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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 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Study of Graphite Ablation at Arc-Jet Conditions using Finite-Rate and Equilibrium Chemistry Models

Moving at hypersonic speeds through the atmosphere generates immense amount of heat that triggers thermo-chemical non-equilibrium effects in the flow approaching the vehicle and leads to surface chemical reactions that cause ablation and consume the material mass. This complex behavior and interaction of the aerothermal environment with a graphite surface is com- putationally modeled in the present work using a fully-coupled simulation between flow solver CHAMPS NBS-Cart and material response solver KATS-MR. In this study, we account for the thermo-chemical non-equilibrium effects occurring in the flow and use an 11-species air-carbon re- action model to simulate the ablation of the material. The reactions at the surface such oxidation, nitridation and recombination are modeled with a newly developed air-carbon reaction model. The coupled simulation is applied to study two experimental cases performed at IHF arc-jet facility at NASA Ames research center. The obtained results are compared against the measured data of surface recession, as well as surface and in-depth temperatures. Additionally, uncoupled sim- ulations, performed with equilibrium chemistry at the wall, point out the substantial differences between the coupled and uncoupled solutions, leading to higher deviation of the predicted temper- atures. Overall, we show excellent agreement between the coupled simulation predictions and the experimental data in all measured quantities.

EDL↗
NASA NTRS1984

Edge crack growth of thermally aged graphite/polyimide composites

Laminates of Celion 6000/LARC-160 and Celion 6000/PMR-15 graphite/polyimide composite materials were aged in air at temperatures of 202, 232, 260 and 288 C for various times up to 15,000 hours. Three unidirectional specimen types were studied: short beam shear (SBS), flexure, and 153 mm square panels. The interior region of the square panels exhibited little or no property degradation, whereas both laminate materials degraded and cracked preferentially at the specimen edge perpendicular to the fibers. Using a dye penetrant, the specimens were X-rayed and the crack depth measured as a function of time and temperature. A time temperature superposition of the crack data was successfully performed using an Arrhenius form for the shift factor. A direct correlation was found for edge crack depth and SBS strength for the LARC-160 laminates but the correlation for PMR-15 laminates was more complex.

Nelson, J. B.↗
NASA NTRS2003

Water Impact Test and Simulation of a Composite Energy Absorbing Fuselage Section

In March 2002, a 25-ft/s vertical drop test of a composite fuselage section was conducted onto water. The purpose of the test was to obtain experimental data characterizing the structural response of the fuselage section during water impact for comparison with two previous drop tests that were performed onto a rigid surface and soft soil. For the drop test, the fuselage section was configured with ten 100-lb. lead masses, five per side, that were attached to seat rails mounted to the floor. The fuselage section was raised to a height of 10-ft. and dropped vertically into a 15-ft. diameter pool filled to a depth of 3.5-ft. with water. Approximately 70 channels of data were collected during the drop test at a 10-kHz sampling rate. The test data were used to validate crash simulations of the water impact that were developed using the nonlinear, explicit transient dynamic codes, MSC.Dytran and LS-DYNA. The fuselage structure was modeled using shell and solid elements with a Lagrangian mesh, and the water was modeled with both Eulerian and Lagrangian techniques. The fluid-structure interactions were executed using the fast general coupling in MSC.Dytran and the Arbitrary Lagrange-Euler (ALE) coupling in LS-DYNA. Additionally, the smooth particle hydrodynamics (SPH) meshless Lagrangian technique was used in LS-DYNA to represent the fluid. The simulation results were correlated with the test data to validate the modeling approach. Additional simulation studies were performed to determine how changes in mesh density, mesh uniformity, fluid viscosity, and failure strain influence the test-analysis correlation.

Fasanella, Edwin L.↗
NASA NTRS2006

Novel Hyperspectral Sun Photometer for Satellite Remote Sensing Data Radiometeic Calibration and Atmospheric Aerosol Studies

A simple and cost-effective, hyperspectral sun photometer for radiometric vicarious remote sensing system calibration, air quality monitoring, and potentially in-situ planetary climatological studies, was developed. The device was constructed solely from off the shelf components and was designed to be easily deployable for support of short-term verification and validation data collects. This sun photometer not only provides the same data products as existing multi-band sun photometers but also the potential of hyperspectral optical depth and diffuse-to-global products. As compared to traditional sun photometers, this device requires a simpler setup, less data acquisition time and allows for a more direct calibration approach. Fielding this instrument has also enabled Stennis Space Center (SSC) Applied Sciences Directorate personnel to cross-calibrate existing sun photometers. This innovative research will position SSC personnel to perform air quality assessments in support of the NASA Applied Sciences Program's National Applications program element as well as to develop techniques to evaluate aerosols in a Martian or other planetary atmosphere.

Pagnutti, Mary↗
NASA NTRS2017

Ground-Based Observing Campaign of Briz-M Debris

In 2015, NASA's Orbital Debris Program Office (ODPO) completed the installation of the Meter Class Autonomous Telescope (MCAT) on Ascension Island. MCAT is a 1.3m optical telescope designed with a fast tracking capability for observing orbital debris at all orbital regimes (Low-Erath orbits to Geosyncronous (GEO) orbits) from a low latitude site. This new asset is dedicated year-round for debris observations, and its location fills a geographical gap in the Ground-based Electro Optical Space Surveillance (GEODSS) network. A commercial off the shelf (COTS) research grade 0.4m telescope (named the Benbrook telescope) will also be installed on Ascension at the end of 2016. This smaller version is controlled by the same master software, designed by Euclid Research, and can be tasked to work independently or in concert with MCAT. Like MCAT, it has a the same suite of filters, a similar field of view, and a fast-tracking Astelco mount, and is also capable of tracking debris at all orbital regimes. These assets are well suited for targeted campagins or surveys of debris. Since 2013, NASA's ODPO has also had extensive access to the 3.8m infrared UKIRT telescope, located on Mauna Kea. At nearly 14,000-ft, this site affords excellent conditions for collecting both photometery and spectroscopy at near-IR (0.9 - 2.5 micrometers SWIR) and thermal-IR (8 - 25 micrometers; LWIR) regimes, ideal for investigating material properties as well as thermal characteristics and sizes of debris. For the purposes of understanding orbital debris, taking data in both survey mode as well as targeting individual objects for more in-depth characterizations are desired. With the recent break-ups of Briz-M rocket bodies, we have collected a suite of data in the optical, near-infrared, and mid-infrared of in-tact objects as well as those classified as debris. A break-up at GEO of a Briz-M rocket occurred in January, 2016, well timed for the first remote observing survey-campaign with MCAT. Access to the 3.8m UKIRT telescope has also allowed for investigating this break-up in the near-infrared at wavelengths where debris is often much more reflective, allowing for the potential detection of a smaller population of these debris. In addition, a suite of near-IR reflectance spectroscopy (0.8-2.5 micrometers) and thermal-IR (8-15 micrometers) of individual in-tact and debris Briz-M objects has been collected. Analysis of the survey data will be discussed.

Lederer, S. M.↗
NASA NTRS1977

Apparent depth/apparent diameter relation for lunar craters

Photogrammetric measurements from Apollo metric-quality pictures ensure high accuracy of apparent depth (R sub a) and apparent diameter (D sub a) data for fresh lunar craters. R sub a is a direct function of D sub a and the R sub a/D sub a distribution inflects sharply at an apparent diameter of about 15 km. Each of the two resulting subgroups of craters requires two separate least-squares fits. For simple lunar craters (less than 15 km across), the ratio of R sub a to D sub a is about 0.2; the ratio for complex (larger) craters ranges from 0.1 to 0.01. Apparent depth does not exceed 3400 m, regardless of crater size, possibly as a result of isostasy, substrate layering, or curvature of the moon. R sub a/D sub a differences for mare versus terra craters are either absent or are equivocal. The ratio of apparent diameter to rim-crest diameter (D sub a/D sub r) averages 0.83 for smaller craters and 0.86 for larger craters, indicating another simple-to-complex contrast in crater morphology on the moon, and confirms a prediction by R. B. Baldwin for simple craters. Close similarity of D sub a/D sub r for terrestrial experimental craters and simple lunar craters is especially consistent with impact origin for the moon's craters.

Pike, R. J.↗
DOE OSTI2023

Continental Scale Hydrostratigraphy: Basin‐Scale Testing of Alternative Data‐Driven Approaches

Abstract Integrated hydrological modeling is an effective method for understanding interactions between parts of the hydrologic cycle, quantifying water resources, and furthering knowledge of hydrologic processes. However, these models are dependent on robust and accurate datasets that physically represent spatial characteristics as model inputs. This study evaluates multiple data‐driven approaches for estimating hydraulic conductivity and subsurface properties at the continental‐scale, constructed from existing subsurface dataset components. Each subsurface configuration represents upper (unconfined) hydrogeology, lower (confined) hydrogeology, and the presence of a vertical flow barrier. Configurations are tested in two large‐scale U.S. watersheds using an integrated model. Model results are compared to observed streamflow and steady state water table depth (WTD). We provide model results for a range of configurations and show that both WTD and surface water partitioning are important indicators of performance. We also show that geology data source, total subsurface depth, anisotropy, and inclusion of a vertical flow barrier are the most important considerations for subsurface configurations. While a range of configurations proved viable, we provide a recommended Selected National Configuration 1 km resolution subsurface dataset for use in distributed large‐and continental‐scale hydrologic modeling.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2021

Thermal Conductivity Estimation from Transient Test Data with Embedded Thermocouples using Genetic Algorithm Optimization

Inverse heat transfer methodology previously developed to estimate thermal properties of high temperature fibrous insulation from embedded thermocouples was applied to the thermoplastic polymer, polyether-ether-ketone (PEEK). A small experimental setup was utilized to test the PEEK sample between temperatures of 300 K and 525 K at atmospheric pressure. Cylindrical plugs of PEEK with three thermocouples embedded at various depths were incorporated in the test sample. The experimental PEEK thermocouple data were used as the boundary and initial conditions of a one-dimensional numerical thermal model to predict the internal temperatures of the material. The thermal conductivity of PEEK was estimated with the Continuous Genetic Algorithm optimization technique by searching for the coefficients of a functional form of thermal conductivity that minimized the difference between the experimentally measured and model predicted internal temperature values. The thermal testing, one-dimensional numerical thermal model, optimization algorithm, analysis, and results are presented.

Thermal Properties↗
DOE OSTI2017

Redox stratification of an ancient lake in Gale crater, Mars

In 2012, NASA’s Curiosity rover landed on Mars to assess its potential as a habitat for past life and investigate the paleoclimate record preserved by sedimentary rocks inside the ~150-kilometer-diameter Gale impact crater. Geological reconstructions from Curiosity rover data have revealed an ancient, habitable lake environment fed by rivers draining into the crater. We synthesize geochemical and mineralogical data from lake-bed mudstones collected during the first 1300 martian solar days of rover operations in Gale. We present evidence for lake redox stratification, established by depth-dependent variations in atmospheric oxidant and dissolved-solute concentrations. Paleoclimate proxy data indicate that a transition from colder to warmer climate conditions is preserved in the stratigraphy. Lastly, a late phase of geochemical modification by saline fluids is recognized.

58 GEOSCIENCES↗
DOE OSTI2020

Hawaii Play Fairway Analysis: Lanai Resistivity and Density 3D Inversion Models

To prepare for its third phase, the Hawaii Play Fairway project conducted groundwater sampling and analyses in ten locations in the Hawaiian islands, magnetotelluric (MT) and gravity surveys, as well as calculations of 3D subsurface stress due to the weight of the rock underlying the topography of the volcano. The subsurface stresses were used to evaluate the potential for fracture-induced permeability. Inversions of the MT and gravity data produce 3D models of resistivity and density, respectively, on Lanai, across Haleakala's SW rift (Maui), and surrounding Mauna Kea (Hawaii Island). The project developed and applied a new method for incorporating depth information about resistivity, density, and potential for fracture-induced permeability into the statistical method for computing resource probability in these three focus areas. The project then incorporated the new groundwater results with the new geophysical results and the calculations of potential for fracture-induced permeability to produce updated maps of resource probability and confidence. These results were used to identify target sites for exploratory drilling. Spreadsheet information: Each sheet contains data for a particular depth in kilometers. Positive depths are above sea level, and negative below. For more information, go to the Hawaii Groundwater and Geothermal Resources Center website linked in the resources.

15 GEOTHERMAL ENERGY↗
DOE OSTI2017

What does fault tolerant Deep Learning need from MPI?

Deep Learning (DL) algorithms have become the {\em de facto} Machine Learning (ML) algorithm for large scale data analysis. DL algorithms are computationally expensive -- even distributed DL implementations which use MPI require days of training (model learning) time on commonly studied datasets. Long running DL applications become susceptible to faults -- requiring development of a fault tolerant system infrastructure, in addition to fault tolerant DL algorithms. This raises an important question: {\em What is needed from MPI for designing fault tolerant DL implementations?} In this paper, we address this problem for permanent faults. We motivate the need for a fault tolerant MPI specification by an in-depth consideration of recent innovations in DL algorithms and their properties, which drive the need for specific fault tolerance features. We present an in-depth discussion on the suitability of different parallelism types (model, data and hybrid); a need (or lack thereof) for check-pointing of any critical data structures; and most importantly, consideration for several fault tolerance proposals (user-level fault mitigation (ULFM), Reinit) in MPI and their applicability to fault tolerant DL implementations. We leverage a distributed memory implementation of Caffe, currently available under the Machine Learning Toolkit for Extreme Scale (MaTEx). We implement our approaches by extending MaTEx-Caffe for using ULFM-based implementation. Our evaluation using the ImageNet dataset and AlexNet neural network topology demonstrates the effectiveness of the proposed fault tolerant DL implementation using OpenMPI based ULFM.

Amatya, Vinay C.↗
DOE OSTI2023

A comparative analysis of green building rating systems in China and the United States

Several studies have compared green building rating systems (GBRSs) in China and the United States, Nonetheless, few studies included in-depth analysis on specific rating tools with project specific data validating green building technologies and actual performance. This study conducted a comprehensive data-driven comparison of the GBRSs of China and the United States. The goal was to understand the current status and further improve China's GBRS and promote green building technologies. The study first conducted thorough comparisons of GBRSs in China and the U.S. by selecting a series of distinct rating tools. Then, it analyzed each tool's development objectives, contents, and rating score settings. Further, the comparison concludes the future development needs for China's GBRS. In addition to standard comparison, green building technologies applied in certified projects were also summarized. The results demonstrated that GBRSs in both China and the U.S. reflect well the technical paths to achieve green building sustainable development. By analyzing certified projects, it was also found that the incremental costs of green building technologies were controllable. Finally, based on the comparison and case analysis, the study provide a set of policy recommendations to further improve China's green building standards.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

(Un)Explained EMIC Waves: Understanding Quiet Time EMIC Wave Drivers

Electromagnetic ion cyclotron (EMIC) waves are known to be generated through cyclotron resonance with the local ion particle population and grow when there is a large enough temperature anisotropy. In general, these temperature anisotropies necessary for wave growth are found to be associated with either solar wind pressure pulses or particle injections during geomagnetic storms or substorms. However, some EMIC events do not show any clear association with these known drivers and appear unexplained. In our analysis of high-amplitude (>1 nT) non-storm time EMIC waves, we find that 24 out of the 223 (~11%) EMIC events with peak amplitude greater than 1 nT were not found to be associated with any clear EMIC wave driver. This raises a compelling question: What magnetospheric or solar wind driver provides the free energy to grow these quiet-time EMIC waves? Here, we examine two EMIC events on 13 April 2017 and 13 February 2014, which were excited during extremely quiet solar wind and geomagnetic conditions. Furthermore, an in-depth analysis of field and particle measurements from multiple data sets, including ground and in situ data for these two events, indicates that extremely weak and otherwise insignificant pressure values and/or very weak substorm injections occurring multiple hours before the event play a significant role in quiet time wave generation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Multimodal X-ray nano-spectromicroscopy analysis of chemically heterogeneous systems

Abstract Understanding the nanoscale chemical speciation of heterogeneous systems in their native environment is critical for several disciplines such as life and environmental sciences, biogeochemistry, and materials science. Synchrotron-based X-ray spectromicroscopy tools are widely used to understand the chemistry and morphology of complex material systems owing to their high penetration depth and sensitivity. The multidimensional (4D+) structure of spectromicroscopy data poses visualization and data-reduction challenges. This paper reports the strategies for the visualization and analysis of spectromicroscopy data. We created a new graphical user interface and data analysis platform named XMIDAS (X-ray multimodal image data analysis software) to visualize spectromicroscopy data from both image and spectrum representations. The interactive data analysis toolkit combined conventional analysis methods with well-established machine learning classification algorithms (e.g. nonnegative matrix factorization) for data reduction. The data visualization and analysis methodologies were then defined and optimized using a model particle aggregate with known chemical composition. Nanoprobe-based X-ray fluorescence (nano-XRF) and X-ray absorption near edge structure (nano-XANES) spectromicroscopy techniques were used to probe elemental and chemical state information of the aggregate sample. We illustrated the complete chemical speciation methodology of the model particle by using XMIDAS. Next, we demonstrated the application of this approach in detecting and characterizing nanoparticles associated with alveolar macrophages. Our multimodal approach combining nano-XRF, nano-XANES, and differential phase-contrast imaging efficiently visualizes the chemistry of localized nanostructure with the morphology. We believe that the optimized data-reduction strategies and tool development will facilitate the analysis of complex biological and environmental samples using X-ray spectromicroscopy techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Ultrafast nuclear dynamics in double-core-ionized water molecules

Double-core-hole (DCH) states in isolated-water and heavy-water molecules, resulting from the sequential absorption of two x-ray photons, have been investigated. Here, a comparison of the subsequent Auger emission spectra from the two isotopes provides direct evidence of ultrafast nuclear motion during the 1.5-fs lifetime of these DCH states. Our numerical results align well with the experimental data, providing for various DCH states an in-depth study of the dynamics responsible of the observed isotope effect.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2018

X-Ray Photoelectron Spectroscopy of Stabilized Zirconia Films with Embedded Au Nanoparticles Formed under Irradiation with Gold Ions

Nanosized films of stabilized zirconia with Au nanoparticles formed by implanting Au ions are studied by X-ray photoelectron spectroscopy and transmission electron microscopy. The effect of irradiation of films with Au ions and postimplantation annealing on the distribution of chemical elements and zirconium- containing ZrO{sub x} compounds over the depth of the films is studied. Based on the data on the dimensional shift of the Au 4 f photoelectron line, the average value of the nanoparticle size is determined.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Lithium-Ion Battery Life Model with Electrode Cracking and Early-Life Break-in Processes

This paper develops a physically justified reduced-order capacity fade model from accelerated calendar- and cycle-aging data for 32 lithium-ion (Li-ion) graphite/nickel-manganese-cobalt (NMC) cells. The large data set reveals temperature-, charge C-rate-, depth-of-discharge-, and state of charge (SOC)-dependent degradation patterns that would be unobserved in a smaller test matrix. Model structure is informed by incremental capacity analysis that shows loss of lithium inventory and cathode-material loss as the dominant capacity fade mechanisms. The model includes terms attributable to solid-electrolyte interface (SEI) growth, electrode cracking, cycling-driven acceleration of SEI growth, and "break-in" mechanisms that slightly decrease or increase available Li inventory early in life. The study explores what mathematical couplings of these mechanisms best describe calendar aging, cycle aging, and mixed calendar/cycle aging. Various approaches are discussed for extracting relevant stress factors from complex cycling profiles to predict lifetime during real-world battery loads using models trained on constant-current laboratory test results. The complexity of the present human-driven model identification process motivates future work in machine learning to more widely search and statistically discern the optimal model that correctly extrapolates capacity fade based on physical knowledge.

25 ENERGY STORAGE↗
DOE OSTI2020

IOMiner v0.3

Modern HPC systems are collecting large amounts of I/O performance data. The massive volume and heterogeneity of this data, however, have made timely performance of in-depth integrated analysis difficult. To overcome this difficulty and to allow users to identify the root causes of poor application I/O performance, we developed IOMiner, an I/O log analytics framework.

Byna, Suren↗