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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Air Quality Science and Regulatory Efforts Require Geostationary Satellite Measurements

Air quality scientists and regulatory agencies would benefit from the high spatial and temporal resolution trace gas and aerosol data that could be provided by instruments on a geostationary platform. More detailed time-resolved data from a geostationary platform could be used in tracking regional transport and in evaluating mesoscale air quality model performance in terms of photochemical evolution throughout the day. The diurnal cycle of photochemical pollutants is currently missing from the data provided by the current generation of atmospheric chemistry satellites which provide only one measurement per day. Often peak surface ozone mixing ratios are reached much earlier in the day during major regional pollution episodes than during local episodes due to downward mixing of ozone that had been transported above the boundary layer overnight. The regional air quality models often do not simulate this downward mixing well enough and underestimate surface ozone in regional episodes. Having high time-resolution geostationary data will make it possible to determine the magnitude of this lower-and mid-tropospheric transport that contributes to peak eight-hour average ozone and 24-hour average PM2.5 concentrations. We will show ozone and PM(sub 2.5) episodes from the CMAQ model and suggest ways in which geostationary satellite data would improve air quality forecasting. Current regulatory modeling is typically being performed at 12 km horizontal resolution. State and regional air quality regulators in regions with complex topography and/or land-sea breezes are anxious to move to 4-km or finer resolution simulations. Geostationary data at these or finer resolutions will be useful in evaluating such models.

Pickering, Kenneth E.↗
NASA NTRS1993

Correct CMOS IC defect models for quality testing

Leading edge, high reliability, and low escape CMOS IC test practices have now virtually removed the stuck-at fault model and replaced it with more defect-orientated models. Quiescent power supply current testing (I(sub DDQ)) combined with strategic use of high speed test patterns is the recommended approach to zero defect and high reliability testing goals. This paper reviews the reasons for the change in CMOS IC test practices and outlines an improved CMOS IC test methodology.

Soden, Jerry M.↗
NASA NTRS1971

Information quality-control model

Model serves as graphic tool for estimating complete product objectives from limited input information, and is applied to cost estimations, product-quality evaluations, and effectiveness measurements for manpower resources allocation. Six product quality levels are defined.

Vincent, D. A.↗
NASA NTRS2011

Handling Qualities of Model Reference Adaptive Controllers with Varying Complexity for Pitch-Roll Coupled Failures

Three model reference adaptive controllers (MRAC) with varying levels of complexity were evaluated on a high performance jet aircraft and compared along with a baseline nonlinear dynamic inversion controller. The handling qualities and performance of the controllers were examined during failure conditions that induce coupling between the pitch and roll axes. Results from flight tests showed with a roll to pitch input coupling failure, the handling qualities went from Level 2 with the baseline controller to Level 1 with the most complex MRAC tested. A failure scenario with the left stabilator frozen also showed improvement with the MRAC. Improvement in performance and handling qualities was generally seen as complexity was incrementally added; however, added complexity usually corresponds to increased verification and validation effort required for certification. The tradeoff between complexity and performance is thus important to a controls system designer when implementing an adaptive controller on an aircraft. This paper investigates this relation through flight testing of several controllers of vary complexity.

Schaefer, Jacob↗
NASA NTRS1976

Noise and vibration ride comfort criteria

A program is underway at Langley Research Center to develop a comprehensive ride quality model based upon the various physical and psychological factors that most affect passenger ride comfort. Two of the most important factors, namely, vibration and noise were studied to (1) determine whether composite or separate noise and vibration criteria are needed for the prediction of ride quality, (2) determine a noise correction for the previously-defined vibration criteria of the ride quality model, (3) assess whether these noise corrections depend on the nature of the vibration stimuli, i.e., deterministic as opposed to random, and (4) specify noise-vibration criteria for this combined environment. The stimuli for the study consisted of octave bands of noise centered at 500 or 2000 Hz and vertical vibrations composed of either 5 Hz sinusoidal vibration or random vibrations centered at 5 Hz and with a 5 Hz bandwidth. The noise stimuli were presented at levels ranging from ambient to 95 dB(A) and the vibrations at levels ranging from 0.02 to 0.13 g-rms.

Dempsey, T. K.↗
NASA NTRS2018

Investigation of NO2 Measurements Made During DISCOVER-AQ and KORUS-AQ Campaigns in Conjunction with NO2 Tropospheric Column from the Ozone Monitoring Instrument (OMI) and High-Resolution Community Multi-Scale Air Quality (CMAQ) Model Simulation

Atmospheric NO2 is produced by combustion, lightning, and in soil. NO2 affects ozone production and criteria pollutant itself.It also has indirect radiative impacts in the troposphere, since ozone has largest warming effect in upper troposphere. Tropospheric vertical column densities (VCD) of NO2 are available from satellites (GOME, OMI, SCIAMACHY, GOME-2). DISCOVER-AQ and KORUS-AQ aircraft campaigns we reconducted to improve the use of satellites to monitor air quality for public health and environmental benefit in United States and South Korea. In this study, we investigate 1) How do these measurements compare? 2) What is the best way to make comparisons of space- and ground-based measurements?

multi-scale air quality↗
DOE OSTI2021

Improving protein tertiary structure prediction by deep learning and distance prediction in CASP14

Abstract Substantial progresses in protein structure prediction have been made by utilizing deep‐learning and residue‐residue distance prediction since CASP13. Inspired by the advances, we improve our CASP14 MULTICOM protein structure prediction system by incorporating three new components: (a) a new deep learning‐based protein inter‐residue distance predictor to improve template‐free (ab initio) tertiary structure prediction, (b) an enhanced template‐based tertiary structure prediction method, and (c) distance‐based model quality assessment methods empowered by deep learning. In the 2020 CASP14 experiment, MULTICOM predictor was ranked seventh out of 146 predictors in tertiary structure prediction and ranked third out of 136 predictors in inter‐domain structure prediction. The results demonstrate that the template‐free modeling based on deep learning and residue‐residue distance prediction can predict the correct topology for almost all template‐based modeling targets and a majority of hard targets (template‐free targets or targets whose templates cannot be recognized), which is a significant improvement over the CASP13 MULTICOM predictor. Moreover, the template‐free modeling performs better than the template‐based modeling on not only hard targets but also the targets that have homologous templates. The performance of the template‐free modeling largely depends on the accuracy of distance prediction closely related to the quality of multiple sequence alignments. The structural model quality assessment works well on targets for which enough good models can be predicted, but it may perform poorly when only a few good models are predicted for a hard target and the distribution of model quality scores is highly skewed. MULTICOM is available at https://github.com/jianlin-cheng/MULTICOM_Human_CASP14/tree/CASP14_DeepRank3 and https://github.com/multicom-toolbox/multicom/tree/multicom_v2.0 .

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2014

Improved Satellite Retrievals of NO2 and SO2 over the Canadian Oil Sands and Comparisons with Surface Measurements

Satellite remote sensing is increasingly being used to monitor air quality over localized sources such as the Canadian oil sands. Following an initial study, significantly low biases have been identified in current NO2 and SO2 retrieval products from the Ozone Monitoring Instrument (OMI) satellite sensor over this location resulting from a combination of its rapid development and small spatial scale. Air mass factors (AMFs) used to convert line-of-sight "slant" columns to vertical columns were re-calculated for this region based on updated and higher resolution input information including absorber profiles from a regional-scale (15 km × 15 km resolution) air quality model, higher spatial and temporal resolution surface reflectivity, and an improved treatment of snow. The overall impact of these new Environment Canada (EC) AMFs led to substantial increases in the peak NO2 and SO2 average vertical column density (VCD), occurring over an area of intensive surface mining, by factors of 2 and 1.4, respectively, relative to estimates made with previous AMFs. Comparisons are made with long-term averages of NO2 and SO2 (2005-2011) from in situ surface monitors by using the air quality model to map the OMI VCDs to surface concentrations. This new OMI-EC product is able to capture the spatial distribution of the in situ instruments (slopes of 0.65 to 1.0, correlation coefficients of greater than 0.9). The concentration absolute values from surface network observations were in reasonable agreement, with OMI-EC NO2 and SO2 biased low by roughly 30%. Several complications were addressed including correction for the interference effect in the surface NO2 instruments and smoothing and clear-sky biases in the OMI measurements. Overall these results highlight the importance of using input information that accounts for the spatial and temporal variability of the location of interest when performing retrievals.

surface concentration↗
NASA NTRS1976

A model for prediction of ride quality in a multifactor environment

Recently a ride quality comfort model has been proposed which accounts for the effect of both multifrequency and multiaxes vibratory inputs, as well as nonvibratory inputs such as noise, on human comfort response. The proposed NASA ride quality model is described in general terms and selected results of several experimental investigations are presented that have contributed to the development of the model and to a more comprehensive understanding of human comfort response to vibration. Human subjective response to vertical vibration, combined vertical-lateral vibrations, and roll vibrations are discussed, and a set of vertical discomfort curves is presented.

Leatherwood, J. D.↗
DOE OSTI2025

PUFFIn Software Modeling for Quality Management

PUFFIn (PENELOPE User Friendly Fast Interface) was designed as a fast and simple Monte Carlo simulation tool for the transport of photons and electrons, with a primary purpose as a learning and education tool for a broad range of static configurations in the radiation processing industry. Development of the PUFFIn software is funded by the Office of Radiological Security (ORS) within the United States National Nuclear Security Administration (NNSA). PUFFIn helps fill the education and knowledge gaps in the industry, as identified in reports by Fermilab (2017) and the IAEA (2020). PUFFIn uses the PENELOPE (NEA-2023) physics engine to perform simulations on static configurations. PUFFIn has support for multiple geometry types from simple, single material simulations to full 3D configurations created from CAD input files or images from X-Ray Tomography scans. PUFFin was designed to be easy for the novice user, it will generate the input and geometry files required by PENLOPE and will display the output plots within the PUFFIn interface. PUFFin is distributed for free but requires a free workshop so users can be adequately trained in its use. Workshops have been presented in the past at Texas A&M university, the Aerial-CRT facility in Strasbourg France and Jakarta Indonesia. PUFFIn simulations have been validated by 10 MeV ebeam experiments done at Aerial-CRT in France (Radiation Physics and Chemistry 222 (2024) 111774). Further user experimental comparisons were made at the medical product hands on workshop at Texas A&M in October 2024.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Machine Learning a Simple Interpretable Short-Range Potential for Silica

A wide array of models, spanning from computationally expensive ab initio methods to a spectrum of force-field approaches, have been developed and employed to probe silica polymorphs and understand growth processes and atomic-level dynamical transitions in silica. However, the quest for a model capable of making accurate predictions with high computational efficiency for various silica polymorphs is still ongoing. Recent developments in short-range machine-learned models, such as GAP and NNPScan, have shown promise in providing reasonable descriptions of silica, but their computational cost remains high compared to force fields such as BKS which are based on simple interpretable functional forms. Here, in this study, we build on the recent success of our reinforcement learning (RL) workflow to derive a new set of optimal parameters for a promising short-range BKS-based model proposed by Soules. We use RL to navigate the eight-dimensional parameter space of the Soules potential using an experimental training data set that includes both local and global structural features from approximately 21 experimentally realized silica polymorphs, including high density phases and porous zeolites. We compare the performance of our machine-learned ML-Soules model with other high quality models including our recent machine-learned parametrization of BKS (ML-BKS), a machine-learned potential (GAP), as well as predictions of ab initio calculations with the highly fidelity SCAN functional. The ML-Soules accurately captures the relative energetic ordering of various polymorphs as well as their structural features at a significantly reduced computational expense. The ML-Soules model also reasonably captures the structure, density, and elastic constants of quartz, as well as metastable silica polymorphs. We further discuss the limitations of the Soules functional form and propose potential enhancements, including the incorporation of additional three-body terms and/or the utilization of different short-ranged functional forms to achieve greater accuracy for both global and local features in the modeling of silica while retaining low computational cost.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Proteome-scale Structure Prediction Data - Pseudodesulfovibrio mercurii

The number of proteins predicted for Pseudodesulfovibrio mercurii is 3,446, each of which have five predicted structures from an AlphaFold run, as well as structural alignment results using the TMscore-based structural alignment method within the APoc program. Specifically, AlphaFold outputs the atoms and coordinates of the protein model in human-readable PDB files and quantitative prediction metrics in Python PICKLE files. The 5 models have been ranked based on the predicted TM-score (pTMS), a quantitative confidence metric output by AlphaFold that reports on protein model quality. The top ranked model has undergone an energy minimization calculation to relax and remove any potential clashes in the atomic coordinates. Structural alignment results are stored in two files for each protein; the top ranked model (as discussed above) is used for all alignment analyses. Both are compressed gzip files that, once unpacked, are human readable. The first file is the TMalign score results and contains the quantitative metrics for the top alignments between the predicted structure and experimental structures from the PDB70, a curated non-redundant database of about 80,000 experimental structures developed by the Soding lab. Each data point in this file is directly associated with one experimental structure; PDB ID and brief meta-data about the protein taken from the PDB70 file are reported alongside the quantitative metrics. The second results file contains the raw results associated with each alignment reported in the score results file. Specifically, the translation and rotation arrays for each alignment are provided so that the structural alignment can be recreated. Additionally, residue-level scores are reported to quantify the closeness of the aligned residues between the predicted and experimental models.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1980

Software cost/resource modeling: Software quality tradeoff measurement

A conceptual framework for treating software quality from a total system perspective is developed. Examples are given to show how system quality objectives may be allocated to hardware and software; to illustrate trades among quality factors, both hardware and software, to achieve system performance objectives; and to illustrate the impact of certain design choices on software functionality.

Lawler, R. W.↗