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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 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Large-scale analysis of structural brain asymmetries in schizophrenia via the ENIGMA consortium

Left–right asymmetry is an important organizing feature of the healthy brain that may be altered in schizophrenia, but most studies have used relatively small samples and heterogeneous approaches, resulting in equivocal findings. We carried out the largest case–control study of structural brain asymmetries in schizophrenia, with MRI data from 5,080 affected individuals and 6,015 controls across 46 datasets, using a single image analysis protocol. Asymmetry indexes were calculated for global and regional cortical thickness, surface area, and subcortical volume measures. Differences of asymmetry were calculated between affected individuals and controls per dataset, and effect sizes were meta-analyzed across datasets. Small average case–control differences were observed for thickness asymmetries of the rostral anterior cingulate and the middle temporal gyrus, both driven by thinner left-hemispheric cortices in schizophrenia. Analyses of these asymmetries with respect to the use of antipsychotic medication and other clinical variables did not show any significant associations. Assessment of age- and sex-specific effects revealed a stronger average leftward asymmetry of pallidum volume between older cases and controls. Case–control differences in a multivariate context were assessed in a subset of the data (N = 2,029), which revealed that 7% of the variance across all structural asymmetries was explained by case–control status. Subtle case–control differences of brain macrostructural asymmetry may reflect differences at the molecular, cytoarchitectonic, or circuit levels that have functional relevance for the disorder. Reduced left middle temporal cortical thickness is consistent with altered left-hemisphere language network organization in schizophrenia.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Modeling freight mode choice using machine learning classifiers: a comparative study using Commodity Flow Survey (CFS) data

This study explores the usefulness of machine learning classifiers for modeling freight mode choice. We investigate eight commonly used machine learning classifiers, namely Naïve Bayes, Support Vector Machine, Artificial Neural Network, K-Nearest Neighbors, Classification and Regression Tree, Random Forest, Boosting and Bagging, along with the classical Multinomial Logit model. US 2012 Commodity Flow Survey data are used as the primary data source; we augment it with spatial attributes from secondary data sources. The performance of the classifiers is compared based on prediction accuracy results. The current research also examines the role of sample size and training-testing data split ratios on the predictive ability of the various approaches. In addition, the importance of variables is estimated to determine how the variables influence freight mode choice. The results show that the tree-based ensemble classifiers perform the best. Specifically, Random Forest produces the most accurate predictions, closely followed by Boosting and Bagging. With regard to variable importance, shipment characteristics, such as shipment distance, industry classification of the shipper and shipment size, are the most significant factors for freight mode choice decisions.

42 ENGINEERING↗
DOE OSTI2025

D–MOPH–25: diverse MOF–molecule pairs for Henry’s constants prediction

Computational methods like grand-canonical Monte Carlo simulations and machine learning (ML) have accelerated metal–organic frameworks (MOF) exploration but are typically limited to a narrow range of adsorbates due to data availability and force field constraints. In this study, we introduce a dataset of diverse MOF–molecule pairs for Henry’s constant prediction, D–MOPH–25, which systematically explores a diverse chemical space by combining 113 molecular adsorbates with over 5000 MOF structures through an active learning process. D–MOPH–25 constitutes the most diverse adsorbate dataset used in any ML study of molecular adsorption in MOFs to date. Our workflow builds a benchmark for predicting Henry’s constants at 300 K, leveraging conformal prediction for uncertainty quantification. Assessment through Shannon entropy and uniform manifold approximation and projection confirms the comprehensiveness of D–MOPH–25 while highlighting the importance of robust classification to filter out unphysical data points in regression tasks. Although future enhancements in model architecture and sampling criteria could improve predictive performance, our dataset already spans the target space using only 2.31% of total possibilities. This comprehensive dataset facilitates assessment of model generalizability across adsorbate species and can establish a foundation for high-throughput MOF screening and ML-driven separation processes.

active learning↗
DOE OSTI2023

Tensor train continuous time solver for quantum impurity models

The simulation of strongly correlated quantum impurity models is a significant challenge in modern condensed matter physics that has multiple important applications. Thus far, the most successful methods for approaching this challenge involve Monte Carlo techniques that accurately and reliably sample perturbative expansions to any order. However, the cost of obtaining high precision through these methods is high. Recently, tensor train decomposition techniques have been developed as an alternative to Monte Carlo integration. In this study, we apply these techniques to the single-impurity Anderson model at equilibrium by calculating the systematic expansion in power of the hybridization of the impurity with the bath. Furthermore, we demonstrate the performance of the method in a paradigmatic application, examining the first-order phase transition on the infinite-dimensional Bethe lattice, which can be mapped to an impurity model through dynamical mean field theory. Our results indicate that using tensor train decomposition schemes allows the calculation of finite-temperature Green's functions and thermodynamic observables with unprecedented accuracy. The methodology holds promise for future applications to frustrated multiorbital systems, using a combination of partially summed series with other techniques pioneered in diagrammatic and continuous time quantum Monte Carlo.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

CROCUS Weather Data at Northeastern Illinois University Rooftop

This dataset is from the Department of Energy Office of Science funded project, Community Research on Urban and Climate Science (CROCUS) (https://crocus-urban.org/). Vaisala WXT sensor is an all-in-one weather instrument that provides 6 of the most important weather parameters: barometric pressure, temperature, relative humidity, rainfall, wind speed and direction. Temperature, pressure, relative humidity, and rainfall are sampled at 1 second frequency, while wind speed/direction is measured at ten per second (10Hz) frequency. These measurements are useful for looking at characterizing local weather, identifying unique weather events, and studying local turbulence, especially given the high temporal resolution of the wind measurements.Datasets are stored in the netCDF data format, and we we encourage users to make use the associated toolkits available from Unidata (https://www.unidata.ucar.edu/software/netcdf/), Project Pythia (https://foundations.projectpythia.org/core/data-formats/netcdf-cf.html), and our “Instrument Cookbooks” (https://crocus-urban.github.io/instrument-cookbooks) for more information on how to process the metadata-rich datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

CROCUS Weather Data at Chicago State University Prairie Site

Vaisala WXT sensor is an all-in-one weather instrument that provides 6 of the most important weather parameters: barometric pressure, temperature, relative humidity, rainfall, wind speed and direction. Temperature, pressure, relative humidity, and rainfall are sampled at 1 second frequency, while wind speed/direction is measured at ten per second (10Hz) frequency. These measurements are useful for looking at characterizing local weather, identifying unique weather events, and studying local turbulence, especially given the high temporal resolution of the wind measurements. These measurements are collected at Chicago State University (CSU) at a prarie site on campus in Chicago, Illinois. Data is available in the netCDF data format, we encourage data users review documentation through Project Pythia to understand how to work with netCDF data https://foundations.projectpythia.org/core/data-formats/netcdf-cf.html. The data is aggregated into daily frequency to make it easier to process multiple days, and compress the higher-resolution fields. Each file contains one day's worth of data (24 hours, starting at 0000 UTC). File naming convention includes the project (CROCUS), location (CSU), data level (raw, a1), date (year, month, day), and hour (0000).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

CROCUS Weather Data at Argonne National Laboratory Prairie Site

Vaisala WXT sensor is an all-in-one weather instrument that provides 6 of the most important weather parameters: barometric pressure, temperature, relative humidity, rainfall, wind speed and direction. Temperature, pressure, relative humidity, and rainfall are sampled at 1 second frequency, while wind speed/direction is measured at ten per second (10Hz) frequency. These measurements are useful for looking at characterizing local weather, identifying unique weather events, and studying local turbulence, especially given the high temporal resolution of the wind measurements. These measurements are collected at the Argonne Testbed for Multiscale Observational Science (ATMOS), a prairie field site at Argonne National Laboratory in Lemont, Illinois. Data is available in the netCDF data format, we encourage data users review documentation through Project Pythia to understand how to work with netCDF data https://foundations.projectpythia.org/core/data-formats/netcdf-cf.html. The data is aggregated into daily frequency to make it easier to process multiple days, and compress the higher-resolution fields. Each file contains one day's worth of data (24 hours, starting at 0000 UTC). File naming convention includes the project (CROCUS), location (atmos), data level (raw, a1), date (year, month, day), and hour (0000).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

CROCUS Weather Data at University of Illinois - Chicago Tower

Vaisala WXT sensor is an all-in-one weather instrument that provides 6 of the most important weather parameters: barometric pressure, temperature, relative humidity, rainfall, wind speed and direction. Temperature, pressure, relative humidity, and rainfall are sampled at 1 second frequency, while wind speed/direction is measured at ten per second (10Hz) frequency. These measurements are useful for looking at characterizing local weather, identifying unique weather events, and studying local turbulence, especially given the high temporal resolution of the wind measurements. These measurements are collected at the University of Illinois in Chicago, Illinois, on the meteorological tower near the greenhouse on campus. Data is available in the netCDF data format, we encourage data users review documentation through Project Pythia to understand how to work with netCDF data https://foundations.projectpythia.org/core/data-formats/netcdf-cf.html. File naming convention includes the project (CROCUS), location (UIC), data level (raw, a1), date (year, month, day), and hour (0000).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

CROCUS Weather Data at Northwestern University Rooftop

This dataset is from the Department of Energy Office of Science funded project, Community Research on Urban and Climate Science (CROCUS) (https://crocus-urban.org/). Vaisala WXT sensor is an all-in-one weather instrument that provides 6 of the most important weather parameters: barometric pressure, temperature, relative humidity, rainfall, wind speed and direction. Temperature, pressure, relative humidity, and rainfall are sampled at 1 second frequency, while wind speed/direction is measured at ten per second (10Hz) frequency. These measurements are useful for looking at characterizing local weather, identifying unique weather events, and studying local turbulence, especially given the high temporal resolution of the wind measurements. Datasets are stored in the netCDF data format, and we we encourage users to make use the associated toolkits available from Unidata (https://www.unidata.ucar.edu/software/netcdf/), Project Pythia (https://foundations.projectpythia.org/core/data-formats/netcdf-cf.html), and our “Instrument Cookbooks” (https://crocus-urban.github.io/instrument-cookbooks) for more information on how to process the metadata-rich datasets.

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC TEMPERATU↗
DOE OSTI2024

Improved Manufacturability and Throughput of Ultra- Transparent, Super-Insulating Aerogels

AeroShield Materials produces a novel silica aerogel material with exemplary thermal performance and unprecedented optical clarity, offering the potential for super-insulating fenestration and insulated glass to reduce thermal losses in the built environment by billions of dollars every year. One of the most significant challenges facing AeroShield today is the total amount of time that is required to produce large monolithic aerogel samples. This overall process can require as much as 144 hours total, which can significantly hinder scale-up to an economically viable product. The purpose of this Phase 1 research was to continue development of our novel aerogel manufacturing process to reduce material processing time by up to 10x, greatly improving product throughput and reducing cost. AeroShield’s manufacturing process can be divided into 4 major stages, each with their own distinct set of parameters and time requirements. Under this Phase 1 award, AeroShield was able to identify and optimize a number of these parameters, including molding materials, solvent rinse conditions, critical point drying time, and annealing conditions. AeroShield also performed thorough analyses on how these optimized parameters affected important final characteristics of the gels, including optical clarity, thermal conductivity, and dimensional stability. This campaign culminated in the production of laboratory scale aerogel samples using significantly lower process times of both 36 and 18 total hours, which represent Phase 1 Target and Stretch goals. In order to achieve widespread market adoption, monolithic sheets of the aerogel material must be made to industry-standard sizes (8’ x 12’) at a cost that provides 5-7 year or less breakeven energy savings for consumers (<$2 sq/ft). The work performed under this Phase 1 award shows that time and materials required to make aerogel samples, which make up a significant portion of their overall cost, can be greatly reduced without sacrificing quality. AeroShield plans to use these optimized processes to produce larger, product-relevant sized aerogels in order to achieve target final material costs.

Wilke, Kyle↗
DOE OSTI2025

Prediction of Silicon Content in a Blast Furnace via Machine Learning: A Comprehensive Processing and Modeling Pipeline

Silicon content plays an important role in determining the operational efficiency of blast furnaces (BFs) and their downstream processes in integrated steelmaking; however, existing sampling methods and first-principles models are somewhat limited in their capability and flexibility. Current data-based prediction models primarily rely on a limited set of manually selected furnace parameters. Additionally, different BFs present a diverse set of operating parameters and state variables that are known to directly influence the hot metal’s silicon content, such as fuel injection, blast temperature, and raw material charge composition, among other process variables that have their own impacts. The expansiveness of the parameter set adds complexity to parameter selection and processing. This highlights the need for a comprehensive methodology to integrate and select from all relevant parameters for accurate silicon content prediction. Providing accurate silicon content predictions would enable operators to adjust furnace conditions dynamically, improving safety and reducing economic risk. To address these issues, a two-stage approach is proposed. First, a generalized data processing scheme is proposed to accommodate diverse furnace parameters. Second, a robust modeling pipeline is used to establish a machine learning (ML) model capable of predicting hot metal silicon content with reasonable accuracy. The method employed herein predicted the average Si content of the upcoming furnace cast with an accuracy of 91% among 200 target predictions for a specific furnace provisioned by the XGBoost model. This prediction is achieved using only the past shift’s operating conditions, which should be available in real time. This performance provides a strong baseline for the modeling approach with potential for further improvement through provision of real-time features.

Chemistry↗
NASA NTRS1971

Transpiration and film cooling boundary layer computer program. Volume 2: Computer program and user's manual

A finite difference turbulent boundary layer computer program which allows for mass transfer wall cooling and equilibrium chemistry effects is presented. The program is capable of calculating laminar or turbulent boundary layer solutions for an arbitrary ideal gas or an equilibrium hydrogen oxygen system. Either two dimensional or axisymmetric geometric configurations may be considered. The equations are solved, in nondimension-alized physical coordinates, using the implicit Crank-Nicolson technique. The finite difference forms of the conservation of mass, momentum, total enthalpy and elements equations are linearized and uncoupled, thereby generating easily solvable tridiagonal sets of algebraic equations. A detailed description of the computer program, as well as a program user's manual is provided. Detailed descriptions of all boundary layer subroutines are included, as well as a section defining all program symbols of principal importance. Instructions are then given for preparing card input to the program and for interpreting the printed output. Finally, two sample cases are included to illustrate the use of the program.

Gloss, R. J.↗
NASA NTRS1987

Infrared emission and star formation in early-type galaxies

Infrared emission from elliptical and S0 galaxies was studied to determine the extent of low-mass star formation in such early-type galaxies. It is found that the infrared colors of about one-third of the sample are consistent with ongoing star formation, although a contribution to the emission from an 'active' nucleus might play an important role in some objects. Apparently star formation has not ceased in some elliptical and S0 galaxies and may be fueled by mass loss from evolved stars or out of the rubble of galaxian mergers. Of four plausible candidate star-forming ellipticals, three show evidence for accretion and/or merger. It is also concluded that IRAS two-color diagrams are often ambiguous in determining whether or not emission arising from star formation dominates far-infrared luminosity.

Thronson, Harley A., Jr.↗
NASA NTRS1993

Lunar scout missions: Galileo encounter results and application to scientific problems and exploration requirements

The Lunar Scout Missions (payload: x-ray fluorescence spectrometer, high-resolution stereocamera, neutron spectrometer, gamma-ray spectrometer, imaging spectrometer, gravity experiment) will provide a global data set for the chemistry, mineralogy, geology, topography, and gravity of the Moon. These data will in turn provide an important baseline for the further scientific exploration of the Moon by all-purpose landers and micro-rovers, and sample return missions from sites shown to be of primary interest from the global orbital data. These data would clearly provide the basis for intelligent selection of sites for the establishment of lunar base sites for long-term scientific and resource exploration and engineering studies. The two recent Galileo encounters with the Moon (December, 1990 and December, 1992) illustrate how modern technology can be applied to significant lunar problems. We emphasize the regional results of the Galileo SSI to show the promise of geologic unit definition and characterization as an example of what can be done with the global coverage to be obtained by the Lunar Scout Missions.

Head, J. W.↗
NASA NTRS1999

A Survey of Environmental Microbial Flora During Closed Chamber Studies

Services, Inc. and NASA Johnson Space Center, Houston, TX As NASA prepares for long-term missions aboard the International Space Station and the eventual exploration of Mars, closed-environment chambers on Earth have become important test beds for systems evaluations. During 2 separate studies of a selfcontained ecosystem containing 4 crewmembers, microbial surveys of samples from 13 surface and 3 air sites were performed. Microbial concentration of samples from surface sites with frequent water contact (e.g., urinal, sink) did not indicate significantly higher levels of contamination than drier areas, though surface cleaning by the crew may have influenced this conclusion. Changes in bacterial diversity on surface sites implied that the number of transient species was high, suggesting movement by crew activities, aerosols, or both. A non-linear relationship between bacterial diversity and enumeration from surface samples indicated that a rapid increase occurred in the number of species as cell concentration increased to 5 CFU/sq cm. Above this concentration, the number of different bacterial species varied between 11 and 16. Airborne bacteria and fungi averaged only 160 and 1 CFU/m3, respectively. Microbial contamination of the potable water system primarily consisted of 3 species of Gram negative bacteria; however, after 60 days during one study, several species of Bacillus became the dominant flora. This study suggests that under these conditions, microbial contamination in the air and water was suppressed by the life-support systems, though contamination was possible. Conversely, the crew and their activities controlled microbial levels on surfaces. Understanding the factors that affect microbial control will improve the design of microbial testing both during space flight and in analogous Earth-based environments.

Ott, C. Mark↗
NASA NTRS2000

Desert Dust Layers Over Polluted Marine Boundary Layers: ACE-2 Measurements and ACE-Asia Plans

Aerosols in ACE-Asia are expected to have some commonalties with those in ACE-2, along with important differences. Among the commonalities are occurrences of desert dust layers over polluted marine boundary layers. Differences include the nature of the dust (yellowish in the East Asia desert outflow, vs. reddish-brown in the Sahara Outflow measured in ACE-2) and the composition of boundary-layer aerosols (e.g., more absorbing, soot and organic aerosol in-the Asian plume, caused by coal and biomass burning, with limited controls). In this paper we present ACE-2 measurements and analyses as a guide to our plans for ACE-2 Asia. The measurements include: (1) Vertical profiles of aerosol optical depth and extinction (380-1558 nm), and of water vapor column and concentration, from the surface through the elevated desert dust, measured by the 14-channel Ames Airborne Tracking Sunphotometer (AATS-14); (2) Comparisons of airborne and shipborne sunphotometer optical depths to satellite-retrieved values, with and without desert dust; (3) Comparisons between airborne Sunphotometer optical depth and extinction spectra and those derived from coincident airborne in situ measurements of aerosol size distribution, scattering and absorption; (4) Comparisons between size distributions measured in situ and retrieved from sunphotometer optical depth spectra; (5) Comparisons between aerosol single scattering albedo values obtained by several techniques, using various combinations of measurements of backscatter, extinction, size distribution, scattering, absorption, and radiative flux. We show how analyses of these data can be used to address questions important to ACE-Asia, such as: (1) How do dust and other absorbing aerosols affect the accuracy of satellite optical depth retrievals? How important are asphericity effects? (2) How important are supermicron dust and seasalt aerosols to overall aerosol optical depth and radiative forcing? How well are these aerosols sampled by aircraft inlets and instruments? (3) How consistent are suborbital in situ and remote measurements of aerosols, among themselves and with satellite retrievals? What are the main reasons for observed inconsistencies?

Russell, Philip B.↗
NASA NTRS2007

The Space Infrared Interferometric Telescope (SPIRIT): High-resolution Imaging and Spectroscopy in the Far-infrared

We report results of a recently-completed study of SPIRIT, a candidate NASA Origins Probe. SPIRIT is a spatial and spectral interferometer with an operating wavelength range 25 - 400 microns. SPIRIT will provide sub-arcsecond resolution images and spectra with resolution R = 3000 in a 1 arcmin field of view to accomplish three primary scientific objectives: (1) Learn how planetary systems form from protostellar disks, and how they acquire their chemical organization; (2) Characterize the family of extrasolar planetary systems by imaging the structure in debris disks to understand how and where planets form, and why some planets are ice giants and others are rocky; and (3) Learn how high-redshift galaxies formed and merged to form the present-day population of galaxies. Observations with SPIRIT will be complementary to those of the James Webb Space Telescope and the ground-based Atacama Large Millimeter Array. All three observatories could be operational contemporaneously. SPIRIT will pave the way to the 1 km maximum baseline interferometer known as the Submillimeter Probe of the Evolution of Cosmic Structure (SPECS). In addition to the SPIRIT mission concept, this talk will emphasize the importance of dense u-v plane coverage and describe some of the practical considerations associated with alternative interferometric baseline sampling schemes.

Leisawitz, D,↗
NASA NTRS2010

Bringing a Chemical Laboratory Named Sam to Mars on the 2011 Curiosity Rover

An important goal of upcoming missions to Mars is to understand if life could have developed there. The task of the Sample Analysis at Mars (SAM) suite of instruments [1] and the other Curiosity investigations [2] is to move us steadily toward that goal with an assessment of the habitability of our neighboring planet through a series of chemical and geological measurements. SAM is designed to search for organic compounds and inorganic volatiles and measure isotope ratios. Other instruments on Curiosity will provide elemental analysis and identify minerals. SAM will analyze both atmospheric samples and gases evolved from powdered rocks that may have formed billions of years ago with Curiosity providing access to interesting sites scouted by orbiting cameras and spectrometers.

Mahaffy, P. R.↗