing a deep-learning based surrogate model for error prediction. We show that the algorithm outperforms random sampling for predicting properties from structures, and provides a convenient tool for efficient mapping of structure–property relationships in materials science.

36 MATERIALS SCIENCE↗
NASA NTRS2008

Total Lightning Observations of Extreme Weather Events over the Contiguous United States

The overall objective is to investigate total lightning characteristics of extreme weather events over the contiguous United States (CONUS) using TRMM (Tropical Rainfall Measuring Mission) LIS (Lightning Image Sensor) and OTD (Optical Transient Detector) satellite observations. A large LIS (10+ years) and OTD (5 years) data base is available to study the instantaneous total or cloud-to-ground (CG) plus intracloud (IC) lightning characteristics of extreme weather events. More specifically, the LIS and OTD data are combined with National Lightning Detection Network (NLDN) observations to examine the total and CG lightning flash rate and density, the IC:CG ratio, and positive CG percentage. These instantaneous lightning characteristics can be used for basic science studies to better understand the physical and dynamical linkages between lightning and precipitation and their environmental controls. They can also provide a first-look of extreme weather events leading up to future satellite observations (e.g., NOAA GOES-R Geostationary Lightning Mapper [GLM]) for use in climate studies and the short-term prediction and warning process. Extreme weather events are defined by the NOAA Storm Data reports of tornadoes, large hail (at least 0.75 inch) and strong straight-line winds (at least 50 kts). Over CONUS, there are over 70,000 severe storm reports in the TRMM spatial domain (< 35 N) from 1998-2007 and over 100,000 storm reports in the OTD spatial domain (5/1995-4/2000). Temporal co-location is on the order of 1% (i.e., 1000 s of coincident overpasses), providing a statistically significant sample of instantaneous total lightning properties. This instantaneous behavior of lightning in extreme weather is then compared to that of typical thunderstorm events, or randomly sampled LIS/OTD events in which the extreme events have been eliminated from the population. Results describing the instantaneous behavior of total lightning within a large sample of extreme and typical thunderstorms over CONUS will be presented. When possible, coincident VHF lightning observations from the ground-based Northern Alabama Lightning Mapping Array (LMA) are compared to the LIS/OTD optical lightning signatures, providing a validation source for instantaneous space-based optical lightning properties and a means to extend lightning inferences over the life-cycle of extreme weather.

Carey, Lawrence D.↗
NASA NTRS1989

An evaluation of selected NASA scientific and technical information products: Results of a pilot study

A pilot study was conducted to evaluate selected NASA scientific and technical information (STI) products. The study, which utilized survey research in the form of a self-administered mail questionnaire, had a two-fold purpose -- to gather baseline data regarding the use and perceived usefulness of selected NASA STI products and to develop/validate questions that could be used in a future study concerned with the role of the U.S. government technical report in aeronautics. The sample frame consisted of 25,000 members of the American Institute of Aeronautics and Astronautics in the U.S. with academic, government or industrial affiliation. Simple random sampling was used to select 2000 individuals to participate in the study. Three hundred fifty-three usable questionnaires (17 percent response rate) were received by the established cutoff date. The findings indicate that: (1) NASA STI is used and is generally perceived as being important; (2) the use rate for NASA-authored conference/meeting papers, journal articles, and technical reports is fairly uniform; (3) a considerable number of respondents are unfamiliar with STAR (Scientific and Technical Aerospace Reports), IAA (International Aerospace Abstracts), SCAN (Selected Current Aerospace Notices), and the RECON on-line retrieval system; (4) a considerable number of respondents who are familiar with these media do not use them; and (5) the perceived quality of NASA-authored journal articles and technical reports is very good.

Pinelli, Thomas E.↗
NASA NTRS1981

FOCIS: A forest classification and inventory system using LANDSAT and digital terrain data

Accurate, cost-effective stratification of forest vegetation and timber inventory is the primary goal of a Forest Classification and Inventory System (FOCIS). Conventional timber stratification using photointerpretation can be time-consuming, costly, and inconsistent from analyst to analyst. FOCIS was designed to overcome these problems by using machine processing techniques to extract and process tonal, textural, and terrain information from registered LANDSAT multispectral and digital terrain data. Comparison of samples from timber strata identified by conventional procedures showed that both have about the same potential to reduce the variance of timber volume estimates over simple random sampling.

Strahler, A. H.↗
NASA NTRS2023

The Oxygen Isotopic Composition of Samples Returned From Asteroid Ryugu With Implications for the Nature of the Parent Planetesimal

We present oxygen isotopic analyses of fragments of the near-Earth C b -type asteroid Ryugu returned by the Hayabusa2 spacecraft that reinforce the close correspondence between Ryugu and CI chondrites. Small differences between Ryugu samples and CI chondrites in ∆' 17 O can be explained at least in part by contamination of the latter by terrestrial water. The discovery that a randomly sampled C-complex asteroid is composed of CI-chondrite-like rock, combined with thermal models for formation prior to significant decay of the short-lived radioisotope 26 Al, suggests that if lithified at the time of alteration, the parent body was small (<<50 km radius). If the parent planetesimal was large (>50 km in radius), it was likely composed of high-permeability, poorly lithified sediment rather than consolidated rock.

Asteroids↗
DOE OSTI2024

The Role of Data Filtering in Open Source Software Ranking and Selection

Faced with more than 100M open source projects, a more manageable small subset is needed for most empirical investigations. More than half of the research papers in leading venues investigated filtering projects by some measure of popularity with explicit or implicit arguments that unpopular projects are not of interest, may not even represent "real" software projects, or that less popular projects are not worthy of study. However, such filtering may have enormous effects on the results of the studies if and precisely because the sought-out response or prediction is in any way related to the filtering criteria.This paper exemplifies the impact of this common practice on research outcomes, specifically how filtering of software projects on GitHub based on inherent characteristics affects the assessment of their popularity. Using a dataset of over 100,000 repositories, we used multiple regression to model the number of stars -a commonly used proxy for popularity- based on factors such as the number of commits, the duration of the project, the number of authors and the number of core developers. Our control model included the entire dataset, while a second filtered model considered only projects with ten or more authors. The results indicated that while certain characteristics of the repository consistently predict popularity, the filtering process significantly alters the relationships between these characteristics and the response. We found that the number of commits exhibited a positive correlation with popularity in the control sample but showed a negative correlation in the filtered sample. These findings highlight the potential biases introduced by data filtering and emphasize the need for careful sample selection in empirical research of mining software repositories. We recommend that empirical work should either analyze complete datasets such as World of Code, or employ stratified random sampling from a complete dataset to ensure that filtering is not biasing the results.

Malviya Thakur, Addi↗
NASA NTRSDate not supplied

Uncertainty Estimates for Fitting Zernike Polynomials to Discrete Data

Zernike polynomials are a widely used metric in modern optical analysis. They conveniently represent surfaces as a series of weighted terms corresponding to various optical aberrations. Ideally, each term is independent of others in the series, but Zernike polynomials lose this property when working with sets of discrete data. This gives rise to uncertainty in each polynomial’s actual contribution and affects metrology and simulation estimates of their relative weights. Several factors influencing these estimates are the number and arrangement of sample locations, the method for calculating the weights, and the total number of Zernike terms used in the calculation. Discussed is the uncertainty associated with linear regression using random sampling. Other topics reviewed are complex Zernike polynomials and vector spaces of functions.

Zernike Polynomials↗
DOE OSTI2024

A Case Study in Assessing a Potential Severity Framework for Incidents from a Decadal Sample

In this study, the primary objective of this case study is to determine the applicability and feasibility of a framework that leverages occupational incident details to prospectively identify “potential Serious Injury or Fatality” (pSIF) cases. This study comprehensively reviewed a random sample of 1,081 injury and illness cases across 21 generalized incident types spanning over a decade at Lawrence Livermore National Laboratory (LLNL), a U.S. Department of Energy research and development facility with more than 9,000 employees. The review applied a general framework that classified each case on information suitability, potential severity, and future incident mitigation. The findings from the study indicate that 86.6% of the cases had sufficient information to make a high-confidence determination on potential severity, underscoring the feasibility of applying this general framework. Additionally, cases with a higher pSIF score had, on average, a higher level of institutional response. Implementing a simplified methodology for incident classification that emphasizes incidents that pose high potential severity, regardless of incident type, can help LLNL prioritize resources and tailor responses to such incidents using a graded approach. LLNL has recognized the value of this capability and is integrating the framework into their injury and illness process in the 2024 calendar year.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

Computing the QRPA level density with the finite amplitude method

Here, we describe a new algorithm to calculate the vibrational nuclear level density of an atomic nucleus. Fictitious perturbation operators that probe the response of the system are generated by drawing their matrix elements from some probability distribution function. We use the Finite Amplitude Method to explicitly compute the response for each such sample. With the help of the Kernel Polynomial Method, we build an estimator of the vibrational level density and provide the upper bound of the relative error in the limit of infinitely many random samples. The new algorithm can give accurate estimates of the vibrational level density. Since it is based on drawing multiple samples of perturbation operators, its computational implementation is naturally parallel and scales like the number of available processing units.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

hiposa v0.1.0

Fast construction of hierarchical N-dimensional experimental design. The software allows construction of sampling strategies that are self-avoiding, tunable in resolution in N dimensions. This code is a drop-in replacement for seeding optimization runs often performed using uniform random sampling. The hierarchical approach allows for a rapid, top down method for construction the most effective design that drives towards a global optimum.

Zwart, PetrusH [Lawrence Berkeley National Laborat↗
DOE OSTI2024

Energy Delivery Systems with Verifiable Trustworthiness (Final Report)

Energy Delivery Systems (EDS) must be verified to be free from intrusive and malicious software. One way of verifying this software is to perform device scans to detect malicious code. Because it is possible to have “fileless” malware that exists only in device (volatile) memory, offline scanning and even many forms of online scanning is insufficient for detection. This project (“Verify”) addresses this need by performing direct sampling of memory during device operation to detect unexpected or modified software while not interfering with device operation. The Verify project provides a proof-of-concept of detection by random sampling combined with remote software- and timing-based attestation methods for robust detection of in-memory threats. An external review of Verify was performed by our partner, General Electric (GE), and a summary of their findings is provided.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A Machine Learning-Based Vulnerability Analysis for Cascading Failures of Integrated Power-Gas Systems

This article proposes a cascading failure simulation (CFS) method and a hybrid machine learning method for vulnerability analysis of integrated power-gas systems (IPGSs). The CFS method is designed to study the propagating process of cascading failures between the two systems, generating data for machine learning with initial states randomly sampled. The proposed method considers generator and gas well ramping, transmission line and gas pipeline tripping, island issue handling and load shedding strategies. Then, a hybrid machine learning model with a combined random forest (RF) classification and regression algorithms is proposed to investigate the impact of random initial states on the vulnerability metrics of IPGSs. Extensive case studies are carried out on three test IPGSs to verify the proposed models and algorithms. Simulation results show that the proposed models and algorithms can achieve high accuracy for the vulnerability analysis of IPGSs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2017

A Large Ordinary Chondrite Shower in the Dominion Range

The US Antarctic Meteorite Program has visited the Dominion Range in the Transantarctic Mountains during several different seasons, including the 1985, 2003, 2008, 2010, and 2014 seasons. Total recovered meteorites from this region is over 2000. The 2008 and 2010 seasons have been fully classified and, respectively) revealing the presence of a large meteorite shower that comprises approximately 60% of all samples recovered in those two seasons. The oil immersion classification suggests that this shower is LL chondrite material, whereas published magnetic susceptibility (MS; log chi) measurements yield L chondrite values. However, usually random sampling of a large collection like this would uncover EOC material for which we have prepared thin sections. In this case, no LL chondrite materials have been found in thin section, suggesting that the shower might instead be an L chondrite. L and LL chondrites are notoriously difficult to distinguish using oil immersion techniques. To better characterize this large group of samples, we have decided to examine some of the large members of this group, using EMPA analysis of the olivines to verify the classifications. With a compositional link between this subset of samples, and the MS measurements, we can more confidently classify the samples making up this pairing group. Subsequently, more accurate and meaningful comparisons may be drawn between this pairing group and some other Antarctic pairing groups such as from the Queen Alexandra Range (QUE), and Lewis Cliffs Ice Tongue (LEW). electron microprobe analysis

Satterwhite, C. E.↗