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At least 1,783 records · Page 99

Particulate Titanium Matrix Composites Tested--Show Promise for Space Propulsion Applications

Uniformly distributed particle-strengthened titanium matrix composites (TMCs) can be manufactured at lower cost than many types of continuous-fiber composites. The innovative manufacturing technology combines cold and hot isostatic pressing procedures to produce near-final-shape components. Material stiffness is increased up to 26-percent greater than that of components made with conventional titanium materials at no significant increase in the weight. The improved mechanical performance and low-cost manufacturing capability motivated an independent review to assess the improved properties of ceramic titanium carbide (TiC) particulate-reinforced titanium at elevated temperature. Researchers at the NASA Glenn Research Center creatively designed and executed deformation and durability tests to reveal operating regimes where these materials could lower the cost and weight of space propulsion systems. The program compares the elevated-temperature performance of titanium alloy Ti-6Al-4V matrix material to an alloy containing 10 wt% of TiC particles. Initial experiments showed that at these relatively low particle concentrations the material stiffness of the TMC was improved 20 percent over that of the plain Ti-6Al-4V alloy when tested at 427 C. The proportional limit and ultimate strength of the composite in tension are 21- and 14-percent greater than those of the plain alloy. Compression tests showed that the proportional limit is about 30 percent greater for TMC than for the plain alloy. The enhanced deformation resistance of the TMC was also evident in a series of tensile and compressive stress relaxation tests that were made. Specimens were subjected to tensile or compressive strain amplitudes of 0.75 percent for 24 hr followed by a return to zero strain imposed for 24 hr. The stress relaxation data were normalized with respect to the maximum stress for each case and plotted as a function of time in the following graph. Tensile stresses relaxed 19 percent for the TMC and 25 percent for the plain Ti-6Al-4V alloy. Compressive stresses relaxed 25 percent for the TMC and 39 percent for the plain Ti-6Al-4V alloy. The superior deformation resistance of the TMC extends to a creep rate that is 28-percent slower for the TMC when it is loaded to stress levels that are 26-percent higher than for the plain Ti-6Al-4V alloy.

Lerch, Bradley A.↗

A Hybrid Parachute Simulation Environment for the Orion Parachute Development Project

A parachute simulation environment (PSE) has been developed that aims to take advantage of legacy parachute simulation codes and modern object-oriented programming techniques. This hybrid simulation environment provides the parachute analyst with a natural and intuitive way to construct simulation tasks while preserving the pedigree and authority of established parachute simulations. NASA currently employs four simulation tools for developing and analyzing air-drop tests performed by the CEV Parachute Assembly System (CPAS) Project. These tools were developed at different times, in different languages, and with different capabilities in mind. As a result, each tool has a distinct interface and set of inputs and outputs. However, regardless of the simulation code that is most appropriate for the type of test, engineers typically perform similar tasks for each drop test such as prediction of loads, assessment of altitude, and sequencing of disreefs or cut-aways. An object-oriented approach to simulation configuration allows the analyst to choose models of real physical test articles (parachutes, vehicles, etc.) and sequence them to achieve the desired test conditions. Once configured, these objects are translated into traditional input lists and processed by the legacy simulation codes. This approach minimizes the number of sim inputs that the engineer must track while configuring an input file. An object oriented approach to simulation output allows a common set of post-processing functions to perform routine tasks such as plotting and timeline generation with minimal sensitivity to the simulation that generated the data. Flight test data may also be translated into the common output class to simplify test reconstruction and analysis.

Moore, James W.↗

Evaluation of Delamination Growth Characterization Methods Under Mode I Fatigue Loading

Reliable delamination characterization data for laminated composites are needed for input to analytical models of structures to predict delamination. The double-cantilevered beam (DCB) specimen is used with laminated composites to measure fracture toughness, G(sub Ic), delamination onset strain energy release rate, and growth rate data under cyclic loading. In the current study, DCB specimens of IM7/8552 graphite/epoxy supplied by two different manufacturers were tested in static and fatigue to compare the measured characterization data from the two sources, and to evaluate a proposed ASTM standard for generating Paris Law equations. Static results were used to generate compliance calibration constants for the fatigue data, and a delamination resistance curve, G(sub IR), which was used to determine the effects of fiber-bridging on delamination growth. Specimens were tested in fatigue at a cyclic G(sub Imax) level equal to 50, 40 or 30% of G(sub Ic), to determine a delamination onset curve and delamination growth rate. The delamination onset curve equations had similar exponents and the same trends. Delamination growth rate was calculated by fitting a Paris Law to the da/dN versus G(sub Imax) data. Both a 2-point and a 7-point data reduction method were used and the Paris Law equations were compared. To determine the effects of fiber-bridging, growth rate results were normalized by the delamination resistance curve for each material and compared to the non-normalized results. Paris Law exponents were found to decrease by 31% to 37% due to normalizing the growth data. Normalizing the data also greatly reduced the amount of scatter between the different specimens. Visual data records from the fatigue testing were used to calculate individual compliance calibration constants from the fatigue data for some of the specimens. The resulting da/dN versus G(sub Imax) plots showed much improved repeatability between specimens. Gretchen

Murri, Gretchen B.↗

Laser Communication Component Technologies: Database; Status and Trends

A database of component and subsystem technologies for free-space laser communications has been compiled. This document discusses technology assessment for free-space lasercomm components, and contains a collection of characteristics of commercially available and one-of-a-kind components that were made for laser communication and other relevant applications. the document also includes quantitative data on laser communication systems that were constructed in the past, along with plots of development trends for specific component technologies as a function of time.

Laser↗

Impedance-Based State-of-Health Estimation for Lithium-Ion Battery Management Systems

This paper discusses an impedance-based state-of-health (SOH) estimation for lithium-ion battery management systems. Features obtained from the Nyquist plot of the electrochemical impedance spectroscopy (EIS) are utilized to estimate the SOH. Two commercial lithium-ion batteries were aged (cycled) in the laboratory to collect aging and impedance data. An algorithm for SOH estimation is presented and evaluated. The performance evaluation results show that the SOH features extracted from the Nyquist plot can be utilized for SOH estimation. Estimated SOH values can be then utilized in various battery management systems (BMS) functions such as for calibrating the available capacity, adjusting charging/discharging strategies, and protection.

Al-Smadi, Mohammad↗

A petabyte size electronic library using the N-Gram memory engine

A model library containing petabytes of data is proposed by Triada, Ltd., Ann Arbor, Michigan. The library uses the newly patented N-Gram Memory Engine (Neurex), for storage, compression, and retrieval. Neurex splits data into two parts: a hierarchical network of associative memories that store 'information' from data and a permutation operator that preserves sequence. Neurex is expected to offer four advantages in mass storage systems. Neurex representations are dense, fully reversible, hence less expensive to store. Neurex becomes exponentially more stable with increasing data flow; thus its contents and the inverting algorithm may be mass produced for low cost distribution. Only a small permutation operator would be recalled from the library to recover data. Neurex may be enhanced to recall patterns using a partial pattern. Neurex nodes are measures of their pattern. Researchers might use nodes in statistical models to avoid costly sorting and counting procedures. Neurex subsumes a theory of learning and memory that the author believes extends information theory. Its first axiom is a symmetry principle: learning creates memory and memory evidences learning. The theory treats an information store that evolves from a null state to stationarity. A Neurex extracts information data without a priori knowledge; i.e., unlike neural networks, neither feedback nor training is required. The model consists of an energetically conservative field of uniformly distributed events with variable spatial and temporal scale, and an observer walking randomly through this field. A bank of band limited transducers (an 'eye'), each transducer in a bank being tuned to a sub-band, outputs signals upon registering events. Output signals are 'observed' by another transducer bank (a mid-brain), except the band limit of the second bank is narrower than the band limit of the first bank. The banks are arrayed as n 'levels' or 'time domains, td.' The banks are the hierarchical network (a cortex) and transducers are (associative) memories. A model Neurex was built and studied. Data were 50 MB to 10 GB samples of text, data base, and images: black/white, grey scale, and high resolution in several spectral bands. Memories at td, S(m(sub td)), were plotted against outputs of memories at td-1. S(m(sub td)) was Boltzman distributed, and memory frequencies exhibited self-organized criticality (SOC); i.e., 'l/f(sup beta)' after long exposures to data. Whereas output signals from level n may be encoded with B(sub output) = O(-log(2)f(sup beta)) bits, and input data encoded with B(sub input) = O((S(td)/S(td-1))(sup n)), B(sup output)/B(sub input) is much less than 1 always, the Neurex determines a canonical code for data and it is a lossless data compressor. Further tests are underway to confirm these results with more data types and larger samples.

Bugajski, Joseph M.↗

Development of a Multivariable Parametric Cost Analysis for Space-Based Telescopes

Over the past 400 years, the telescope has proven to be a valuable tool in helping humankind understand the Universe around us. The images and data produced by telescopes have revolutionized planetary, solar, stellar, and galactic astronomy and have inspired a wide range of people, from the child who dreams about the images seen on NASA websites to the most highly trained scientist. Like all scientific endeavors, astronomical research must operate within the constraints imposed by budget limitations. Hence the importance of understanding cost: to find the balance between the dreams of scientists and the restrictions of the available budget. By logically analyzing the data we have collected for over thirty different telescopes from more than 200 different sources, statistical methods, such as plotting regressions and residuals, can be used to determine what drives the cost of telescopes to build and use a cost model for space-based telescopes. Previous cost models have focused their attention on ground-based telescopes due to limited data for space telescopes and the larger number and longer history of ground-based astronomy. Due to the increased availability of cost data from recent space-telescope construction, we have been able to produce and begin testing a comprehensive cost model for space telescopes, with guidance from the cost models for ground-based telescopes. By separating the variables that effect cost such as diameter, mass, wavelength, density, data rate, and number of instruments, we advance the goal to better understand the cost drivers of space telescopes.. The use of sophisticated mathematical techniques to improve the accuracy of cost models has the potential to help society make informed decisions about proposed scientific projects. An improved knowledge of cost will allow scientists to get the maximum value returned for the money given and create a harmony between the visions of scientists and the reality of a budget.

Dollinger, Courtnay↗

Higher than expected N 2 O emissions from soybean crops in the Pampas Region of Argentina: Estimates from DayCent simulations and field measurements

In developing countries, agriculture generally represents a large fraction of GHG emissions reported in National Inventories, and emissions are typically estimated using Tier 1 IPCC guidelines. However, field data and locally adapted simulation models can improve the accuracy of IPCC estimations. In this report we aimed to quantify anthropogenic N2O emissions from croplands of Argentina through field measurements, model simulations and IPCC guidelines. Here we measured N 2 O emissions and their controlling factors in 62 plots of the Pampas Region with corn, soybean and wheat/soybean crops and in unmanaged grasslands. We accounted for gross emissions from crops and background emissions from unmanaged grasslands to calculate net anthropogenic emissions from crops as the difference between them. We calibrated and evaluated the DayCent model and then simulated different weather and management scenarios. Finally, we applied IPCC guidelines to estimate anthropogenic N 2 O emissions at the same plots. The DayCent model accurately simulated annual N 2 O emission for all crops as compared to measured data (RMSE = 1.4 g N ha -1 day -1 ). Measured and simulated emissions in soybean crops were higher than in corn and wheat/soybean crops. Gross N 2 O emissions ranged from 1.4 to 5.1 kg N ha -1 yr -1 for current environmental (soil and weather) and management (crops and fertilizer doses) conditions. Background emissions ranged between 1.1 and 1.3 kg N ha -1 yr -1 , and therefore net anthropogenic emissions ranged from 0.3 to 4.0 kg N ha-1 yr -1 . IPCC Tier 1 emission factors underestimated N2O releases from soybean, that were on average 4.87 times greater when estimated with DayCent and observations (0.53 vs 2.47 and 2.69 kg N ha -1 yr -1 , respectively). On the contrary, IPCC estimates for corn and wheat/soybean crops were similar to modeled and measured values. Our results suggest that N 2 O emissions from the vast 15 million ha of soybean croplands in the Pampas Region may be substantially underestimated.

59 BASIC BIOLOGICAL SCIENCES↗

[Activities of the Department of Electrical Engineering, Howard University]

Theoretical derivations, computer analysis and test data are provided to demonstrate that the cavity model is a feasible one to analyze thin-substrate, rectangular-patch microstrip antennas. Seven separate antennas were tested. Most of the antennas were designed to resonate at L-band frequencies (1-2 GHz). One antenna was designed to resonate at an S-band (2-4 GHz) frequency of 2.025 GHz. All dielectric substrates were made of Duroid, and were of varying thicknesses and relative dielectric constant values. Theoretical derivations to calculate radiated free space electromagnetic fields and antenna input impedance were performed. MATHEMATICA 2.2 software was used to generate Smith Chart input impedance plots, normalized relative power radiation plots and to perform other numerical manipulations. Network Analyzer tests were used to verify the data from the computer programming (such as input impedance and VSWR). Finally, tests were performed in an anechoic chamber to measure receive-mode polar power patterns in the E and H planes. Agreement between computer analysis and test data is presented. The antenna with the thickest substrate (e(sub r) = 2.33,62 mils thick) showed the worst match to theoretical impedance data. This is anticipated due to the fact that the cavity model generally loses accuracy when the dielectric substrate thickness exceeds 5% of the antenna's free space wavelength. A method of reducing computer execution time for impedance calculations is also presented.

Yalamanchili, Raj C.↗

NGEE Arctic Soil Pit and Core Inventory for Samples Collected Between 2016-2019: Locations, Sampling Characteristics, Collection, and Contacts, Seward Peninsula, Alaska, USA

This dataset includes associated information about individual pit and core samples (e.g., location, contact, date, data collected) sampled between 2016 and 2019 from NGEE Arctic sites at Teller (MM 27 and MM47), Kougarok (MM47 and MM56, Hillslope, and vegetation plot areas), and Council (MM71). The inventory is qualitative and excludes those datasets on soil pit cores that included time-series information. The package includes one each *.csv data file, *.kml and *.pdf. All quantitative data is available in the related datasets https://doi.org/10.5440/1417652, https://doi.org/10.5440/1423892, https://doi.org/10.5440/1342956, https://doi.org/10.5440/1854940, https://doi.org/10.5440/1544760, https://doi.org/10.5440/1346200, and https://doi.org/10.5440/1856042. The goal of this dataset is to help modelers understand when, where, and what data was collected with respect to physical soil properties on the Seward Peninsula, AK, USA over the course of NGEE Arctic’s campaigns in the region from 2016-2019. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

A New Display Format Relating Azimuth-Scanning Radar Data and All-Sky Images in 3-D

Here we correlate features in a sequence of all-sky images of 630 nm airglow with the three-dimensional (3-D) structure of electron densities in the F region above Arecibo. Pairs of 180 azimuth scans (using the Gregorian and line feeds) of the two-beam incoherent scatter radar (ISR) have been plotted in cone pictorials of the line-of-sight electron densities. The plots include projections of the 630 nm airglow onto the ground using the same spatial scaling as for the ISR data. Selected sequential images from the night of 16-17 June 2004 correlate ionospheric plasma features with scales comparable to the ISR density-cone diameter. The entire set of over 100 images spanning about eight hours is available as a movie. The correlation between the airglow and the electron densities is not unexpected, but the new display format shows the 3-D structures better than separate 2-D plots in latitude and longitude for the airglow and in height and time for the electron densities. Furthermore, the animations help separate the bands of airglow from obscuring clouds and the star field.

Swartz, Wesley E.↗

Machine Learning-Based Anomaly Detection for PMT Data Quality Monitoring in the SBN and DUNE

Maintaining high-quality detector data is essential for achieving the scientific objectives of the Short-Baseline Neutrino (SBN) Program at Fermilab. Current data quality monitoring (DQM) procedures rely primarily on threshold-based metrics and manual inspection of detector monitoring plots, making the detection of subtle or gradually developing anomalies both time-consuming and dependent on expert interpretation. This project developed and evaluated a machine-learning workflow for automatically identifying anomalous photomultiplier tube (PMT) channels in the Short-Baseline Near Detector (SBND) using optical-hit amplitude data. A Python-based analysis program was developed to process ROOT files, extract statistical features describing individual PMT amplitude distributions, and generate feature vectors for anomaly detection. These features were used to train an Isolation Forest model using data representing normal detector operation. The trained model was subsequently applied to independent detector runs to identify channels exhibiting statistically unusual behavior relative to the learned reference response. To support expert interpretation, the workflow generated complementary diagnostic products, including anomaly score distributions, normalized amplitude comparisons, decision-tree visualizations, and principal component analysis (PCA) projections. This project demonstrated the feasibility of integrating unsupervised machine learning into detector data-quality monitoring and developed a complete workflow for automated PMT performance assessment to aid expert-driven review. Beyond its technical contributions, the VFP appointment fostered a research collaboration between Aurora University and Fermilab and provided direct workforce development benefits by training the visiting faculty member in detector-scale machine-learning methods that are now being incorporated into undergraduate coursework and research. The methodology developed here provides a foundation for future applications to ProtoDUNE and other liquid argon time projection chamber (LArTPC) detectors, contributing to ongoing efforts to improve detector reliability, reduce manual monitoring requirements, and enable scalable data quality monitoring for future large-scale neutrino experiments, including the Deep Underground Neutrino Experiment (DUNE).

Colón Santana, Juan A. [Unlisted, US, IL]↗

Southern Durchmusterung (Schoenfeld 1886): Documentation for the machine-readable version

The machine-readable version of the catalog, as it is currently being distributed from the Astronomical Data Center, is described. The Southern Durchmusterung (SD) was computerized at the Centre de Donnees Astronomiques de Strasbourg and at the Astronomical Data Center at the National Space Science Data Center, NASA/Goddard Space Flight Center. Corrigenda listed in the original SD volume and published by Kuenster and Sticker were incorporated into the machine file. In addition, one star indicated to be missing in a published list, and later verified, is flagged so that it can be omitted from computer plotted charts if desired. Stars deleted in the various errata lists were similarly flagged, while those with revised data are flagged and listed in a separate table. This catalog covers the zones -02 to -23 degrees; zones +89 to -01 degrees (the Bonner Durchmusterung) are included in a separate catalog available in machine-readable form.

Warren, Wayne H., Jr.↗

Data documentation for the bare soil experiment at the University of Arkansas

The reflectivities of several controlled moisture test plots were investigated. These test plots were of a similar soil texture which was clay loam and were prepared to give a desired initial soil moisture and density profile. Measurements were conducted on the plots as the soil water redistributed for both long term and diurnal cycles. These measurements included reflectivity, gravimetric and volumetric soil moisture, soil moisture potential, and soil temperature.

Waite, W. P.↗

SAS-2 gamma-ray observations of PSR 1747-46

Observations with the SAS-2 high energy ( 35 MeV) gamma-ray telescope show evidence of gamma-ray emission from the radio pulsar PSR 1747-46. When the arrival times of gamma-rays from the region of the pulsar were converted to pulsar phases using the radio period and period derivative, a single peak was found in the phase plot, with a Poisson probability of occurring by chance of .00008. Independently, the time-averaged data for the PSR 1747-46 region show an enhancement over the surrounding region of the sky at the same galactic latitude, with a Poisson probability of chance occurrence of less than .008. The probability that these results are chance is the product of these two probabilities times the number of radio pulsars examined (73). This overall probability is sufficiently small (.00005) to suggest an identification of a new gamma-ray pulsar. In the gamma-ray pulsar plot, the peak falls 0.16 + or - 0.03 period after the radio pulsar peak. This phase shift is, within uncertainties, the same as that observed between the single radio peak and the first of the two gamma-ray peaks seen in the phase plot for PSR-0833-45 (the Vela pulsar).

Thompson, D. J.↗

Thermal surveillance of Cascade Range volcanoes using ERTS-1 multispectral scanner, aircraft imaging systems, and ground-based data communication platforms

A combination of infrared images depicting areas of thermal emission and ground calibration points have proved to be particularly useful in plotting time-dependent changes in surface temperatures and radiance and in delimiting areas of predominantly convective heat flow to the earth's surface in the Cascade Range and on Surtsey Volcano, Iceland. In an integrated experiment group using ERTS-1 multispectral scanner (MSS) and aircraft infrared imaging systems in conjunction with multiple thermistor arrays, volcano surface temperatures are relayed daily to Washington via data communication platform (DCP) transmitters and ERTS-1. ERTS-1 MSS imagery has revealed curvilinear structures at Lassen, the full extent of which have not been previously mapped. Interestingly, the major surface thermal manifestations at Lassen are aligned along these structures, particularly in the Warner Valley.

Friedman, J. D.↗

Offshore Wind Technology Data Update (2019) [Slides]

The 2019 Offshore Wind Technology Data Update compiles information from peer-reviewed literature, market reports, press releases, industry news reports, manufacturer specification sheets, and offshore wind project announcements to provide a comprehensive snapshot of the state of the global wind industry in 2019. These data, including capacity projections, project characteristics, technology trends, and cost estimates, are categorized, tabulated, and plotted to provide easily recognizable and understandable summaries. A particular focus is given to the United States offshore wind project pipeline, including project announcements, state procurements, deployment timelines, infrastructure investments, grid interconnections, and other related developments. The update is intended to be used as a reference document by researchers, analysts, industry practitioners, and government officials.

17 WIND ENERGY↗