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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

The Simons Observatory: Combining cross-spectral foreground cleaning with multitracer B -mode delensing for improved constraints on inflation

The Simons Observatory (SO), due to start full science operations in early 2025, aims to set tight constraints on inflationary physics by inferring the tensor-to-scalar ratio r from measurements of cosmic microwave background (CMB) polarization B-modes. Its nominal design including three small-aperture telescopes (SATs) targets a precision σ⁡(r = 0) ≤ 0.003 without delensing. Achieving this goal and further reducing uncertainties requires a thorough understanding and mitigation of other large-scale B-mode sources such as Galactic foregrounds and weak gravitational lensing. We present an analysis pipeline aiming to estimate r by including delensing within a cross-spectral likelihood, and demonstrate it for the first time on SO-like simulations accounting for various levels of foreground complexity, inhomogeneous noise and partial sky coverage. As introduced in an earlier SO delensing paper, lensing B-modes are synthesized using internal CMB lensing reconstructions as well as Planck-like cosmic infrared background maps and LSST-like galaxy density maps. We then extend SO’s power-spectrum-based foreground-cleaning algorithm to include all auto- and cross-spectra between the lensing template and the SAT B-modes in the likelihood function. This allows us to constrain r and the parameters of our foreground model simultaneously. Within this framework, we demonstrate the equivalence of map-based and cross-spectral delensing and use it to motivate an optimized pixel-weighting scheme for power spectrum estimation. We start by validating our pipeline in the simplistic case of uniform foreground spectral energy distributions. In the absence of primordial B-modes, we find that the 1⁢σ statistical uncertainty on r, σ⁡(r), decreases by 37% as a result of delensing. Tensor modes at the level of r = 0.01 are successfully detected by our pipeline. Even when using more realistic foreground models including spatial variations in the dust and synchrotron spectral properties, we obtain unbiased estimates of r both with and without delensing by employing the moment-expansion method. In this case, uncertainties are increased due to the higher number of model parameters, and delensing-related improvements range between 27% and 31%. These results constitute the first realistic assessment of the delensing performance at SO’s nominal sensitivity level.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

A Measurement-Based Adaptive Voltage Regulation Method Considering Topology Changes

This paper proposes an online adaptive data-driven distributed energy resource (DER) dispatch optimization method for voltage control considering topology changes. By using a local sensitivity factor (LSF)-enabled voltage control, traditional DER control can be reformulated into a linear programming (LP) problem, leading to faster computation speeds. Power injection alteration and topology changes are two common operational changes in the distribution network that can affect the LSF and voltage control performance. To address this issue, a robust estimation method is developed to adjust the sensitivity matrix at each time step for the time-varying power injection changes. When topology changes occur, only the allocated predominant LSF submatrices are updated based on measurement data, allowing for a fast adaptation to the system reconfiguration. Results obtained from a real distribution feeder in Southern California demonstrate its robustness as compared to traditional volt-var control and constant LSF matrix dispatch control methods.

DERs↗
DOE OSTI2020

Deconstructing laws of accessibility and facility distribution in cities

The era of the automobile has seriously degraded the quality of urban life through costly travel and visible environmental effects. A new urban planning paradigm must be at the heart of our road map for the years to come, the one where, within minutes, inhabitants can access their basic living needs by bike or by foot. In this work, we present novel insights of the interplay between the distributions of facilities and population that maximize accessibility over the existing road networks. Results in six cities reveal that travel costs could be reduced in half through redistributing facilities. In the optimal scenario, the average travel distance can be modeled as a functional form of the number of facilities and the population density. As an application of this finding, it is possible to estimate the number of facilities needed for reaching a desired average travel distance given the population distribution in a city.

42 ENGINEERING↗
DOE OSTI2023

Surface and subsurface oceanographic features drive forage fish distributions and aggregations: Implications for prey availability to top predators in the US Northeast Shelf ecosystem

Abstract Forage fishes are a critical food web link in marine ecosystems, aggregating in a hierarchical patch structure over multiple spatial and temporal scales. Surface‐level forage fish aggregations (FFAs) represent a concentrated source of prey available to surface‐ and shallow‐foraging marine predators. Existing survey and analysis methods are often imperfect for studying forage fishes at scales appropriate to foraging predators, making it difficult to quantify predator–prey interactions. In many cases, general distributions of forage fish species are known; however, these may not represent surface‐level prey availability to predators. Likewise, we lack an understanding of the oceanographic drivers of spatial patterns of prey aggregation and availability or forage fish community patterns. Specifically, we applied Bayesian joint species distribution models to bottom trawl survey data to assess species‐ and community‐level forage fish distribution patterns across the US Northeast Continental Shelf (NES) ecosystem. Aerial digital surveys gathered data on surface FFAs at two project sites within the NES, which we used in a spatially explicit hierarchical Bayesian model to estimate the abundance and size of surface FFAs. We used these models to examine the oceanographic drivers of forage fish distributions and aggregations. Our results suggest that, in the NES, regions of high community species richness are spatially consistent with regions of high surface FFA abundance. Bathymetric depth drove both patterns, while subsurface features, such as mixed layer depth, primarily influenced aggregation behavior and surface features, such as sea surface temperature, sub‐mesoscale eddies, and fronts influenced forage fish diversity. In combination, these models help quantify the availability of forage fishes to marine predators and represent a novel application of spatial models to aerial digital survey data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Distributed Wind Development Potential at United States Correctional Facilities

The goal of this assessment was to provide a high-level overview of distributed wind development potential at correctional facilities across the United States. The assessment considered the wind resource, electricity rates, and electricity consumption at facilities. In total, Pacific Northwest National Laboratory (PNNL) estimates that 2,421 facilities in 1,280 counties, projected to consume a combined 12,000 GWh/year, have the potential to host distributed wind projects.

17 WIND ENERGY↗
DOE OSTI2022

Quasar Identification Using Multivariate Probability Density Estimated from Nonparametric Conditional Probabilities

Nonparametric estimation for a probability density function that describes multivariate data has typically been addressed by kernel density estimation (KDE). A novel density estimator recently developed by Farmer and Jacobs offers an alternative high-throughput automated approach to univariate nonparametric density estimation based on maximum entropy and order statistics, improving accuracy over univariate KDE. This article presents an extension of the single variable case to multiple variables. The univariate estimator is used to recursively calculate a product array of one-dimensional conditional probabilities. In combination with interpolation methods, a complete joint probability density estimate is generated for multiple variables. Good accuracy and speed performance in synthetic data are demonstrated by a numerical study using known distributions over a range of sample sizes from 100 to 10 6 for two to six variables. Performance in terms of speed and accuracy is compared to KDE. The multivariate density estimate developed here tends to perform better as the number of samples and/or variables increases. As an example application, measurements are analyzed over five filters of photometric data from the Sloan Digital Sky Survey Data Release 17. The multivariate estimation is used to form the basis for a binary classifier that distinguishes quasars from galaxies and stars with up to 94% accuracy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Review of the November 11, 1905 Earthquake: Seismic Intensity Data, Magnitude, and Location Report

The macroseismic location and magnitude of the Shoshone 1905 earthquake has been based on the application of objective and quantitative approaches that produce estimates of earthquake source location and magnitude, and associated uncertainties. The performance of all three approaches applied depends critically on the characteristics of the seismic intensity field. Regional intensity attenuation relations were derived based on a calibration set of earthquakes and then, the procedure was validated using three independent very recent events. The macroseismic epicenter location was determined by either a grid search procedure, the spatial distribution of the sites experiencing the largest intensities, or a combination of both. The macroseismic magnitude estimates are based on the derived regional intensity attenuation relations. There is consistency in the location and magnitude of the November 1905 earthquake as obtained by the three methods. The overlapping region of the 68% bootstrap resampling solutions suggests a reliable epicenter location within 41.550N ? 42.060N and 113.478W ? 112.320W. This region encloses the original Oaks (1992) epicenter location. Macroseismic magnitude estimates range between 5.87 and 6.05.

58 GEOSCIENCES↗
DOE OSTI2023

Improving multiwell petrophysical interpretation from well logs via machine learning and statistical models

Well-log interpretation estimates in situ rock properties along well trajectory, such as porosity, water saturation, and permeability, to support reserve-volume estimation, production forecasts, and decision making in reservoir development. However, due to measurement errors, variability of well logs caused by multiple measurement vendors, different borehole tools, and nonuniform drilling/borehole conditions, estimations of rock properties with original well logs without proper preprocessing may not be accurate, especially in the context of multiwell estimation. Well-log normalization techniques such as two-point scaling and mean-variance normalization are commonly used to improve the robustness of multiwell rock-property estimation. However, these techniques do not consider the correlation between well logs and require subjective knowledge for their effective implementation. To reduce uncertainties and processing time associated with multiwell rock-property estimation from well logs, we develop discriminative adversarial (DA) and linear constraint models for well-log normalization and rock-property estimation. The DA neural network model developed for well-log normalization and interpretation can perform linear and nonlinear well-log normalization while considering the joint distribution of each well log and rock properties. However, the linear constraint model uses an ensemble of predictions from linear models to constrain well-log normalization and rock-property estimation. We also develop a divergence-based type well identification method to select type (training) wells for a test well based on the statistical similarity of associated well-log distributions instead of the interwell distance. We apply the DA model to perform well-log normalization and prediction of permeability for the Seminole San Andres Unit carbonate reservoir. Compared with the permeability predicted with the classical machine learning model without well-log normalization and models with two-point scaling normalization, the DA model yields the most accurate permeability prediction by decreasing the mean-squared error of permeability prediction by 20%–50%.

Geochemistry & Geophysics↗
DOE OSTI2021

Sealing of fractures in a representative CO 2 reservoir caprock by migration of fines

The impact of fines migration on fracture transmissivity reduction was investigated by injecting a brine solution containing a suspension of 0.1 wt. % kaolinite particles with a mean particle size distribution of 9.6 µm through fractured shale core samples. The fractures had apertures estimated to be approximately 100 µm. A mass balance approach was used to determine the quantity of kaolinite that was deposited within the fractures (influent – effluent = amount deposited in fractures). Large fractions (44 to 90%) of the suspended kaolinite pumped through the fractures were deposited within the fractures. Based on fracture volumes estimated with X-ray computed tomography, it was determined that approximately 10 to 17% of the fracture volume was filled with kaolinite at the point when flow was completely restricted. These results indicate that 100 µm fractures in CO 2 reservoir caprocks could be sealed within hours if the brines passing through the fractures contain a proportional volume of particulates to the tests performed in this laboratory study.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2020

Di-Higgs production in the 4b channel and gravitational wave complementarity

We present a complementarity study of gravitational waves and double Higgs production in the 4 b channel, exploring the gauge singlet scalar extension of the SM. This new physics extension serves as a simplified benchmark model that realizes a strongly first-order electroweak phase transition necessary to generate the observed baryon asymmetry in the universe. In calculating the signal-to-noise ratio of the gravitational waves, we incorporate the effect of the recently discovered significant suppression of the gravitational wave signals from sound waves for strong phase transitions, make sure that supercooled phase transitions do complete and adopt a bubble wall velocity that is consistent with a successful electroweak baryogenesis by solving the velocity profiles of the plasma. The high-luminosity LHC sensitivity to the singlet scalar extension of the SM is estimated using a shape-based analysis of the invariant 4 b mass distribution. We find that while the region of parameter space giving detectable gravitational waves is shrunk due to the new gravitational wave simulations, the qualitative complementary role of gravitational waves and collider searches remain unchanged.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Light quark Yukawas in triboson final states

Triple heavy vector boson production, pp → VVV (V = W, Z), has recently been observed for the first time. We propose that precision measurements of this process provide an excellent probe of the first generation light quark Yukawa couplings. Modified quark interactions with the off-shell Higgs in this process lead to a rapid growth of the partonic cross sections with energy, which manifests in an enhanced p T distribution of the final state leptons and quarks. We quantify this effect and estimate the present and future 2σ sensitivity to the up, down, and strange Yukawas. In particular, we find that HL-LHC can reach $\mathscr{O}$(400) sensitivity to the down Yukawa relative to the Standard Model value, improving the current sensitivity in this process by a factor of 10, and which can be further improved to $\mathscr{O}$(30) at FCC-hh. This is competitive with and complementary to constraints from global fits and other on-shell probes of the first generation Yukawas. The triboson sensitivity at HL-LHC corresponds to probing dimension-6 SMEFT operators suppressed by an $\mathscr{O}$(1) TeV scale, similarly to other LHC Higgs probes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Search for pair-produced higgsinos decaying via Higgs or Z bosons to final states containing a pair of photons and a pair of b -jets with the ATLAS detector

A search is presented for the pair production of higgsinos $\tilde{X}$ in gauge-mediated supersymmetry models, where the lightest neutralinos $\tilde{X}^{0}_{1}$ decay into a light gravitino $\tilde{G}$ in association with either a Higgs h or a Z boson. The search is performed with the ATLAS detector at the Large Hadron Collider using 139 fb -1 of proton–proton collisions at a centre-of-mass energy of $\sqrt{s}$ = 13TeV. It targets final states in which a Higgs boson decays into a photon pair, while the other Higgs or Z boson decays into a $b\overline{b}$ pair, with missing transverse momentum associated with the two gravitinos. Search regions dependent on the amount of missing transverse momentum are defined by the requirements that the diphoton mass should be consistent with the mass of the Higgs boson, and the $b\overline{b}$ mass with the mass of the Higgs or Z boson. The main backgrounds are estimated with data-driven methods using the sidebands of the diphoton mass distribution. No excesses beyond Standard Model expectations are observed and higgsinos with masses up to 320 GeV are excluded, assuming a branching fraction of 100% for $\tilde{X}^{0}_{1}$ → h$\tilde{G}$. This analysis excludes higgsinos with masses of 130GeV for branching fractions to h$\tilde{G}$ as low as 36%, thus providing complementarity to previous ATLAS searches in final states with multiple leptons or multiple b-jets, targeting different decays of the electroweak bosons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

A Cellular Automaton Simulation for Predicting Phase Evolution in Solid-State Reactions

New computational tools for solid-state synthesis recipe design are needed in order to accelerate the experimental realization of novel functional materials proposed by high-throughput materials discovery workflows. This work contributes a cellular automaton simulation framework for predicting the time-dependent evolution of intermediate and product phases during solid-state reactions as a function of precursor choice and amount, reaction atmosphere, and heating profile. The simulation captures the effects of reactant particle spatial distribution, particle melting, and reaction atmosphere. Reaction rates based on rudimentary kinetics are estimated using density functional theory data from the Materials Project and machine learning estimators for the melting point and the vibrational entropy component of the Gibbs free energy. The resulting simulation framework allows for the prediction of the likely outcome of a reaction recipe before any experiments are performed. We analyze five experimental solid-state recipes for BaTiO 3 , CaZrN 2 , and YMnO 3 found in the literature to illustrate the performance of the model in capturing reaction selectivity and reaction pathways as a function of temperature and precursor choice. This simulation framework offers an easier way to optimize existing recipes, aid in the identification of intermediates, and design effective recipes for yet unrealized inorganic solids in silico .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Weibel-mediated filamentary structures observed in the ICF context

Here, in light of novel and past experimental results, we demonstrate how Weibel-mediated filamentary structures can develop in the expanding plasma plume of a laser-irradiated foil. The transverse ballistic cooling that occurs during the quasi-spherical plasma expansion naturally drives an electron pressure anisotropy, resulting in the growth of electron current filaments. This effect competes with electron–ion Coulomb collisions, which tend to isotropize the electron distribution function. Based on theoretical and particle-in-cell modeling, we provide estimates of the dominant wavelength and amplitude of the self-generated magnetic fluctuations, which are found to explain experimental data obtained at the OMEGA and Laser Megajoule facilities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

CMB-PAInT: An inpainting tool for the cosmic microwave background

Abstract The presence of astrophysical emissions in microwave observations forces us to perform component separation to extract the Cosmic Microwave Background (CMB) signal. However, even in the most optimistic cases, there are still strongly contaminated regions, such as the Galactic plane or those with emission from extragalactic point sources, which require the use of a mask. Since many CMB analyses, especially the ones working in harmonic space, need the whole sky map, it is crucial to develop a reliable inpainting algorithm that replaces the values of the excluded pixels by others statistically compatible with the rest of the sky. This is especially important when working withQandUsky maps in order to obtainE- andB-mode maps which are free fromE-to-Bleakage. In this work we study a method based on Gaussian Constrained Realizations (GCR), that can deal with both intensity and polarization. Several tests have been performed to asses the validation of the method, including the study of the one-dimensional probability distribution function (1-PDF),E- andB-mode map reconstruction, and power spectra estimation. We have considered two scenarios for the input simulation: one case with only CMB signal and a second one including also Planck PR4 semi-realistic noise. Even if we are limited to low resolution maps, N side = 64 ifT,QandUare considered, we believe that this is a useful approach to be applied to future missions such as LiteBIRD, where the target are the largest scales.

Astronomy & Astrophysics↗
DOE OSTI2023

Deep neural network uncertainty quantification for LArTPC reconstruction

We evaluate uncertainty quantification (UQ) methods for deep learning applied to liquid argon time projection chamber (LArTPC) physics analysis tasks. As deep learning applications enter widespread usage among physics data analysis, neural networks with reliable estimates of prediction uncertainty and robust performance against overconfidence and out-of-distribution (OOD) samples are critical for their full deployment in analyzing experimental data. While numerous UQ methods have been tested on simple datasets, performance evaluations for more complex tasks and datasets are scarce. Here we assess the application of selected deep learning UQ methods on the task of particle classification using the PiLArNet monte carlo 3D LArTPC point cloud dataset. We observe that UQ methods not only allow for better rejection of prediction mistakes and OOD detection, but also generally achieve higher overall accuracy across different task settings. We assess the precision of uncertainty quantification using different evaluation metrics, such as distributional separation of prediction entropy across correctly and incorrectly identified samples, receiver operating characteristic curves (ROCs), and expected calibration error from observed empirical accuracy. We conclude that ensembling methods can obtain well calibrated classification probabilities and generally perform better than other existing methods in deep learning UQ literature.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Dark matter haloes of massive elliptical galaxies at z ∼ 0.2 are well described by the Navarro–Frenk–White profile

ABSTRACT We investigate the internal structure of elliptical galaxies at z ∼ 0.2 from a joint lensing–dynamics analysis. We model Hubble Space Telescope images of a sample of 23 galaxy–galaxy lenses selected from the Sloan Lens ACS (SLACS) survey. Whereas the original SLACS analysis estimated the logarithmic slopes by combining the kinematics with the imaging data, we estimate the logarithmic slopes only from the imaging data. We find that the distribution of the lensing-only logarithmic slopes has a median 2.08c ± 0.03 and intrinsic scatter 0.13 ± 0.02, consistent with the original SLACS analysis. We combine the lensing constraints with the stellar kinematics and weak lensing measurements, and constrain the amount of adiabatic contraction in the dark matter (DM) haloes. We find that the DM haloes are well described by a standard Navarro–Frenk–White halo with no contraction on average for both of a constant stellar mass-to-light ratio (M/L) model and a stellar M/L gradient model. For the M/L gradient model, we find that most galaxies are consistent with no M/L gradient. Comparison of our inferred stellar masses with those obtained from the stellar population synthesis method supports a heavy initial mass function (IMF) such as the Salpeter IMF. We discuss our results in the context of previous observations and simulations, and argue that our result is consistent with a scenario in which active galactic nucleus feedback counteracts the baryonic-cooling-driven contraction in the DM haloes.

Shajib, Anowar J.↗
DOE OSTI2022

Detecting cosmic strings with lensed fast radio bursts

Correlated red noise recently reported from pulsar timing observations may be an indication of stochastic gravitational waves emitted by cosmic strings that formed during a primordial phase transition near the grand unification energy scale. Unfortunately, known probes of cosmic strings, namely the cosmic microwave background anisotropies and string lensing of extragalactic galaxies, are not sensitive enough for low dimensionless string tensions of Gμc -2 = 10 -10 – 10 -7 (where the tension μ is the string energy per unit length) that are needed to explain this putative signal. We show that strong gravitational lensing of fast radio bursts (FRBs) by cosmic strings is a potentially unambiguous avenue to probe that range of string tension values. The image pair of string lensing are expected to have identical magnification factor and parity, and have a typical time delay of ~10 2 (Gμc -2 /10 -8 ) 2 s. Here, the unique spectral fingerprint of each FRB, as well as the possibility to detect correlations in the time series of the electric field of the radio waves, will enable verification of the string lensing interpretation. Very-long-baseline interferometry observations can spatially resolve the image pair and provide a lower bound on the string tension based on the image separation. We calculate the FRB lensing rate as a function of the FRB detection number for several different models of the FRB redshift distribution. We find that a survey detecting ~10 5 FRBs, in line with estimates for the detection rate of the forthcoming survey CHORD, can uncover a strong lensing event for a string tension of Gμc -2 ≃ 10 -7 . Larger FRB surveys, such as Phase 2 of the Square Kilometre Array, have the potential to significantly improve the sensitivity on the string tension to Gμc -2 ≃ 10 -9 .

79 ASTRONOMY AND ASTROPHYSICS↗