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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Dark Energy Survey Identification of A Low-Mass Active Galactic Nucleus at Redshift 0.823 from Optical Variability

We report the identification of a low-mass active galactic nucleus (AGN), DES J0218−0430, in a redshift z = 0.823 galaxy in the Dark Energy Survey (DES) Supernova field. We select DES J0218−0430 as an AGN candidate by characterizing its long-term optical variability alone based on DES optical broad-band light curves spanning over 6 yr. An archival optical spectrum from the fourth phase of the Sloan Digital Sky Survey shows both broad Mg ii and broad H β lines, confirming its nature as a broad-line AGN. Archival XMM–Newton X-ray observations suggest an intrinsic hard X-ray luminosity of |$L_{{\rm 2-12\, keV}}\approx 7.6\pm 0.4\times 10^{43}$| erg s^−1, which exceeds those of the most X-ray luminous starburst galaxies, in support of an AGN driving the optical variability. Based on the broad H β from SDSS spectrum, we estimate a virial black hole (BH) mass of M_• ≈ 10^6.43–10^6.72 M_⊙ (with the error denoting the systematic uncertainty from different calibrations), consistent with the estimation from OzDES, making it the lowest mass AGN with redshift > 0.4 detected in optical. We estimate the host galaxy stellar mass to be M_* ≈ 10^10.5 ± 0.3 M_⊙ based on modelling the multiwavelength spectral energy distribution. DES J0218−0430 extends the M_•–M_* relation observed in luminous AGNs at z ∼ 1 to masses lower than being probed by previous work. Our work demonstrates the feasibility of using optical variability to identify low-mass AGNs at higher redshift in deeper synoptic surveys with direct implications for the upcoming Legacy Survey of Space and Time at Vera C. Rubin Observatory.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Spectroscopic classification, variability, and SED of the Fermi -detected CSS 3C 286: the radio-loudest NLS1 galaxy?

ABSTRACT 3C 286 is a well-known calibrator source in radio astronomy. It is also one of very few compact steep-spectrum (CSS) sources detected in γ-rays. Here, we perform a detailed spectroscopic and variability analysis and present the first quasi-simultaneous optical to X-ray spectral energy distribution (SED) in order to reveal physical mechanisms that dominate its emission at different wavelengths, and arrive at a reliable optical source classification. The first main result of our study reveals several pitfalls when applying simple broad- or narrow-line Seyfert 1 (BLS1 or NLS1) classification criteria that only look at the [O iii]–Hβ complex. [O iii] and Hβ can be dominated by the same outflow components, in which case full width at half-maximum (Hβ) is no reliable classification criterion, and extinction by intrinsic or intervening material can make the highest velocity Hβ component undetectable. After careful combination of all information from ultraviolet (UV)–optical spectra along with multiwavelength data, we confirm that 3C 286 can be classified as NLS1 galaxy, with line properties and supermassive black hole mass (of order 108 M⊙ and accreting near the Eddington limit) close to the BLS1 regime, making it an important borderline object. The quasi-simultaneous SED taken with Swift shows a sharp rise in the optical–UV, implying the presence of a strong accretion-disc component with extreme UV excess, consistent with emission-line diagnostics. Finally, we report the discovery of X-ray variability of 3C 286, plausibly dominated by jet emission, and variable by at least a factor of ∼4. This result suggests to exercise caution when using 3C 286 as radio calibrator in high-resolution radio very long baseline interferometry observations.

Yao, Su↗
DOE OSTI2021

ASAS J071404+7004.3 – a close, bright nova-like cataclysmic variable with gusty winds

ABSTRACT Despite being bright (V ≃ 11.8) and nearby (d = 212 pc) ASAS J071404+7004.3 has only recently been identified as a nova-like cataclysmic variable. We present time-resolved optical spectroscopy obtained at the Isaac Newton and the Hiltner and McGraw-Hill Telescopes, together with Swift X-ray and ultraviolet observations. We combined these with TESS photometry and find a period of 3.28 h and a mass transfer rate of $4\!-\!9\times 10^{-9}\, {\mathrm{M_{\odot }\, yr}^{-1}}$. Historical photometry shows at least one low state establishing the system as a VY Scl star. Our high-cadence spectroscopy also revealed rapidly changing winds emanating from the accretion disc. We have modelled these using the Monte Carlo python code and shown that all the emission lines could emanate from the wind – which would explain the lack of double-peaked lines in such systems. In passing, we discuss the effect of variability on the position of cataclysmic variables in the Gaia Hertzsprung–Russell diagram.

Inight, K. (ORCID:0000000222002416)↗
DOE OSTI2022

Optical variability of quasars with 20-yr photometric light curves

ABSTRACT We study the optical gri photometric variability of a sample of 190 quasars within the SDSS Stripe 82 region that have long-term photometric coverage during ∼1998−2020 with SDSS, PanSTARRS-1, the Dark Energy Survey, and dedicated follow-up monitoring with Blanco 4m/DECam. With on average ∼200 nightly epochs per quasar per filter band, we improve the parameter constraints from a Damped Random Walk (DRW) model fit to the light curves over previous studies with 10–15 yr baselines and ≲ 100 epochs. We find that the average damping time-scale τDRW continues to rise with increased baseline, reaching a median value of ∼750 d (g band) in the rest frame of these quasars using the 20-yr light curves. Some quasars may have gradual, long-term trends in their light curves, suggesting that either the DRW fit requires very long baselines to converge, or that the underlying variability is more complex than a single DRW process for these quasars. Using a subset of quasars with better-constrained τDRW (less than 20 per cent of the baseline), we confirm a weak wavelength dependence of τDRW∝λ0.51 ± 0.20. We further quantify optical variability of these quasars over days to decades time-scales using structure function (SF) and power spectrum density (PSD) analyses. The SF and PSD measurements qualitatively confirm the measured (hundreds of days) damping time-scales from the DRW fits. However, the ensemble PSD is steeper than that of a DRW on time-scales less than ∼ a month for these luminous quasars, and this second break point correlates with the longer DRW damping time-scale.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Pulse profile modelling of thermonuclear burst oscillations − I. The effect of neglecting variability

ABSTRACT We study the effects of the time-variable properties of thermonuclear X-ray bursts on modelling their millisecond-period burst oscillations. We apply the pulse profile modelling technique that is being used in the analysis of rotation-powered millisecond pulsars by the Neutron Star Interior Composition Explorer to infer masses, radii, and geometric parameters of neutron stars. By simulating and analysing a large set of models, we show that overlooking burst time-scale variability in temperatures and sizes of the hot emitting regions can result in substantial bias in the inferred mass and radius. To adequately infer neutron star properties, it is essential to develop a model for the time-variable properties or invest a substantial amount of computational time in segmenting the data into non-varying pieces. We discuss prospects for constraints from proposed future X-ray telescopes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Multiband optical variability of a newly discovered 12 blazars sample from 2013–2019

ABSTRACT Here we present the first optical photometric monitoring results of a sample of 12 newly discovered blazars from the ICRF – Gaia CRF astrometric link. The observations were performed from April 2013 to August 2019 using eight telescopes located in Europe. For a robust test for the brightness and colour variability, we use Abbé criterion and F-test. Moreover, linear fittings are performed to investigate the relation in the colour-magnitude variations of the blazars. Variability was confirmed in the case of 10 sources; two sources, 1429+249 and 1556+335 seem to be possibly variable. Three sources (1034+574, 1722+119, and 1741+597) have displayed large amplitude brightness change of more than one magnitude. We found that the seven sources displayed bluer-when-brighter variations, and one source showed redder-when-brighter variations. We briefly explain the various AGN emission models which can explain our results.

Astronomy & Astrophysics↗
DOE OSTI2024

Superscaling variable and neutrino energy reconstruction from theoretical predictions to experimental limitations

We introduce the novel approach of using the superscaling variable as an observable and an analysis tool in the context of charged current neutrino-nucleus interactions. We study the relation between the superscaling variable and the removal energy, in addition to other fundamental parameters of the neutrino-nucleus interaction models. In the second half of the paper, we discuss the experimental viability of this measurement following a study of neutrino energy and missing momentum reconstruction. We show that the superscaling variable is measurable in neutrino interaction experiments provided that the proton is detected in the final state. We discuss the resolution of this measurement, and the limitation imposed by the proton’s detection threshold. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Distributed Optimization Approaches with Discrete Variables in the Power Distribution Systems

Traditionally, centralized approaches have predominantly been used for the power system operation and control. With increasing penetration of small-scale distributed energy resources (DERs) in the distribution network, especially independently owned renewable resources, distributed algorithms can serve as a potential alternative for improving scalability, resiliency and addressing privacy concerns. However, the complexity of distributed algorithms significantly increases with the integration of the legacy devices, the operation of which depend on discrete control variables. This paper aims to provide a review of the distributed optimization algorithms incorporating discrete control variables for the power distribution system. While the research in this domain is still at its nascence, an extensive comparison of the approaches in the literature for applying quadratic penalty, branch and bound,ordinal optimization and proximal operator to handle discrete variables in the framework of ADMM and dual decomposition have been addressed. Future research direction in this field have been also provided.

Adan, Jannatul↗
DOE OSTI2020

A Hierarchical Volt-var Optimization with Discrete Variables in Unbalanced Distribution Systems

This paper proposes a framework to determine the optimal active and reactive power dispatch of distributed photovoltaic (PV) generation, switched capacitors, and voltage regulators in multi-phase unbalanced distribution systems. The objectives of the optimal dispatch are minimization of the energy loss, PV real power curtailment, and switching operations of capacitors and voltage regulators, in addition to elimination of voltage violation and reverse power flow. The optimization problem is formulated in rectangular coordinates as a nonlinear, nonconvex problem with discrete variables. A hierarchical twostage framework is proposed to effectively handle those discrete variables and reduce the computational time compared to the unified approach in which all variables are solved simultaneously. The efficacy of the proposed approach and the accuracy of the obtained numerical solution is validated using the unbalanced multi-phase IEEE 34-bus with 15-minute load and PV data.

Nguyen, Quan H.↗
DOE OSTI2024

Verification of Adaptive Protection in Hardware in the Loop for Coordination with Solar Variability

As inverter-based resources continue to be installed at all levels of the electric grid, the fixed protection schemes used at the distribution level will continue to be stressed until they no longer ensure the protection of the grid. Adaptive protection has been proposed as a solution with the ability to update the protection schemes in near real-time to ensure reliability and increase the resilience of the grid. However, weather variability poses a significant challenge to the ability of these methods to keep the selectivity and reliability of these schemes coordinated. If the ramp rates, due to solar variability, of the inverter-based resources change faster than the adaptive protection can issue new settings, the protection system could be uncoordinated, with the wrong device responding to a system fault. The proposed adaptive protection method ensures that due to solar variability, communication, and protection calculation latency, it can issu e coordinated protection settings promptly, in one minute or less. The hardware-in-the-loop results show the protection settings being issued and maintaining system coordination in under a minute.

Summers, Adam↗
DOE OSTI2024

Scrutinizing Variables for Checkpoint Using Automatic Differentiation

Checkpoint/Restart (C/R) saves the running state of the programs periodically, which consumes considerable time and system resources. We observe that not every piece of data is involved in the computation in typical HPC applications; such unused data should be excluded from checkpointing for better storage and compute efficiency. We propose a systematic approach that leverages automatic differentiation (AD) to scrutinize every element within variables (e.g., arrays) necessary for checkpointing. This allows us to identify critical and uncritical elements and eliminate uncritical elements from checkpointing. Specifically, we inspect every single element within a variable necessary for checkpointing with an AD tool to determine whether the element has an impact on the application output or not. We validate our approach with all benchmarks from the NPB suite. We visualize the distribution of critical and uncritical elements within a variable with respect to its binary impact (yes or no) on the application output.

Huang, Xin [Kobe University]↗
DOE OSTI2025

Reliability Analysis of Power Grids Considering Component Failures of Variable Energy Resources

This paper proposes an improved model for the reliability assessment of power systems considering component failures of variable energy resources (VER). The inherent intermittency of VER such as solar photovoltaic (PV) and wind farms, along with their susceptibility to component failures, present significant challenges to reliable system operation. These issues, combined with power grid operation and network constraints, complicate the reliable operation of VER-integrated power systems. Here, to address these concerns, this paper introduces a reliability assessment framework that considers VER input variability, its impact on component availability, and their resulting impact on overall system reliability. Stochastic models based on discrete Markov processes are developed to incorporate variable irradiance, wind speeds, and their effects on PV and wind component failure rates. A next-event and state transition-based approach is then developed to integrate the stochastic models into a mixed-timing sequential Monte Carlo simulation framework for composite reliability assessment. Case studies on the RTS-GMLC system demonstrate the effectiveness of the proposed model in evaluating the reliability of VER-integrated systems.

Pandit, Dilip [Sandia National Laboratories (SNL-N↗
DOE OSTI2023

A Deep Learning Filter for the Intraseasonal Variability of the Tropics

Abstract This paper presents a novel application of convolutional neural network (CNN) models for filtering the intraseasonal variability of the tropical atmosphere. In this deep learning filter, two convolutional layers are applied sequentially in a supervised machine learning framework to extract the intraseasonal signal from the total daily anomalies. The CNN-based filter can be tailored for each field similarly to fast Fourier transform filtering methods. When applied to two different fields (zonal wind stress and outgoing longwave radiation), the index of agreement between the filtered signal obtained using the CNN-based filter and a conventional weight-based filter is between 95% and 99%. The advantage of the CNN-based filter over the conventional filters is its applicability to time series with the length comparable to the period of the signal being extracted. Significance Statement This study proposes a new method for discovering hidden connections in data representative of tropical atmosphere variability. The method makes use of an artificial intelligence (AI) algorithm that combines a mathematical operation known as convolution with a mathematical model built to reflect the behavior of the human brain known as artificial neural network. Our results show that the filtered data produced by the AI-based method are consistent with the results obtained using conventional mathematical algorithms. The advantage of the AI-based method is that it can be applied to cases for which the conventional methods have limitations, such as forecast (hindcast) data or real-time monitoring of tropical variability in the 20–100-day range.

Stan, Cristiana↗
DOE OSTI2021

Evaluating the Conservation of Energy Variables in Simulations of Deep Moist Convection

Abstract It is often assumed in parcel theory calculations, numerical models, and cumulus parameterizations that moist static energy (MSE) is adiabatically conserved. However, the adiabatic conservation of MSE is only approximate because of the assumption of hydrostatic balance. Two alternative variables are evaluated here: MSE − IB and MSE + KE, wherein IB is the path integral of buoyancy ( B ) and KE is kinetic energy. Both of these variables relax the hydrostatic assumption and are more precisely conserved than MSE. This article quantifies the errors that result from assuming that the aforementioned variables are conserved in large-eddy simulations (LES) of both disorganized and organized deep convection. Results show that both MSE − IB and MSE + KE better predict quantities along trajectories than MSE alone. MSE − IB is better conserved in isolated deep convection, whereas MSE − IB and MSE + KE perform comparably in squall-line simulations. These results are explained by differences between the pressure perturbation behavior of squall lines and isolated convection. Errors in updraft B diagnoses are universally minimized when MSE − IB is assumed to be adiabatically conserved, but only when moisture dependencies of heat capacity and temperature dependency of latent heating are accounted for. When less accurate latent heat and heat capacity formulae were used, MSE − IB yielded poorer B predictions than MSE due to compensating errors. Our results suggest that various applications would benefit from using either MSE − IB or MSE + KE instead of MSE with properly formulated heat capacities and latent heats.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Strong Red Noise Ocean Forcing on Atlantic Multidecadal Variability Assessed from Surface Heat Flux: Theory and Application

The role of ocean forcing on Atlantic multidecadal variability (AMV) is assessed from the (downward) heat flux–SST relation in the framework of a new stochastic climate theory forced by red noise ocean forcing. Previous studies suggested that atmospheric forcing drives SST variability from monthly to interannual time scales, with a positive heat flux–SST correlation, while heat flux induced by ocean processes can drive SST variability at decadal and longer time scales, with a negative heat flux–SST correlation. Here, first, we develop a theory to show how the sign of heat flux–SST correlation is affected by atmospheric and oceanic forcing with time scale. In particular, a red noise ocean forcing is necessary for the sign reversal of heat flux–SST correlation. Furthermore, this sign reversal can be detected equivalently in three approaches: the low-pass correlation at lag zero, the unfiltered correlation at long (heat flux) lead, and the real part of the heat flux–SST coherence. Second, we develop a new scheme in combination with the theory to assess the magnitude and time scale of the red noise ocean forcing for AMV in the GFDL SPEAR model (Seamless System for Prediction and Earth System Research) and observations. In both the model and observations, the ocean forcing on AMV is in general comparable with the atmospheric forcing, with a 90% probability greater than the atmospheric forcing in observations. In contrast to the white noise atmospheric forcing, the ocean forcing has a persistence time comparable or longer than a year, much longer than the SST persistence of ~3 months. This slow ocean forcing is associated implicitly with slow subsurface ocean dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Biomass Burning Emissions of Black Carbon over the Maritime Continent and ENSO Variability

Fire emissions from the Maritime Continent (MC) over the western tropical Pacific are strongly influenced by El Niño–Southern Oscillation (ENSO), posing various climate effects to the Earth system. Here, in this study, we show that the historical biomass burning emissions of black carbon (BC bb ) aerosol in the dry season from the MC are strengthened in El Niño years due to the dry conditions. The eastern Pacific type of El Niño exerts a stronger modulation in BC bb emissions over the MC region than the central Pacific type of El Niño. Based on simulations using the fully coupled Community Earth System Model (CESM), the impacts of increased BC bb emissions on ENSO variability and frequency are also investigated in this study. With BC bb emissions from the MC scaled up by a factor of 10, which enables the identification of climate response from the internal variability, the increased BC bb heats the local atmosphere and changes land–sea thermal contrast, which suppresses the westward transport of the eastern Pacific surface water. It leads to an increase in sea surface temperature in the eastern tropical Pacific, which further enhances ENSO variability and increases the frequency of extreme El Niño and La Niña events. This study highlights the potential role of BC bb emissions on extreme ENSO frequency, and this role may be increasingly important in the warming future with higher wildfire risks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Quantifying the Role of Ocean Dynamics in SST Variability across GCMs and Observations

Abstract Midlatitude SSTs forced by mesoscale oceanic processes can affect the large-scale atmosphere, pointing to the ocean’s crucial role outside the tropics. Previous studies have shown oceanic mesoscale processes’ effect on global and regional climate variability. This study quantifies the local contribution of ocean dynamics to mixed-layer temperature across the globe by directly estimating the ocean heat flux divergence resolved by state-of-the-art ocean reanalysis, eddy-resolving, and eddy-parameterized versions of two U.S. national climate models and indirectly from air–sea flux satellite-based estimates. Our results show that the eddy-resolving climate simulations resolve mixed-layer temperature variances that are larger and closer to those inferred from observations than both their eddy-parameterized counterparts and ECCO over much of the extratropics. The observations and the eddy-resolving models indicate a more significant role of ocean dynamics in the mixed-layer temperature variability than the surface fluxes over most extratropics compared to their eddy-parameterized versions. A frequency domain analysis shows that the better-resolved ocean mesoscale and thermal gradients enhance the variance over a time scale from 2 months to 30 years. Results show agreement in the ocean’s contribution among satellite-based estimates, ocean reanalysis products, and ocean eddy-resolving simulations. At the same time, differences emerge for ECCO and the eddy-parameterized models, suggesting that surface fluxes account for a larger fraction of the mixed-layer temperature variability in most of the extratropics.

Siqueira, L.↗
DOE OSTI2020

A Computationally Efficient Linear Semi-Lagrangian Scheme for the Advection of Microphysical Variables in Cloud-Resolving Models

An efficient semi-Lagrangian (SL) numerical scheme for the advection of positive-definite microphysical variables in cloud-resolving models is proposed. The scheme is a linear combination of SL schemes of the first and second order. The proposed scheme is compared with two high-order, monotonic, nonlinear Eulerian schemes, in two 2D tests. In the first test, advection of a positive scalar field with large gradients is performed within complicated idealized steering flows. In the second test, a hail storm is simulated using the 2D Hebrew University Cloud Model, describing the interactions between 15 size distributions of different microphysical quantities (each distribution is described by 43 mass bins). The proposed scheme is computationally efficient, has a low numerical diffusion and a high level of mass conservation accuracy, and preserves the sum of multiple advected variables as well as the linear relationships between the advected scalar variables. Although the proposed SL scheme is not exactly positive definite, the negative values and their number, which may appear only in the case of very strong gradients, are negligible. The scheme produces results similar to those of nonlinear Eulerian advection schemes while reducing computation time by approximately a factor of 10.

54 ENVIRONMENTAL SCIENCES↗