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At least 1,477 records · Page 82

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NASA NTRS2021

A Recursive Multi-step Machine Learning Approach for Airport Configuration Prediction

Airport configuration selection is a complex decision-making process that involves several operational and human factors. In this paper we propose a novel recursive multi-step machine learning (ML) approach to predict airport configuration. The multi-step approach guarantees stability of the predicted configuration by taking as input the configuration predicted at the previous time step. The features of the proposed model include weather data, future arrival and departure counts and current configuration. Due to the importance of arrival and departure counts in predicting the airport configuration, arrival counts are calculated using landing time predictions selected from physics-based landing time predictions available in FAA System Wide Information Management data feeds for each flight. The selection rules were developed and refined to select the most accurate time for different phases of flight. The proposed model predicts the airport configurations up to 6 hours ahead. In this paper we show the predictive performance of the proposed model for six major US airports, including Charlotte Douglas International Airport (CLT), Dallas/Fort Worth International Airport (DFW), John F. Kennedy International Airport (JFK), Newark Liberty International Airport (EWR), LaGuardia Airport (LGA) and Dallas Love Field Airport (DAL). We trained and evaluated models on 2019 and 2020 data in order to study the effect of the pandemic and how changes in traffic patterns affected the performance of the proposed model. Results are compared with a baseline assuming no airport configuration changes. In our results for DFW, we obtained a prediction accuracy of 89.3% for 3 hours ahead prediction, and 82.8% for 6 hours ahead when applied on 2019 data.

machine learning↗

NASA NTRS2021

A Recursive Multi-step Machine Learning Approach for Airport Configuration Prediction

machine learning↗

DOE OSTI2022

Effect of silver($\mathrm{I}$) ion reduction on the selectivity of olefins, paraffins, and aromatic compounds by gas chromatographic stationary phases consisting of silver($\mathrm{I}$) salts in ionic liquids

We report the olefin/paraffin selectivity offered by ionic liquid (IL) stationary phases can be enhanced through the addition of silver(I) ion, which is well-known to undergo selective complexation with unsaturated compounds. However, such stationary phases often suffer from the loss of chromatographic selectivity as silver(I) ion can be reduced to elemental silver. To maintain the separation performance of silver(I) ion/IL stationary phases, an understanding of factors and conditions that promote the reduction of silver(I) ion is needed. In this study, capillary gas chromatography columns featuring a stationary phase consisting of the 1-decyl-3-methylimidazolium bis[(trifluoromethyl)sulfonyl]imide ([C 10 MIM + ][NTf 2 - ]) IL impregnated with [Ag + ][NTf 2 - ] were examined to investigate the effects of temperature, hydrogen content in exposure gas stream, and time of heating/exposure events on olefin selectivity. Retention factors of representative analytes, such as C 6 olefins and paraffins as well as aromatic compounds, were measured after subjecting the columns to the aforementioned conditions, followed by an evaluation of selectivity factors over time. Selectivity factors of olefins and aromatic compounds were observed to decrease significantly when the stationary phases were heated to temperatures higher than 110°C as well as being subjected to mixed gas streams containing greater than 50 mol% of hydrogen. As constant column heating temperatures were applied under exposure gas mixtures containing hydrogen and nitrogen, a gradual decrease in analyte selectivity factors was observed under prolonged periods of time. However, application of a ternary gas mixture comprised of 25/50/25 mol% hydrogen/nitrogen/methane resulted in an increase in the 3-hexyne/cis-2-hexene selectivity when measured at 120°C for 60 h, due to a smaller decrease in the retention factor of 3-hexyne compared to cis-2-hexene.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Protein3D: Enabling analysis and extraction of metal‐containing sites from the Protein Data Bank with molSimplify

Abstract Metalloenzymes catalyze a wide range of chemical transformations, with the active site residues playing a key role in modulating chemical reactivity and selectivity. Unlike smaller synthetic catalysts, a metalloenzyme active site is embedded in a larger protein, which makes interrogation of electronic properties and geometric features with quantum mechanical calculations challenging. Here we implement the ability to fetch crystallographic structures from the Protein Data Bank and analyze the metal binding sites in the program molSimplify. We show the usefulness of the newly created protein3D class to extract the local environment around non‐heme iron enzymes containing a two histidine motif and prepare 372 structures for quantum mechanical calculations. Our implementation of protein3D serves to expand the range of systems molSimplify can be used to analyze and will enable high‐throughput study of metal‐containing active sites in proteins.

Edholm, Freya↗

DOE OSTI2022

SNAD transient miner: Finding missed transient events in ZTF DR4 using k-D trees

Here we report the automatic detection of 11 transients (7 possible supernovae and 4 active galactic nuclei candidates) within the Zwicky Transient Facility fourth data release (ZTF DR4), all of them observed in 2018 and absent from public catalogs. Among these, three were not part of the ZTF alert stream. Our transient mining strategy employs 41 physically motivated features extracted from both real light curves and four simulated light curve models (SN Ia, SN II, TDE, SLSN-I). These features are input to a k-D tree algorithm, from which we calculate the 15 nearest neighbors. After pre-processing and selection cuts, our dataset contained approximately a million objects among which we visually inspected the 105 closest neighbors from seven of our brightest, most well-sampled simulations, comprising 89 unique ZTF DR4 sources. Our result illustrates the potential of coherently incorporating domain knowledge and automatic learning algorithms, which is one of the guiding principles directing the SNAD team. It also demonstrates that the ZTF DR is a suitable testing ground for data mining algorithms aiming to prepare for the next generation of astronomical data.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Interpretation of high-harmonic fast-wave propagation in the scrape-off layer of NSTX-U as a geometrically bounded-waveguide mode

This paper revisits the onset of high-harmonic fast-wave (HHFW) propagation in the scrape-off layer (SOL) plasma of the NSTX/NSTX-U spherical tokamak, motivated by past HHFW heating and current drive experiments and modelling. Previously, the fast-wave propagation in the SOL was correlated with the opening (suppression) of the fast-wave right-hand cutoff layer in front of the antenna. In this work, the SOL propagation is interpreted as a geometric waveguide mode guided by the SOL geometry, whose radial width can be comparable to the wave’s perpendicular wavelength in the HHFW regime. A two-dimensional circular model is first employed using full-wave solvers to characterise the poloidal eigenmode structures and to clarify their relationship to annulus resonance. By progressively adding a tokamak-like magnetic-field configuration, starting from a uniform axial field, the effects of magnetic-field gradients and pitch on the SOL waveguide mode are characterised. The poloidal mode numbers supported by the SOL plasma agree well with analytic estimates, indicating that an anisotropic plasma in a bounded geometry selectively supports and amplifies the resonant poloidal mode number. Additionally, two-dimensional axisymmetric NSTX-U simulations demonstrate that the SOL eigenmode features identified in the circular model persist in the experimentally relevant configurations. A control approach based on lengthening the wave perpendicular wavelength relative to the SOL width, including a higher magnetic (B)-field operation, is discussed. The analysis here shows the key role of a bounded geometry in interpreting HHFW eigenmode coupling and propagation in the NSTX-U SOL plasma.

plasma heating↗

DOE OSTI2021

Complex Formation and Dissociation Dynamics on Amorphous Silica Surfaces

Benzene complex formation and dissociation dynamics with silanols on the amorphous silica surfaces of nanoporous SiO 2 , from a benzene/carbon tetrachloride solution, were measured by the growth of off-diagonal peaks in the two dimensional infrared (2D IR) chemical exchange spectrum of the isolated Si-OD stretch. The presence of two types of isolated silanols, referred to as type I and II, was revealed, with dissociation time constants of 82 ps and 4.0 ps for type I and II complexes, respectively. The type I silanols are associated with the main IR absorption feature in the Si-OD stretching region, while the type II silanols give rise to a broader shoulder to lower frequency. Polarization selective pump-probe (PSPP) measurements provided the vibrational lifetimes and orientational relaxation rates of the two silanols in the CCl 4 (free) and benzene (complex) environments. The type II silanols constitute roughly 30% of the isolated silanol population and exhibit a substantially faster rate of vibrational relaxation, making the type I dynamics the dominant contribution to the PSPP and 2D IR signals. From the measured dissociation times, the enthalpies of formation for the two surface complexes were obtained; the formation of the type I complex being significantly more exothermic. Furthermore, as the type II site is preferentially removed from the amorphous silica surface with increasing activation temperature, the results provide a reasonable explanation for the increased exothermicity of benzene adsorption on silica with increasing activation temperature in previous calorimetry experiments.

14 SOLAR ENERGY↗

DOE OSTI2022

Numerical Simulation of Vibrational Sum Frequency Generation Intensity for Non-Centrosymmetric Domains Interspersed in an Amorphous Matrix: A Case Study for Cellulose in Plant Cell Wall

Vibrational sum frequency generation (SFG) spectroscopy can specifically probe molecular species non-centrosymmetrically arranged in a centrosymmetric or isotropic medium. This capability has been extensively utilized to detect and study molecular species present at the two-dimensional (2D) interface at which the centrosymmetry or isotropy of bulk phases is naturally broken. The same principle has been demonstrated to be very effective for the selective detection of non-centrosymmetric crystalline nanodomains interspersed in three-dimensional (3D) amorphous phases. However, the full spectral interpretation of SFG features has been difficult due to the complexity associated with the theoretical calculation of SFG responses of such 3D systems. This paper describes a numerical method to predict the relative SFG intensities of non-centrosymmetric nanodomains in 3D systems as functions of their size and concentration as well as their assembly patterns, i.e., the distributions of tilt, azimuth, and rotation angles with respect to the lab coordinate. We applied the developed method to predict changes in the CH and OH stretch modes characteristic to crystalline cellulose microfibrils distributed with various orders, which are relevant to plant cell wall structures. As a result, the same algorithm can also be applied to any SFG-active nanodomains interspersed in 3D amorphous matrices.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Prospects for detecting UF6 hydrolysis intermediates by mass spectrometry, resonance Raman, and NQR spectroscopy

Simulations are performed to consider several spectrometric and spectroscopic candidates for elucidating the mechanism of the hydrolysis of uranium hexafluoride (UF6). This study is among the first to benchmark the def-mTZVP basis sets for actinide-containing molecules, and it is shown to be a suitable basis set for surveying geometrical structures and vibrational spectra when used in conjunction with density functional theory. An experiment is proposed coupling mass spectrometric ion selection with vibrational spectroscopy, and supporting infrared and Raman spectral simulations demonstrate that ionization blue-shifts bands and can change their qualitative features. Ultraviolet resonance Raman is shown to have good prospects for discriminating U–O–U bridged intermediates, evidence for which was observed recently [L. E. McNamara et al., J. Phys. Chem. A 130, 775–786 (2026)]. As a more speculative approach, we also consider the prospect of addressing 233U or 235U nuclei by quadrupole resonance (NQR) spectroscopy for assigning early stage intermediate complexes. In doing so, we provide a first order-of-magnitude estimate for the collision-induced NQR signal for the UF6 dimer, which is of interest for the interpretation of a fast decoherence time observed in liquid-phase nuclear magnetic resonance. Having provided critical insights into the formation and stability of UF6 hydrolysis intermediates in previous studies, this computational spectroscopy survey is expected to help guide and expedite future laboratory campaigns.

Lutz, Jesse J. [Center for Computing Research, San↗

DOE OSTI2024

Orbital-selective correlations and renormalized electronic structure in LiFeAs

Multiorbital physics is important to both the correlation physics and topological behavior of quantum materials. LiFeAs is a prototype iron pnictide suitable for in-depth investigation of this issue. Its electronic structure is strikingly different from the prediction of the noninteracting description. Here, a multiorbital Hubbard model is studied using a U(1) slave-spin theory. We demonstrate a mechanism for a substantial change to the Fermi surface, namely, orbital selectivity of the energy-level renormalization cooperating with its counterpart in quasiparticle spectral weight. Using this effect, we show how the dominating features of the electronic structure in LiFeAs are understood by the local correlations alone. In conclusion, our results set the stage to understand the origins and nature of both the unconventional superconductivity and likely electronic topology in this prototype iron pnictide and, more generally, reveal a remarkable degree of universality out of the seemingly complex multiorbital building blocks across a broad range of strongly correlated superconductors.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Data from: "Towards CONUS-Wide ML-Augmented Conceptually-Interpretable Modeling of Catchment-Scale Precipitation-Storage-Runoff Dynamics"

This data package was generated to support the manuscript “Towards CONUS-Wide Machine Learning-Augmented Conceptually Interpretable Modeling of Catchment-Scale Precipitation-Storage-Runoff Dynamics.” It provides input files, model outputs, plotting data, scripts, notebooks, and documentation used to develop, evaluate, and reproduce Mass-Conserving Perceptron (MCP)-based hydrologic modeling experiments across 513 selected Catchment Attributes and Meteorology for Large-sample Studies in the United States (CAMELS-US) basins. The files are organized by modeling component and analysis purpose, including rainfall–runoff experiments, snow module experiments, coupled hydrologic-snow experiments, Long Short-Term Memory (LSTM) benchmark results, model skill metrics, initialization and epoch records, cell-state normalization files, Akaike Information Criterion (AIC)-based model comparison files, and data used to generate manuscript figures. Tabular files can be opened using standard spreadsheet software or Python/R data-analysis tools. Python scripts, Jupyter notebooks, and selected MATLAB scripts are included for model execution, postprocessing, plotting, and statistical analysis. Quality assurance and quality control were conducted through the source-data selection and modeling workflow. Meteorological forcing, streamflow, and static catchment attributes were derived from the CAMELS-US dataset, and snow water equivalent data were derived from the University of Arizona (UA) Snow Water Equivalent dataset. Selected basins and time periods were screened during the associated research workflow to avoid missing observations or poor-quality cases. Static geospatial features were processed primarily using Quantum Geographic Information System (QGIS) and Geospatial Data Abstraction Library (GDAL) workflows. Additional details are provided in the associated manuscript and documentation.

ESS-DIVE CSV File Formatting Guidelines Reporting ↗

DOE OSTI2025

The Development of Catalysts for Upgrading of Pyrolysis Vapor for Refinery Feedstocks and Intermediates (CRADA Final Report)

Catalytic fast pyrolysis (CFP) is a versatile technology platform to convert biomass into fungible hydrocarbon transportation fuels and chemical co-products. Key technical barriers to reaching this goal include increasing the product yields and achieving the desired fuel properties for gasoline, diesel, and jet range fuels or blendstocks that would be suitable for introduction into existing refinery unit operations. Overcoming these barriers will require durable catalysts that are effective at upgrading and stabilizing biomass pyrolysis vapors. Towards these goals, this CRADA leveraged NREL experience as a leader in biomass pyrolysis research and Johnson Matthey's (JM) experience as a leader in the production of advanced catalytic materials. The scope spanned CFP catalyst development, characterization, multi-scale reaction testing, and computational modeling. CRADA benefits to DOE, Participant, and U.S. Taxpayer: Assists laboratory in achieving programmatic scope, Uses the laboratory’s core competencies. The purpose of this CRADA was to develop and deploy catalysts for biomass CFP to help achieve cost-competitive biofuels and bio-based products. This was accomplished through a close collaboration between biomass conversion researchers at NREL and catalyst development researchers at JM. Summary of Research Results: Focus Area 1. Foundational research on catalytic conversion and deactivation: Key interactions between pyrolysis vapors and heterogeneous catalysts were probed through catalyst characterization, model compound reaction testing, and atomistic-scale computational modeling. Catalyst development focused on multifunctional materials, which include zeolites, oxides, carbides, and nitrides. Computational modeling identified reaction mechanisms and elucidated surface chemistry to test hypotheses regarding mechanisms of deoxygenation, coupling, cracking, dehydration, coke formation, hydrogen transfer, and aromatic ring reactions. This information was used to design multifunctional catalysts to increase product yields, control product selectivity, and reduce deactivation during CFP and downstream processing steps. The results served to increase fundamental understanding of key catalyst attributes and durability features for the upgrading of biomass pyrolysis vapors. Model compound experiments confirmed the importance of metal-acid bifunctionality for the deoxygenation of lignin-derived phenolic species under hydrodeoxygenation conditions. This insight led to the development of catalysts such as Pt/TiO2 and Mo2C, which were confirmed as high-performing materials during subsequent bench-scale experiments using biomass-derived pyrolysis vapors. This focus area also led to the identification of important catalyst deactivation mechanisms associated with the deposition of inorganic contaminants such as potassium. The molecular-level insight from model compound experiments and computational modeling, shown in Figure 1, informed the development of regeneration procedures that have been shown to be effective for restoration of > 90% of initial catalyst activity. This understanding has subsequently been translated to other catalyst systems, including zeolite materials that can be operated without requirements for co-fed hydrogen.

09 BIOMASS FUELS↗

DOE OSTI2022

Robust Wheel Detection for Vehicle Re-Identification

Vehicle re-identification is a demanding and challenging task in automated surveillance systems. The goal of vehicle re-identification is to associate images of the same vehicle to identify re-occurrences of the same vehicle. Robust re-identification of individual vehicles requires reliable and discriminative features extracted from specific parts of the vehicle. In this work, we construct an efficient and robust wheel detector that precisely locates and selects vehicular wheels from vehicle images. The associated hubcap geometry can hence be utilized to extract fundamental signatures from vehicle images and exploit them for vehicle re-identification. Wheels pattern information can yield additional information about vehicles in questions. To that end, we utilized a vehicle imagery dataset that has thousands of side-view vehicle collected under different illumination conditions and elevation angles. The collected dataset was used for training and testing the wheel detector. Experiments show that our approach could detect vehicular wheels accurately for 99.41% of the vehicles in the dataset.

47 OTHER INSTRUMENTATION↗

NASA NTRS1974

Overall evaluation of Skylab (EREP) images for cartographic application

The author has identified the following significant results. The importance of photomap products derived from Skylab type imagery for portrayal of previously unmapped (or poorly mapped) areas is recognized as truly significant. Updating of maps of any scale from Skylab type imaging can only be accomplished on a selective basis. Relative positional accuracy commensurate with 1:100,000 scale (Sl90A) or even 1:50,000 (S190B) is considered correct. However, many features required on such maps cannot be properly identified or classified from such imagery. The comprehensive updating of larger scale maps requires supplementary photography or ground truth.

Colvocoresses, A. P.↗

NASA NTRS1974

Noise reduction programs for DC-8 and DC-9 airplanes

A summary review is presented of the results of current and recently completed noise-reduction programs for DC-8 and DC-9 airplanes. The relationship of these programs to other efforts by Douglas to develop quieter CTOL airplanes is briefly outlined. The engine/nacelle concepts studied were: (1) application of nacelle acoustic treatment, (2) variable-area exhaust nozzles, (3) jet exhaust noise suppressors, and (4) engines with larger-diameter new front fans. Acoustic analyses leading to the selection of certain engine/nacelle configurations are described, as well as design constraints which limit the noise reduction capability of certain designs. Acoustic design features of the modified engine/nacelles are discussed along with estimates of the changes in aircraft community noise levels, as well as estimates of the changes in aircraft weight, performance, cost, and operational restrictions.

Frasca, R. L.↗

NASA NTRS1975

The Skylab Parasol

An alternate thermal protection system for the Skylab space station cluster was deemed necessary shortly after launch when severe damage occured to the orbital workshop as it passed through the period of maximum dynamic pressure. Data indicated that the combination micrometeoroid and thermal shield on the sun facing side of the vehicle had been destroyed. The simultaneous design, fabrication, and test of the Skylab Parasol System which was completed in 6 days of around-the-clock effort is described. The Skylab Parasol design was selected as the primary sunshade device based on simplicity of design, ability to fabricate quickly, and early demonstration of a working prototype which featured semiautomatic deployment from within the workshop under shirt sleeve environment conditions.

Kinzler, J. A.↗

NASA NTRS1976

A microprocessor controlled pressure scanning system

A microprocessor-based controller and data logger for pressure scanning systems is described. The microcomputer positions and manages data from as many as four 48-port electro-mechanical pressure scanners. The maximum scanning rate is 80 pressure measurements per second (20 ports per second on each of four scanners). The system features on-line calibration, position-directed data storage, and once-per-scan display in engineering units of data from a selected port. The system is designed to be interfaced to a facility computer through a shared memory. System hardware and software are described. Factors affecting measurement error in this type of system are also discussed.

Anderson, R. C.↗

NASA NTRS1976

A microprocessor controlled pressure scanning system

Anderson, R. C.↗