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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 1,603 records · Page 89

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NASA NTRS2001

The Oxidation Kinetics of Continuous Carbon Fibers in a Cracked Ceramic Matrix Composite

Experimental observations and results suggest two primary regimes as a function of temperature, i.e., diffusion and reaction controlled kinetics. Thermogravimetric analysis of carbon fiber in flowing oxygen gave an activation energy of 64.1 kJ/mol in the temperature range of 500 to 600 C and an apparent activation energy of 7.6 kJ/mol for temperatures from 600 to 1400 C. When C/SiC composite material was unstressed, matrix effects at temperatures from 900 to 1400 C protected the internal fibers. When under stress, self-protection was not observed. Increasing the stress from 10 to 25 ksi caused a 67 to 82 percent reduction in times to failure at temperatures from 750 to 1500 C. Based on experimental results, observation, and theory, a finite difference model was developed, which simulates the diffusion of oxygen into a matrix crack that is bridged by carbon fibers. The model allows the influence of important variables on oxidation kinetics to be studied systematically, i.e., temperature, reaction rate constant, diffusion coefficient, environment, and sample geometry.

Halbig, Michael C.↗

NASA NTRS1991

Acridine orange staining reaction as an index of physiological activity in Escherichia coli

The assumption that the acridine orange (AO) color reaction may be used as an index of physiological activity was investigated in laboratory grown Escherichia coli. Spectrofluorometric observations of purified nucleic acids, ribosomes and the microscopic color of bacteriophage-infected cells stained with AO confirmed the theory that single-stranded nucleic acids emit orange to red fluorescence while those that are double-stranded fluoresce green in vivo. Bacteria growing actively in a rich medium could be distinguished from cells in stationary phase by the AO reaction. Cells from log phase appeared red, whereas those in stationary phase were green. However, this differentiation was not seen when the bacteria were grown in a minimal medium or when a variation of the staining method was used. Also, shifting bacteria in stationary phase to starvation conditions rapidly changed their AO staining reaction. Boiling and exposure to lethal concentrations of azide and formalin resulted in stationary-phase cells that appeared red after staining but bacteria killed with chlorine remained green. These findings indicate that the AO staining reaction may be suggestive of physiological activity under defined conditions. However, variables in staining and fixation procedures as well as uncertainties associated with mixed bacterial populations in environmental samples may produce results that are not consistent with the classical interpretation of this reaction. The importance of validating the putative physiological implications of this staining reaction is stressed.

NASA Discipline Number 04-10↗

NASA NTRS2001

NASA/American Cancer Society High-Resolution Flow Cytometry Project-I

BACKGROUND: The NASA/American Cancer Society (ACS) flow cytometer can simultaneously analyze the electronic nuclear volume (ENV) and DNA content of cells. This study describes the schematics, resolution, reproducibility, and sensitivity of biological standards analyzed on this unit. METHODS: Calibrated beads and biological standards (lymphocytes, trout erythrocytes [TRBC], calf thymocytes, and tumor cells) were analyzed for ENV versus DNA content. Parallel data (forward scatter versus DNA) from a conventional flow cytometer were obtained. RESULTS: ENV linearity studies yielded an R value of 0.999. TRBC had a coefficient of variation (CV) of 1.18 +/- 0.13. DNA indexes as low as 1.02 were detectable. DNA content of lymphocytes from 42 females was 1.9% greater than that for 60 males, with a noninstrumental variability in total DNA content of 0.5%. The ENV/DNA ratio was constant in 15 normal human tissue samples, but differed in the four animal species tested. The ENV/DNA ratio for a hypodiploid breast carcinoma was 2.3 times greater than that for normal breast tissue. CONCLUSIONS: The high-resolution ENV versus DNA analyses are highly reliable, sensitive, and can be used for the detection of near-diploid tumor cells that are difficult to identify with conventional cytometers. ENV/DNA ratio may be a useful parameter for detection of aneuploid populations.

NASA Center JSC↗

NASA NTRS2016

Streamlining the Design Tradespace for Earth Imaging Constellations

Science Data Processing↗

NASA NTRS2017

Navigating the Deployment and Downlink Tradespace for Earth Imaging Constellations

Distributed Spacecraft Missions (DSMs) are gaining momentum in their application to Earth Observation (EO) missions owing to their unique ability to increase observation sampling in spatial, spectral, angular and temporal dimensions simultaneously. DSM design includes a much larger number of variables than its monolithic counterpart, therefore, Model-Based Systems Engineering (MBSE) has been often used for preliminary mission concept designs, to understand the trade-offs and interdependencies among the variables. MBSE models are complex because the various objectives a DSM is expected to achieve are almost always conflicting, non-linear and rarely analytical. NASA Goddard Space Flight Center (GSFC) is developing a pre-Phase A tool called Tradespace Analysis Tool for Constellations (TAT-C) to initiate constellation mission design. The tool will allow users to explore the tradespace between various performance, cost and risk metrics (as a function of their science mission) and select Pareto optimal architectures that meet their requirements. This paper will describe the different types of constellations that TAT-C’s Tradespace Search Iterator is capable of enumerating (homogeneous Walker, heterogeneous Walker, precessing type, ad-hoc) and their impact on key performance metrics such as revisit statistics, time to global access and coverage. We will also discuss the ability to simulate phased deployment of the given constellations, as a function of launch availabilities and/or vehicle capability, and show the impact on performance. All performance metrics are calculated by the Data Reduction and Metric Computation module within TAT-C, which issues specific requests and processes results from the Orbit and Coverage module. Our TSI is also capable of generating tradespaces for downlinking imaging data from the constellation, based on permutations of available ground station networks - known (default) or customized (by the user). We will show the impact of changing ground station options for any given constellation, on data latency and required communication bandwidth, which in turn determines the responsiveness of the space system.

Nag, Sreeja↗

NASA NTRSDate not supplied

Assessing the Viability of Using GEOS-Forecast Product for Landslides Forecasting: A Step Toward Early Warning System

Landslides across the globe are mostly triggered by extreme rainfall events affecting infrastructure, transportation and livelihoods. The risks are rarely quantified due to lack of data, analytical skills and limited modeling techniques. Knowledge of local to global scale landslide risks provides communities and national agencies the ability to adapt disaster management practices to mitigate and recover from these hazards. In order to minimize the risks and improve characterization of community resilience to landslides, it is vital to have reliable information about the factors triggering landslides such as rainfall, well ahead in time. Forecasting potential landslide activity and impacts can be achieved through reliable precipitation forecast models. However, it is challenging because of the temporal and spatial variability of precipitation, an important factor in triggering landslides. Evaluation of the precipitation field, associated errors, and sampling uncertainties is integral for development of efficient and reliable landslide forecasting and early warning system. This study develops a methodology to assess the viability of using a precipitation field provided by a global model and its potential integration in the landslide forecasting system. The study focuses on the comparison between the IMERG (Integrated Multi-satellitE Retrievals for Global Precipitation Mission) and GEOS (NASA Goddard Earth Observing System)-Forecast product over contiguous United States (CONUS). GEOS model assimilates new observations every 6 hours, at 00, 06, 12, and 18 UTC. The framework is tested on the GEOS-Forecast Model initialized at 00 UTC using daily IMERG early product as reference using both categorical and continuous statistics. The categorical statistics includes the probability of detection (POD), success ratio (SR), critical success index (CSI), and the hit bias. Continuous statistics such as correlation, normalized standard deviation, and root-mean-square error are also evaluated. Overall, GEOS-Forecast precipitation field over the analysis period (~1 year) show underestimation with respect to IMERG early for the daily accumulated rainfall. However, the probability distribution function and cumulative distribution function of both show similar patterns. In terms of correlations, POD, SR, CSI, hit bias, the performance varies with respect to the rainfall threshold used.

Sana Khan↗

NASA NTRSDate not supplied

Evaluation of CFD as a Surrogate for Wind-Tunnel Testing: Experimental Uncertainty Quantification for the UPWT Flow Survey Test

A series of wind tunnel tests are being performed at the Unitary Plan Wind Tunnel (UPWT)at NASA Langley Research Center to assess the validity of using computational fluid dynamics(CFD) as a surrogate for wind tunnel testing. In order to make proper comparisons, uncertainties in CFD results and experimental data must be well understood. The material presented highlights the methods, assumptions, and inputs used to achieve experimental uncertainty estimates. Results for a small subset of tunnel conditions and variables of interest from the first test in the series, the Flow Survey Test, are highlighted and sample CFD comparisons are shown. The bulk of the results from this work are used for comparisons in other AIAA conference papers related to this test series.

Erin P Hubbard↗

NASA NTRS2022

Si5345, SY88422L, LT3482, and MSK130 components Total Ionizing Dose Test Report

The purpose of this test was to characterize the SI-5345, SY88422L, LT3482 and MSK130 parameter degradation for total dose response. The components are associated with REAG ID #21-024. In the test, each device was exposed to high dose rate (HDR) irradiation using gamma radiation. Device parameters such as leakage currents, timing, and overall chip health were investigated. These devices were tested for an interstellar mission on a trajectory between 0.9 AU and 5.3 AU with a 2.5-year mission, yielding an expected overall dose of 29 krad(Si)behind 1 mm of aluminum shielding (at 95% confidence; environment and dose determined through SPENVIS). This test report gives an initial look at candidate parts. Extremely small sample sizes (only 1 or 2 devices tested) do not allow consideration of part-to-part variability. High dose rates were used despite LT3482 and MSK130 having potential enhanced low dose rate sensitivity (ELDRS). Care should be taken in interpreting results given these limitations.

Total Ionizing Dose (TID)↗

DOE OSTI2021

A Scalable Gradient Free Method for Bayesian Experimental Design with Implicit Models

Bayesian experimental design (BED) is to answer the question that how to choose designs that maximize the information gathering. For implicit models, where the likelihood is intractable but sampling is possible, conventional BED methods have difficulties in efficiently estimating the posterior distribution and maximizing the mutual information (MI) between data and parameters. Recent work proposed the use of gradient ascent to maximize a lower bound on MI to deal with these issues. However, the approach requires a sampling path to compute the pathwise gradient of the MI lower bound with respect to the design variables, and such a pathwise gradient is usually inaccessible for implicit models. In this paper, we propose a novel approach that leverages recent advances in stochastic approximate gradient ascent incorporated with a smoothed variational MI estimator for efficient and robust BED. Without the necessity of pathwise gradients, our approach allows the design process to be achieved through a unified procedure with an approximate gradient for implicit models. Several experiments show that our approach outperforms baseline methods, and significantly improves the scalability of BED in high-dimensional problems.

Zhang, Jiaxin↗

NASA NTRS2004

Signal Processing Variables for Optimization of Flaw Detection in Composites Using Ultrasonic Guided Wave Scanning

This study analyzes the effect of signal processing variables on the ability of the ultrasonic guided wave scan method at NASA Glenn Research Center to distinguish various flaw conditions in ceramic matrix composites samples. In the ultrasonic guided wave scan method, several time- and frequency-domain parameters are calculated from the ultrasonic guided wave signal at each scan location to form images. The parameters include power spectral density, centroid mean time, total energy (zeroth moment), centroid frequency, and ultrasonic decay rate. A number of signal processing variables are available to the user when calculating these parameters. These signal processing variables include 1) the time portion of the time-domain waveform processed, 2) integration type for the properties requiring integrations, 3) bounded versus unbounded integrations, 4) power spectral density window type, 5) and the number of time segments chosen if using the short-time fourier transform to calculate ultrasonic decay rate. Flaw conditions examined included delamination, cracking, and density variation.

Roth, Don J.↗

NASA NTRS2010

Robustness-Based Design Optimization Under Data Uncertainty

This paper proposes formulations and algorithms for design optimization under both aleatory (i.e., natural or physical variability) and epistemic uncertainty (i.e., imprecise probabilistic information), from the perspective of system robustness. The proposed formulations deal with epistemic uncertainty arising from both sparse and interval data without any assumption about the probability distributions of the random variables. A decoupled approach is proposed in this paper to un-nest the robustness-based design from the analysis of non-design epistemic variables to achieve computational efficiency. The proposed methods are illustrated for the upper stage design problem of a two-stage-to-orbit (TSTO) vehicle, where the information on the random design inputs are only available as sparse point and/or interval data. As collecting more data reduces uncertainty but increases cost, the effect of sample size on the optimality and robustness of the solution is also studied. A method is developed to determine the optimal sample size for sparse point data that leads to the solutions of the design problem that are least sensitive to variations in the input random variables.

Zaman, Kais↗

DOE OSTI2023

Sample Preparation Method for Low-Level Total 129 I Measurements by ICP-MS

Trace-level measurements of iodine’s isotopic ( 129 I and 127 I) and chemical species distributions are needed for an accurate understanding of radioiodine migration in the Hanford subsurface. Pacific Northwest National Laboratory (PNNL) previously developed a novel analytical method for iodine characterization that uses ion chromatography (IC) coupled to inductively coupled mass spectrometry (ICP-MS). While the method can measure speciated forms of 129 I at levels below the drinking water standard, an interference from molybdenum (Mo) prevents the assay from quantifying the $\underline{total}$ 129 I concentration in many Hanford sample matrices. In this work, solvent extraction was evaluated as a sample preparation method for eliminating the Mo interference. A series of 10 experiments was conducted in which solutions containing known amounts of iodate or iodide were treated by solvent extraction, and the extracted solutions were analyzed for total iodine concentrations by ICP MS. Several extraction parameters such as reagent concentrations and chemical reaction times were systematically adjusted in attempts to optimize the extraction process. While solvent extraction was shown to be effective at removing Mo, there was a consistent inability to recover more than approximately 75% of the total iodine in most experiments. This would reduce the ability to detect 129 I at levels near the drinking water standard. Additionally, the extraction efficiencies in several experiments were highly variable, suggesting that solvent extraction could add significant uncertainty to radioiodine measurements. We recommend evaluating ion exchange as an alternative sample preparation approach in fiscal year (FY) 2024.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2017

Stochastic modeling of phosphorus transport in the Three Gorges Reservoir by incorporating variability associated with the phosphorus partition coefficient

Phosphorus (P) fate and transport plays a crucial role in the ecology of rivers and reservoirs in which eutrophication is limited by P. A key uncertainty in models used to help manage P in such systems is the partitioning of P to suspended and bed sediments. By analyzing data from field and laboratory experiments, we stochastically characterize the variability of the partition coefficient (Kd) and derive spatio-temporal solutions for P transport in the Three Gorges Reservoir (TGR). We formulate a set of stochastic partial different equations (SPDEs) to simulate P transport by randomly sampling Kd from the measured distributions, to obtain statistical descriptions of the P concentration and retention in the TGR. The correspondence between predicted and observed P concentrations and P retention in the TGR combined with the ability to effectively characterize uncertainty suggests that a model that incorporates the observed variability can better describe P dynamics and more effectively serve as a tool for P management in the system. This study highlights the importance of considering parametric uncertainty in estimating uncertainty/variability associated with simulated P transport.

Partition coefficient↗

NASA NTRS1976

Toward the modeling of land use change: A spatial analysis using remote sensing and historical data

It was hypothesized that the chronological observation of land use change could be shown to follow a predictable pattern and these patterns could be correlated with other statistical data to develop transition probabilities suitable for modeling purposes. A literature review and preliminary research, however, indicated a totally stochastic approach was not practical for simulating land use change and thus a more deterministic approach was adopted. The approach used assumes the determinants of the land use conversion process are found in the market place, where land transactions among buyers and sellers occur. Only one side of the market transaction process is studied, however, namely, the purchaser's desires in securing an ideal or suitable site. The problem was to identify the ideal qualities, quantities or attributes desired in an industrial site (or housing development), and to formulate a general algorithmic statement capable of identifying potential development sites. Research procedures involved developing a list of variables previously noted in the literature to be related to site selection and streamlining the list to a set suitable for statistical testing. A sample of 157 industries which have located (or relocated) in the 16-county Knoxville metropolitan region since 1950 was selected for industrial location analysis. Using NASA color infrared photography and Tennessee Valley Authority historical aerial photography, data were collected on the spatial characteristics of each industrial location event. These data were then subjected to factor analysis to determine the interrelations of variables.

Honea, R. B.↗

DOE OSTI2016

Single crystal magnetic structure and susceptibility of CoSe{sub 2}O{sub 5}

The structure of CoSe{sub 2}O{sub 5} consists of one-dimensional ribbons of edge-sharing CoO{sub 6} octahedra bound together by polyanionic subunits of Se{sub 2}O{sub 5}. Previous work on polycrystalline samples reported a canted antiferromagnetic arrangement of the magnetic moments below the ordering temperature of 8.5 K. Here, we report a single crystal investigation using variable temperature and field magnetic susceptibility and low-temperature neutron diffraction to more precisely characterize the nature of the magnetic ground state of CoSe{sub 2}O{sub 5}. Contrary to previous reports, we find that the single crystal magnetic structure shows no canting of the antiferromagnetic ground state, and in the process have identified several field-induced changes to the magnetization. We discuss these results in the context of the revised magnetic structure and highlight the importance of crystal growth for the accurate characterization of these properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Source Attribution of Cyanides using Anionic Impurity Profiling, Stable Isotope Ratios, Trace Elemental Analysis and Chemometrics

Chemical attribution signatures (CAS) for chemical threat agents (CTAs) are being investigated to provide an evidentiary link between CTAs and specific sources to support criminal investigations and prosecutions. In a previous study, anionic impurity profiles developed using high performance ion chromatography (HPIC) were demonstrated as CAS for matching samples from eight potassium cyanide (KCN) stocks to their reported countries of origin. Herein, a larger number of solid KCN stocks (n = 13) and, for the first time, solid sodium cyanide (NaCN) stocks (n = 15) were examined to determine what additional sourcing information can be obtained through anion, carbon stable isotope, and elemental analyses of cyanide stocks by HPIC, isotope ratio mass spectrometry (IRMS), and inductively coupled plasma optical emission spectroscopy (ICP-OES), respectively. The HPIC anion data was evaluated using the variable selection methods of Fisher-ratio (F-ratio), interval partial least squares (iPLS), and genetic algorithm-based partial least squares (GAPLS) and the classification methods of partial least squares discriminate analysis (PLSDA), K nearest neighbors (KNN), and support vector machines discriminate analysis (SVMDA). In summary, hierarchical cluster analysis (HCA) of anion impurity profiles from multiple cyanide stocks from six reported country of origins resulted in cyanide samples clustering into three groups: Czech Republic, Germany, and United States, independent of the associated alkali metal (K or Na). The three country groups were independently corroborated by HCA of cyanide elemental profiles and corresponded to countries with known solid cyanide factories. Both the anion and elemental CAS are believed to originate from the aqueous alkali hydroxides used in cyanide manufacture. Carbon stable isotope measurements resulted in two clusters: Germany and United States (the single Czech stock grouped with United States stocks). The carbon isotope CAS is believed to originate from the carbon source and process used to make the HCN utilized in cyanide synthesis. Classification errors for two validation studies using anion impurity profiles collected over five years on different instruments were as low as zero for KNN and SVMDA, demonstrating the excellent reliability (so far) of using anion impurities for matching a cyanide sample to its country of manufacture (i.e., factory). Variable selection reduced errors for those classification methods having errors greater than zero with iPLS-forward selection, and F-ratio typically providing the lowest errors. Finally, using anion profiles to match cyanides to a specific stock or stock group resulted in cross-validation errors ranging from zero to 5.3%.

chemical forensics↗

DOE OSTI2019

Ongoing solution reproducibility of earth system models as they progress toward exascale computing

We present a methodology for solution reproducibility for the Energy Exascale Earth System Model during its ongoing software infrastructure development to prepare for exascale computers. The nonlinear chaotic nature of climate system simulations precludes traditional model verification approaches since machine precision differences—resulting from code refactoring, changes in software environment, and so on—grow exponentially to a different weather state. Here, we leverage the nature of climate as a statistical description of the atmosphere in order to establish model reproducibility. We evaluate the degree to which two-sample equality of distribution tests can confidently detect the change in climate from minor tuning parameter changes on model output variables in order to establish the level of difference that indicates a new climate. To apply this (baselined test), we target a section of the model’s development cycle wherein no intentional science changes have been applied to its source code. We compare an ensemble of short simulations that were conducted using a verified model configuration against a new ensemble with the same configuration but with the latest software infrastructure (Common Infrastructure for Modeling the Earth, CIME5.0), compiler versions, and software libraries. We also compare these against ensemble simulations conducted using the original version of the software infrastructure (CIME4.0) of the earlier model configuration, but with the latest compilers and software libraries, to test the impact of new compilers and libraries in isolation from additional software infrastructure. The two-sample equality of distribution tests indicates that these ensembles indeed represent the same climate.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Prediction of the J C (B) Behavior of Bi-2212 Wires at High Field

Bi-2212 wires have been produced for much of the last decade with varying architectures, powder sources and great variability of final J c (B) properties. As Bi-2212 transitions from an R&D materials development to a magnet technology, means to predictably forecast J c (B) become increasingly valuable. Here we report on characterizations of short samples having J c (15T, 4.2 K) varying from 1210 to 6560 A/mm 2 , measured in fields up to 31 T, and drawn from 10 billets. Using both 4 K transport and variable temperature VSM measurements capable of probing the 20 K irreversibility field, B irr = μ 0 H k , we discovered that the vortex pinning properties are very stable across these wires, which all used the same standard powder composition (Bi 2.17 Sr 1.94 Ca 0.89 Cu 2.00 O 8+x ), even though it has been made by three different manufacturers over nine years. We conclude that a power-law fit J c ∝ B -α , where α = 0.280 (σ = 0.015), works well at 4.2 K over the field range of at least 3-30 T and that μ 0 H k (20 K) remains stable at 8.6 ± 0.4 T. We conclude that the dominant current limiting mechanism predicting J c (B) in Bi-2212 is the effective filament connectivity. J c (B) at high fields may thus be predicted by simple I c measurements at easily accessible fields in the 3-15 T range.

36 MATERIALS SCIENCE↗