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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 379 records · Page 21

Study of Carrier Mobilities in 4H-SiC MOSFETS Using Hall Analysis

The channel conduction in 4H-SiC metal–oxide–semiconductor field effect transistors (MOSFETs) are highly impacted by charge trapping and scattering at the interface. Even though nitridation reduces the interface trap density, scattering still plays a crucial role in increasing the channel resistance in these transistors. In this work, the dominant scattering mechanisms are distinguished for inversion layer electrons and holes using temperature and body-bias-dependent Hall measurements on nitrided lateral 4H-SiC MOSFETs. The effect of the transverse electric field (E eƒƒ ) on carrier mobility is analyzed under strong inversion condition where surface roughness scattering becomes prevalent. Power law dependencies of the electron and hole Hall mobility for surface roughness scattering are determined to be E$^{-1.8}_{eƒƒ}$ and E$^{-2.4}_{eƒƒ}$, respectively, analogous to those of silicon MOSFETs. Moreover, for n-channel MOSFETs, the effect of phonon scattering is observed at zero body bias, whereas in p-channel MOSFETs, it is observed only under negative body biases. Along with the identification of regimes governed by different scattering mechanisms, these results highlight the importance of the selection of substrate doping and of E eƒƒ in controlling the value of channel mobility in 4H-SiC MOSFETs.

36 MATERIALS SCIENCE↗

Galaxy assembly bias and large-scale distribution: a comparison between IllustrisTNG and a semi-analytic model

In this work, we compare large scale structure observables for stellar mass selected samples at z = 0, as predicted by two galaxy models, the hydrodynamical simulation IllustrisTNG and the Santa-Cruz semi-analytic model (SC-SAM). Although both models have been independently calibrated to match observations, rather than each other, we find good agreement between the two models for two-point clustering and galaxy assembly bias signatures. The models also show a qualitatively similar response of occupancy and clustering to secondary halo parameters other than mass, such as formation history and concentration, although with some quantitative differences. Thus, our results demonstrate that the galaxy–halo relationships in SC-SAM and TNG are quite similar to first order. However, we also find areas in which the models differ. For example, we note a strong correlation between halo gas content and environment in TNG, which is lacking in the SC-SAM, as well as differences in the occupancy predictions for low-mass haloes. Moreover, we show that higher order statistics, such as cumulants of the density field, help us to accurately describe the galaxy distribution and discriminate between models that show degenerate behaviour for two-point statistics. Our results suggest that SAMs are a promising cost-effective and intuitive method for generating mock catalogues for next generation cosmological surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

Demonstration of Optimal Benchmark Selection Website and Validation of the q c Coverage Metric Using HEU-SOL-THERM-013-003 Experiment

In the work documented in this interim report, the experiment selection toolkit web site was demonstrated and q C coverage metric methodology was validated for IEU-MET-FAST-002-001, MIX-COMP-THERM 004-004, and HEU-SOL-THERM-013-003 experiments. 𝑞 𝐶 is an information-theoretic measure based on mutual information that quantifies the ability of candidate benchmark experiments to reduce the bias and uncertainty of a target criticality safety application. The metric and an accompanying open-source Python toolkit with a web-based interface were tested against a benchmark set of 425 experiments drawn from the International Criticality Safety Benchmark Evaluation Project Handbook. The interface is hosted at https://edim.covdef.com. It accepts sensitivity data files produced by the TSUNAMI-IP module of the SCALE code system and supports both (i) deterministic analysis using the ENDF/B-VII.0 covariance library and (ii) stochastic analysis based on user-supplied keff samples. Demonstrations on representative applications across a range of material composition, spectrum, and form show that q C -guided benchmark selection achieves greater uncertainty reduction with fewer experiments and yields more stable posterior bias and uncertainty estimates than traditional similarity coefficient ( c k )–based selection, while also capturing valuable low-ck experiments that one-to-one metrics overlook.

Abdel-khalik, Hany S. [Indiana Univ.-Purdue Univ. ↗

Biased-receiver digital interface

Coupling circuits converts TTL signals to higher voltage, higher current logic with good noise rejection. Depending on selected components, circuit may also be adapted to low-power applications.

Fitzgerald, F. C.↗

Improved Field Evaluation of Reference Cell Using Spectral Measurements

Output from a reference solar cell mounted on a one-axis tracking surface is investigated using 350 nm to 1650 nm spectral irradiance measurements on selected days throughout the year. Comparisons are made to a Class-A pyranometer also mounted on the tracking surface. The ratio of the reference cell's measurements to reference pyranometer measurements exhibit systematic biases over the day and year. Most of this bias is linked to spectral, temperature, and angle-of-incident effects that differ for the reference cell and the pyranometer. The comparison is done for selected clear and totally cloudy days to determine the magnitude of the effects and to characterize they influence the measurements made with reference cells.

14 SOLAR ENERGY↗

Data-driven building energy modeling with feature selection and active learning for data predictive control

Three gaps impede the development of cost-effective and accurate data-driven building energy modeling/models (DBEM) for energy forecasting and predictive control strategies. Gap 1: data bias is common in building operation data, but this topic is hardly studied in DBEM; Gap 2: high data dimensionality is common in DBEM, but a systematic and scalable methodology is lacking to solve the problem; Gap 3: the interactions between data bias and high dimensionality have not been systematically studied for DBEM and predictive control in buildings. In this work, to address the three gaps mentioned above, we develop a framework that integrates active learning and feature selection for DBEM used for whole building data predictive control (or DPC, which is a branch of model predictive control). The framework provides a systematic methodology and automatic workflow that starts with raw data from building automation systems to the establishment of data-driven energy models for DPC controllers. The developed strategies and framework are evaluated in a virtual testbed based on EnergyPlus and BCVTB. Improved performance and reduced computational complexity are observed from the DBEM built with the developed framework, as well as the DPC controller based on that DBEM, indicating the effectiveness of the developed framework.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Design and optimization of high temperature optocouplers as galvanic isolation

The commercial InGaN-based (blue and green) and AlGaInP-based (red) multiple quantum well (MQW) lighting emitting diodes (LEDs) were studied in a wide range of temperatures up to 800 K for their light emission and detection (i.e., LEDs operated under reverse bias as photodiodes (PDs)) characteristics. The results indicate the feasibility of integrating a pair of selected LEDs to fabricate high temperature (HT) optocouplers, which can be utilized as galvanic isolation to replace the bulky isolation transforms in the high-density power modules. A detailed study on LEDs and PDs were performed. The external quantum efficiency (EQE) of the LED and PDs were calculated. Higher relative external quantum efficiency (EQE) and lower efficiency droops with temperatures are obtained from the blue and green LEDs for display compared with the blue one for lighting and red LED for display. The blue for lighting and red for display devices show superior responsivity, specific detectivity (D*), and EQE compared with blue and green for display when operated as PDs. The results suggest that red LED devices for display can be used to optimize HT optocouplers due to the highest wavelength overlapping compared with others.

42 ENGINEERING↗

Evaluating Climate Models with the CLIVAR 2020 ENSO Metrics Package

El Niño–Southern Oscillation (ENSO) is the dominant mode of interannual climate variability on the planet, with far-reaching global impacts. It is therefore key to evaluate ENSO simulations in state-of-the-art numerical models used to study past, present, and future climate. Recently, the Pacific Region Panel of the International Climate and Ocean: Variability, Predictability and Change (CLIVAR) Project, as a part of the World Climate Research Programme (WCRP), led a community-wide effort to evaluate the simulation of ENSO variability, teleconnections, and processes in climate models. The new CLIVAR 2020 ENSO metrics package enables model diagnosis, comparison, and evaluation to 1) highlight aspects that need improvement; 2) monitor progress across model generations; 3) help in selecting models that are well suited for particular analyses; 4) reveal links between various model biases, illuminating the impacts of those biases on ENSO and its sensitivity to climate change; and to 5) advance ENSO literacy. By interfacing with existing model evaluation tools, the ENSO metrics package enables rapid analysis of multipetabyte databases of simulations, such as those generated by the Coupled Model Intercomparison Project phases 5 (CMIP5) and 6 (CMIP6). The CMIP6 models are found to significantly outperform those from CMIP5 for 8 out of 24 ENSO-relevant metrics, with most CMIP6 models showing improved tropical Pacific seasonality and ENSO teleconnections. Only one ENSO metric is significantly degraded in CMIP6, namely, the coupling between the ocean surface and subsurface temperature anomalies, while the majority of metrics remain unchanged.

54 ENVIRONMENTAL SCIENCES↗

MicroBooNE NS Timing Corrections

MicroBooNE has achieved a neutrino interaction timing resolution of O(1 ns), enabling improved background rejection and new physics searches. We identify a systematic bias in the reconstructed times of NCpi0 and nueCC events, which appear earlier than numuCC events, with a strong dependence on drift distance (reco_nuvtxX). An empirical correction, applied to high-energy showers, removes this spatial bias and aligns timing across topologies. The correction is validated across data runs and event selections, though the root cause remains under investigation.

Chan, Andrew [Michigan U.]↗

BASS. XXVI. DR2 Host Galaxy Stellar Velocity Dispersions

We present new central stellar velocity dispersions for 484 Sy 1.9 and Sy 2 from the second data release of the Swift/BAT AGN Spectroscopic Survey (BASS DR2). This constitutes the largest study of velocity dispersion measurements in X-ray-selected obscured active galactic nuclei (AGN) with 956 independent measurements of the Ca II H and K λ3969, 3934 and Mg I λ5175 region (3880–5550 Å) and the calcium triplet region (8350–8730 Å) from 642 spectra mainly from VLT/X-Shooter or Palomar/DoubleSpec. Our sample spans velocity dispersions of 40–360 km s 1 , corresponding to 4–5 orders of magnitude in black hole mass (M BH = 10 5.5-9.6 M ⊙ ), bolometric luminosity (L bol ~ 10 42–46 erg s -1 ), and Eddington ratio (L/L Edd ~ 10 -5 to 2). For 281 AGN, our data and analysis provide the first published central velocity dispersions, including six AGN with low-mass black holes (M BH = 10 5.5-6.5 M ⊙ ), discovered thanks to high spectral resolution observations (σ inst ~ 25 km s -1 ). The survey represents a significant advance with a nearly complete census of velocity dispersions of hard X-ray–selected obscured AGN with measurements for 99% of nearby AGN (z < 0.1) outside the Galactic plane (|b| > 10°). The BASS AGN have much higher velocity dispersions than the more numerous optically selected narrow-line AGN (i.e., ~150 versus ~100 km s -1 ) but are not biased toward the highest velocity dispersions of massive ellipticals (i.e., >250 km s -1 ). Despite sufficient spectral resolution to resolve the velocity dispersions associated with the bulges of small black holes (~10 4–5 M ⊙ ), we do not find a significant population of super-Eddington AGN. Using estimates of the black hole sphere of influence from velocity dispersion, direct stellar and gas black hole mass measurements could be obtained with existing facilities for more than ~100 BASS AGN.

79 ASTRONOMY AND ASTROPHYSICS↗

Equivalent source modeling of the main field using Magsat data

Magsat dipole solution models were obtained with both 32 deg and 21 deg resolution based on a data set extending over 4 months. Time dependence was modeled using first time derivatives for the dipole magnetization vector components. This doubles the n total number of parameters in the solution. The solutions displayed a very slow convergence in time derivatives although at each iteration the conversion of the dipole parameters to spherical harmonic coefficients showed close agreement with the MGST (12/80) spherical harmonic model to degree 13 in the constant terms and 8 in the secular variation terms. The program error in the option to simultaneously estimate observatory anomaly biases was found and corrected. A 32 deg resolution dipole model was generated using the selected magnetic observatory data from 1960-1977 used in the GSFC (9/80) spherical harmonic model.

Source record↗

Sensor failure detection for jet engines

Revisions to the advanced sensor failure detection, isolation, and accommodation (DIA) algorithm, developed under the sensor failure detection system program were studied to eliminate the steady state errors due to estimation filter biases. Three algorithm revisions were formulated and one revision for detailed evaluation was chosen. The selected version modifies the DIA algorithm to feedback the actual sensor outputs to the integral portion of the control for the nofailure case. In case of a failure, the estimates of the failed sensor output is fed back to the integral portion. The estimator outputs are fed back to the linear regulator portion of the control all the time. The revised algorithm is evaluated and compared to the baseline algorithm developed previously.

Beattie, E. C.↗

Sun shield

A shading device which is capable of compactly storing a flexible shade on a biased, window shade type spring roller is disclosed. It is controlled to deliver the shade selectively to either its operative shading or compact storage orientation.

Frank, Arthur M.↗

A Statistical Simulation Approach to Safe Life Fatigue Analysis of Redundant Metallic Components

This paper introduces a dual active load path fail-safe fatigue design concept analyzed by Monte Carlo simulation. The concept utilizes the inherent fatigue life differences between selected pairs of components for an active dual path system, enhanced by a stress level bias in one component. The design is applied to a baseline design; a safe life fatigue problem studied in an American Helicopter Society (AHS) round robin. The dual active path design is compared with a two-element standby fail-safe system and the baseline design for life at specified reliability levels and weight. The sensitivity of life estimates for both the baseline and fail-safe designs was examined by considering normal and Weibull distribution laws and coefficient of variation levels. Results showed that the biased dual path system lifetimes, for both the first element failure and residual life, were much greater than for standby systems. The sensitivity of the residual life-weight relationship was not excessive at reliability levels up to R = 0.9999 and the weight penalty was small. The sensitivity of life estimates increases dramatically at higher reliability levels.

Matthews, William T.↗

The impact of Los Angeles Basin pollution and stratospheric intrusions on the surrounding San Gabriel Mountains as seen by surface measurements, lidar, and numerical models

In this work, the impact of Los Angeles Basin pollution transport and stratospheric intrusions on the surface ozone levels observed in the San Gabriel Mountains is investigated based on a combination of surface and lidar measurements as well as WRF-Chem (Weather Research and Forecasting with Chemistry) and WACCM (Whole Atmosphere Community Climate Model) runs. The number of days with observed surface ozone levels exceeding the National Ambient Air Quality Standards exhibit a clear seasonal pattern, with a maximum during summer, when models suggest a minimum influence of stratospheric intrusions and the largest impact from Los Angeles Basin pollution transport. Additionally, measured and modeled surface ozone and PM10 were analyzed as a function of season, time of the day, and wind direction. Measurements and models are in good qualitative agreement, with maximum surface ozone observed for southwest and west winds. For the prevailing summer wind direction, slightly south of the ozone maximum and corresponding to south-southwest winds, lower ozone levels were observed. Back trajectories suggest that this is associated with transport from the central Los Angeles Basin, where titration limits the amount of surface ozone. A quantitative comparison of the lidar profiles with WRF-Chem and WACCM models revealed good agreement near the surface, with models showing an increasing positive bias as function of altitude, reaching 75 % at 15 km above sea level. Finally, three selected case studies covering the different mechanisms affecting the near-surface ozone concentration over the San Gabriel Mountains, namely stratospheric intrusions and pollution transport, are analyzed based on surface and ozone lidar measurements, as well as co-located ceilometer measurements and models.

Impact↗

Long Term Stability Monitoring of Aqua MODIS Thermal Emissive Bands through Radiative Transfer Modeling

Moderate Resolution Imaging Spectroradiometer (MODIS) on Aqua has been in operation providing continuous global observations for science research and applications since 2002. The long-term stability of thermal emissive bands (TEBs) of Aqua MODIS was monitored through inter-comparisons with measurements by hyperspectral infrared sensors, such as AIRS on Aqua and IASI on MetOp satellite, or through long term vicarious monitoring over cold targets, such as Dome- C and deep convective clouds (DCC). In this paper, a radiative transfer modeling-based simulation model using Community Radiative Transfer Model (CRTM) is developed to perform the long-term monitoring of the stability of TEBs of Aqua MODIS. CRTM is a fast-radiative transfer model for calculations of radiances for satellite infrared radiometers and is able to output infrared radiance and brightness temperature at spectral bands of MODIS. Long term European Centre for Medium-Range Weather Forecasts (ECMWF) global atmospheric reanalysis data, such as temperature and humidity profiles, are used as inputs to the CRTM simulation. By confining the area of interest to be over low to middle latitude ocean, the long-term stabilities of selected Aqua MODIS TEBs are monitored through Observation–Background (O-B) brightness temperature (BT) bias between MODIS measurements and BT retrieval from CRTM simulation. The consistency and relative stability between Aqua MODIS and ECMWF reanalysis data for surface channels of MODIS are evaluated. In addition, the radiative transfer modeling with CRTM enables us to evaluate the impacts of long term variation of global CO2 distribution on the O-B BT biases for CO2 channels of Aqua MODIS through comparison of simulations with constant or long term variable CO2 as inputs. The O-B analysis with RTM show that Aqua MODIS surface channels are all radiometrically stable with yearly BT bias drift less than 0.004K/year for B20, B22, B23 and ~0.01K/year for B31 and B32. The CO2 absorption channels of Aqua MODIS, e.g. B33-B36, are stable with BT bias drift < 0.005K/year.

MODIS↗

Optimal Asteroid Mass Determination from Planetary Range Observations: A Study of a Simplified Test Model

Mars ranging observations are available over the past 10 years with an accuracy of a few meters. Such precise measurements of the Earth-Mars distance provide valuable constraints on the masses of the asteroids perturbing both planets. Today more than 30 asteroid masses have thus been estimated from planetary ranging data (see [1] and [2]). Obtaining unbiased mass estimations is nevertheless difficult. Various systematic errors can be introduced by imperfect reduction of spacecraft tracking observations to planetary ranging data. The large number of asteroids and the limited a priori knowledge of their masses is also an obstacle for parameter selection. Fitting in a model a mass of a negligible perturber, or on the contrary omitting a significant perturber, will induce important bias in determined asteroid masses. In this communication, we investigate a simplified version of the mass determination problem. Instead of planetary ranging observations from spacecraft or radar data, we consider synthetic ranging observations generated with the INPOP [2] ephemeris for a test model containing ~25000 asteroids. We then suggest a method for optimal parameter selection and estimation in this simplified framework.

asteroids↗

DeepMerge: Classifying high-redshift merging galaxies with deep neural networks

In this work, we investigate and demonstrate the use of convolutional neural networks (CNNs) for the task of distinguishing between merging and non-merging galaxies in simulated images, and for the first time at high redshifts (i.e. $z=2$). We extract images of merging and non-merging galaxies from the Illustris-1 cosmological simulation and apply observational and experimental noise that mimics that from the Hubble Space Telescope; the data without noise form a "pristine" data set and that with noise form a "noisy" data set. The test set classification accuracy of the CNN is $79\%$ for pristine and $76\%$ for noisy. The CNN outperforms a Random Forest classifier, which was shown to be superior to conventional one- or two-dimensional statistical methods (Concentration, Asymmetry, the Gini, $M_{20}$ statistics etc.), which are commonly used when classifying merging galaxies. We also investigate the selection effects of the classifier with respect to merger state and star formation rate, finding no bias. Finally, we extract Grad-CAMs (Gradient-weighted Class Activation Mapping) from the results to further assess and interrogate the fidelity of the classification model.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗