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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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DOE OSTI2022

Observational window effects on multi-object reverberation mapping

ABSTRACT Contemporary reverberation mapping campaigns are employing wide-area photometric data and high-multiplex spectroscopy to efficiently monitor hundreds of active galactic nuclei (AGNs). However, the interaction of the window function(s) imposed by the observation cadence with the reverberation lag and AGN variability time-scales (intrinsic to each source over a range of luminosities) impact our ability to recover these fundamental physical properties. Time dilation effects due to the sample source redshift distribution introduce added complexity. We present comprehensive analysis of the implications of observational cadence, seasonal gaps, and campaign baseline duration (i.e. the survey window function) for reverberation lag recovery. We find that the presence of a significant seasonal gap dominates the efficacy of any given campaign strategy for lag recovery across the parameter space, particularly for those sources with observed-frame lags above 100 d. Using the Australian Dark Energy Survey as a baseline, we consider the implications of this analysis for the 4MOST/Time-Domain Extragalactic Survey campaign providing concurrent follow-up of the Legacy Survey of Space and Time deep-drilling fields, as well as upcoming programmes. We conclude that the success of such surveys will be critically limited by the seasonal visibility of some potential field choices, but show significant improvement from extending the baseline. Optimizing the sample selection to fit the window function will improve survey efficacy.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Designing Remote Monitoring for Smart Manufacturing Facilities: Hazard Identification and Classification

This study investigates the process of hazard identification in complex manufacturing environments during the design phase, emphasizing the significance of the design process in developing designs that effectively mitigate hazards in contexts with numerous variables, such as a variety of machines, sensors, actuators, and agents. Through a mixed-methods approach, the objective of this work is to understand how the evolution of design outcomes across various stages might influence a designer’s ability to recognize both standard and novel hazards. To achieve this understanding, an experimental design task was conducted with six designers from a national lab specializing in manufacturing technologies. This approach combined qualitative and quantitative data analysis from a one-hour virtual session with participants. Findings suggest that the complexity of identifying hazards in a high-dimensional design space is challenging within a limited time frame and that the identification of hazards is significantly influenced by the stage of the design task and the initial design decisions, indicating the need for extended time and strategic initial planning in the design process to enhance hazard identification.

Ballestas, Caseysimone↗

DOE OSTI2022

Bayesian State-Space Modeling Framework for Understanding and Predicting Golden Eagle Movements Using Telemetry Data

Predicting raptor movements through a wind power plant under given atmospheric and topographical conditions is a crucial first step in the overall goal of quantifying the risk of turbine-related collisions and mortalities. Extracting behavioral traits of golden eagles (Aquila chrysaetos) from telemetry data requires the fusion of noisy and sparse movement data (location, heading, velocity) with a stochastic mathematical representation of the eagles' decision-making processes. In this study, we framed this problem in a Bayesian state-space framework where both observations and decision-making are assumed to be stochastic processes connected through hidden states (mode of flight, intent), and the unknown model parameters are assumed to be random variables that are calibrated using the available telemetry data. This framework allowed for rigorous consideration of underlying uncertainties while allowing for both data and prior biological knowledge to contribute to a probabilistic and predictive agent-based movement model. We implemented and applied the Bayesian framework to understand movement behavior of 23 GPS-tagged golden eagles travelling in the western US for years 2019 and 2020. Our preliminary findings show that the Bayesian state-space framework provides a robust inverse modeling apparatus to decode eagle behavioral characteristics from telemetry data. This study was primarily aimed at verifying and validating the framework with selected golden eagle tracks (both long- and short-ranged), with future research aimed at extending the framework to include multi-mode flight, consideration of atmospheric data and uplift mechanisms, eagle-to-eagle interaction, and eagle-to-turbine interaction.

Bayesian modeling↗

DOE OSTI2022

Early Results from GLASS-JWST. V: The First Rest-frame Optical Size–Luminosity Relation of Galaxies at z > 7

We present the first rest-frame optical size–luminosity relation of galaxies at z > 7, using the NIRCam imaging data obtained by the GLASS James Webb Space Telescope Early Release Science (GLASS-JWST-ERS) program, providing the deepest extragalactic data of the ERS campaign. Our sample consists of 19 photometrically selected bright galaxies with m F444W ≤ 27.8 at 7 < z < 9 and m F444W < 28.2 at z ~ 9–15. We measure the size of the galaxies in five bands, from rest-frame optical (~4800 Å) to the UV (~1600 Å) based on the Sérsic model, and analyse the size–luminosity relation as a function of wavelength. Remarkably, the data quality of the NIRCam imaging is sufficient to probe the half-light radius r e down to ~100 pc at z > 7. Given the limited sample size and magnitude range, we first fix the slope to that observed for larger samples in rest-frame UV using Hubble Space Telescope samples. The median size r 0 at the reference luminosity M = –21 decreases slightly from rest-frame optical (600 ± 80 pc) to UV (450 ± 130 pc). We then refit the size–luminosity relation allowing the slope to vary. The slope is consistent with β ~ 0.2 for all bands except F150W, where we find a marginally steeper slope of β = 0.53 ± 0.15. The steep UV slope is mainly driven by the smallest and faintest galaxies. If confirmed by larger samples, it implies that the UV size–luminosity relation breaks toward the faint end, as suggested by lensing studies.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Fully gauge-fixed SU(2) Hamiltonian for quantum simulations

Here, we demonstrate how to construct a fully gauge-fixed lattice Hamiltonian for a pure SU(2) gauge theory. Our work extends upon previous work, where a formulation of an SU(2) lattice gauge theory was developed that is efficient to simulate at all values of the gauge coupling. That formulation utilized maximal-tree gauge, where all local gauge symmetries are fixed and a residual global gauge symmetry remains. By using the geometric picture of an SU(2) lattice gauge theory as a system of rotating rods, we demonstrate how to fix the remaining global gauge symmetry. In particular, the quantum numbers associated with total charge can be isolated by rotating between the lab and body frames using the three Euler angles. The Hilbert space in this new “sequestered” basis partitions cleanly into sectors with differing total angular momentum, which makes gauge-fixing to a particular total charge sector trivial, particularly for the charge-zero sector. In addition to this sequestered basis inheriting the property of being efficient at all values of the coupling, we show that, despite the global nature of the final gauge-fixing procedure, this Hamiltonian can be simulated using quantum resources scaling only polynomially with the lattice volume.

Lattice gauge theory↗

DOE OSTI2022

Convective Heat Transfer Potential of Particles/Airflow Through Single Cell Thick Additively Manufactured Octet-Shaped Lattice Frame Material

Abstract Particle-to-Supercritical Carbon Dioxide (sCO2) heat exchangers are one of the most critical components of the next-generation Concentrating Solar Power (CSP) plants. There have been several efforts to enhance the overall heat exchanger performance which essentially comprises of thermal resistances offered by sCO2 channel, wall (separating sCO2 with particles) thickness, particle-wall contact resistance and particle-side effective heat transfer coefficient. This study is focused towards reducing the particle side thermal resistance by incorporating single unit cell thick reticulated Octet lattice frame structures on the falling particle side to enhance the effective thermal conductivity of the particle channel and to enhance convective heat transfer between the falling particles and the solid phase of the falling particle channel (endwalls and fibers). Steady-state experiments were conducted to measure the effective thermal conductivity of lattice frame material for two cases: a) when void space was occupied by air, b) when void space was occupied with particles. Further, convective heat transfer experiments have been conducted with both air (steady-state) and particles (quasi steady-state) as “working fluid” for panels sandwiching the Octet array. Three different lattice porosities ranging from 0.75 to 0.9 have been tested for a wide range of air flow rates and a fixed particle flow rate (highest potential).

Aider, Youssef↗

DOE OSTI2025

VAIM-CFF: a variational autoencoder inverse mapper solution to Compton form factor extraction from deeply virtual exclusive reactions

We develop a new methodology for extracting Compton form factors (CFFs) from deeply virtual exclusive reactions such as the unpolarized DVCS cross section using a specialized inverse problem solver, a variational autoencoder inverse mapper (VAIM). The VAIM-CFF framework not only allows us access to a fitted solution set possibly containing multiple solutions in the extraction of all 8 CFFs from a single cross section measurement, but also accesses the lost information contained in the forward mapping from CFFs to cross section. We investigate various assumptions and their effects on the predicted CFFs such as cross section organization, number of extracted CFFs, use of uncertainty quantification technique, and inclusion of prior physics information. We then use dimensionality reduction techniques such as principal component analysis to visualize the missing physics information tracked in the latent space of the VAIM framework. Through re-framing the extraction of CFFs as an inverse problem, we gain access to fundamental properties of the problem not comprehensible in standard fitting methodologies: exploring the limits of the information encoded in deeply virtual exclusive experiments.

Accelerator Physics↗

DOE OSTI2024

Accelerating uncertainty quantification in incremental dynamic analysis using dimension reduction-based surrogate modeling

We propose a surrogate modeling framework based on dimension reduction to facilitate the quantification of seismic risk of structural systems in performance-based earthquake engineering. The framework adopts incremental dynamic analysis (IDA) for addressing hazard variability, and promotes significant computational efficiency improvement for propagating epistemic uncertainties associated with the structural models. It utilizes both linear and nonlinear dimension reduction approaches, equipped with inverse mappings, to learn a functional between the input parameter space (e.g., the epistemic uncertainties of the structure) to the high-dimensional output space created through the IDA implementation across different ground motions and seismic intensity levels. Polynomial chaos expansion is adopted as the surrogate model to learn this functional in the reduced space. A nine-story steel moment-resisting frame with uncertain structural properties is used as a testbed. Furthermore, we select the seismic fragility curves as a measure of the structure’s seismic performance, since it provides an estimate of the probability of entering specified damage states for given levels of ground shaking.

42 ENGINEERING↗

DOE OSTI2023

Modeling of the cold electron plasma density for radiation belt physics

This review focusses strictly on existing plasma density models, including ionospheric source models, empirical density models, physics-based and machine-learning density models. This review is framed in the context of radiation belt physics and space weather codes. The review is limited to the most commonly used models or to models recently developed and promising. A great variety of conditions is considered such as the magnetic local time variation, geomagnetic conditions, ionospheric source regions, radial and latitudinal dependence, and collisional vs. collisionless conditions. These models can serve to complement satellite observations of the electron plasma density when data are lacking, are for most of them commonly used in radiation belt physics simulations and can improve our understanding of the plasmasphere dynamics.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Dark Matter Velocity Distributions for Direct Detection: Astrophysical Uncertainties Are Smaller Than They Appear

The sensitivity of direct detection experiments depends on the phase-space distribution of dark matter near the Sun, which can be modeled theoretically using cosmological hydrodynamical simulations of Milky Way–like galaxies. However, capturing the halo-to-halo variation in the local dark matter speeds—a necessary step for quantifying the astrophysical uncertainties that feed into experimental results—requires a sufficiently large sample of simulated galaxies, which has been a challenge. In this Letter, we quantify this variation with nearly 100 Milky Way–like galaxies from the tng50 simulation, the largest sample to date at this resolution. Moreover, we introduce a novel phase-space scaling procedure that endows every system with a reference frame that accurately reproduces the local standard-of-rest speed of our Galaxy, providing a principled way of extrapolating the simulation results to real-world data. The ensemble of predicted speed distributions is well characterized by the standard halo model, a Maxwell-Boltzmann distribution truncated at the escape speed, though the individual distributions can deviate from it, especially at high speeds. The dark matter–nucleon cross section limits placed by these speed distributions vary by ∼ 60% about the median. This places the 1⁢𝜎 astrophysical uncertainty at or below the level of the systematic uncertainty of current ton-scale detectors, even down to the energy threshold. The predicted uncertainty remains unchanged when subselecting on those TNG 50 galaxies with merger histories similar to the Milky Way. Tabulated speed distributions, as well as Maxwell-Boltzmann fits, are provided for use in computing direct detection bounds or projecting sensitivities.

Milky Way↗

DOE OSTI2021

Unmanned aircraft system (UAS) detection and assessment via temporal intensity aliasing

A method and system for temporal frequency analysis for identification of unmanned aircraft systems. The method includes obtaining a sequence of video image frames and providing a pixel from an output frame of the video; generating a fluctuating pixel value vector; examining the fluctuating pixel value vector over a period of time; obtaining the frequency information present in the pixel fluctuations; summing the frequency coefficients for the vectorized pixel values from the fluctuating pixel value vector; obtaining an image representing a two dimensional space based on the summed center frequency coefficients; generating a series of still frames equal to a summation of the center frequency coefficients for pixel variations; and combining the temporal information into spatial locations in a matrix to provide a single image containing the spatial and temporal information present in the sequence of video image frame.

Woo, Bryana Lynn↗

DOE OSTI2023

Unmanned aircraft system (UAS) detection and assessment via temporal intensity aliasing

Woo, Bryana Lynn↗

DOE OSTI2026

A State-Space Model for Stability Boundary Analysis of Grid-Following Voltage Source Converters Considering Grid Conditions

With the growing significance of renewable energy resources and energy storage systems, the number of grid-connected inverters has been rising at an increasingly rapid pace. Generally, these inverters are directly integrated with the distribution network by synchronizing with the grid voltage at the point of common coupling. However, the low grid strength and varying R/X ratios, as the common characteristics of most distribution networks or weak grids, can lead to dynamic interactions that comprise stability and limit the power transfer capacity of grid-connected inverters. To ensure stable operation of the inverters, researchers must determine the stability boundary, described as the maximum power transfer capacity of grid-connected inverters under the premise of maintaining system small-signal stability. For this purpose, we propose to formulate a state-space model of the system in the synchronously rotating dq-frame of reference and perform eigenvalue analysis to determine the stability boundary. With a detailed model of the control structure and parameters of the grid-connected inverters, the stability boundary is identified as a surface with respect to different grid strengths and R/X ratios. Case study results of proposed eigenvalue analysis are compared with those of admittance model-based stability analysis as well as time-domain simulation using a switching model in Matlab/Simulink, validating the effectiveness and accuracy of the proposed eigenvalue analysis for stability boundary identification.

grid-connected inverters↗

DOE OSTI2025

Automated and highly parallelized Bayesian optimization scheme for direct drive fusion experiments on OMEGA

Finding the optimal implosion design on existing experimental facilities for inertial confinement fusion requires an exhaustive search of the vast design parameter space. This is infeasible both with experiments and with simulations. Consequently, a large fraction of the experimentally realizable design space remains unexplored, and new design schemes are challenging to optimize in a reasonable time frame. On the OMEGA laser facility, predictive machine learning models have been developed to accurately forecast the result of an experiment using only inexpensive simulations and the large dataset of prior experimental data. However, the full design space remains vast enough to be unassailable with simple optimization techniques. Here we develop an automated and optimally parallel Bayesian optimization algorithm that can entirely optimize the target and pulse shape of a direct-drive ICF implosion under a given design paradigm. We use this algorithm to find a markedly improved design for the performance implosions on OMEGA that is predicted to hydroequivalently scale to ignition at 2.15 MJ.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

New Determinations of the UV Luminosity Functions from z ~ 9 to 2 Show a Remarkable Consistency with Halo Growth and a Constant Star Formation Efficiency

Here we provide the most comprehensive determinations of the rest-frame UV luminosity function (LF) available to date with the Hubble Space Telescope (HST) at z ~ 2–9. Essentially all of the noncluster extragalactic legacy fields are utilized, including the Hubble Ultra Deep Field, the Hubble Frontier Fields parallel fields, and all five CANDELS fields, for a total survey area of 1136 arcmin{sup 2}. Our determinations include galaxies at z ~ 2–3 leveraging the deep HDUV, UVUDF, and ERS WFC3/UVIS observations available over an ~150 arcmin{sup 2} area in the GOODS-North and GOODS-South regions. All together, our collective samples include >24,000 sources, >2.3× larger than previous selections with HST. We identify 5766, 6332, 7240, 3449, 1066, 601, 246, and 33 sources at z ~ 2, 3, 4, 5, 6, 7, 8, and 9, respectively. Combining our results with an earlier z ~ 10 LF determination by Oesch et al., we quantify the evolution of the UV LF. Our results indicate that there is (1) a smooth flattening of the faint-end slope α from α ~ -2.4 at z ~ 10 to α ~ -1.5 at z ~ 2, (2) minimal evolution in the characteristic luminosity M* at z ≥ 2.5, and (3) a monotonic increase in the normalization log{sub 10}&straightphi;* from z ~ 10 to 2, which can be well described by a simple second-order polynomial, consistent with an “accelerated” evolution scenario. We find that each of these trends (from z ~ 10 to 2.5 at least) can be readily explained on the basis of the evolution of the halo mass function and a simple constant star formation efficiency model.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

The Foundation Supernova Survey: Photospheric Velocity Correlations in Type Ia Supernovae

The ejecta velocities of Type Ia supernovae (SNe Ia), as measured by the Si ii λ6355 line, have been shown to correlate with other supernova properties, including color and standardized luminosity. We investigate these results using the Foundation Supernova Survey, with a spectroscopic data release presented here, and photometry analyzed with the SALT2 light-curve fitter. We find that the Foundation data do not show significant evidence for an offset in color between SNe Ia with high and normal photospheric velocities, with Δc = 0.004 ± 0.015. Our SALT2 analysis does show evidence for redder high-velocity SNe Ia in other samples, including objects from the Carnegie Supernova Project, with a combined sample yielding Δc = 0.018 ± 0.008. When split on velocity, the Foundation SNe Ia also do not show a significant difference in Hubble diagram residual, ΔHR = 0.015 ± 0.049 mag. Intriguingly, we find that SN Ia ejecta velocity information may be gleaned from photometry, particularly in redder optical bands. For high-redshift SNe Ia, these rest-frame red wavelengths will be observed by the Nancy Grace Roman Space Telescope. Our results are in line with previous work that suggests SN Ia host-galaxy stellar mass is correlated with ejecta velocity: high-velocity SNe Ia are found nearly exclusively in high-stellar-mass hosts. However, host-galaxy properties alone do not explain velocity-dependent differences in supernova colors and luminosities across samples. Measuring and understanding the connection between intrinsic explosion properties and supernova environments, across cosmic time, will be important for precision cosmology with SNe Ia.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Multi-frequency signatures of space-leader evolution in negative cloud-to-ground lightning stepped leaders

In this study, we examined 364 space leaders in 18 negative natural cloud-to-ground lightning strokes whose stepped leaders created new channels to ground. All strokes were captured on ultra-high-speed video cameras operating at frame rates ranging from 400k to 783k frames per second. Additionally, broadband electromagnetic field measurements were available for a subset of these strokes. The median space leader inception-to-attachment-point length and retrograde propagation speed towards the pre-existing leader channel (PELC) were 8.2 m and 4.0 x 10 6 m/s, respectively. Space leader lengths were longer and retrograde propagation speeds faster for return strokes with higher peak currents. This is likely due to the relative proximity of space leader inception points to the PELC, which makes the electric field produced by the PELC line charge density one of the primary factors in determining space leader characteristics. Space leader characteristics were weakly related to their inception altitude. We observed bursts of very high frequency (VHF) emissions preceding, by around 0.5 – 1 μs, electric field leader-step pulses; visible-frequency-range luminosity pulses started during the step pulses. The median downward leader propagation speed for all 18 strokes was 4.3 x 10 5 m/s; leader propagation speeds were generally faster for return strokes with higher peak currents. Also, leaders appeared to accelerate (on their way to ground) at altitudes lower than about 200 and 1000 m above ground level for strokes in the 10 – 60 and 84 – 228 kA peak current ranges, respectively.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

The Pantheon+ analysis: Improving the redshifts and peculiar velocities of Type Ia supernovae used in cosmological analyses

We examine the redshifts of a comprehensive set of published Type Ia supernovae, and provide a combined, improved catalogue with updated redshifts. We improve on the original catalogues by using the most up-to-date heliocentric redshift data available; ensuring all red shifts have uncertainty estimates; using the exact formulae to convert heliocentric redshifts into the Cosmic Microwave Background (CMB) frame; and utilising an improved peculiar velocity model that calculates local motions in redshift-space and more realistically accounts for the external bulk flow at high-redshifts. We review 2607 supernova redshifts; 2285 are from unique supernovae and 322 are from repeat observations of the same supernova. In total, we updated 990 unique heliocentric redshifts, and found 5 cases of missing or incorrect heliocentric corrections, 44 incorrect or missing supernova coordinates, 230 missing heliocentric or CMB frame redshifts, and 1200 missing redshift uncertainties. The absolute corrections range between 10 -8 ≤ Δz ≤ 0.038, and RMS(Δz) ~ 3 × 10 -3 . The sign of the correction was essentially random, so the mean and median corrections are small: 4 × 10 -4 and 4 × 10 -6 respectively. We examine the impact of these improvements for H 0 and the dark energy equation of state w and find that the cosmological results change by ΔH 0 = -0.12 km s -1 Mpc -1 and Δw = 0.003, both significantly smaller than previously reported uncertainties for H 0 of 1.0 km s -1 Mpc -1 and w of 0.04 respectively.

79 ASTRONOMY AND ASTROPHYSICS↗