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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Statistical energy analysis of a geared rotor system

The vibroacoustic response of a generic geared rotor system is analyzed on an order of magnitude basis utilizing an approximate statistical energy analysis method. This model includes a theoretical coupling loss factor for a generic bearing component, which properly accounts for the vibration transmission through rolling element bearing. A simplified model of a NASA test stand that assumes vibratory energy flow from the gear mesh source to the casing through shafts and bearings is given as an example. Effects of dissipation loss factor and gearbox radiation efficiency models are studied by comparing predictions with NASA test results.

Lim, Teik C.↗
NASA NTRS1998

T wave alternans as a predictor of recurrent ventricular tachyarrhythmias in ICD recipients: prospective comparison with conventional risk markers

INTRODUCTION: The current standard for arrhythmic risk stratification is electrophysiologic (EP) testing, which, due to its invasive nature, is limited to patients already known to be at high risk. A number of noninvasive tests, such as determination of left ventricular ejection fraction (LVEF) or heart rate variability, have been evaluated as additional risk stratifiers. Microvolt T wave alternans (TWA) is a promising new risk marker. Prospective evaluation of noninvasive risk markers in low- or moderate-risk populations requires studies involving very large numbers of patients, and in such studies, documentation of the occurrence of ventricular tachyarrhythmias is difficult. In the present study, we identified a high-risk population, recipients of an implantable cardioverter defibrillator (ICD), and prospectively compared microvolt TWA with invasive EP testing and other risk markers with respect to their ability to predict recurrence of ventricular tachyarrhythmias as documented by ICD electrograms. METHODS AND RESULTS: Ninety-five patients with a history of ventricular tachyarrhythmias undergoing implantation of an ICD underwent EP testing, assessment of TWA, as well as determination of LVEF, baroreflex sensitivity, signal-averaged ECG, analysis of 24-hour Holter monitoring, and QT dispersion from the 12-lead surface ECG. The endpoint of the study was first appropriate ICD therapy for electrogram-documented ventricular fibrillation or tachycardia during follow-up. Kaplan-Meier survival analysis revealed that TWA (P < 0.006) and LVEF (P < 0.04) were the only significant univariate risk stratifiers. EP testing was not statistically significant (P < 0.2). Multivariate Cox regression analysis revealed that TWA was the only statistically significant independent risk factor. CONCLUSIONS: Measurement of microvolt TWA compared favorably with both invasive EP testing and other currently used noninvasive risk assessment methods in predicting recurrence of ventricular tachyarrhythmias in ICD recipients. This study suggests that TWA might also be a powerful tool for risk stratification in low- or moderate-risk patients, and needs to be prospectively evaluated in such populations.

Non-NASA Center↗
NASA NTRS2007

Analyzing Responses of Chemical Sensor Arrays

NASA is developing a third-generation electronic nose (ENose) capable of continuous monitoring of the International Space Station s cabin atmosphere for specific, harmful airborne contaminants. Previous generations of the ENose have been described in prior NASA Tech Briefs issues. Sensor selection is critical in both (prefabrication) sensor material selection and (post-fabrication) data analysis of the ENose, which detects several analytes that are difficult to detect, or that are at very low concentration ranges. Existing sensor selection approaches usually include limited statistical measures, where selectivity is more important but reliability and sensitivity are not of concern. When reliability and sensitivity can be major limiting factors in detecting target compounds reliably, the existing approach is not able to provide meaningful selection that will actually improve data analysis results. The approach and software reported here consider more statistical measures (factors) than existing approaches for a similar purpose. The result is a more balanced and robust sensor selection from a less than ideal sensor array. The software offers quick, flexible, optimal sensor selection and weighting for a variety of purposes without a time-consuming, iterative search by performing sensor calibrations to a known linear or nonlinear model, evaluating the individual sensor s statistics, scoring the individual sensor s overall performance, finding the best sensor array size to maximize class separation, finding optimal weights for the remaining sensor array, estimating limits of detection for the target compounds, evaluating fingerprint distance between group pairs, and finding the best event-detecting sensors.

Zhou, Hanying↗
NASA NTRS1994

Statistical analysis of microgravity experiment performance using the degrees of success scale

This paper describes an approach to identify factors that significantly influence microgravity experiment performance. Investigators developed the 'degrees of success' scale to provide a numerical representation of success. A degree of success was assigned to 293 microgravity experiments. Experiment information including the degree of success rankings and factors for analysis was compiled into a database. Through an analysis of variance, nine significant factors in microgravity experiment performance were identified. The frequencies of these factors are presented along with the average degree of success at each level. A preliminary discussion of the relationship between the significant factors and the degree of success is presented.

Upshaw, Bernadette↗
NASA NTRS1978

Linear stochastic control using the UDU matrix factorization

The classical LQG stochastic control law is reformulated using the matrix factorization S equals UDU super T. This method yields a statistical guidance analysis algorithm that is numerically superior to the classical solution yet requires negligible additional computation and storage. Moreover, experience with U-D algorithms has shown them to be adaptable and easy to implement on a variety of problems.

Thornton, C. L.↗
NASA NTRS2003

Ectomycorrhizal Community Structure and Soil Characteristics of Mature Lodgepole Pine (Pinus Contorta) and Adjacent Stands of Old Growth Mixed Conifer in Yellowstone National Park, Wyoming USA

Forest development patterns following disturbance are known to influence the physical and chemical attributes of soils at different points in time. Changes in soil resources are thought to have a corresponding effect on ectomycorrhizal (ECM) community structure. We used molecular methods to compare below-ground ECM species richness, composition, and abundance between adjacent stands of homogenous lodgepole pine and old growth mixed conifer in Yellowstone National Park (YNP). In each stand-type we collected soil cores to both identify mycorrhizae and assess soil chemistry. Although no statistical difference was observed in the mean number of ECM root tips per core between stand types, the total number of species identified (85 versus 35) and the mean number of species per core (8.8 +/- 0.6 versus 2.5 +/- 0.3) were significantly higher in lodgepole pine. Differences between the actual and estimated species richness levels indicated that these forest types support a high number of ECM species and that undersampling was severe. Species compositions were widely disparate between stands where only four species were shared out of a total of 116. Soil analysis also revealed that mixed conifer was significantly lower in pH, but higher in organic matter, potassium, phosphorus, and ammonium when compared to lodgepole pine stands. Species richness per core was correlated with these chemical data, however, analysis of covariance indicated that stand type was the only statistically significant factor in the observed difference in species richness. Our data suggest that ECM fungal richness increases as homogenous lodgepole pine stands grow and mature, but declines after Engelmann spruce and subalpine fir colonize. Despite difficulties linking species composition with soil chemistry, there are a variety of physical and chemical factors that could be influencing ECM community structure. Future field experiments are necessary to test some of the mechanisms potentially operating within this system.

Douglas, Robert B.↗
NASA NTRS2020

Charles River Watershed Water Resources: Assessing Flooding Vulnerability to Assist High Water Intervention and Urban Planning Programs in the Charles River Watershed

The Charles River watershed intersects 35 municipalities within the Boston Metropolitan Area and has a population of 1.2 million, making it one of the most densely populated watersheds in New England. In recent years, the watershed has observed higher rates of flood inundation, mainly due to increased development, extreme precipitation events, and increased surface runoff. As the frequency of flood events increases and a changing climate poses an ongoing threat to local communities, governments, and organizations in Massachusetts need accurate flood risk assessments. This project partnered with the Charles River Watershed Association, the Town of Natick’s Office of Sustainability, and the Massachusetts Audubon Society to assess the potential for watershed degradation, flood vulnerability, and flood susceptibility in the watershed. The team used Landsat 5 Thematic Mapper (TM), Landsat 8 Operational Land Imager (OLI), Sentinel-1 C-Band Synthetic Aperture Radar (C-SAR), and Sentinel-2 MultiSpectral Instrument (MSI) to assess the feasibility of identifying flood events using remote sensing. After identifying images that overlapped with the reported flood events, the team concluded that it was not feasible to use Earth observation data to detect localized flooding. Instead, the Federal Emergency Management Agency (FEMA) 100-year floodplain was used as a proxy for areas where flooding may occur. The team used statistical analysis and supervised classification to develop a flood susceptibility map, incorporating factors like soil drainage, height above nearest drainage, and topographic wetness index. This was overlaid with demographic and socioeconomic data to create a flood vulnerability map. The flood susceptibility map captured over 2/3 of reported flood events in the watershed, an improvement over the 1/3 of events captured by the FEMA 100-year and 500-year floodplain maps.

DEVELOP Project Summary↗
NASA NTRS2002

Multiple Component Event-Related Potential (mcERP) Estimation

We show how model-based estimation of the neural sources responsible for transient neuroelectric signals can be improved by the analysis of single trial data. Previously, we showed that a multiple component event-related potential (mcERP) algorithm can extract the responses of individual sources from recordings of a mixture of multiple, possibly interacting, neural ensembles. McERP also estimated single-trial amplitudes and onset latencies, thus allowing more accurate estimation of ongoing neural activity during an experimental trial. The mcERP algorithm is related to informax independent component analysis (ICA); however, the underlying signal model is more physiologically realistic in that a component is modeled as a stereotypic waveshape varying both in amplitude and onset latency from trial to trial. The result is a model that reflects quantities of interest to the neuroscientist. Here we demonstrate that the mcERP algorithm provides more accurate results than more traditional methods such as factor analysis and the more recent ICA. Whereas factor analysis assumes the sources are orthogonal and ICA assumes the sources are statistically independent, the mcERP algorithm makes no such assumptions thus allowing investigators to examine interactions among components by estimating the properties of single-trial responses.

Knuth, K. H.↗
NASA NTRS1982

Effects of miso- and mesoscale obstructions on PAM winds obtained during project NIMROD

Data from 27 PAM (Portable Automated Mesonet) stations, operational as a phase of project NIMROD (Northern Illinois Meteorological Research on Downburst), are presented. It was found that PAM-measured winds are influenced by the mesoscale obstruction of the Chicago metropolitan area, as well as by the misoscale obstruction of identified trees and buildings. The mesoscale obstruction was estimated within the range of near zero to 50%, increasing toward the city limits, while the misoscale obstruction was estimated as being as large as 58% near obstructing trees which were empirically calculated to cause a wind speed deficit 50-80 times their height. Despite a statistical analysis based on one-million PAM winds, wind speed and stability transmission factors could not be accurately calculated; thus, in order to calculate the airflow free from obstacle, PAM-measured winds must be corrected.

Fujita, T. T.↗
NASA NTRS1987

Zirconia toughened SiC whisker reinforced alumina composites small business innovation research

The objective of this phase 1 project was to develop a ceramic composite with superior fracture toughness and high strength, based on combining two toughness inducing materials: zirconia for transformation toughening and SiC whiskers for reinforcement, in a controlled microstructure alumina matrix. The controlled matrix microstructure is obtained by controlling the nucleation frequency of the alumina gel with seeds (submicron alpha-alumina). The results demonstrate the technical feasibility of producing superior binary composites (Al2O3-ZrO2) and tertiary composites (Al2O3-ZrO2-SiC). Thirty-two composites were prepared, consolidated, and fracture toughness tested. Statistical analysis of the results showed that: (1) the SiC type is the key statistically significant factor for increased toughness; (2) sol-gel processing with a-alumina seed had a statistically significant effect on increasing toughness of the binary and tertiary composites compared to the corresponding mixed powder processing; and (3) ZrO2 content within the range investigated had a minor effect. Binary composites with an average critical fracture toughness of 6.6MPam sup 1/2, were obtained. Tertiary composites with critical fracture toughness in the range of 9.3 to 10.1 MPam sup 1/2 were obtained. Results indicate that these composites are superior to zirconia toughened alumina and SiC whisker reinforced alumina ceramic composites produced by conventional techniques with similar composition from published data.

Loutfy, R. O.↗
NASA NTRS2019

Large Contribution of Meteorological Factors to Inter-Decadal Changes in Regional Aerosol Optical Depth

Aerosol optical depth (AOD) has become a crucial metric for assessing global climate change. Although global and regional AOD trends have been studied extensively, it remains unclear what factors are driving the inter-decadal variations in regional AOD and how to quantify the relative contribution of each dominant factor. This study used a long-term (1980–2016) aerosol dataset from the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) reanalysis, along with two satellite-based AOD datasets (MODIS/Terra and MISR) from 2001 to 2016, to investigate the long-term trends in global and regional aerosol loading. Statistical models based on emission factors and meteorological parameters were developed to identify the main factors driving the inter-decadal changes of regional AOD and to quantify their contribution. Evaluation of the MERRA-2 AOD with the ground-based measurements of AERONET indicated significant spatial agreement on the global scale (r= 0.85, root-mean-square error = 0.12, mean fractional error = 38.7 %, fractional gross error = 9.86 % and index of agreement = 0.94). However, when AOD observations from the China Aerosol Remote Sensing Network (CARSNET) were employed for independent verification, the results showed that MERRA-2 AODs generally underestimated CARSNET AODs in China (relative mean bias = 0.72 and fractional gross error =−34.3 %). In general, MERRA-2 was able to quantitatively reproduce the annual and seasonal AOD trends on both regional and global scales, as observed by MODIS/Terra, although some differences were found when compared to MISR. Over the 37-year period in this study, significant decreasing trends were observed over Europe and the eastern United States. In contrast, eastern China and southern Asia showed AOD increases, but the increasing trend of the former reversed sharply in the most recent decade. The statistical analyses suggested that the meteorological parameters explained a larger proportion of the AOD variability (20.4 %–72.8 %) over almost all regions of interest (ROIs) during 1980–2014 when compared with emission factors (0 %–56 %). Further analysis also showed that SO2 was the dominant emission factor, explaining 12.7 %–32.6 % of the variation in AOD over anthropogenic-aerosol-dominant regions, while black carbon or organic carbon was the leading factor over the biomass-burning-dominant (BBD) regions, contributing 24.0 %–27.7 % of the variation. Additionally, wind speed was found to be the leading meteorological parameter, explaining 11.8 %–30.3 % of the variance over the mineral-dust-dominant regions, while ambient humidity (including soil moisture and relative humidity) was the top meteorological parameter over the BBD regions, accounting for 11.7 %–35.5 % of the variation. The results of this study indicate that the variation in meteorological parameters is a key factor in determining the inter-decadal change in regional AOD.

Huizheng Che↗
NASA NTRS1999

A procedure of multiple period searching in unequally spaced time-series with the Lomb-Scargle method

Periodogram analysis of unequally spaced time-series, as part of many biological rhythm investigations, is complicated. The mathematical framework is scattered over the literature, and the interpretation of results is often debatable. In this paper, we show that the Lomb-Scargle method is the appropriate tool for periodogram analysis of unequally spaced data. A unique procedure of multiple period searching is derived, facilitating the assessment of the various rhythms that may be present in a time-series. All relevant mathematical and statistical aspects are considered in detail, and much attention is given to the correct interpretation of results. The use of the procedure is illustrated by examples, and problems that may be encountered are discussed. It is argued that, when following the procedure of multiple period searching, we can even benefit from the unequal spacing of a time-series in biological rhythm research.

NASA Discipline Space Human Factors↗
NASA NTRS1981

Variation Principles and Applications in the Study of Cell Structure and Aging

In this report we have attempted to show that "some reality lies concealed in biological variation". This "reality" has its principles, laws, mechanisms, and rules, only a few of which we have sketched. A related idea we pursued was that important information may be lost in the process of ignoring frequency distributions of physiological variables (as is customary in experimental physiology and gerontology). We suggested that it may be advantageous to expand one's "statistical field of vision" beyond simple averages +/- standard deviations. Indeed, frequency distribution analysis may make visible some hidden information not evident from a simple qualitative analysis, particularly when the effect of some external factor or condition (e.g., aging, dietary chemicals) is being investigated. This was clearly illustrated by the application of distribution analysis in the study of variation in mouse liver cellular and fine structure, and may be true of fine structural studies in general. In living systems, structure and function interact in a dynamic way; they are "inseparable," unlike in technological systems or machines. Changes in fine structure therefore reflect changes in function. If such changes do not exceed a certain physiologic range, a quantitative analysis of structure will provide valuable information on quantitative changes in function that may not be possible or easy to measure directly. Because there is a large inherent variation in fine structure of cells in a given organ of an individual and among individuals, changes in fine structure can be analyzed only by studying frequency distribution curves of various structural characteristics (dimensions). Simple averages +/- S.D. do not in general reveal all information on the effect of a certain factor, because often this effect is not uniform; on the contrary, this will be apparent from distribution analysis because the form of the curves will be affected. We have also attempted to show in this chapter that similar general statistical principles and mechanisms may be operative in biological and technological systems. Despite the common belief that most biological and technological characteristics of interest have a symmetric bell-shaped (normal or Gaussian) distribution, we have shown that more often than not, distributions tend to be asymmetric and often resemble a so-called log-normal distribution. We saw that at least three general mechanisms may be operative, i.e., nonadditivity of influencing factors, competition among individuals for a common resource, and existence of an "optimum" value for a studied characteristic; more such mechanisms could exist.

Economos, Angelos C.↗
NASA NTRS2014

MARGInS: Model-Based Analysis of Realizable Goals in Systems

Under NASAs Constellation effort, the Exploration Technology Development Program funded research toward a system validation capability that applied machine learning and test-case generation techniques to the analysis of black-box system behavior. The behavior analysis capability scaled to spaces of hundreds of input parameters and tens of thousands of test cases. Aerospace systems at the vehicle level, especially those systems which contain some level of autonomy, are best described by hybrid and non-linear mathematics. Even simplified models of such systems need parameter dimensionalities in the hundreds or thousands of parameters in order to capture sufficient fidelity. The System Safety Assessments (such as those described in the SAE ARP 4761A Safety Assessment Process guidelines) for these systems are prone to errorinteractions between the vehicles subsystems are complex, and can display emergent behaviors. NASA captured this new analysis in the Model-based Analysis of Realizable Goals in Systems (MARGInS) tool and applied it to the Pad Abort 1 (PA-1) simulation as part of the independent validation and verification cycle before the PA-1 flight test in May of 2010. MARGInS evaluated the adherence of the high-fidelity simulation to its requirements, and deter- mined the margins to failure from the expected nominal input conditions. Following the PA-1 test, the capabilities within the MARGInS framework have been extended with sophisticated statistical and white-box test case generation techniques and applied to other NASA missions. The frame- work now includes a critical factors analysis that was applied to NASAs Orion simulation and design. NASAs Aeronautics Research Mission Directorate (ARMD) leveraged the existing MARGInS framework for work on aviation safety for civil transport vehicles and for research on autonomy issues. The NASA ARMD effort created a time series output prediction capability that has been used to characterize trajectories for a plane with an adaptive control system, and a safety boundary detection capability that has been applied to an air traffic control concept of operation for the Federal Aviation Administration. The statistical and machine- learning based techniques within MARGInS have been successfully combined with concolic execution to improve the coverage of a critical unit by driving system-level inputs. The use case driving the concolic execution and MARGInS integration was inspired by the Air France 447 disaster in which the loss of a critical functionality (the airspeed calculation from the pitot tubes) led to loss of the entire plane with the people aboard. To illustrate capabilities and limitations, we will highlight the analyses for the applications listed above. We will then discuss the future plans for MARGInS and its interfaces with other tools.

Validation↗
NASA NTRS1985

An Integrated Analysis of the Physiological Effects of Space Flight: Executive Summary

A large array of models were applied in a unified manner to solve problems in space flight physiology. Mathematical simulation was used as an alternative way of looking at physiological systems and maximizing the yield from previous space flight experiments. A medical data analysis system was created which consist of an automated data base, a computerized biostatistical and data analysis system, and a set of simulation models of physiological systems. Five basic models were employed: (1) a pulsatile cardiovascular model; (2) a respiratory model; (3) a thermoregulatory model; (4) a circulatory, fluid, and electrolyte balance model; and (5) an erythropoiesis regulatory model. Algorithms were provided to perform routine statistical tests, multivariate analysis, nonlinear regression analysis, and autocorrelation analysis. Special purpose programs were prepared for rank correlation, factor analysis, and the integration of the metabolic balance data.

Leonard, J. I.↗
NASA NTRS1988

Fuel neutralization by ozone oxidation

The viability of a hazardous waste disposal system based on ozone oxidation of hydrazine fuels at low aqueous concentrations in the presence of ultraviolet light (UV at 2.537 x 10(exp -7) m or 8.324 x 10(exp -7) ft) excitation was investigated. Important parameters investigated include temperature, solution pH, and ultraviolet light power. Statistically relevant experimentation was done to estimate main factor effects on performance. The best available chemical analysis technology was used to evaluate the performance of the system.

Swartz, A. B.↗
NASA NTRS1976

Subjective assessment of simulated helicopter blade-slap noise

The effects of several characteristics of helicopter blade slap upon human annoyance are examined. Blade slap noise was simulated by using continuous and impulsive noises characterized by five parameters: The number of sine waves in a single impulse; the frequency of the sine waves; the impulse repetition frequency; the sound pressure level (SPL) of the continuous noise; and the idealized crest factor of the impulses. Ten second samples of noise were synthesized with each of the five parameters at representative levels. The annoyance of each noise was judged by 40 human subjects. Analysis of the subjective data indicated that each of the five parameters had a statistically significant effect upon the annoyance judgments. The impulse crest factor and SPL of the continuous noise had very strong positive relationships with annoyance. The other parameters had smaller, but still significant, effects upon the annoyance judgments.

Lawton, B. W.↗
NASA NTRS1994

Improving Learning Performance Through Rational Resource Allocation

This article shows how rational analysis can be used to minimize learning cost for a general class of statistical learning problems. We discuss the factors that influence learning cost and show that the problem of efficient learning can be cast as a resource optimization problem. Solutions found in this way can be significantly more efficient than the best solutions that do not account for these factors. We introduce a heuristic learning algorithm that approximately solves this optimization problem and document its performance improvements on synthetic and real-world problems.

resource optimization↗