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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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DOE OSTI2020

Extended experimental inferential structure determination method in determining the structural ensembles of disordered protein states

Proteins with intrinsic or unfolded state disorder comprise a new frontier in structural biology, requiring the characterization of diverse and dynamic structural ensembles. Here we introduce a comprehensive Bayesian framework, the Extended Experimental Inferential Structure Determination (X-EISD) method, which calculates the maximum log-likelihood of a disordered protein ensemble. X-EISD accounts for the uncertainties of a range of experimental data and back-calculation models from structures, including NMR chemical shifts, J-couplings, Nuclear Overhauser Effects (NOEs), paramagnetic relaxation enhancements (PREs), residual dipolar couplings (RDCs), hydrodynamic radii (R h ), single molecule fluorescence Förster resonance energy transfer (smFRET) and small angle X-ray scattering (SAXS). We apply X-EISD to the joint optimization against experimental data for the unfolded drkN SH3 domain and find that combining a local data type, such as chemical shifts or J-couplings, paired with long-ranged restraints such as NOEs, PREs or smFRET, yields structural ensembles in good agreement with all other data types if combined with representative IDP conformers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Revealing power, energy and thermal dynamics of a 200PF pre-exascale supercomputer

As we approach the exascale computing era, the focused understanding of power consumption and its overall constraint on HPC architectures and applications are becoming increasingly paramount. Summit, located at the Oak Ridge Leadership Computing Facility (OLCF), is one of the fastest and largest pre-exascale platforms in operation today. This paper provides a first-order examination and analysis of power consumption at the component-level, node-level, and system-level, from all 4,626 Summit compute nodes, each with over 100 metrics at 1Hz frequency over the entire year of 2020. We also investigate the power characteristics and energy efficiency of over 840k Summit jobs and 250k GPU failure logs for further operational insights. To the best of our knowledge, this is the first systematic analysis of power data of HPC system at this scale.

Shin, Woong↗

NASA NTRS1980

Cosmological tests of the Hoyle-Narlikar conformal gravity

For the first time the Hoyle-Narlikar theory with creation of matter and a variable gravitational constant G, is subjected to the following cosmological tests: (1) the magnitude versus z relation, (2) the N(m) versus m relation for quasars, (3) the metric angular diameters versus z relation, (4) the isophotal angles versus z relation, (5) the log N-log S radio source count, and finally (6) the 3 K radiation. It is shown that the theory passes all these tests just as well as the standard cosmology, with the additional advantage that the geometry of the universe is uniquely determined, with a curvature parameter equal to zero. It is also interesting to note that the variability of G affects the log N-log S curve in a way similar to the density evolution introduced in standard cosmologies. The agreement with the data is therefore achieved without recourse to an ad hoc density evolution.

Canuto, V. M.↗

NASA NTRS1982

Helical screw expander evaluation project

A one MW helical rotary screw expander power system for electric power generation from geothermal brine was evaluated. The technology explored in the testing is simple, potentially very efficient, and ideally suited to wellhead installations in moderate to high enthalpy, liquid dominated field. A functional one MW geothermal electric power plant that featured a helical screw expander was produced and then tested with a demonstrated average performance of approximately 45% machine efficiency over a wide range of test conditions in noncondensing, operation on two-phase geothermal fluids. The Project also produced a computer equipped data system, an instrumentation and control van, and a 1000 kW variable load bank, all integrated into a test array designed for operation at a variety of remote test sites. Data are presented for the Utah testing and for the noncondensing phases of the testing in Mexico. Test time logged was 437 hours during the Utah tests and 1101 hours during the Mexico tests.

Mckay, R.↗

NASA NTRS1994

NASA/DOD Aerospace Knowledge Diffusion Research Project. Paper 39: The role of computer networks in aerospace engineering

This paper presents selected results from an empirical investigation into the use of computer networks in aerospace engineering. Such networks allow aerospace engineers to communicate with people and access remote resources through electronic mail, file transfer, and remote log-in. The study drew its subjects from private sector, government and academic organizations in the U.S. aerospace industry. Data presented here were gathered in a mail survey, conducted in Spring 1993, that was distributed to aerospace engineers performing a wide variety of jobs. Results from the mail survey provide a snapshot of the current use of computer networks in the aerospace industry, suggest factors associated with the use of networks, and identify perceived impacts of networks on aerospace engineering work and communication.

Bishop, Ann P.↗

NASA NTRS1997

Land-use in Amazonia and the Cerrado of Brazil: State of Knowledge and GIS Database

We have assembled datasets to strengthen the LargeScale Biosphere Atmosphere Experiment in Amazonia (LBA). These datasets can now be accessed through the Woods Hole Research Center homepage (www.whrc.org), and will soon be linked to the Pre-LBA homepages of the Brazilian Space Research Institute's Center for Weather and Climate Prediction (Instituto de Pesquisas Espaciais, Centro de Previsao de Tempo e Estudos Climaticos, INPE/CPTEC) and through the Oak Ridge National Laboratory, Distributed Active Archive Center (ORNL/DMC). Some of the datasets that we are making available involved new field research and/or the digitization of data available in Brazilian government agencies. For example, during the grant period we conducted interviews at 1,100 sawmills across Amazonia to determine their production of sawn timber, and their harvest intensities. These data provide the basis for the first quantitative assessment of the area of forest affected each year by selective logging (Nepstad et al, submitted to Nature). We digitized the locations of all of the rural households in the State of Para that have been mapped by the Brazilian malaria combat agency (SUCAM). We also mapped and digitized areas of deforestation in the state of Tocantins, which is comprised largely of savanna (cerrado), an ecosystem that has been routinely excluded from deforestation mapping exercises.

Nepstad, Daniel C.↗

NASA NTRS1994

Van Driest transformation and compressible wall-bounded flows

The transformation validity question utilizing resulting data from direct numerical simulations (DNS) of supersonic, isothermal cold wall channel flow was investigated. The DNS results stood for a wide scope of parameter and were suitable for the purpose of examining the generality of Van Driest transformation. The Van Driest law of the wall can be obtained from the inner-layer similarity arguments. It was demonstrated that the Van Driest transformation cannot be incorporated to collapse the sublayer and log-layer velocity profiles simultaneously. Velocity and temperature predictions according to the preceding composite mixing-length model were presented. Despite satisfactory congruity with the DNS data, the model must be perceived as an engineering guide and not as a rigorous analysis.

TRT-THEORETICAL↗

DOE OSTI2025

Mass Spectrometry Sample Submission Portal

Each step in the scientific process generates contextual information about the data that is important to consider when performing data integration, developing models of biological process, or training AI models. We will develop a flexible, template-driven tool that will log biological samples, capture metadata about those samples, and track the type(s) of analysis being performed by researchers providing samples for analysis by mass spectrometry.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1994

Stochastic decision analysis

Small space flight project design at NASA Langley Research Center goes through a multi-phase process from preliminary analysis to flight operations. The process insures that each system achieves its technical objectives with demonstrated quality and within planned budgets and schedules. A key technical component of early phases is decision analysis, which is a structure procedure for determining the best of a number of feasible concepts based upon project objectives. Feasible system concepts are generated by the designers and analyzed for schedule, cost, risk, and technical measures. Each performance measure value is normalized between the best and worst values and a weighted average score of all measures is calculated for each concept. The concept(s) with the highest scores are retained, while others are eliminated from further analysis. This project automated and enhanced the decision analysis process. Automation of the decision analysis process was done by creating a user-friendly, menu-driven, spreadsheet macro based decision analysis software program. The program contains data entry dialog boxes, automated data and output report generation, and automated output chart generation. The enhancements to the decision analysis process permit stochastic data entry and analysis. Rather than enter single measure values, the designers enter the range and most likely value for each measure and concept. The data can be entered at the system or subsystem level. System level data can be calculated as either sum, maximum, or product functions of the subsystem data. For each concept, the probability distributions are approximated for each measure and the total score for each concept as either constant, triangular, normal, or log-normal distributions. Based on these distributions, formulas are derived for the probability that the concept meets any given constraint, the probability that the concept meets all constraints, and the probability that the concept is within a given amount of the best score. Formulas are also derived for the probability that one concept's total score is within a given amount of a second concept's total score. These probabilistic calculations provide more realistic data entry and output information for designers, enabling designers to better determine which concepts to eliminate and which concepts to retain at the decision points of each design phase.

Lacksonen, Thomas A.↗

DOE OSTI2024

LYNM PE1 Pre-Experiment A Site Characterization Report

Underground chemical explosive experiments such as LYNM PE1 generate large multiphenomenological datasets, require complex site preparation and build out, and utilize cutting edge models and analysis techniques to analyze and simulate the explosion-induced signals. This wide range of outcomes makes it a necessity to thoroughly characterize the testbed in advance of experiments in a way that complements the wide suite of data being generated. Here, we present a broad overview of the site characterization work and data collection that was conducted before Experiment A, which is the first in a series of three PE1 experiments. This work includes, but is not limited to, geologic mapping, physical sample collection, analysis of material properties, geophysical borehole logging, and in-situ measurements. This information was collected by a large, dedicated team and was used to inform site construction, finalize instrumentation placement, generate Geologic Framework Models, feed pre-experiment predictions, and facilitate post-experiment data analysis

58 GEOSCIENCES↗

DOE OSTI2024

LYNM PE1 Pre-Experiment A Site Characterization Report

Underground chemical explosive experiments such as LYNM PE1 generate large multi-phenomenological datasets, require complex site preparation and build out, and utilize cutting edge models and analysis techniques to analyze and simulate the explosion-induced signals. This wide range of outcomes makes it a necessity to thoroughly characterize the testbed in advance of experiments in a way that complements the wide suite of data being generated. Here, we present a broad overview of the site characterization work and data collection that was conducted before Experiment A, which is the first in a series of three PE1 experiments. This work includes, but is not limited to, geologic mapping, physical sample collection, analysis of material properties, geophysical borehole logging, and in-situ measurements. This information was collected by a large, dedicated team and was used to inform site construction, finalize instrumentation placement, generate Geologic Framework Models, feed pre-experiment predictions, and facilitate post-experiment data analysis.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2025

Nearby stellar substructures in the Galactic halo from DESI Milky Way Survey Year 1 Data Release

We report five nearby ($d_{\mathrm{helio}} < 5$ kpc) stellar substructures in the Galactic halo from a subset of 138 661 stars in the Dark Energy Spectroscopic Instrument (DESI) Milky Way Survey Year 1 Data Release. With an unsupervised clustering algorithm, HDBSCAN*, these substructures are independently identified in Integrals of Motion ($E_{\rm tot}$, $L_{\rm z}$, $\log {J_r}$, $\log {J_z}$) space and Galactocentric cylindrical velocity space ($V_{R}$, $V_{\phi }$, $V_{z}$). We associate all identified clusters with known nearby substructures (Helmi streams, M18-Cand10/MMH-1, Sequoia, Antaeus, and ED-2) previously reported in various studies. With metallicities precisely measured by DESI, we confirm that the Helmi streams, M18-Cand10, and ED-2 are chemically distinct from local halo stars. We have characterized the chemodynamic properties of each dynamic group, including their metallicity dispersions, to associate them with their progenitor types (globular cluster or dwarf galaxy). Our approach for searching substructures with HDBSCAN* reliably detects real substructures in the Galactic halo, suggesting that applying the same method can lead to the discovery of new substructures in future DESI data. With more stars from future DESI data releases and improved astrometry from the upcoming Gaia Data Release 4, we will have a more detailed blueprint of the Galactic halo, offering a significant improvement in our understanding of the formation and evolutionary history of the Milky Way Galaxy.

dynamics↗

DOE OSTI2022

A Catalog of Quasar Properties from Sloan Digital Sky Survey Data Release 16

We present a catalog of continuum and emission-line properties for 750,414 broad-line quasars included in the Sloan Digital Sky Survey Data Release 16 quasar catalog (DR16Q), measured from optical spectroscopy. These quasars cover broad ranges in redshift (0.1 ≲ z ≲ 6) and luminosity (44 ≲ log(L bol /erg s -1 ) ≲ 48), and probe lower luminosities than an earlier compilation of SDSS DR7 quasars. Derived physical quantities such as single-epoch virial black hole masses and bolometric luminosities are also included in this catalog. We present improved systemic redshifts and realistic redshift uncertainties for DR16Q quasars using the measured line peaks and correcting for velocity shifts of various lines with respect to the systemic velocity. About 1%, 1.4%, and 11% of the original DR16Q redshifts deviate from the systemic redshifts by |ΔV| > 1500 km s -1 , |ΔV| $\in$ [1000, 1500] km s -1 , and |ΔV| $\in$ [500, 1000] km s -1 , respectively; about 1900 DR16Q redshifts were catastrophically wrong (|ΔV| > 10,000 km s -1 ). We demonstrate the utility of this data product in quantifying the spectral diversity and correlations among physical properties of quasars with large statistical samples.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Learning-Based Real-Time Event Identification Using Rich Real PMU Data

A large-scale deployment of phasor measurement units (PMUs) that reveal the inherent physical laws of power systems from a data perspective enables an enhanced awareness of power system operation. However, the high-granularity and non-stationary nature of PMU data and imperfect data quality could bring great technical challenges for real-time system event identification. To address these challenges, this paper proposes a two-stage learning-based framework. In the first stage, a Markov transition field (MTF) algorithm is exploited to extract the latent data features by encoding temporal dependency and transition statistics of PMU data in graphs. Then, a spatial pyramid pooling (SPP)-aided convolutional neural network (CNN) is established to efficiently and accurately identify power events. The proposed method fully builds on and is also tested on a large real-world dataset from several tens of PMU sources (and the corresponding event logs), located across the U.S., with a time span of two consecutive years. We report the numerical results validate that our method has high identification accuracy while showing good robustness against poor data quality.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Big Sky Regional Carbon Sequestration Partnership (Phase III Final Scientific/Technical Report)

The Big Sky Carbon Sequestration Partnership (BSCSP) pursued a Phase III demonstration project at Kevin Dome in north central Montana. Kevin Dome covers approximately 700 square miles and is a naturally occurring CO 2 reservoir that is flanked by oil and gas fields. The carbon dioxide (CO 2 ) is in the upper Devonian Duperow (carbonate) formation and does not reach the spill point of the dome; therefore, the dome has potential as a CO 2 sequestration reservoir, a CO 2 supply, or as both if anthropogenic sources and enhanced oil recovery (EOR) operations are associated with the dome. Kevin Dome could potentially act as a buffer to continue accepting anthropogenic CO 2 when EOR flooding operations are interrupted or completed. The project objective was to produce one million tonnes of CO 2 from the gas cap of Kevin Dome, pipe it laterally, inject, and re-store it in the brine leg of the same formation to test the hub / buffer storage concept. This was to be accomplished by drilling up to five production wells, building a short pipeline and compression facilities, and drilling an injection well and several monitoring wells. BSCSP commenced outreach and site characterization activities including acquiring baseline data for near-surface insurance monitoring, acquiring 3-dimensional, 9-component surface seismic over the project area, drilling two test wells (one in the production area and one in the injection area), coring key intervals, and performing comprehensive logging. Well tests of those wells revealed two barriers to the project. The production (Danielson 33-17) well was perforated in multiple zones but failed to produce any significant CO 2 . This was despite being drilled in the near vicinity of a historic well that had produced 3700 MCF per day in a drill stem test. Modeling indicated that this was likely due to a phase change during production causing a temperature drop resulting in hydrate and/or water ice formation that clogged the formation. Tests of the injection zone (Wallewein 22-1) well indicated total dissolved solids (TDS) slightly below the EPA required 10,000 parts per million (ppm) for a Class VI underground injection control permit. While the project was initiated before Class VI rules were promulgated, and this was an experimental project (seemingly qualified for a Class V permit), the Environmental Protection Agency (EPA) indicated that injection would require a Class VI permit. The low salinity result was unexpected as contours plotted based on regional formation water quality data indicated an expected TDS above 20,000 ppm, and wells between the recharge zone and the Wallewein well tested above 10,000 ppm. Faced with the inability to obtain an injection permit, the demonstration project could not proceed. However, the project had generated valuable samples and data on a large natural analog including 32 sq. mi. of 3-D, 9-C seismic, 430 ft. of carbonate core covering seven different depositional environments taken from areas with, and without the presence of CO 2 , 30 ft. of core of two caprocks, a tight carbonate and an anhydrite, a full set of modern logs on both wells, and well tests. DOE decided to re-scope the project around completing studies utilizing this data. This report covers both the initial scope and the re-scope (Task / Section numbers preceded with an R). While the report covers a wide range of project activities, highlights of this work include: Development of a geostatic model using neural nets to match well logs to facies and using multi-waveform seismic to inform reservoir heterogeneity; Unique mechanical testing of permeability – stress relationship in two caprock materials; Development of full waveform inversion to generate a high resolution velocity model; Model development for dual permeability (fracture and matrix) systems to better account for matrix-matrix interactions; Joint seismic wave inversion (including the first quadr-joint inversion) exhibiting better imaging of a challenging reservoir zone in stiff rock; Core flow and core flood results on a reactive carbonate; and Innovative laboratory measurements of seismic response of fractured core as a function of fluid fill.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Seismic Monitoring at the Farnsworth CO2-EOR Field Using Time-Lapse Elastic-Waveform Inversion of 3D-3C VSP Data

During the Development Phase of the U.S. Southwest Regional Partnership on Carbon Sequestration, supercritical CO2 was continuously injected into the deep oil-bearing Morrow B formation of the Farnsworth Unit in Texas for Enhanced Oil Recovery (EOR). The project injected approximately 94 kilotons of CO2 to study geologic carbon storage during CO2-EOR. A three-dimensional (3D) surface seismic dataset was acquired in 2013 to characterize the subsurface structures of the Farnsworth site. Following this data acquisition, the baseline and three time-lapse three-dimensional three-component (3D-3C) vertical seismic profiling (VSP) data were acquired at a narrower surface area surrounding the CO2 injection and oil/gas production wells between 2014 and 2017 for monitoring CO2 injection and migration. With these VSP datasets, we inverted for subsurface velocity models to quantitatively monitor the CO2 plume within the Morrow B formation. We first built 1D initial P-wave (Vp) and S-wave (Vs) velocity models by upscaling the sonic logs. We improved the deep region of the Vp and Vs models by incorporating the deep part of a migration velocity model derived from the 3D surface seismic data. We improved the shallow region of 3D Vp and Vs models using 3D traveltime tomography of first arrivals of VSP downgoing waves. We further improved the 3D baseline velocity models using elastic-waveform inversion (EWI) of the 3D baseline VSP upgoing data. Our advanced EWI method employs alternative tomographic and conventional gradients and total-variation-based regularization to ensure the high-fidelity updates of the 3D baseline Vp and Vs models. We then sequentially applied our 3D EWI method to the three time-lapse datasets to invert for spatiotemporal changes of Vp and Vs in the reservoir. Our inversion results reveal the volumetric changes of the time-lapse Vp and Vs models and show the evolution of the CO2 plume from the CO2 injection well to the oil/gas production wells.

42 ENGINEERING↗

DOE OSTI2026

2002 Champaign-Urbana Urbanized Area Transportation Study

This travel survey, conducted by Champaign County Regional Planning Commission, collected daily weekday travel data from 395 urbanized-area households—accounting for every individual 12 years old or older—in the Champaign-Urbana-Savoy region. The information gathered from the survey was used to forecast future transportation demand and update the Champaign Urbana Urbanized Area Transportation Study Long Range Transportation Plan 2035. Of the 395 households recruited for the study, 362 completed their travel logs. The household travel survey was completed during the summer and fall of 2002, and it was the first large-scale attempt at collecting single-weekday travel data in Champaign, Urbana, and Savoy.

1Hz data↗

DOE OSTI2023

Effects of forest degradation classification on the uncertainty of aboveground carbon estimates in the Amazon

Tropical forests are critical for the global carbon budget, yet they have been threatened by deforestation and forest degradation by fire, selective logging, and fragmentation. Existing uncertainties on land cover classification and in biomass estimates hinder accurate attribution of carbon emissions to specific forest classes. In this study, we used textural metrics derived from PlanetScope images to implement a probabilistic classification framework to identify intact, logged and burned forests in three Amazonian sites. We also estimated biomass for these forest classes using airborne lidar and compared biomass uncertainties using the lidar-derived estimates only to biomass uncertainties considering the forest degradation classification as well. Our classification approach reached overall accuracy of 0.86, with accuracy at individual sites varying from 0.69 to 0.93. Logged forests showed variable biomass changes, while burned forests showed an average carbon loss of 35%. We found that including uncertainty in forest degradation classification significantly increased uncertainty and decreased estimates of mean carbon density in two of the three test sites. Our findings indicate that the attribution of biomass changes to forest degradation classes needs to account for the uncertainty in forest degradation classification. By combining very high-resolution images with lidar data, we could attribute carbon stock changes to specific pathways of forest degradation. This approach also allows quantifying uncertainties of carbon emissions associated with forest degradation through logging and fire. Both the attribution and uncertainty quantification provide critical information for national greenhouse gas inventories.

54 ENVIRONMENTAL SCIENCES↗