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At least 1,567 records · Page 87

Evaluation of classification procedures for estimating wheat acreage in Kansas

This report presents the results of experiments which were performed to evaluate procedures for estimating wheat acreage in intensive test sites (ITS's) in Kansas. An analyst/interpreter (AI) selected and labeled fields from Landsat-1 satellite imagery. Statistics were generated for each selected ITS, and the imagery was classified using a maximum likelihood classifier. Various components of the classification process were tested.

Flores, L. M.↗

Improved silicon nitride for advanced heat engines

The technology base required to fabricate silicon nitride components with the strength, reliability, and reproducibility necessary for actual heat engine applications is presented. Task 2 was set up to develop test bars with high Weibull slope and greater high temperature strength, and to conduct an initial net shape component fabrication evaluation. Screening experiments were performed in Task 7 on advanced materials and processing for input to Task 2. The technical efforts performed in the second year of a 5-yr program are covered. The first iteration of Task 2 was completed as planned. Two half-replicated, fractional factorial (2 sup 5), statistically designed matrix experiments were conducted. These experiments have identified Denka 9FW Si3N4 as an alternate raw material to GTE SN502 Si3N4 for subsequent process evaluation. A detailed statistical analysis was conducted to correlate processing conditions with as-processed test bar properties. One processing condition produced a material with a 97 ksi average room temperature MOR (100 percent of goal) with 13.2 Weibull slope (83 percent of goal); another condition produced 86 ksi (6 percent over baseline) room temperature strength with a Weibull slope of 20 (125 percent of goal).

Yeh, Hun C.↗

Statistical Symbolic Execution with Informed Sampling

Symbolic execution techniques have been proposed recently for the probabilistic analysis of programs. These techniques seek to quantify the likelihood of reaching program events of interest, e.g., assert violations. They have many promising applications but have scalability issues due to high computational demand. To address this challenge, we propose a statistical symbolic execution technique that performs Monte Carlo sampling of the symbolic program paths and uses the obtained information for Bayesian estimation and hypothesis testing with respect to the probability of reaching the target events. To speed up the convergence of the statistical analysis, we propose Informed Sampling, an iterative symbolic execution that first explores the paths that have high statistical significance, prunes them from the state space and guides the execution towards less likely paths. The technique combines Bayesian estimation with a partial exact analysis for the pruned paths leading to provably improved convergence of the statistical analysis. We have implemented statistical symbolic execution with in- formed sampling in the Symbolic PathFinder tool. We show experimentally that the informed sampling obtains more precise results and converges faster than a purely statistical analysis and may also be more efficient than an exact symbolic analysis. When the latter does not terminate symbolic execution with informed sampling can give meaningful results under the same time and memory limits.

Reliability↗

Susceptibility of pESI positive Salmonella to treatment with biocide chemicals approved for use in poultry meat processing as compared to Salmonella without the pESI plasmid

Abstract Salmonella is a common cause of human foodborne illness, which is frequently associated with consumption of contaminated or undercooked poultry meat. Serotype Infantis is among the most common serotypes isolated from poultry meat products globally. Isolates of serotype Infantis carrying the pESI plasmid, the most dominant strain of Infantis, have been shown to exhibit oxidizer tolerance. Therefore, 16 strains of Salmonella with and without pESI carriage were investigated for susceptibility to biocide chemical processing aids approved for use in US poultry meat processing: peracetic acid (PAA), cetylpyridinium chloride (CPC), calcium hypochlorite, and sodium hypochlorite. Strains were exposed for 15 s to simulate spray application and 90 min to simulate application in an immersion chiller. All strains tested were susceptible to all concentrations of PAA, CPC, and sodium hypochlorite when applied for 90 min. When CPC, calcium hypochlorite, and sodium hypochlorite were applied for 15 s to simulate spray time, strains responded similarly to each other. However, strains responded variably to exposure to PAA. The variation was not statistically significant and appears unrelated to pESI carriage. Results highlight the necessity of testing biocide susceptibility in the presence of organic material and in relevant in situ applications.

Biotechnology & Applied Microbiology↗

Using Trajectory Smoothness Metrics to Identify Drones in Radar Track Data

The identification of unmanned aircraft systems (UAS) using trajectory data is considered. Specifically, a number of smoothness metrics are proposed, which can be used to distinguish UAS from other aerial objects even when they are engaged in accelerative maneuvers (non-constant-velocity flight). The metrics are evaluated on a data set from a UAS sense-and-avoid field test, which contains track data of aerial objects recorded by a vehicle-board radar system during a flight test. The metrics are found to effectively differentiate UAS from other objects such as birds for this data set. In addition, an initial statistical performance analysis of one of the smoothness metrics is undertaken, using 15 data sets deriving from multiple flight tests. The smoothness metric is shown to identify the target UAS with 95% accuracy (95% true positive rate), while achieving a false positive rate of less than 9%.

Sandip Roy↗

Study of muon-induced neutron production using accelerator muon beam at CERN

Cosmogenic muon-induced neutrons are one of the most problematic backgrounds for various underground experiments for rare event searches. In order to accurately understand such backgrounds, experimental data with high-statistics and well-controlled systematics is essential. We performed a test experiment to measure muon-induced neutron production yield and energy spectrum using a high-energy accelerator muon beam at CERN. We successfully observed neutrons from 160 GeV/c muon interaction on lead, and measured kinetic energy distributions for various production angles. Works towards evaluation of absolute neutron production yield is underway. This work also demonstrates that the setup is feasible for a future large-scale experiment for more comprehensive study of muon-induced neutron production.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A Statistics-Based Threshold for the RMS-Energy Oscillation Detector

System operators and reliability coordinators currently rely on extensive baselining studies to set thresholds for their oscillation detectors. The resulting thresholds are based largely on engineering judgment and may vary significantly between organizations. In this paper, statistical distribution theory is used to derive a detection threshold for the widely deployed root-mean-square (RMS)-energy detector. This expression provides a theoretical basis for the detector's configuration, simplifies the process of selecting the threshold, and enables improved consistency among organizations that need to coordinate during system-wide events. Three methods for calculating the threshold using synchrophasor measurements are also proposed. These methods ensure that the threshold can be calculated reliably for various applications. Tests with simulated and field-measured data demonstrate that the statistics-based threshold provides consistent detection of grid disturbances while maintaining a low probability of false alarm.

Follum, James D.↗

Systematic assessment of wellbore integrity for geologic carbon storage projects using regulatory and industry information

Under this three year project, the condition of legacy oil and gas wells in the Midwest United States was evaluated through analysis of well records, well plugging information, CBL evaluation, sustained casing pressure (SCP) field testing, and analysis of hypothetical CO 2 test areas to provide a realistic description of wellbore integrity factors. The research included a state-wide review of oil and gas well records for Ohio and Michigan, along with more detailed testing of wells in Ohio. Results concluded that oil and gas wells are clustered along fields in areas. Well records vary in quality, and there may be wells that have not been identified in records, but there are options for surveying unknown wells. Many of the deep saline formations being considered for CO 2 storage have few wells that penetrate the storage zone or confining layers. Research suggests that a variety of well construction and plugging approaches have been used over time in the region. The project concluded that wellbore integrity is an important issue for CO 2 storage applications in the Midwest United States. Realistic CO 2 storage projects may cover an area in the subsurface with several hundred legacy oil and gas wells. However, closer inspection may often establish that most of the wells do not penetrate the confining layers or storage zone. Therefore, addressing well integrity may be manageable. Field monitoring of SCP also indicated that tested wells provided zonal isolation of the reservoirs they were designed to isolate. Most of these wells appeared to exhibit gas pressure originating from intermediate zones. Based on these results, more flexibility in terms of cementing wells to surface, allowing well testing, and monitoring wells may aid operators in completing CO 2 storage project. Several useful products were developed under this project for examining wellbore integrity for CO 2 storage applications including, a database of over 4 million items on well integrity parameters in the study areas, a systematic CBL evaluation tool for rating cement in boreholes, SCP field testing procedures and analysis methodology, a process for summarizing well integrity at CO 2 storage fields, a statistical analysis of well integrity indicators, and an assessment of practical methods and costs necessary to repair/remediate typical wells in the region based on assessment of six test study areas. Project results may benefit both CO 2 storage and improved oil recovery applications. This study of wellbore integrity is a useful precursor to support development of geologic storage in the Midwest United States because it sheds more light on the actual well conditions (rather than the perceived condition) of historic oil and gas wells in the region.

42 ENGINEERING↗

Gear Performance Improved by Coating

Gears, bearings, and other mechanical elements transmit loads through contacting surfaces. Even if properly designed, manufactured, installed, and maintained, gears and bearings will eventually fail because of the fatigue of the working surfaces. Economical means for extending the fatigue lives of gears and bearings are highly desired, and coatings offer the opportunity to engineer surfaces to extend the fatigue lives of mechanical components. A tungsten-containing diamondlike-carbon coating exhibiting high hardness, low friction, and good toughness was evaluated for application to spur gears. Fatigue testing was done at the NASA Glenn Research Center on both uncoated and coated spur gears. The results showed that the coating extended the surface fatigue lives of the gears by a factor of about 5 relative to the uncoated gears. For the experiments, a lot of spur test gears made from AISI 9310 gear steel were case-carburized and ground to aerospace specifications. The geometries of the 28-tooth, 8-pitch gears were verified as meeting American Gear Manufacturing Association (AGMA) quality class 12. One-half of the gears were randomly selected for coating. The method of coating was selected to achieve desired adherence, toughness, hardness, and low-friction characteristics. First the gears to be coated were prepared by blasting (vapor honing) with Al2O3 particles and cleaning. Then, the gears were provided with a thin adhesion layer of elemental chromium followed by magnetron sputtering of the outer coating consisting of carbon (70 at.%), hydrogen (15 at.%), tungsten (12 at.%), and nickel (3 at.%) (atomic percent at the surface). In total, the coating thickness was about 2.5 to 3 microns. As compared with the steel substrate, the coated surface was harder by a factor of about 2 and had a smaller elastic modulus. All gears were tested using a 5-centistoke synthetic oil, a 10,000-rpm rotation speed, and a hertzian contact stress of at least 1.7 GPa (250 ksi). Tests were run until either surface fatigue occurred or 300 million stress cycles were completed. Tests were run using either a pair of uncoated gears or a pair of coated gears (coated gears mated with uncoated gears were not evaluated). The fatigue test results, shown on Weibull coordinates in the graph, demonstrate that the coating provided substantially longer fatigue lives even though some of the coated gears endured larger stresses. The increase in fatigue life was a factor of about 5 and the statistical confidence for the improvement is high (greater than 99 percent). Examination of the tested gears revealed substantial reductions of total wear for coated gears in comparison to uncoated gears. The coated gear surface topography changed with running, with localized areas of the tooth surface becoming smoother with running. Theories explaining how coatings can extend gear fatigue lives are research topics for coating, tribology, and fatigue specialists. This work was done as a partnership between NASA, the U.S. Army Research Laboratory, United Technologies Research Corporation, and Sikorsky Aircraft.

Krantz, Timothy L.↗

Implementing Software Safety in the NASA Environment

Until recently, NASA did not consider allowing computers total control of flight systems. Human operators, via hardware, have constituted the ultimate safety control. In an attempt to reduce costs, NASA has come to rely more and more heavily on computers and software to control space missions. (For example. software is now planned to control most of the operational functions of the International Space Station.) Thus the need for systematic software safety programs has become crucial for mission success. Concurrent engineering principles dictate that safety should be designed into software up front, not tested into the software after the fact. 'Cost of Quality' studies have statistics and metrics to prove the value of building quality and safety into the development cycle. Unfortunately, most software engineers are not familiar with designing for safety, and most safety engineers are not software experts. Software written to specifications which have not been safety analyzed is a major source of computer related accidents. Safer software is achieved step by step throughout the system and software life cycle. It is a process that includes requirements definition, hazard analyses, formal software inspections, safety analyses, testing, and maintenance. The greatest emphasis is placed on clearly and completely defining system and software requirements, including safety and reliability requirements. Unfortunately, development and review of requirements are the weakest link in the process. While some of the more academic methods, e.g. mathematical models, may help bring about safer software, this paper proposes the use of currently approved software methodologies, and sound software and assurance practices to show how, to a large degree, safety can be designed into software from the start. NASA's approach today is to first conduct a preliminary system hazard analysis (PHA) during the concept and planning phase of a project. This determines the overall hazard potential of the system to be built. Shortly thereafter, as the system requirements are being defined, the second iteration of hazard analyses takes place, the systems hazard analysis (SHA). During the systems requirements phase, decisions are made as to what functions of the system will be the responsibility of software. This is the most critical time to affect the safety of the software. From this point, software safety analyses as well as software engineering practices are the main focus for assuring safe software. While many of the steps proposed in this paper seem like just sound engineering practices, they are the best technical and most cost effective means to assure safe software within a safe system.

Wetherholt, Martha S.↗

Mobile satellite system fade statistics for shadowing and multipath from roadside trees at UHF and L-band

Field tests related to planned mobile satellite systems were performed, and results that add to the existing database of propagation measurements at L-band (1.5 GHz) are described. They are considered particularly useful in that propagation effects were studied systematically, with repeated and controlled runs pertaining to different path elevation angles, road types, and path geometries defining shadowing and line-of-sight modes. In addition, simultaneous L-band and UHF measurements were performed for the purpose of establishing scaling factors applicable to previous UHF (870 MHz) results. The control of the experimental parameters was made possible by using a helicopter as the source platform and a mobile van to house the receiver.

Goldhirsh, Julius↗

Statistical Approach on Utilizing Ground-based Experiments to Model Break-up Events

Two laboratory-based impact tests have been conducted to develop and extend the capability of NASA satellite breakup models. The first experiment, the Satellite Orbital Debris Characterization Impact Test (SOCIT), was conducted by the U.S. Department of Defense and NASA in 1992. It employed a fully functional U.S. Navy Transit spacecraft, fabricated from materials commonly used in the 1960s. SOCIT fragmentation data formed the basis of the current NASA Standard Satellite Breakup Model (SSBM). A second experiment, DebriSat, was conducted in 2014 by the DebriSat consortium: the NASA Orbital Debris Program Office; the United States Space Force Space Systems Command, formerly the Air Force Space and Missile Systems Center, the Air Force Arnold Engineering Development Complex, and the University of Florida. This impact test was performed on a high-fidelity mock-up satellite assembled from modern components. Data from both experiments are expected to contribute to the next-generation models for on-orbit breakup analyses, long-term environment predictions, and debris risk assessment. This paper uses the direct statistical sampling of the SOCIT and DebriSat data ensembles to model an on-orbit breakup event, rather than the analytic expressions estimated from the samples as with as with the NASA SSBM and its predecessor. This direct method involves drawing fragments (i.e., sampling with replacement) from each fragmentation data-subset containing mass, shape category, material density, characteristic length, mass, and cross-sectional area. As part of the sampling process, the properties of sampled fragment data (e.g., area-to-mass ratios) are numerically checked to ensure they do not contain unrealistic quantities. The process to simulate a breakup cloud composed of fragments from SOCIT and DebriSat datasets is discussed. The methodology for ensuring that conservation of overall mass of the sampled fragment cloud under this sampling approach is highlighted. Finally, the results are compared with simulated clouds generated from SSBM for specific historical breakup events.

Andrew Vavrin↗

Statistical Approach on Utilizing Ground-Based Experiments to Model Break-Up Events

Two laboratory-based impact tests have been conducted to develop and extend the capability of NASA satellite breakup models. The first experiment, the Satellite Orbital Debris Characterization Impact Test (SOCIT), was conducted by the U.S. Department of Defense and NASA in 1992. It employed a fully functional U.S. Navy Transit spacecraft, fabricated from materials commonly used in the 1960s. SOCIT fragmentation data formed the basis of the current NASA Standard Satellite Breakup Model (SSBM). A second experiment, DebriSat, was conducted in 2014 by the DebriSat consortium: the NASA Orbital Debris Program Office, the United States Space Force Space Systems Command, formerly the Air Force Space and Missile Systems Center, the Air Force Arnold Engineering Development Complex, and the University of Florida. This impact test was performed on a high-fidelity mock-up satellite assembled from modern components. Data from both experiments are expected to contribute to the next-generation models for on-orbit breakup analyses, long-term environment predictions, and debris risk assessment. This paper uses the direct statistical sampling of the SOCIT and DebriSat data ensembles to model an on-orbit breakup event, rather than the analytic expressions estimated from the samples in the SSBM and its predecessor. This direct method involves drawing fragments (i.e., sampling with replacement) from each fragmentation data-subset containing mass, shape category, material density, characteristic length, mass, and cross-sectional area. As part of the sampling process, the properties of sampled fragment data (e.g., area-to-mass ratios) are numerically checked to ensure they do not contain unrealistic quantities. The process to simulate a breakup cloud composed of fragments from SOCIT and DebriSat datasets is discussed. The methodology for ensuring that conservation of overall mass of the sampled fragment cloud under this sampling approach is highlighted. Finally, the results are compared with simulated clouds generated from SSBM for specific historical breakup events.

Andrew Vavrin↗

Accuracy of Aerodynamic Model Parameters Estimated from Flight Test Data

An important put of building mathematical models based on measured date is calculating the accuracy associated with statistical estimates of the model parameters. Indeed, without some idea of this accuracy, the parameter estimates themselves have limited value. An expression is developed for computing quantitatively correct parameter accuracy measures for maximum likelihood parameter estimates when the output residuals are colored. This result is important because experience in analyzing flight test data reveals that the output residuals from maximum likelihood estimation are almost always colored. The calculations involved can be appended to conventional maximum likelihood estimation algorithms. Monte Carlo simulation runs were used to show that parameter accuracy measures from the new technique accurately reflect the quality of the parameter estimates from maximum likelihood estimation without the need for correction factors or frequency domain analysis of the output residuals. The technique was applied to flight test data from repeated maneuvers flown on the F-18 High Alpha Research Vehicle. As in the simulated cases, parameter accuracy measures from the new technique were in agreement with the scatter in the parameter estimates from repeated maneuvers, whereas conventional parameter accuracy measures were optimistic.

Morelli, Eugene A.↗

Data From Experiments on Bubbling Fluidization of Zeolite in a Rectangular Bubbling Fluidized Bed

Fluidization experiments were conducted in a lab-scale rectangular bubbling fluidized bed with the objective of generating a high-quality dataset for model validation and artificial intelligence/machine learning (AI/ML) training. Zeolite was chosen as the bed material, and the fluidizing medium was air as supplied by a compressor. Three different flow rates at the inlet were chosen such that the particles were fluidized but not elutriated from the system. The test matrix involved randomization and replicates to provide uncertainty estimates as well as four different batches of zeolite as the bed material. The quantities of interest obtained from this study were statistics of differential pressures, interface heights, and particle velocities. Considering all the components of the elaborate test plan, the results obtained were consistent and reproducible. Characterization tests were performed to estimate particle properties including size, density, coefficient of friction, coefficient of restitution, and minimum fluidization velocity. In addition, the angle of repose from granular discharge experiments has been reported to account for rolling friction, though its effect on the overall process is expected to be negligible.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

More Data Needed for Failure Rate Estimation, Validation, and Uncertainty Reduction

Current Environmental Control and Life Support System (ECLSS) development and test activities are not generating data fast enough to provide statistically-supportable precise Orbital Replacement Unit (ORU) failure rate estimates for future missions. Accurate and precise failure rate estimates are critical for missions beyond Low Earth Orbit (LEO) because current risk mitigation approaches – namely regular resupply and rapid abort capabilities – will not be available. Safe operations will depend on mission planners’ ability to accurately forecast spares demand and efficiently provide the necessary resources. However, even after more than a decade of operations on board the International Space Station (ISS), a significant amount of uncertainty remains in failure rate estimates. Uncertain or inaccurate failure rates result in increased risk and spares mass for future missions. A Bayesian failure rate estimation approach, such as the one currently implemented by the ISS Program, can help reduce uncertainty by incorporating engineering judgement into failure rate estimates. However, experience on the ISS and with other complex systems shows that these prior failure rate estimates are often inaccurate. In addition, prior failure rate estimates are typically point values; some level of uncertainty must be added to convert these into probability distributions for Bayesian updating, and there are several potential methods for doing so. Due to the low rate of data collection, these subjective (and often inaccurate) prior estimates currently have a strong influence on the end result. This paper examines the challenges associated with failure rate estimation, validation, and uncertainty reduction in the context of ECLSS development for beyond-LEO missions. A variety of techniques for generating and updating Bayesian priors are discussed and evaluated using both real-world and simulated data. Potential solutions for improving failure rate estimation, including testing additional units, are analyzed and discussed, and a set of recommendations are provided for next-generation system development activities.

Supportability↗

Repeatability of Cryogenic Multilayer Insulation

Due to the variety of requirements across aerospace platforms, and one off projects, the repeatability of cryogenic multilayer insulation has never been fully established. The objective of this test program is to provide a more basic understanding of the thermal performance repeatability of MLI systems that are applicable to large scale tanks. There are several different types of repeatability that can be accounted for: these include repeatability between multiple identical blankets, repeatability of installation of the same blanket, and repeatability of a test apparatus. The focus of the work in this report is on the first two types of repeatability. Statistically, repeatability can mean many different things. In simplest form, it refers to the range of performance that a population exhibits and the average of the population. However, as more and more identical components are made (i.e. the population of concern grows), the simple range morphs into a standard deviation from an average performance. Initial repeatability testing on MLI blankets has been completed at Florida State University. Repeatability of five GRC provided coupons with 25 layers was shown to be +/- 8.4 whereas repeatability of repeatedly installing a single coupon was shown to be +/- 8.0. A second group of 10 coupons have been fabricated by Yetispace and tested by Florida State University, through the first 4 tests, the repeatability has been shown to be +/- 16. Based on detailed statistical analysis, the data has been shown to be statistically significant.

multilayer insulation↗

Guidelines for Design and Analysis of Large, Brittle Spacecraft Components

There were two related parts to this work. The first, conducted at The Aerospace Corporation was to develop and define methods for integrating the statistical theory of brittle strength with conventional finite element stress analysis, and to carry out a limited laboratory test program to illustrate the methods. The second part, separately funded at Aerojet Electronic Systems Division, was to create the finite element postprocessing program for integrating the statistical strength analysis with the structural analysis. The second part was monitored by Capt. Jeff McCann of USAF/SMC, as Special Study No.11, which authorized Aerojet to support Aerospace on this work requested by NASA. This second part is documented in Appendix A. The activity at Aerojet was guided by the Aerospace methods developed in the first part of this work. This joint work of Aerospace and Aerojet stemmed from prior related work for the Defense Support Program (DSP) Program Office, to qualify the DSP sensor main mirror and corrector lens for flight as part of a shuttle payload. These large brittle components of the DSP sensor are provided by Aerojet. This document defines rational methods for addressing the structural integrity and safety of large, brittle, payload components, which have low and variable tensile strength and can suddenly break or shatter. The methods are applicable to the evaluation and validation of such components, which, because of size and configuration restrictions, cannot be validated by direct proof test.

Robinson, E. Y.↗