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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 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Facility Detection and Popularity Assessment from Text Classification of Social Media and Crowdsourced Data

Advances in technology have continually progressed our understanding of where people are, how they use the environment around them, and why they are at their current location. Having a better knowledge of when various locations become popular through space and time could have large impacts on research fields like urban dynamics and energy consumption. In this paper, we discuss the ability to identify and locate various facility types (e.g. restaurant, airport, stadiums) using social media, and assess methods in determining when these facilities become popular over time. We use natural language processing tools and machine learning classifiers to interpret geotagged Twitter text and determine if a user is seemingly at a location of interest when the tweet was sent. On average our classifiers are approximately 85% accurate varying across multiple facility types, with a peak precision of 98%. By using these methods to classify unstructured text, geotagged social media data can be an extremely useful tool to better understanding the composition of places and how and when people use them.

crowd-sourced data↗
DOE OSTI2025

Unlocking Scholarly Insights: Leveraging Machine Learning Approaches for Citation Analysis and Intent Classification

Publicly funded organizations, notably institutions like the Los Alamos National Laboratory (LANL), are deeply vested in acquiring robust productivity metrics to gauge the entirety of their research output. Motivated by the imperative to enhance institutional productivity assessment, this study investigates the utilization of Large Language Models (LLM) such as BERT-based models, as well as local LLaMa-30b-instruct and Mixtral-8x7b-instruct architectures for classifying type of URL referenced resources in academic papers such as software, dataset, as well as authorship intent. Challenges in discerning resource types from context are highlighted, along with the potential of BERT and LLMs to address these challenges. Through comprehensive analysis, this research unveils a notable surge in documents featuring URL citations, indicative of the escalating importance of digital resources in scholarly publications. Moreover, citations to datasets and software demonstrate consistent growth over time, underscoring their increasing significance. Our findings also reveal that LANL authors contribute substantially to accessible science, comprising about 10% of dataset and software mentions in LANL

Large Language Models, BERT, citation classificati↗
DOE OSTI2023

Machine Learning Benchmarks for the Classification of Equivalent Circuit Models from Electrochemical Impedance Spectra

Analysis of Electrochemical Impedance Spectroscopy (EIS) data for electrochemical systems often consists of defining an Equivalent Circuit Model (ECM) using expert knowledge and then optimizing the model parameters to deconvolute various resistance, capacitive, inductive, or diffusion responses. For small data sets, this procedure can be conducted manually; however, it is not feasible to manually define a proper ECM for extensive data sets with a wide range of EIS responses. Automatic identification of an ECM would substantially accelerate the analysis of large sets of EIS data. We showcase machine learning methods to classify the ECMs of 9,300 impedance spectra provided by QuantumScape for the BatteryDEV hackathon. The best-performing approach is a gradient-boosted tree model utilizing a library to automatically generate features, followed by a random forest model using the raw spectral data. A convolutional neural network using boolean images of Nyquist representations is presented as an alternative, although it achieves a lower accuracy. We publish the data and open source the associated code. The approaches described in this article can serve as benchmarks for further studies. A key remaining challenge is the identifiability of the labels, underlined by the model performances and the comparison of misclassified spectra.

25 ENERGY STORAGE↗
DOE OSTI2016

Wave Classification Statistical Data for US Waters

Wave statistics computed using output from the NOAA WWIII hindcast simulations, spanning thirty years from 1980 to 2009. The statistics are computed based on frequency-directional variance density spectra every three hours for 1951 locations in US waters.

16 TIDAL AND WAVE POWER↗
DOE OSTI2017

Classification of the Z-Pinch Waste Stream as Low-Level Waste for Disposal

The purpose of this document is to describe the waste stream from Z-Pinch Residual Waste Project that due to worker safety concerns and operational efficiency is a candidate for blending Transuranic and low level waste together and can be safely packaged as low-level waste consistent with DOE Order 435.1 requirements and NRC guidance 10 CFR 61.42. This waste stream consists of the Pu-ICE post-shot containment systems, including plutonium targets, generated from the Z Machine experiments requested by LANL and conducted by SNL/NM. In the past, this TRU waste was shipped back to LANL after Sandia sends the TRU data package to LANL to certify the characterization (by CCP), transport and disposition at WIPP (CBFO) per LANL MOU-0066. The Low Level Waste is managed, characterized, shipped and disposed of at NNSS by SNL/NM per Sandia MOU # 11-S-560.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Classification and Calculation of Drive Loads

To permit calculation of the fatigue strength of drive components, drives are classified in terms of their loading conditions. Formulas are presented for the equivalence factors used in converting the actual variable loading conditions to conventional constant conditions. The overload coefficients required in calculating the static strength of drive components at the peak load are also determined.

42 ENGINEERING↗
DOE OSTI2022

Classification of Photovoltaic Failures with Hidden Markov Modeling, an Unsupervised Statistical Approach

Failure detection methods are of significant interest for photovoltaic (PV) site operators to help reduce gaps between expected and observed energy generation. Current approaches for field-based fault detection, however, rely on multiple data inputs and can suffer from interpretability issues. In contrast, this work offers an unsupervised statistical approach that leverages hidden Markov models (HMM) to identify failures occurring at PV sites. Using performance index data from 104 sites across the United States, individual PV-HMM models are trained and evaluated for failure detection and transition probabilities. This analysis indicates that the trained PV-HMM models have the highest probability of remaining in their current state (87.1% to 93.5%), whereas the transition probability from normal to failure (6.5%) is lower than the transition from failure to normal (12.9%) states. A comparison of these patterns using both threshold levels and operations and maintenance (O&M) tickets indicate high precision rates of PV-HMMs (median = 82.4%) across all of the sites. Although additional work is needed to assess sensitivities, the PV-HMM methodology demonstrates significant potential for real-time failure detection as well as extensions into predictive maintenance capabilities for PV.

classification↗
DOE OSTI2016

THE ANATOMY OF A LONG GAMMA-RAY BURST: A SIMPLE CLASSIFICATION SCHEME FOR THE EMISSION MECHANISM(S)

Ultra-relativistic motion and efficient conversion of kinetic energy to radiation are required by gamma-ray burst (GRB) observations, yet they are difficult to simultaneously achieve. Three leading mechanisms have been proposed to explain the observed emission emanating from GRB outflows: radiation from either relativistic internal or external shocks, or thermal emission from a photosphere. Previous works were dedicated to independently treating these three mechanisms and arguing for a sole, unique origin of the prompt emission of GRBs. In contrast, herein, we first explain why all three models are valid mechanisms and that a contribution from each of them is expected in the prompt phase. Additionally, we show that a single parameter, the dimensionless entropy of the GRB outflow, determines which mechanism contributes the most to the emission. More specifically, internal shocks dominate for low values of the dimensionless entropy, external shocks for intermediate values, and finally, photospheric emission for large values. We present a unified framework for the emission mechanisms of GRBs with easily testable predictions for each process.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

ON THE CLASSIFICATION OF UGC 1382 AS A GIANT LOW SURFACE BRIGHTNESS GALAXY

We provide evidence that UGC 1382, long believed to be a passive elliptical galaxy, is actually a giant low surface brightness (GLSB) galaxy that rivals the archetypical GLSB Malin 1 in size. Like other GLSB galaxies, it has two components: a high surface brightness disk galaxy surrounded by an extended low surface brightness (LSB) disk. For UGC 1382, the central component is a lenticular system with an effective radius of 6 kpc. Beyond this, the LSB disk has an effective radius of ∼38 kpc and an extrapolated central surface brightness of ∼26 mag arcsec{sup 2}. Both components have a combined stellar mass of ∼8 × 10{sup 10} M {sub ⊙}, and are embedded in a massive (10{sup 10} M {sub ⊙}) low-density (<3 M {sub ⊙} pc{sup 2}) HI disk with a radius of 110 kpc, making this one of the largest isolated disk galaxies known. The system resides in a massive dark matter halo of at least 2 × 10{sup 12} M {sub ⊙}. Although possibly part of a small group, its low-density environment likely plays a role in the formation and retention of the giant LSB and HI disks. We model the spectral energy distributions and find that the LSB disk is likely older than the lenticular component. UGC 1382 has UV–optical colors typical of galaxies transitioning through the green valley. Within the LSB disk are spiral arms forming stars at extremely low efficiencies. The gas depletion timescale of ∼10{sup 11} years suggests that UGC 1382 may be a very-long-term resident of the green valley. We find that the formation and evolution of the LSB disk in UGC 1382 is best explained by the accretion of gas-rich LSB dwarf galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

On the classification of GRBs and their occurrence rates

There is mounting evidence for the binary nature of the progenitors of gamma-ray bursts (GRBs). For a long GRB, the induced gravitational collapse paradigm proposes as progenitor, or “in-state,” a tight binary system composed of a carbon–oxygen core (CO{sub core}) undergoing a supernova explosion that triggers hypercritical accretion onto a neutron star (NS) companion. For a short GRB (S-GRB), an NS–NS merger is traditionally adopted as the progenitor. We divide long and S-GRBs into two subclasses, depending on whether or not a black hole (BH) is formed in the merger or in the hypercritical accretion process exceeding the NS critical mass. For long bursts, when no BH is formed, we have the subclass of X-ray flashes (XRFs), with isotropic energy E{sub iso}≲10{sup 52} erg and rest-frame spectral peak energy E{sub p,i}≲200 keV. When a BH is formed, we have the subclass of binary-driven hypernovae (BdHNe), with E{sub iso}≳10{sup 52} erg and E{sub p,i}≳200 keV. In analogy, short bursts are similarly divided into two subclasses. When no BH is formed, short gamma-ray flashes (S-GRFs) occur, with E{sub iso}≲10{sup 52} erg and E{sub p,i}≲2 MeV. When a BH is formed, the authentic S-GRBs occur, with E{sub iso}≳10{sup 52} erg and E{sub p,i}≳2 MeV. We give examples and observational signatures of these four subclasses and their rate of occurrence. From their respective rates it is possible that “in-states” of S-GRFs and S-GRBs originate from the “out-states” of XRFs. We indicate two additional progenitor systems: white dwarf–NS and BH–NS. These systems have hybrid features between long and short bursts. In the case of S-GRBs and BdHNe evidence is given of the coincidence of the onset of the high-energy GeV emission with the birth of a Kerr BH.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

UTILIZING SYNTHETIC VISIBLE SPECTRA TO EXPLORE THE PHYSICAL BASIS FOR THE CLASSIFICATION OF LAMBDA BOÖTIS STARS

Since the peculiar nature of Lambda Boötis was first noticed in 1943, the Lambda Boo stars have been recognized as a group of peculiar A-type stars. They are Population I dwarfs that show deficiencies of iron-peak elements (up to 2 dex), but have near-solar C, N, O, and S abundances. In a previous paper, we used both observed and synthetic ultraviolet spectra to demonstrate that the C i 1657 Å/Al ii 1671 Å equivalent width ratio can help distinguish between Lambda Boo stars and other metal-weak stars hotter than 8000 K. In this paper, using observed and synthetic visible (4000–6800 Å) spectra, we demonstrate that the C i 5052.17 Å/Mg ii 4481 Å equivalent width ratio can be used as a quantitative diagnostic for cooler Lambda Boo stars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

WIRED for EC: New White Dwarfs with WISE Infrared Excesses and New Classification Schemes from the Edinburgh–Cape Blue Object Survey

We present a simple method for identifying candidate white dwarf systems with dusty exoplanetary debris based on a single temperature blackbody model fit to the infrared excess. We apply this technique to a sample of Southern Hemisphere white dwarfs from the recently completed Edinburgh–Cape Blue Object Survey and identify four new promising dusty debris disk candidates. We demonstrate the efficacy of our selection method by recovering three of the four Spitzer confirmed dusty debris disk systems in our sample. Further investigation using archival high-resolution imaging shows that Spitzer data of the unrecovered fourth object is likely contaminated by a line-of-sight object that either led to a misclassification as a dusty disk in the literature or is confounding our method. Finally, in our diagnostic plot, we show that dusty white dwarfs, which also host gaseous debris, lie along a boundary of our dusty debris disk region, providing clues to the origin and evolution of these especially interesting systems.

79 ASTRONOMY AND ASTROPHYSICS↗