Search NASA⌕ Search

SEARCH · Search NASA

Results for “tabular”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Deriving iceberg ablation rates using an on-iceberg autonomous phase-sensitive radar (ApRES)

Abstract The increase in iceberg discharge into the polar oceans highlights the importance of understanding how quickly icebergs are deteriorating and where the resulting freshwater injection is occurring. Recent advances in quantifying iceberg deterioration through combinations of modeling, remote sensing and direct in situ measurements have successfully calculated overall ablation rates, and surface and sidewall ablation; however, in situ measurements of basal melt rates have been difficult to obtain. Radar has successfully measured iceberg thickness, but repeat measurements, which would capture a change in iceberg thickness with time, have not yet been collected. Here we test the applicability of using an on-iceberg autonomous phase-sensitive radar (ApRES) to quantify basal ablation rates of a large (~800 m long) non-tabular Arctic iceberg during an intensive 2019 summer field campaign in Sermilik Fjord, southeast Greenland. We find that ApRES can be used to measure basal ablation even over a short deployment period (10 d), and also provide a lower bound on sidewall melt. This study fills a critical gap in iceberg research and pushes the limits of field instrumentation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

AutoSourceID-Classifier: Star-galaxy classification using a convolutional neural network with spatial information

Aims.Traditional star-galaxy classification techniques often rely on feature estimation from catalogs, a process susceptible to introducing inaccuracies, thereby potentially jeopardizing the classification’s reliability. Certain galaxies, especially those not manifesting as extended sources, can be misclassified when their shape parameters and flux solely drive the inference. We aim to create a robust and accurate classification network for identifying stars and galaxies directly from astronomical images. Methods.The AutoSourceID-Classifier (ASID-C) algorithm developed for this work uses 32x32 pixel single filter band source cutouts generated by the previously developed AutoSourceID-Light (ASID-L) code. By leveraging convolutional neural networks (CNN) and additional information about the source position within the full-field image, ASID-C aims to accurately classify all stars and galaxies within a survey. Subsequently, we employed a modified Platt scaling calibration for the output of the CNN, ensuring that the derived probabilities were effectively calibrated, delivering precise and reliable results. Results.We show that ASID-C, trained on MeerLICHT telescope images and using the Dark Energy Camera Legacy Survey (DECaLS) morphological classification, is a robust classifier and outperforms similar codes such as SourceExtractor. To facilitate a rigorous comparison, we also trained an eXtreme Gradient Boosting (XGBoost) model on tabular features extracted by SourceExtractor. While this XGBoost model approaches ASID-C in performance metrics, it does not offer the computational efficiency and reduced error propagation inherent in ASID-C’s direct image-based classification approach. ASID-C excels in low signal-to-noise ratio and crowded scenarios, potentially aiding in transient host identification and advancing deep-sky astronomy.

Astronomy & Astrophysics↗
DOE OSTI2020

Local measurements of the spatial magnetic field distribution in a z-pinch plasma during and near stagnation using polarization spectroscopy

We present here the detailed measurements of radial distribution of the magnetic field in a gas-puff z-pinch plasma at the final stages of the implosion phase and at stagnation. While the measurements are chordal, the radial distribution of different charge states was utilized to measure the magnetic field locally for certain radii, so that unlike chordal measurements in general, the magnetic field radial distribution was obtained with no need for the Abel inversion of the data. The distribution was measured using the Zeeman effect via a novel spectroscopic technique, at several axial locations, and demonstrates striking features such as the peak field remaining at a radius much larger than the stagnation radius at all times. Furthermore, while the distribution observed is sometimes monotonic with respect to the radius, it is often not, a behavior that can be linked to 2D features in the plasma column resulting from the Rayleigh–Taylor instability. The current flowing through the stagnating plasma was found to be a small fraction of the total current, resulting in clearly insufficient magnetic pressure to balance the plasma pressure at stagnation. The magnetic field data, taken over several axial positions, are used to obtain the true inductance in the imploding plasma for the first time; it is found that the data cannot explain the current turnover at stagnation. A simulation with the MACH2-Tabular Collisional-Radiative Equilibrium magnetohydrodynamics code in the r–z plane shows that the peak of the magnetic field pinches to a much smaller radius than is observed in the spectroscopic data. Furthermore, the depth of the computed current turnover at stagnation is smaller than the measured one. The two observed features of a radially extended magnetic field at stagnation together with a deep current turnover are a challenge to match in simulations. Various calculations and estimates of the inductive and resistive load voltages are examined to ascertain if they are responsible for the observed current notch. Lastly, the results demonstrate that the knowledge of the true inductance in the driven load requires such magnetic-field-distribution measurements and that imaging data or electrical measurements are insufficient.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Determining the electrical conductivity of metals using the 2 MA Thor pulsed power driver

We present the development of a pulsed power experimental technique to infer the electrical conductivity of metals from ambient to high energy density conditions. The method is implemented on Thor, a moderate scale (1–2 MA) pulsed power driver. The electrical conductivity of copper at elevated temperature (>4000 K) and pressure (>10 GPa) is determined, and a new tabular material model is developed, guided by density functional theory, which preserves agreement with existing experimental data. Minor modifications (<10%) are found to be necessary to the previous Lee–More–Desjarlais model isotherms in the vicinity of the melt transition in order to account for observed discrepancies with the new experimental data. An analytical model for magnetic direct drive flyer acceleration and Joule heating induced vaporization based on the Tsiolkovsky “rocket equation” is presented to assess sensitivity of the method to minor changes in electrical conductivity.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Equation-of-state, sound speed, and reshock of shock-compressed fluid carbon dioxide

Mechanical equation-of-state data of initially liquid and solid CO2 shock-compressed to terapascal conditions are reported. Diamond-sapphire anvil cells were used to vary the initial density and state of CO2 samples that were then further compressed with laser-driven shock waves, resulting in a data set from which precise derivative quantities, including Grüneisen parameter and sound speed, are determined. Reshock states are measured to 800 GPa and map the same pressure-density conditions as the single shock using different thermodynamic paths. The compressibility data reported here do not support current density-functional-theory calculations, but are better represented by tabular equation-of-state models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

The equation of state and shock-driven decomposition of polymethylmethacrylate (PMMA)

We present new equations of state (EOS) for polymethylmethacrylate and its shock-driven decomposition products, generated in both tabular form and as linear U S – u p fits to all previously available shock data. Different approaches are taken for materials shocked above and below the apparent threshold for chemical reactions at pressures P ≈ 30 GPa. Both EOSs are calibrated to and compared with a broad array of experimental results, as well as new ab initio molecular dynamics simulations presented here. Comparisons are good in most cases, and we focus our particular attention on those observables that test the distinction between reactants and products.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Resonance Scattering Treatment with the Windowed Multipole Formalism

A new method for directly sampling the resonance upscattering effect is presented. Alternatives have relied on inefficient rejection sampling techniques or large tabular storage of relative velocities. None of these approaches, which require pointwise energy data, are particularly well suited to the windowed multipole cross-section representation. The new method, called multipole analytic resonance scattering, overcomes these limitations by inverse transform sampling from the target relative velocity distribution where the cross section is expressed in the multipole formalism. The closed-form relative speed distribution contains a novel special function we deem the incomplete Faddeeva function, and we present the first results on its efficient numerical evaluation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Development, Verification, and Validation of an OpenFOAM-Based Solver for Modeling Inertial Fusion Energy Chambers

Our work seeks to introduce a computational tool tailored to the physics of inertial fusion energy chambers, in particular, those concepts based on thick liquid walls. In this approach, the structural materials are protected by several neutron mean-free-paths of renewable liquid and thus will be able to survive much longer than un-shielded walls, with virtually all structures lasting for the life of the plant and enabling the use of commercially available and qualified materials. The OpenFOAM-based solver named rhoCentralFoam has been used as a starting point. rhoCentralFoam belongs to the standard OpenFOAM solver toolset. It is a high-speed, explicit compressible flow solver with shock-capturing capability. While the main features have been retained, the solver had to be restructured to make use of tabular data for equations of states, a necessary addition to model the complex thermo-physical properties of ionized gasses. This entailed the need to change the independent state variables used by the solver, resulting in a new thermodynamic library and slightly different solution algorithm. Moreover, a radiation heat transfer model based on the P-1 approximation was added to the solver. The solver is verified against an analytical solution from the Sedov-Taylor-Neumann test problem to showcase the ability of the hydrodynamic solvers to handle strong shocks, whereas the P-1 model was verified using a simple one-dimensional problem with an analytical solution. Additionally, a validation case involving shock-wave propagation through jet array is presented, and the results are compared with experimental data from the open literature. Lastly, in order to showcase the utility of the solver for practical cases, we applied the refined solver to two representative scenarios: gas venting within the HYLIFE-II chamber and the compression of the gas following the partial ablation of the liquid wall.

Chamber dynamics↗
DOE OSTI2020

A line-binned treatment of opacities for the spectra and light curves from neutron star mergers

ABSTRACT The electromagnetic observations of GW170817 were able to dramatically increase our understanding of neutron star mergers beyond what we learned from gravitational waves alone. These observations provided insight on all aspects of the merger from the nature of the gamma-ray burst to the characteristics of the ejected material. The ejecta of neutron star mergers are expected to produce such electromagnetic transients, called kilonovae or macronovae. Characteristics of the ejecta include large velocity gradients, relative to supernovae, and the presence of heavy r-process elements, which pose significant challenges to the accurate calculation of radiative opacities and radiation transport. For example, these opacities include a dense forest of bound–bound features arising from near-neutral lanthanide and actinide elements. Here we investigate the use of fine-structure, line-binned opacities that preserve the integral of the opacity over frequency. Advantages of this area-preserving approach over the traditional expansion–opacity formalism include the ability to pre-calculate opacity tables that are independent of the type of hydrodynamic expansion and thus eliminate the computational expense of calculating opacities within radiation-transport simulations. Tabular opacities are generated for all 14 lanthanides as well as a representative actinide element, uranium. We demonstrate that spectral simulations produced with the line-binned opacities agree well with results produced with the more accurate continuous Monte Carlo Sobolev approach, as well as with the commonly used expansion–opacity formalism. The agreement between the line-binned and expansion–opacity results is explained as arising from the similarity in their opacities in the limit of low optical depth, where radiation transport is important in the ejecta. Additional investigations illustrate the convergence of opacity with respect to the number of included lines, and elucidate sensitivities to different atomic physics approximations, such as fully and semirelativistic approaches.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Actinide opacities for modelling the spectra and light curves of kilonovae

ABSTRACT We extend previous ab initio calculations of lanthanide opacities to include a complete set of actinide opacities for use in the modelling of kilonova (KN) light curves and spectra. Detailed, fine-structure line features are generated using the configuration-interaction approach. These actinide opacities display similar trends to those observed for lanthanide opacities, such as the lighter actinides producing higher opacity than the heavier ones for relevant conditions in the dynamical ejecta. A line-binned treatment is employed to pre-compute opacity tables for 14 actinide elements (89 ≤ Z ≤ 102) over a grid of relevant temperatures and densities. These tabular opacities will be made publicly available for general usage in KN modelling. We demonstrate the usefulness of these opacities in KN simulations by exploring the sensitivity of light curves and spectra to different actinide abundance distributions that are predicted by different nuclear theories, as well as to different choices of ejecta mass and velocity. We find very little sensitivity to the two considered distributions, indicating that opacities for actinides with Z ≥ 99 do not contribute strongly. On the other hand, a single actinide element, protactinium, is found to produce faint spectral features in the far-infrared at late times (5–7 d post merger). More generally, we find that the choice of ejecta mass and velocity have the most significant effect on KN emission for this study.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Shock compression of liquid helium to 360 GPa

Data for the shock equation of state of helium are obtained up to 360⁢G⁡Pa, nearly doubling the pressure of previous experimental measurements. The helium samples are first precompressed to 2.7 g⁡c⁢m −3 in a diamond anvil cell prior to laser-driven shock compression at the Omega Laser Facility. Time-resolved Doppler velocimetry and pyrometry reveal significant reflectivity and greater compressibility compared to the predictions of existing broad-range tabular equation of state models, which may be caused by the onset of ionization. These experimental observations, however, are largely captured with molecular-dynamics simulations based on density functional theory, affirming the ability of first-principles techniques to capture complex physics, while enabling critical insight for the behavior of warm dense helium in Jovian interiors and white dwarf atmospheres.

Physics - Plasma physics↗
DOE OSTI2021

Multiphase tin equation of state using density functional theory

In this work, we perform density functional theory (DFT) calculations of five solid phases and the liquid phase of tin. The calculations include cold curves of the five solid phases, phonon calculations in the quasiharmonic approximation over a range of volumes for each solid phase, and DFT-based molecular dynamics (DFT-MD) simulations of the liquid phase, including those of the melt curve using the Z method. Using the DFT results, we construct a tabular multiphase sesame equation of state for tin, referred to as sesame 2162. Comparisons to experimental data are made and show a high level of agreement in isobaric data, isothermal data, shock data, and phase boundary measurements, including measurements of the melt curve. The 2162 EOS will be useful for hydrodynamics simulations and has been designed with an eye toward hydrodynamics simulations that incorporate materials strength models and allow for modeling of the kinetics of phase transitions.

3-dimensional systems↗
DOE OSTI2024

Tree-based algorithms for weakly supervised anomaly detection

Weakly supervised methods have emerged as a powerful tool for model-agnostic anomaly detection at the Large Hadron Collider (LHC). While these methods have shown remarkable performance on specific signatures such as dijet resonances, their application in a more model-agnostic manner requires dealing with a larger number of potentially noisy input features. In this paper, we show that using boosted decision trees as classifiers in weakly supervised anomaly detection gives superior performance compared to deep neural networks. Boosted decision trees are well known for their effectiveness in tabular data analysis. Our results show that they not only offer significantly faster training and evaluation times, but they are also robust to a large number of noisy input features. By using advanced gradient boosted decision trees in combination with ensembling techniques and an extended set of features, we significantly improve the performance of weakly supervised methods for anomaly detection at the LHC. This advance is a crucial step toward a more model-agnostic search for new physics. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2024

Gravitational waves from binary neutron star mergers with a spectral equation of state

In numerical simulations of binary neutron star systems, the equation of state of the dense neutron star matter is an important factor in determining both the physical realism and the numerical accuracy of the simulations. Some equations of state used in simulations are C 2 or smoother in the pressure/density relationship function, such as a polytropic equation of state, but may not have the flexibility to model stars or remnants of different masses while keeping their radii within known astrophysical constraints. Other equations of state, such as tabular or piece-wise polytropic, may be flexible enough to model additional physics and multiple stars' masses and radii within known constraints, but are not as smooth, resulting in additional numerical error. We will study in this paper a recently developed family of equation of state, using a spectral expansion with sufficient free parameters to allow for a larger flexibility than current polytropic equations of state, and with sufficient smoothness to reduce numerical errors compared to tabulated or piece-wise polytropic equations of state. We perform simulations at three mass ratios with a common chirp mass, using two distinct spectral equations of state, and at multiple numerical resolutions. We evaluate the gravitational waves produced from these simulations, comparing the phase error between resolutions and equations of state, as well as with respect to analytical models. From our simulations we estimate that the phase difference at merger for binaries with a dimensionless weighted tidal deformability difference greater than Δ$\tilde{Λ}$=55 can be captured by the SpEC code for these equations of state.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Efficient Clustering of Software Vulnerabilities using Self Organizing Map (SOM)

The common vulnerabilities and exposures (CVE) database was created with a mission to ``identify, define, and catalog publicly disclosed cybersecurity vulnerabilities''. This rich body of information can be used to enable rapid and efficient response to secure and defend cyber operations and protect critical cyber infrastructure. The main goal of this paper is to develop a visual analytics tool to enable deep analysis of CVEs using unsupervised clustering techniques. We enhance our analysis by first mapping CVEs to hierarchical-classes in Common Weakness Enumeration (CWE) using information in the National Vulnerability Database (NVD). Both the mapping and the numerical representation of CVEs are enabled by V2W-BERT, which uses natural language processing of the extensive information in NVD to generate a large tabular database of 137,226 CVE entries from 1999 to 2020, where each CVE is represented by a vector of 768 numerical features. The vectorized data is processed by Self-Organizing Maps (SOM), which is an unsupervised machine learning technique for dimensionality reduction, visual representation and clustering. Using a Torus map of 6417 units, we achieve ~10-fold data compression of ~140k CVEs using SOM. The trained map is further clustered using standard K-means clustering into 138 clusters of CVEs. We conducted a brief investigation of the rich mapping of CVEs to best-matching-units to K-means clusters, as well as CVEs to CWEs. For example, this novel mapping provided insight into the role of CWE-59 and CWE-264 in several CVEs that is otherwise hard to explore in the original data. We conclude that our this novel approach will not only enable deep analysis of the complex relationships between CVEs and CWEs, but also a mechanism to quickly respond to and design mitigation actions for rapidly evolving vulnerabilities that have not been mapped to existing CWEs.

Panchal, Khyati↗
DOE OSTI2025

Engineering Privacy at the Edge: A Practical Guide to Differential Privacy in System Architectures

The rapid expansion of distributed and edge computing platforms—spanning autonomous vehicles, IoT sensors, and healthcare monitors—has heightened concerns about data privacy. Differential Privacy (DP) offers a rigorous mathematical framework to protect sensitive information while retaining analytical utility. This tutorial introduces the foundations of DP for both numerical and categorical datasets and extends the discussion to correlation-aware techniques tailored for structured and high-dimensional data. Hands-on demonstrations will begin with the PETINA (Privacy prEservaTIoN Algorithms) package for numerical data and continue with MIC-DP (Maximum Information Correlated Differential Privacy) for tabular data. Designed for researchers and practitioners in secure systems, embedded architectures, and AI accelerators, the tutorial emphasizes practical and scalable methods for integrating DP into real-world system designs.

Kotevska, Olivera [ORNL] (ORCID:0000000316772243)↗
DOE OSTI2021

Analysis of Weather and Climate Extremes Impact on Power System Outage

This paper provides statistical analysis of the characteristics of power system outages to gain a better understanding of the impacts of the increasing severe weather conditions on the outages. 10-year historical power system outage data from the Bonneville Power Administration (BPA) were gathered together with co-located weather attributes and recorded extreme weather events in the service area, which are paired in comparable spatial and temporal scales, with a focus on each outage transmission line. Statistical frequency analysis and cross-tabular evaluation are performed to investigate the occurring frequency and duration of outages associated with extreme weather in this area of study. The study reveals that the weather-related outages can be mainly attributed to hail and thunderstorm events which correspond to up to 60% out of all failures in several transmission line types.

Ren, Huiying↗
DOE OSTI2021

Albedo Data Sets for Bifacial PV Systems

For use by the PV and financial communities to better estimate the performance and to reduce the risk of bifacial PV systems, data sets of ground albedo and associated meteorological data were developed by using existing measurement network data and data contributed by the PV industry. The data sets include time-series data as well as summary information of tabular monthly and yearly data and plots of monthly and hourly albedo values. Complete information is presented in a user's guide and data are available for download from NREL's DuraMAT website.

albedo↗