Resonance integrals of rhenium for a wide range of sample sizes
Resonance absorption integrals for rhenium 185, rhenium 187, and natural rhenium in foils and thin films
Bogart, D.↗
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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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Optimal GSTDN/TDRSS bit error rate evaluation using limited sample sizes
Statistical studies of telemetry errors were made on data from the Solar Mesosphere Explorer (SME). Examination of frame sync words, as received at the ground station, indicated a wide spread of Bit Error Rates (BER) among stations. A study of the distribution of errors per station pass, however, showed that there was a tendency for the station software to add an even number of spurious errors to the count. A count of wild points in science data, rejecting drop-outs and other system errors, yielded an average random BER of 3.1 x 10 to the -6 with 99% confidence limits of 2.6 and 3.8 x 10 to the -6. The system errors are typically 5 to 100 times more frequent than the truly random errors.
Coffey, R. E.↗
The Effect of Sample Size on the Determination of Maximum Gust Velocities in Clouds
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Press, Harry↗
The Path to Krypton and Xenon Isotopic Measurements from Few-Micron Sized Samples: III Kr Calibration and First Applications of the RIS-TOF System
We describe progress towards the micron-scale analysis of krypton isotopes in extraterrestrial material.
Ocker, K. D.↗
Size distribution sampling errors introduced by the point-plane electrostatic precipitator sampling device
Size distribution sampling errors of point plane electrostatic precipitator for aerosol sampling
SAMPLING DEVICE↗
NASA GRC and MSFC Space-Plasma Arc Testing Procedures
Tests of arcing and current collection in simulated space plasma conditions have been performed at the NASA Glenn Research Center (GRC) in Cleveland, Ohio, for over 30 years and at the Marshall Space Flight Center (MSFC) in Huntsville, Alabama, for almost as long. During this period, proper test conditions for accurate and meaningful space simulation have been worked out, comparisons with actual space performance in spaceflight tests and with real operational satellites have been made, and NASA has achieved our own internal standards for test protocols. It is the purpose of this paper to communicate the test conditions, test procedures, and types of analysis used at NASA GRC and MSFC to the space environmental testing community at large, to help with international space-plasma arcing-testing standardization. Discussed herein are neutral gas conditions, plasma densities and uniformity, vacuum chamber sizes, sample sizes and Debye lengths, biasing samples versus self-generated voltages, floating samples versus grounded samples, test electrical conditions, arc detection, preventing sustained discharges during testing, real samples versus idealized samples, validity of LEO tests for GEO samples, extracting arc threshold information from arc rate versus voltage tests, snapover, current collection, and glows at positive sample bias, Kapton pyrolysis, thresholds for trigger arcs, sustained arcs, dielectric breakdown and Paschen discharge, tether arcing and testing in very dense plasmas (i.e. thruster plumes), arc mitigation strategies, charging mitigation strategies, models, and analysis of test results. Finally, the necessity of testing will be emphasized, not to the exclusion of modeling, but as part of a complete strategy for determining when and if arcs will occur, and preventing them from occurring in space.
Ferguson, Dale C.↗
FY12 End of Year Report for NEPP DDR2 Reliability
This document reports the status of the NEPP Double Data Rate 2 (DDR2) Reliability effort for FY2012. The task expanded the focus of evaluating reliability effects targeted for device examination. FY11 work highlighted the need to test many more parts and to examine more operating conditions, in order to provide useful recommendations for NASA users of these devices. In order to develop these approaches, it is necessary to develop test capability that can identify reliability outliers. To do this we must test many devices to ensure outliers are in the sample, and we must develop characterization capability to measure many different parameters. For FY12 we increased capability for reliability characterization and sample size. We increased sample size by moving from loose devices to DIMMs with an approximate reduction of 20 to 50 times in terms of per DUT cost. By increasing sample size we have improved our ability to characterize devices that may be considered reliability outliers. This report provides an update on the effort to improve DDR2 testing capability. Although focused on DDR2, the methods being used can be extended to DDR and DDR3 with relative ease.
temperature stress↗
FY12 End of Year Report for NEPP DDR2 Reliability
This document reports the status of the NASA Electronic Parts and Packaging (NEPP) Double Data Rate 2 (DDR2) Reliability effort for FY2012. The task expanded the focus of evaluating reliability effects targeted for device examination. FY11 work highlighted the need to test many more parts and to examine more operating conditions, in order to provide useful recommendations for NASA users of these devices. This year's efforts focused on development of test capabilities, particularly focusing on those that can be used to determine overall lot quality and identify outlier devices, and test methods that can be employed on components for flight use. Flight acceptance of components potentially includes considerable time for up-screening (though this time may not currently be used for much reliability testing). Manufacturers are much more knowledgeable about the relevant reliability mechanisms for each of their devices. We are not in a position to know what the appropriate reliability tests are for any given device, so although reliability testing could be focused for a given device, we are forced to perform a large campaign of reliability tests to identify devices with degraded reliability. With the available up-screening time for NASA parts, it is possible to run many device performance studies. This includes verification of basic datasheet characteristics. Furthermore, it is possible to perform significant pattern sensitivity studies. By doing these studies we can establish higher reliability of flight components. In order to develop these approaches, it is necessary to develop test capability that can identify reliability outliers. To do this we must test many devices to ensure outliers are in the sample, and we must develop characterization capability to measure many different parameters. For FY12 we increased capability for reliability characterization and sample size. We increased sample size this year by moving from loose devices to dual inline memory modules (DIMMs) with an approximate reduction of 20 to 50 times in terms of per device under test (DUT) cost. By increasing sample size we have improved our ability to characterize devices that may be considered reliability outliers. This report provides an update on the effort to improve DDR2 testing capability. Although focused on DDR2, the methods being used can be extended to DDR and DDR3 with relative ease.
Guertin, Steven M.↗
An empirical analysis of the quantitative effect of data when fitting quadratic and cubic polynomials
A study is made of the extent to which the size of the sample affects the accuracy of a quadratic or a cubic polynomial approximation of an experimentally observed quantity, and the trend with regard to improvement in the accuracy of the approximation as a function of sample size is established. The task is made possible through a simulated analysis carried out by the Monte Carlo method in which data are simulated by using several transcendental or algebraic functions as models. Contaminated data of varying amounts are fitted to either quadratic or cubic polynomials, and the behavior of the mean-squared error of the residual variance is determined as a function of sample size. Results indicate that the effect of the size of the sample is significant only for relatively small sizes and diminishes drastically for moderate and large amounts of experimental data.
Canavos, G. C.↗
Improved ASTM G72 Test Method for Ensuring Adequate Fuel-to-Oxidizer Ratios
The ASTM G72/G72M-15 Standard Test Method for Autogenous Ignition Temperature of Liquids and Solids in a High-Pressure Oxygen-Enriched Environment is currently used to evaluate materials for the ignition susceptibility driven by exposure to external heat in an enriched oxygen environment. Testing performed on highly volatile liquids such as cleaning solvents has proven problematic due to inconsistent test results (non-ignitions). Non-ignition results can be misinterpreted as favorable oxygen compatibility, although they are more likely associated with inadequate fuel-to-oxidizer ratios. Forced evaporation during purging and inadequate sample size were identified as two potential causes for inadequate available sample material during testing. In an effort to maintain adequate fuel-to-oxidizer ratios within the reaction vessel during test, several parameters were considered, including sample size, pretest sample chilling, pretest purging, and test pressure. Tests on a variety of solvents exhibiting a range of volatilities are presented in this paper. A proposed improvement to the standard test protocol as a result of this evaluation is also presented. Execution of the final proposed improved test protocol outlines an incremental step method of determining optimal conditions using increased sample sizes while considering test system safety limits. The proposed improved test method increases confidence in results obtained by utilizing the ASTM G72 autogenous ignition temperature test method and can aid in the oxygen compatibility assessment of highly volatile liquids and other conditions that may lead to false non-ignition results.
Juarez, Alfredo↗
Improved ASTM G72 Test Method for Ensuring Adequate Fuel-to-Oxidizer Ratios
The ASTM G72/G72M-15 Standard Test Method for Autogenous Ignition Temperature of Liquids and Solids in a High-Pressure Oxygen-Enriched Environment is currently used to evaluate materials for the ignition susceptibility driven by exposure to external heat in an enriched oxygen environment. Testing performed on highly volatile liquids such as cleaning solvents has proven problematic due to inconsistent test results (non-ignitions). Non-ignition results can be misinterpreted as favorable oxygen compatibility, although they are more likely associated with inadequate fuel-to-oxidizer ratios. Forced evaporation during purging and inadequate sample size were identified as two potential causes for inadequate available sample material during testing. In an effort to maintain adequate fuel-to-oxidizer ratios within the reaction vessel during test, several parameters were considered, including sample size, pretest sample chilling, pretest purging, and test pressure. Tests on a variety of solvents exhibiting a range of volatilities are presented in this paper. A proposed improvement to the standard test protocol as a result of this evaluation is also presented. Execution of the final proposed improved test protocol outlines an incremental step method of determining optimal conditions using increased sample sizes while considering test system safety limits. The proposed improved test method increases confidence in results obtained by utilizing the ASTM G72 autogenous ignition temperature test method and can aid in the oxygen compatibility assessment of highly volatile liquids and other conditions that may lead to false non-ignition results.
Juarez, Alfredo↗
Estimating optimal sampling unit sizes for satellite surveys
This paper reports on an approach for minimizing data loads associated with satellite-acquired data, while improving the efficiency of global crop area estimates using remotely sensed, satellite-based data. Results of a sampling unit size investigation are given that include closed-form models for both nonsampling and sampling error variances. These models provide estimates of the sampling unit sizes that effect minimal costs. Earlier findings from foundational sampling unit size studies conducted by Mahalanobis, Jessen, Cochran, and others are utilized in modeling the sampling error variance as a function of sampling unit size. A conservative nonsampling error variance model is proposed that is realistic in the remote sensing environment where one is faced with numerous unknown nonsampling errors. This approach permits the sampling unit size selection in the global crop inventorying environment to be put on a more quantitative basis while conservatively guarding against expected component error variances.
Hallum, C. R.↗
Sampling system for wheat (Triticum aestivum L) area estimation using digital LANDSAT MSS data and aerial photographs
A procedure to estimate wheat (Triticum aestivum L) area using sampling technique based on aerial photographs and digital LANDSAT MSS data is developed. Aerial photographs covering 720 square km are visually analyzed. To estimate wheat area, a regression approach is applied using different sample sizes and various sampling units. As the size of sampling unit decreased, the percentage of sampled area required to obtain similar estimation performance also decreased. The lowest percentage of the area sampled for wheat estimation with relatively high precision and accuracy through regression estimation is 13.90% using 10 square km as the sampling unit. Wheat area estimation using only aerial photographs is less precise and accurate than those obtained by regression estimation.
Parada, N. D. J.↗
Laboratory and Airborne BRDF Analysis of Vegetation Leaves and Soil Samples
Laboratory-based Bidirectional Reflectance Distribution Function (BRDF) analysis of vegetation leaves, soil, and leaf litter samples is presented. The leaf litter and soil samples, numbered 1 and 2, were obtained from a site located in the savanna biome of South Africa (Skukuza: 25.0degS, 31.5degE). A third soil sample, number 3, was obtained from Etosha Pan, Namibia (19.20degS, 15.93degE, alt. 1100 m). In addition, BRDF of local fresh and dry leaves from tulip tree (Liriodendron tulipifera) and acacia tree (Acacia greggii) were studied. It is shown how the BRDF depends on the incident and scatter angles, sample size (i.e. crushed versus whole leaf,) soil samples fraction size, sample status (i.e. fresh versus dry leaves), vegetation species (poplar versus acacia), and vegetation s biochemical composition. As a demonstration of the application of the results of this study, airborne BRDF measurements acquired with NASA's Cloud Absorption Radiometer (CAR) over the same general site where the soil and leaf litter samples were obtained are compared to the laboratory results. Good agreement between laboratory and airborne measured BRDF is reported.
Georgiev, Georgi T.↗
Carbon isotopic analysis of atmospheric methane by isotope-ratio-monitoring gas chromatography-mass spectrometry
Less than 15 min are required for the determination of delta C(sub PDB)-13 with a precision of 0.2 ppt(1 sigma, single measurement) in 5-mL samples of air containing CH4 at natural levels (1.7 ppm). An analytical system including a sample-introduction unit incorporating a preparative gas chromatograph (GC) column for separation of CH4 from N2, O2, and Ar is described. The 15-min procedure includes time for operation of that system, high-resolution chromatographic separation of the CH4, on-line combustion and purification of the products, and isotopic calibration. Analyses of standards demonstrate that systematic errors are absent and that there is no dependence of observed values of delta on sample size. For samples containing 100 ppm or more CH4, preconcentration is not required and the analysis time is less than 5 min. The system utilizes a commercially available, high-sensitivity isotope-ratio mass spectrometer. For optimal conditions of smaple handling and combustion, performance of the system is within a factor of 2 of the shot-noise limit. The potential exists therefore for analysis of samples as small as 15 pmol CH4 with a standard deviation of less than 1 ppt.
Merritt, Dawn A.↗
A Monte Carlo investigation of experimental data requirements for fitting polynomial functions
This report examines the extent to which sample size affects the accuracy of a low order polynomial approximation of an experimentally observed quantity and establishes a trend toward improvement in the accuracy of the approximation as a function of sample size. The task is made possible through a simulated analysis carried out by the Monte Carlo method, in which data are generated by using several transcendental or algebraic functions as models. Contaminated data of varying amounts are fitted to linear quadratic or cubic polynomials, and the behavior of the mean-squared error of the residual variance is determined as a function of sample size. Results indicate that the effect of the size of the sample is significant only for relatively small sample sizes and diminishes drastically for moderate and large amounts of experimental data.
Canavos, G. C.↗
Sampling for area estimation: A comparison of full-frame sampling with the sample segment approach
The author has identified the following significant results. Full-frame classifications of wheat and non-wheat for eighty counties in Kansas were repetitively sampled to simulate alternative sampling plans. Evaluation of four sampling schemes involving different numbers of samples and different size sampling units shows that the precision of the wheat estimates increased as the segment size decreased and the number of segments was increased. Although the average bias associated with the various sampling schemes was not significantly different, the maximum absolute bias was directly related to sampling size unit.
Hixson, M.↗
A sampling system for estimating the cultivation of wheat (Triticum aestivum L) from LANDSAT data
Using digitally processed MSS/LANDSAT data as auxiliary variable, a methodology to estimate wheat (Triticum aestivum L) area by means of sampling techniques was developed. To perform this research, aerial photographs covering 720 sq km in Cruz Alta test site at the NW of Rio Grande do Sul State, were visually analyzed. LANDSAT digital data were analyzed using non-supervised and supervised classification algorithms; as post-processing the classification was submitted to spatial filtering. To estimate wheat area, the regression estimation method was applied and different sample sizes and various sampling units (10, 20, 30, 40 and 60 sq km) were tested. Based on the four decision criteria established for this research, it was concluded that: (1) as the size of sampling units decreased the percentage of sampled area required to obtain similar estimation performance also decreased; (2) the lowest percentage of the area sampled for wheat estimation with relatively high precision and accuracy through regression estimation was 90% using 10 sq km s the sampling unit; and (3) wheat area estimation by direct expansion (using only aerial photographs) was less precise and accurate when compared to those obtained by means of regression estimation.
Parada, N. D. J.↗