A study of inert-gas welding process transferability of set-up parameters Final report
Test program and statistical analysis of setup parameter transferability for inert gas welding
STATISTICAL ANALYSIS↗
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Peak-acceleration limiter
Statistical limiter, which protects test specimens during random vibration testing, differentiates between peak acceleration levels that are normal components of vibration signal and those that exhibit damaging characteristics. Device aborts test only when statistical properties of vibration signal change significantly or when catastrophic transient occurs.
Woodbury, R. C.↗
ExMASS: A viable model for authentic student-scientist research partnerships
The Exploration of the Moon and Asteroids by Secondary Students (ExMASS) program provides students the opportunity to conduct authentic, student-led, open-inquiry research with assistance from their teacher and a scientist. One goal of the program is to enhance participants’ attitudes toward science. Most students enter the ExMASS program with positive attitudes toward science. However, the attitude survey developed for ExMASS measured small but statistically significant increases in attitudes. This paper discusses the ExMASS program, an attitude towards science survey designed for the program’s specific audience, and the results of statistical analyses of the survey. The validity of the attitudes survey was tested with an exploratory factor analysis (EFA). The results of the EFA revealed two salient factors measured by the survey: 1) Personal Importance of Science and 2) Importance of Science to Society. A reliability analysis revealed a Cronbach alpha value of 0.89. Paired t-tests revealed statistically significant differences in students’ attitudes before and after the program. For Factor 1, participants’ before scores were statistically significantly lower than their post scores, t(88) = 3.16, p<0.05. For Factor 2, participants’ before scores were statistically significantly lower than their post scores, t(88) = 4.47, p<0.05. ExMASS has been shown to be a practical model for programs designed to increase high school student attitudes toward science. More information on the ExMASS program is available at https://www.lpi.usra.edu/exploration/education/hsResearch/.
science↗
Statistical corrections to numerical predictions. IV
The National Meteorological Center Barotropic-Mesh Model has been used to test a statistical correction procedure, designated as M-II, that was developed in Schemm et al. (1981). In the present application, statistical corrections at 12 h resulted in significant reductions of the mean-square errors of both vorticity and the Laplacian of thickness. Predictions to 48 h demonstrated the feasibility of applying corrections at every 12 h in extended forecasts. In addition to these improvements, however, the statistical corrections resulted in a shift of error from smaller to larger-scale motions, improving the smallest scales dramatically but deteriorating the largest scales. This effect is shown to be a consequence of randomization of the residual errors by the regression equations and can be corrected by spatially high-pass filtering the field of corrections before they are applied.
Schemm, Jae-Kyung↗
Fault detection using a two-model test for changes in the parameters of an autoregressive time series
This article describes an investigation of a statistical hypothesis testing method for detecting changes in the characteristics of an observed time series. The work is motivated by the need for practical automated methods for on-line monitoring of Deep Space Network (DSN) equipment to detect failures and changes in behavior. In particular, on-line monitoring of the motor current in a DSN 34-m beam waveguide (BWG) antenna is used as an example. The algorithm is based on a measure of the information theoretic distance between two autoregressive models: one estimated with data from a dynamic reference window and one estimated with data from a sliding reference window. The Hinkley cumulative sum stopping rule is utilized to detect a change in the mean of this distance measure, corresponding to the detection of a change in the underlying process. The basic theory behind this two-model test is presented, and the problem of practical implementation is addressed, examining windowing methods, model estimation, and detection parameter assignment. Results from the five fault-transition simulations are presented to show the possible limitations of the detection method, and suggestions for future implementation are given.
Scholtz, P.↗
Linear Mixed-Effects Models for Human-in-the-Loop Tracking Experiment Data
Linear mixed-effects models provide several benefits over more traditional statistical inference tests that are particularly useful for most human-in-the-loop tracking experiment data. However, surprisingly, mixed models are virtually not used for the analysis of tracking experiment data. This paper uses of linear mixed-effects models to analyze combined tracking data from two previous human-in-the-loop roll tracking experiments that compared control behavior metrics collected in both a research aircraft and a motion-base simulator. In the experiments, pilots' behavior under 10 different motion configurations with varying motion filter gains and break frequencies was evaluated and compared to that in the real aircraft. The linear mixed-effects model analysis on the combined dataset confirmed the main statistical outcomes of the individual experiments. The main benefits of mixed models for this type of data were demonstrated by successfully combining data from two experiments that used different experimental conditions and of which one had an additional apparatus and the other a missing participant. Finally, the mixed-model analysis was able to explicitly test for scientifically relevant statistical differences in the dependent measures between the aircraft and simulator, as well as both experiments.
manual control↗
Combined dietary and exercise intervention for control of serum cholesterol in the workplace
PURPOSE: To elucidate a potential combined dietary and exercise intervention affect on cardiovascular risk reduction of the National Aeronautics and Space Administration Headquarters employees. DESIGN: A nonexperimental, longitudinal, clinical-chart review study (1987 to 1996) of an identified intervention group and a reference (not a control) group. SETTING: The study group worked in an office environment and participated in the annual medical examinations. SUBJECTS: An intervention group of 858 people with initially elevated serum cholesterol, and a reference group of 963 people randomly sampled from 10% of the study group. MEASURES: Serum cholesterol data were obtained for both groups, respectively, from pre- and postintervention and annual examinations. The reference group was adjusted by statistical exclusion of potential intervention participants. Regression equations (cholesterol vs. study years) for the unadjusted/adjusted reference groups were tested for statistical significance. INTERVENTION: An 8-week individualized, combined dietary and exercise program was instituted with annual follow-ups and was repeated where warranted. RESULTS: Only the unadjusted (but not the adjusted) reference group with initial mean total serum cholesterol levels above 200 mg/dL shows a significant 9-year decline trend and significant beta coefficient tests. An intervention effect is suggested. Mean high density lipoprotein cholesterol rose slightly in the intervention group but was maintained in the reference group. CONCLUSION: With potential design limitations, the NASA intervention program focusing on a high risk group may be associated to some degree, if not fully, with an overall cardiovascular risk profile improvement.
Occupational Health Services↗
Shuttle payload vibroacoustic test plan evaluation
Statistical decision theory is used to evaluate seven alternate vibro-acoustic test plans for Space Shuttle payloads; test plans include component, subassembly and payload testing and combinations of component and assembly testing. The optimum test levels and the expected cost are determined for each test plan. By including all of the direct cost associated with each test plan and the probabilistic costs due to ground test and flight failures, the test plans which minimize project cost are determined. The lowest cost approach eliminates component testing and maintains flight vibration reliability by performing subassembly tests at a relatively high acoustic level.
Stahle, C. V.↗
A simple test of independence for truncated data with applications to redshift surveys
This paper presents an easily applied permutation test for H0, closely related to Lyden-Bell's (1971) estimate of the marginal distribution of truncated data. The test is applied to two redshift-magnitude surveys, one of galaxies and one of quasars. Assuming statistical independence, testing H0 amounts to testing validity of the cosmological model. Segal's (1986) chronomatic cosmological model is rejected under H0. On the other hand, for the quasar sample H0 is rejected strongly in a conventional cosmological model (and in a chronomatic model as well) indicating either incorrectness of the models or, as is more commonly assumed, indicating strong luminosity evolution.
Efron, Bradley↗
Determination of the Corrosive Conditions Present within Aircraft Lap-Splice Joints
The complexity of airframe structure lends itself to damage resulting from crevice corrosion. Fuselage lap-splice joints are a particularly important structural detail in this regard because of the difficulty associated with detection and measurement of corrosion in these occluded regions. The objective of this work is to develop a laboratory corrosion test protocol to identify the chemistry to which lap joints are exposed and to develop a model of the corrosion within the joints. A protocol for collecting and identifying the chemistry of airframe crevice corrosion has been developed. Capillary electrophoresis (CE) is used to identify the ionic species contained in corrosion product samples removed from fuselage lap splice joints. CE analysis has been performed on over sixty corrosion product samples removed from both civilian and military aircraft. Over twenty different ions have been detected. Measurements of pH of wetted corroded surfaces indicated an alkaline occluded solution. After determining the species present and their relative concentrations, the resultant solution was reproduced in bulk and electrochemical tests were performed to determine the corrosion rate. Electrochemical analyses of the behavior of AA2024-T3 in these solutions gave corrosion rates of up to 250 microns per year (10 mpy). Additional tests have determined the relative importance of each of the detected ions in model solutions used for future predictive tests. The statistically significant ions have been used to create a second generation solution. Laboratory studies have also included exposure tests involving artificial lap joints exposed to various simulated bulk and crevice environments. The extent and morphology of the attack in artificial lap joints has been compared to studies of corroded samples from actual aircraft. Other effects, such as temperature and potential, as well as the impact of the environment on fatigue crack growth have also been studied.
Lewis, Karen S.↗
JAN transistor and diode characterization test program
A statistical summary of electrical characterization was performed on JAN diodes and transistors. Parameters are presented with test conditions, mean, standard deviation, lowest reading, 10% point, 90% point and highest reading.
Takeda, H.↗
QuantifyML: How good is my machine learning model?
This paper presents an approach, QuantifyML, which employs model counting to assess the learnability and robustness of machine learning models. Typically the efficacy of machine learning models is determined by computing their accuracy statistically on test data sets. However, this may be misleading, if the test data is not representative of the problem that is being studied. Further, two different models may have the same accuracy on a given data set, measured statistically, but may be very different in their behavior on unseen data. Also, models with high accuracy could have poor adversarial robustness. In QuantifyML, our goal is to precisely quantify the extent to which machine learning models have learned and generalized from the given data. In QuantifyML, a trained model is translated into a C program, which is fed to the CBMC model checking tool to produce a formula in Conjunctive Normal Form (CNF), which in turn is analyzed with state-of-the-art model counters to efficiently obtain precise counts w.r.t different outputs. QuantifyML enables i) evaluating the learnability of models by comparing the counts for the outputs to ground truth, expressed as logical predicates (if available), ii) comparing the performance of different models that may be built with different machine learning algorithms (e.g., decision-trees vs. neural networks), and iii) quantifying the robustness of trained models around given inputs. Our evaluation demonstrates these applications of QuantifyML on decision trees and neural networks trained to learn relational properties of graphs, for which we know the ground truth, and to perform image classification, for which we do not have the ground truth, but we can quantify local robustness.
Deep Neural Networks↗
Statistical modeling of scintillation effects
Scintillation produces fluctuation of the complex envelope of a modulated signal. A useful way to characterize scintillation effects is to describe the signal statistics that result when a CW wave is transmitted through a random medium. Many theoretical treatments describe the signal statistics in a manner identical with the noise theory of Rice. These theories, however, predict Rice statistics only at a very great distance from the perturbing medium, and it has been suspected that generalization to permit the quadrature components of the scattered signal to be partially correlated Gaussian variates might better match the observed signal statistics. Recent tests of signals observed through three types of structured plasma have consistently confirmed this speculation and have revealed a surprising consistency in parameters describing the first-order signal statistics.
Fremouw, E. J.↗
Assessing the Relationships Between Sensorimotor Biomarkers and Post-Landing Functional Task Performance
Spaceflight drives adaptive changes in healthy individuals appropriate for sensorimotor function in a microgravity environment. These changes are maladaptive for return to earth's gravity. The inter-individual variability of sensorimotor decrements is striking, although poorly understood. The goal of this study was to identify a set of behavioral, neuroimaging and genetic measures that can be used to predict early post-flight performance on a set of sensorimotor tasks. Astronauts were recruited who previously participated in sensorimotor field tests and/or posturography soon after long-duration spaceflight. Behavioral tests included assessments of sensory dependency and adaptability. Visual dependency involved treadmill walking while viewing a moving virtual visual scene. Vestibular perceptual thresholds were measured while seated during lateral translations. Proprioception dependency was measured during one-legged stance on a horizontal air-bearing surface. Ground assessment of adaptability was performed (1) during treadmill walking with a virtual linear hallway and a moving walking surface, and (2) during multiple trials of navigating an obstacle course while wearing reversing prisms (adaptive Functional Mobility Test, aFMT). The neuroimaging tests characterized individual differences in regional brain volumes (using Structural MRI) and white matter microstructure (using Diffusion Tensor Imaging) to serve as potential predictors of adaptive capacity. The genetic tests utilized saliva samples to examine variations in four genes chosen because of their ability to differentiate sensorimotor adaptation ability in a normative population, including Catechol-O-methyltransferase (COMT), Dopamine Receptor D2 (DRD2), Brain-derived neurotrophic factor (BDNF) and the α2-adrenergic receptor. Thirty ISS crewmembers were recruited, including 12 first-time fliers, 6F, and mission durations lasting 185.5 ± 45.5 days, mean ± std. We utilized a combination of three post-flight functional task outcomes: tandem walk, recovery from fall and dynamic posturography. There was considerable variability among all post-flight performance outcomes. Based on an ordinal scale survey, 72% indicated their ability to perform functional tasks were more impacted postflight relative to inflight with 50% indicating they needed to restrict movements for a longer period postflight relative to inflight. While there is a strong association within tests obtained at different R+0 timepoints, by R+24 hr performance on one post-flight test does not necessarily correlate with performance on other post-flight tests. Preliminary statistical analysis indicates combining biomarkers will increase predictive power and this will be explored with future analyses. Our preliminary findings underscore the importance of a comprehensive post-flight test battery including different types of tasks with varying sensory feedback. Understanding the relationships between these sensorimotor biomarkers and post-flight functional task performance improve both our understanding of the individual variability and our strategy to optimize sensorimotor countermeasures.
biomarkers↗
An evaluation of grease ball bearing lubricants in vacuum
Because many future spacecraft will require mechanisms to operate for long periods of time in environments which are inimical to most bearing lubricants, a series of tests has been started to evaluate 25 grease type lubricants in R-4 size bearings in vacuum at ambient temperature for a 1 year period. Four repetitions of each test are made to provide statistical samples. These tests will be used to select from two to five lubricants for 5 year tests in the same environment. At the present time fifteen test sets have been completed and five sets are being tested. The best results to date have been obtained with perfluoropolyether greases.
Demorest, K. E.↗
An evaluation of grease type ball bearing lubricants operating in various environments /Status report no. 2/
Because many future spacecraft or space stations will require mechanisms to operate for long periods of time in environments which are inimical to most bearing lubricants, a series of tests has been started to evaluate 25 grease type lubricants in R-4 size bearings in five different environments for a 1 year period. Four repetitions of each test are made to provide statistical samples. These tests will be used to select from two to five lubricants for 5 year tests in the same environments. At the present time, approximately 30 test sets have been completed and 25 sets are underway. To date, best results in all environments have been obtained with a high viscosity index perfluoropolyether grease.
Demorest, K. E.↗
Terrestrial photovoltaic cell process testing
The paper examines critical test parameters, criteria for selecting appropriate tests, and the use of statistical controls and test patterns to enhance PV-cell process test results. The coverage of critical test parameters is evaluated by examining available test methods and then screening these methods by considering the ability to measure those critical parameters which are most affected by the generic process, the cost of the test equipment and test performance, and the feasibility for process testing.
Burger, D. R.↗
SEE Rate Estimation: Model Complexity and Data Requirements
Statistical Methods outlined in [Ladbury, TNS20071 can be generalized for Monte Carlo Rate Calculation Methods Two Monte Carlo Approaches: a) Rate based on vendor-supplied (or reverse-engineered) model SEE testing and statistical analysis performed to validate model; b) Rate calculated based on model fit to SEE data Statistical analysis very similar to case for CREME96. Information Theory allows simultaneous consideration of multiple models with different complexities: a) Model with lowest AIC usually has greatest predictive power; b) Model averaging using AIC weights may give better performance if several models have similar good performance; and c) Rates can be bounded for a given confidence level over multiple models, as well as over the parameter space of a model.
Ladbury, Ray↗