SEARCH · Engineering Papers

Results for “low observability”

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.

SourceResearch connectionFrom yearThrough year

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

At least 271 records · Page 15

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Identifying the Connections between Grain Growth and Flux Expulsion in Low RRR Niobium SRF Cavities

The SRF community has shown that high temperature annealing can improve the flux expulsion of niobium cavities during cooldown. The required temperature will vary between cavities and different batches of material, typically around 800 C and up to 1000 C. However, for niobium with a low residual resistance ratio (RRR), even 1000 C is not enough to improve its poor flux expulsion. The purpose of this study is to observe the grain growth behavior of low RRR niobium coupons subjected to high temperature annealing to identify the mechanism for improving flux expulsion. We observe that low RRR material experiences less grain growth than high RRR when annealed at the same temperature. We search for the limitations to grain growth in low RRR material and develop a diagnostic based on grain structure to determine the appropriate recipe for good flux expulsion. The results of this study have the potential to unlock a new understanding on SRF materials and enable the next generation of high Q/high gradient surface treatments.

Howard, Katrina [Chicago U.] (ORCID:00000003256133↗

DOE OSTI2026

Identifying the connections between grain growth and flux expulsion in low RRR niobium SRF cavities

Howard, K. [Chicago U.] (ORCID:0000000325613308)↗

DOE OSTI2025

Identifying the connections between grain growth and flux expulsion in low RRR niobium SRF cavities

Howard, K. [Chicago U.] (ORCID:0000000325613308)↗

DOE OSTI2021

Geometry versus growth: Internal consistency of the flat ΛCDM model with KiDS-1000

Here, we carry out a multi-probe self-consistency test of the flat Lambda Cold Dark Matter (ΛCDM) model with the aim of exploring potential causes of the reported tensions between high- and low-redshift cosmological observations. We divide the model into two theory regimes determined by the smooth background (geometry) and the evolution of matter density fluctuations (growth), each governed by an independent set of ΛCDM cosmological parameters. This extended model is constrained by a combination of weak gravitational lensing measurements from the Kilo-Degree Survey, galaxy clustering signatures extracted from Sloan Digital Sky Survey campaigns and the Six-Degree Field Galaxy Survey, and the angular baryon acoustic scale and the primordial scalar fluctuation power spectrum measured in Planck cosmic microwave background (CMB) data. For both the weak lensing data set individually and the combined probes, we find strong consistency between the geometry and growth parameters, as well as with the posterior of standard ΛCDM analysis. In the non-split analysis, for which one single set of parameters was used, tension in the amplitude of matter density fluctuations as measured by the parameter S 8 persists at around 3σ, with a 1.5% constraint of S 8 = 0.776$_{–0.008}^{+0.016}$ for the combined probes. We also observe a less significant preference (at least 2σ) for higher values of the Hubble constant, H 0 = 70.5$_{–1.5}^{+0.7}$ km s –1 Mpc –1 , as well as for lower values of the total matter density parameter Ω m = 0.289$_{–0.005}^{+0.007}$ compared to the full Planck analysis. Including the subset of the CMB information in the probe combination enhances these differences rather than alleviate them, which we link to the discrepancy between low and high multipoles in Planck data. Our geometry versus growth analysis does not yet yield clear signs regarding whether the origin of the discrepancies lies in ΛCDM structure growth or expansion history but holds promise as an insightful test for forthcoming, more powerful data.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Sea-surface temperature pattern effects have slowed global warming and biased warming-based constraints on climate sensitivity

The observed rate of global warming since the 1970s has been proposed as a strong constraint on equilibrium climate sensitivity (ECS) and transient climate response (TCR)—key metrics of the global climate response to greenhouse-gas forcing. Using CMIP5/6 models, we show that the inter-model relationship between warming and these climate sensitivity metrics (the basis for the constraint) arises from a similarity in transient and equilibrium warming patterns within the models, producing an effective climate sensitivity (EffCS) governing recent warming that is comparable to the value of ECS governing long-term warming under CO 2 forcing. However, CMIP5/6 historical simulations do not reproduce observed warming patterns. When driven by observed patterns, even high ECS models produce low EffCS values consistent with the observed global warming rate. The inability of CMIP5/6 models to reproduce observed warming patterns thus results in a bias in the modeled relationship between recent global warming and climate sensitivity. Correcting for this bias means that observed warming is consistent with wide ranges of ECS and TCR extending to higher values than previously recognized. These findings are corroborated by energy balance model simulations and coupled model (CESM1-CAM5) simulations that better replicate observed patterns via tropospheric wind nudging or Antarctic meltwater fluxes. Because CMIP5/6 models fail to simulate observed warming patterns, proposed warming-based constraints on ECS, TCR, and projected global warming are biased low. The results reinforce recent findings that the unique pattern of observed warming has slowed global-mean warming over recent decades and that how the pattern will evolve in the future represents a major source of uncertainty in climate projections.

58 GEOSCIENCES↗

DOE OSTI2025

Multiple Carrier Generation at an Exceptionally Low Energy Threshold

Multiple carrier generation (MCG), a process wherein two or more carriers are generated from a single high-energy absorbed photon, holds immense promise for quantum sensing, metrology, low-threshold lasers, and photovoltaics. Despite its potential, MCG has faced obstacles such as low efficiency and a high threshold photon energy at least twice the band gap (2?Eg) of the semiconductor, limiting its application only to a class of materials with low Eg. Here, we present a new approach that overcomes this limitation by leveraging carrier-donor scattering to excite secondary electrons from donor states strategically positioned below the conduction band. Our method relies on strong Coulomb interaction, reduced dielectric screening, slow hot carrier cooling, and strictly follows the energy conservation rules. We experimentally demonstrated this idea in a model system of monolayer (1L) MoS2 by exploiting electron-donating chalcogen vacancy states. We observed an exceptionally low MCG threshold of ~1.12?Eg for the first time in 1L MoS2. Remarkably, the quantum yield can be further increased to >3 by increasing the photon energy to 1.65?Eg, representing a substantial advancement over existing methods. Our findings extend the horizon of MCG into next-generation high-performance optoelectronic devices with an on-demand operating spectral range spanning from infrared to ultraviolet.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS↗

DOE OSTI2021

Measurement of the anisotropy power spectrum of the radio synchrotron background

We present the first targeted measurement of the power spectrum of anisotropies of the radio synchrotron background, at 140 MHz, where it is the overwhelmingly dominant photon background. This measurement is important for understanding the background level of radio sky brightness, which is dominated by steep-spectrum synchrotron radiation at frequencies below ν ~ 0.5 GHz and has been measured to be significantly higher than that produced by known classes of extragalactic sources and most models of Galactic halo emission. We determine the anisotropy power spectrum on scales ranging from 2° to 0.2 arcmin with Low-Frequency Array observations of two 18-deg 2 fields – one centred on the Northern hemisphere’s coldest patch of radio sky where the Galactic contribution is smallest and the other offset from that location by 15°. We find that the anisotropy power is higher than that attributable to the distribution of point sources above 100 μJy in flux. Furthermore, this level of radio anisotropy power indicates that if it results from point sources, those sources are likely at low fluxes and incredibly numerous, and likely clustered in a specific manner.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Overcoming environmental constraints to high-yielding eastern cottonwood productivity in the southeastern United States

The global demand for biomass is rising, and Populus species are among the most productive temperate woody plants. This 6-year study, conducted in Sumter County, South Carolina, USA evaluated the effects of supplemental irrigation and fertilization on crown and leaf traits, dry weight productivity, and clonal variation in Populus deltoides. Eight commercially available clones (‘ST148’, ‘S2C20’, ‘3167’, ‘ST72’, ‘20WV’, ‘S7C1’, ‘ST70’, and ‘S7C15’) were assessed. Drip irrigation was applied to maintain soil tension at either 33 kPa (15% volumetric soil moisture) or 1500 kPa (10%). Nutrient treatments via weekly fertigation applications consisted of two levels: a high annual rate (initially 85 kg elemental nitrogen ha−1 year−1, increasing to 182 kg ha−1 year−1 at Year 3, then reduced to 135 kg ha−1 year−1 thereafter) and a low rate at 50% of the high treatment. Dry weight yields were estimated using standing tree measurements. Results revealed significant clonal differences in leaf area index (LAI) that peaked in Year 3, with the fastest-growing clones exhibiting lower LAI values. At Ages 2 and 3, these clones also showed higher concentrations of K, Ca, B, Cu, and Mn in leaves, along with lower Mg and Zn concentrations. Both annual height and diameter growth varied significantly by treatment and clone, with the largest height increases observed in the low fertilizer treatments from Year 3 onward. Biomass production in all irrigated plots exceeded that of non-irrigated plots across all biomass components at Ages 4, 5, and 6. Furthermore, stem-to-root dry weight ratios increased more rapidly in the best-performing treatment–clone combinations compared to non-irrigated plots. Notably, P. deltoides plots receiving fertilizer had higher soil carbon concentrations (i.e., percent C) compared to adjacent sweetgum, sycamore, and agricultural plots. These findings highlight the potential of targeted irrigation strategies to enhance biomass productivity in P. deltoides plantations.

Tuskan, Gerald [ORNL] (ORCID:0000000301061289)↗

DOE OSTI2021

Effects of aluminum content on thermoelectric performance of Al x CoCrFeNi high-entropy alloys

Introducing a non-regular distribution in the mass and bonding by including distinctly different elements can reduce the phonon transport even within structurally well-ordered materials. These distributions are a quality of all high-entropy alloys (HEAs), however the inclusion of aluminum in Al x CoCrFeNi is particularly impactful due to the large mismatch in atomic mass with other components. The resultant low phonon conductivity is a requirement for high thermoelectric performance, motivating the investigation of the effects of Al content on phonon transport as well as other thermoelectric properties. This work examines the phonon and electron transport and thermoelectric conversion properties with various Al contents (0 ≤ x Al ≤ 2) in this Cantor alloy using first-principles calculations, molecular dynamics, and semi-classical Boltzmann transport theory. The calculated phonon density of states and thermoelectric properties present reasonable agreements with experiments, including neutron scattering. A large reduction of phonon conductivity (k L ) is observed even with low x Al s, which we attribute to effective phonon scatterings by the large mass mismatch. However, its temperature dependence is not significant, demonstrating a minor contribution of interphonon scattering. In contrast, electrical conductivity (σ) and Seebeck coefficient (S) increase with temperature at higher x Al s with body-centered cubic structures. Therefore, the thermoelectric figure of merit (ZT) of Al x CoCrFeNi HEAs is enhanced by increasing the Al content mainly due to the increase of the thermoelectric power factor (σS 2 ) at high temperatures, while at low temperatures the phonon-scattering enhancement by mass mismatch is also important.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Response of Ecosystem Productivity to High Vapor Pressure Deficit and Low Soil Moisture: Lessons Learned From the Global Eddy-Covariance Observations

Although there is mounting concern about how high vapor pressure deficit (VPD) and low soil moisture (SM) affect ecosystem productivity, their relative importance is still under debate. Here, we comprehensively quantified the relative impacts of these two factors on ecosystem gross primary production (GPP) using observations from a global network of eddy-covariance towers and two approaches (sensitivity analysis and linear regression model). Both approaches agree that a higher percentage of sites experience GPP reduction from high VPD than from low SM over the growing season. However, the constraint of high VPD and low SM on GPP reduction is tightly linked with climates and plant functional types. Humid and mesic ecosystems including forests and grasslands are dominated by VPD, while the semi-arid and arid ecosystems including shrublands and savannas are dominated by SM. The varying dominant role of these two factors on GPP is closely related to plant stomatal behavior, as predicted by a stomatal conductance model. Additionally, we highlight the non-linear impact of SM on GPP during droughts and the possible underestimation of the SM effects for deep-rooted plants when only using surface-layer SM. Our results shed light on a better understanding of the impacts of VPD and SM on vegetation productivity, with important implications for modeling the response and feedback of ecosystem dynamics to current and future climates.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

A Rapid Compression Machine Study of 2-Phenylethanol Autoignition at Low-To-Intermediate Temperatures

To meet the increasing anti-knocking quality demand of boosted spark-ignition engines, fuel additives are considered an effective approach to tailor fuel properties for satisfying the performance requirements. Thus, screening/developing bio-derived fuel additives that are best-suited for advanced spark-ignition engines has become a significant task. 2-Phenylethanol (2-PE) is an attractive candidate that features high research octane number, high octane sensitivity, low vapor pressure, and high energy density. Recognizing that the low temperature autoignition chemistry of 2-PE is not well understood and the need for fundamental experimental data at engine-relevant conditions, rapid compression machine (RCM) experiments are therefore conducted herein to measure ignition delay times (IDTs) of 2-PE in air over a wide range of conditions to fill this fundamental void. These newly acquired IDT data at low-to-intermediated temperatures, equivalence ratios of 0.35–1.5, and compressed pressures of 10–40 bar are then used to validate the 2-PE model developed by Shankar et al. (2017). It is found that this literature model greatly overpredicts the current RCM data. The comparison of experimental and simulated results also provides insights into 2-PE autoignition behaviors at varying conditions. Further chemical kinetic analyses demonstrate that the absence of the O2-addition pathway of β-R. radical in the 2-PE model of Shankar et al. (2017) could account for the model discrepancies observed at low-to-intermediated temperatures.

Fang, Ruozhou (ORCID:0000000348315100)↗

DOE OSTI2024

Shedding light on the MiniBooNE excess with searches at the LHC

The origin of the excess of low-energy events observed by the MiniBooNE experiment remains a mystery, despite exhaustive investigations of backgrounds and a series of null measurements from complementary experiments. One intriguing explanation is the production of beyond-the-Standard-Model particles that could mimic the experimental signature of additional ν e appearance seen in MiniBooNE. In one proposed mechanism, muon neutrinos up-scatter to produce a new “dark neutrino” state that decays by emitting highly collimated electron-positron pairs. We propose high-energy neutrinos produced from W boson decays at the Large Hadron Collider as an ideal laboratory to study such models. Simple searches for a low-mass, boosted dilepton resonance produced in association with a high- p T muon from the W decay with run 2 data would already provide unique sensitivity to a range of dark neutrino scenarios, with prompt and displaced searches providing complementarity. Looking farther ahead, we show how the unprecedented sample of W boson decays anticipated at the HL-LHC, together with improved lepton acceptance would explore much of the parameter space most compatible with the MiniBooNE excess. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Ordered magnetic fields around the 3C 84 central black hole

Context. 3C 84 is a nearby radio source with a complex total intensity structure, showing linear polarisation and spectral patterns. A detailed investigation of the central engine region necessitates the use of very-long-baseline interferometry (VLBI) above the hitherto available maximum frequency of 86 GHz.Aims. Using ultrahigh resolution VLBI observations at the currently highest available frequency of 228 GHz, we aim to perform a direct detection of compact structures and understand the physical conditions in the compact region of 3C 84.Methods. We used Event Horizon Telescope (EHT) 228 GHz observations and, given the limited (u, v)-coverage, applied geometric model fitting to the data. Furthermore, we employed quasi-simultaneously observed, ancillary multi-frequency VLBI data for the source in order to carry out a comprehensive analysis of the core structure.Results. We report the detection of a highly ordered, strong magnetic field around the central, supermassive black hole of 3C 84. The brightness temperature analysis suggests that the system is in equipartition. We also determined a turnover frequency of νm = (113 ± 4) GHz, a corresponding synchrotron self-absorbed magnetic field of BSSA = (2.9 ± 1.6) G, and an equipartition magnetic field of Beq = (5.2 ± 0.6) G. Three components are resolved with the highest fractional polarisation detected for this object (mnet = (17.0 ± 3.9)%). The positions of the components are compatible with those seen in low-frequency VLBI observations since 2017–2018. We report a steeply negative slope of the spectrum at 228 GHz. We used these findings to test existing models of jet formation, propagation, and Faraday rotation in 3C 84.Conclusions. The findings of our investigation into different flow geometries and black hole spins support an advection-dominated accretion flow in a magnetically arrested state around a rapidly rotating supermassive black hole as a model of the jet-launching system in the core of 3C 84. However, systematic uncertainties due to the limited (u, v)-coverage, however, cannot be ignored. Our upcoming work using new EHT data, which offer full imaging capabilities, will shed more light on the compact region of 3C 84.Key words: techniques: high angular resolution / techniques: interferometric / galaxies: active / galaxies: individual: NGC 1275 / galaxies: jets

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Muon neutrino charged current single pion production on various targets in the MINERvA detector

Measurements of neutrino oscillation parameters at accelerator-based experiments require precise knowledge of neutrino interaction cross sections. A significant fraction of neutrino interactions observed in these experiments produce single charged pions. While single charged pion production has been measured on hydrocarbon and water, few precise measurements exist for heavier targets, and there are no high statistics measurements that directly compare pion production on different targets. This thesis measures differential cross sections of muon neutrino charged current single charged pion production with no other mesons in the final state in a neutrinobeam with a mean energy of ≈ 6 GeV. The pion production is studied on targets of scintillator, carbon, water, iron, and lead at MINERvA, a neutrino cross section experiment located in the NuMI beamline at Fermilab. These measured cross sections are differential in μ - and π + kinematics. A strong suppression of low Q 2 and an enhancement of low π are observed relative to commonly used neutrino interaction models in both the light and heavy nuclear targets. Incorporation of these observed effects in future neutrino oscillation experiments will improve their ability to measure energy of neutrino interactions, and therefore measure the parameters governing neutrino oscillations.

Bercellie, Aaron↗

DOE OSTI2020

Panel Session 98B: Treatment of Low-Activity Tank Waste at Hanford: Considering the Alternatives

This panel focused on alternative treatment of the Hanford Low-Activity Tank Waste. Currently, Tank Waste at the Hanford Site is to be separated into low-activity (LAW) and high-level waste (HLW) fractions, and then vitrified to produce immobilized LAW glass for onsite disposal, and HLW glass for ultimate geologic disposal. This panel discussed several commissioned studies by the National Laboratories, National Academies, and General Accountability Office to evaluate the risks, costs, and benefits associated with considering options for immobilizing portions of the Hanford LAW waste forms. Panelists with presentations: Analysis of Supplemental Treatment Approaches for Low-Activity Waste at the Hanford Nuclear Reservation Overview and Conclusions (Michael Stone); Analysis of Supplemental Treatment Approaches for Low-Activity Waste at the Hanford Nuclear Reservation: Disposal Performance Evaluation (Tom Brouns); National Academies Review of the Study on Supplemental Treatment Approaches of Low-Activity Waste at the Hanford Nuclear Reservation (Charles Ferguson); GAO Observations on Immobilizing Low-Activity Waste at DoE's Hanford Site (David Trimble)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Modeling Spatial Distribution of Snow Water Equivalent by Combining Meteorological and Satellite Data with Lidar Maps

Abstract An accurate characterization of the water content of snowpack, or snow water equivalent (SWE), is necessary to quantify water availability and constrain hydrologic and land surface models. Recently, airborne observations (e.g., lidar) have emerged as a promising method to accurately quantify SWE at high resolutions (scales of ∼100 m and finer). However, the frequency of these observations is very low, typically once or twice per season in the Rocky Mountains of Colorado. Here, we present a machine learning framework that is based on random forests to model temporally sparse lidar-derived SWE, enabling estimation of SWE at unmapped time points. We approximated the physical processes governing snow accumulation and melt as well as snow characteristics by obtaining 15 different variables from gridded estimates of precipitation, temperature, surface reflectance, elevation, and canopy. Results showed that, in the Rocky Mountains of Colorado, our framework is capable of modeling SWE with a higher accuracy when compared with estimates generated by the Snow Data Assimilation System (SNODAS). The mean value of the coefficient of determination R 2 using our approach was 0.57, and the root-mean-square error (RMSE) was 13 cm, which was a significant improvement over SNODAS (mean R 2 = 0.13; RMSE = 20 cm). We explored the relative importance of the input variables and observed that, at the spatial resolution of 800 m, meteorological variables are more important drivers of predictive accuracy than surface variables that characterize the properties of snow on the ground. This research provides a framework to expand the applicability of lidar-derived SWE to unmapped time points. Significance Statement Snowpack is the main source of freshwater for close to 2 billion people globally and needs to be estimated accurately. Mountainous snowpack is highly variable and is challenging to quantify. Recently, lidar technology has been employed to observe snow in great detail, but it is costly and can only be used sparingly. To counter that, we use machine learning to estimate snowpack when lidar data are not available. We approximate the processes that govern snowpack by incorporating meteorological and satellite data. We found that variables associated with precipitation and temperature have more predictive power than variables that characterize snowpack properties. Our work helps to improve snowpack estimation, which is critical for sustainable management of water resources.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Radiation-Induced Oxidation Reactions of 2-Selenouracil in Aqueous Solutions: Comparison with Sulfur Analog of Uracil

One-electron oxidation of 2-selenouracil (2-SeU) by hydroxyl (●OH) and azide (●N3) radicals leads to various primary reactive intermediates. Their optical absorption spectra and kinetic characteristics were studied by pulse radiolysis with UV-vis spectrophotometric and conductivity detection and by the density functional theory (DFT) method. The transient absorption spectra recorded in the reactions of ●OH with 2-SeU are dominated by an absorption band with an λmax = 440 nm, the intensity of which depends on the concentration of 2-SeU and pH. Based on the combination of conductometric and DFT studies, the transient absorption band observed both at low and high concentrations of 2-SeU was assigned to the dimeric 2c-3e Se-Se-bonded radical in neutral form (2●). The dimeric radical (2●) is formed in the reaction of a selenyl-type radical (6●) with 2-SeU, and both radicals are in equilibrium with Keq = 1.3 × 104 M−1 at pH 4 (below the pKa of 2-SeU). Similar equilibrium with Keq = 4.4 × 103 M−1 was determined for pH 10 (above the pKa of 2-SeU), which admittedly involves the same radical (6●) but with a dimeric 2c-3e Se-Se bonded radical in anionic form (2●−). In turn, at the lowest concentration of 2-SeU (0.05 mM) and pH 10, the transient absorption spectrum is dominated by an absorption band with an λmax = 390 nm, which was assigned to the ●OH adduct to the double bond at C5 carbon atom (3●) based on DFT calculations. Similar spectral and kinetic features were also observed during the ●N3-induced oxidation of 2-SeU. In principle, our results mostly revealed similarities in one-electron oxidation pathways of 2-SeU and 2-thiouracil (2-TU). The major difference concerns the stability of dimeric radicals with a 2c-3e chalcogen-chalcogen bond in favor of 2-SeU.

2-selenouracil↗

DOE OSTI2022

Robust Event Classification Using Imperfect Real-world PMU Data

Here, this paper studies robust event classification using imperfect real-world phasor measurement unit (PMU) data. By analyzing the real-world PMU data, we find it is challenging to directly use this dataset for event classifiers due to the low data quality observed in PMU measurements and event logs. To address these challenges, we develop a novel machine learning framework for training robust event classifiers, which consists of three main steps: data preprocessing, fine-grained event data extraction, and feature engineering. Specifically, the data preprocessing step addresses the data quality issues of PMU measurements (e.g., bad data and missing data); in the fine-grained event data extraction step, a model-free event detection method is developed to accurately localize the events from the inaccurate event timestamps in the event logs; and the feature engineering step constructs the event features based on the patterns of different event types, in order to improve the performance and the interpretability of the event classifiers. Based on the proposed framework, we develop a workflow for event classification using the real-world PMU data streaming into the system in real time. Using the proposed framework, robust event classifiers can be efficiently trained based on many off-the-shelf lightweight machine learning models. Numerical experiments using the real-world dataset from the Western Interconnection of the U.S power transmission grid show that the event classifiers trained under the proposed framework can achieve high classification accuracy while being robust against low-quality data.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗