Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “variability analysis”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Remote sensing of global snowpack energy and mass balance: In-situ measurements on the snow of interior and Arctic Alaska

This project is continuing along the lines of the semiannual report dated January 1993. Four major tasks have been addressed: analysis of variability in the seasonal snow of interior and arctic Alaska, the interpretation of microwave brightness temperature across Alaska on transects from south to north, study of nonclimatic controls which affect glaciers, and the location of glacier facies boundaries.

Benson, Carl S.↗
NASA NTRS1997

Asteroseismology of White Dwarf Stars

The primary purpose of this investigation has been to study various aspects of multimode pulsations in variable white dwarfs. In particular, nonlinear interactions among pulsation modes in white dwarfs (and, to some extent, in other variable stars), analysis of recent observations where such interactions are important, and preliminary work on the effects of crystallization in cool white dwarfs are reported.

Hansen, Carl J.↗
NASA NTRS1999

Statistical Quality Control of Moisture Data in GEOS DAS

A new statistical quality control algorithm was recently implemented in the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The final step in the algorithm consists of an adaptive buddy check that either accepts or rejects outlier observations based on a local statistical analysis of nearby data. A basic assumption in any such test is that the observed field is spatially coherent, in the sense that nearby data can be expected to confirm each other. However, the buddy check resulted in excessive rejection of moisture data, especially during the Northern Hemisphere summer. The analysis moisture variable in GEOS DAS is water vapor mixing ratio. Observational evidence shows that the distribution of mixing ratio errors is far from normal. Furthermore, spatial correlations among mixing ratio errors are highly anisotropic and difficult to identify. Both factors contribute to the poor performance of the statistical quality control algorithm. To alleviate the problem, we applied the buddy check to relative humidity data instead. This variable explicitly depends on temperature and therefore exhibits a much greater spatial coherence. As a result, reject rates of moisture data are much more reasonable and homogeneous in time and space.

Dee, D. P.↗
NASA NTRS1993

Alveolar ventilation to perfusion heterogeneity and diffusion impairment in a mathematical model of gas exchange

This study describes a two-compartment model of pulmonary gas exchange in which alveolar ventilation to perfusion (VA/Q) heterogeneity and impairment of pulmonary diffusing capacity (D) are simultaneously taken into account. The mathematical model uses as input data measurements usually obtained in the lung function laboratory. It consists of two compartments and an anatomical shunt. Each compartment receives fractions of alveolar ventilation and blood flow. Mass balance equations and integration of Fick's law of diffusion are used to compute alveolar and blood O2 and CO2 values compatible with input O2 uptake and CO2 elimination. Two applications are presented. The first is a method to partition O2 and CO2 alveolar-arterial gradients into VA/Q and D components. The technique is evaluated in data of patients with chronic obstructive pulmonary disease (COPD). The second is a theoretical analysis of the effects of blood flow variation in alveolar and blood O2 partial pressures. The results show the importance of simultaneous consideration of D to estimate VA/Q heterogeneity in patients with diffusion impairment. This factor plays an increasing role in gas alveolar-arterial gradients as severity of COPD increases. Association of VA/Q heterogeneity and D may produce an increase of O2 arterial pressure with decreasing QT which would not be observed if only D were considered. We conclude that the presented computer model is a useful tool for description and interpretation of data from COPD patients and for performing theoretical analysis of variables involved in the gas exchange process.

NASA Discipline Environmental Health↗
NASA NTRS1991

Aging and the complexity of cardiovascular dynamics

Biomedical signals often vary in a complex and irregular manner. Analysis of variability in such signals generally does not address directly their complexity, and so may miss potentially useful information. We analyze the complexity of heart rate and beat-to-beat blood pressure using two methods motivated by nonlinear dynamics (chaos theory). A comparison of a group of healthy elderly subjects with healthy young adults indicates that the complexity of cardiovascular dynamics is reduced with aging. This suggests that complexity of variability may be a useful physiological marker.

Non-NASA Center↗
NASA NTRS2005

Gesture Based Control and EMG Decomposition

This paper presents two probabilistic developments for use with Electromyograms (EMG). First described is a new-electric interface for virtual device control based on gesture recognition. The second development is a Bayesian method for decomposing EMG into individual motor unit action potentials. This more complex technique will then allow for higher resolution in separating muscle groups for gesture recognition. All examples presented rely upon sampling EMG data from a subject's forearm. The gesture based recognition uses pattern recognition software that has been trained to identify gestures from among a given set of gestures. The pattern recognition software consists of hidden Markov models which are used to recognize the gestures as they are being performed in real-time from moving averages of EMG. Two experiments were conducted to examine the feasibility of this interface technology. The first replicated a virtual joystick interface, and the second replicated a keyboard. Moving averages of EMG do not provide easy distinction between fine muscle groups. To better distinguish between different fine motor skill muscle groups we present a Bayesian algorithm to separate surface EMG into representative motor unit action potentials. The algorithm is based upon differential Variable Component Analysis (dVCA) [l], [2] which was originally developed for Electroencephalograms. The algorithm uses a simple forward model representing a mixture of motor unit action potentials as seen across multiple channels. The parameters of this model are iteratively optimized for each component. Results are presented on both synthetic and experimental EMG data. The synthetic case has additive white noise and is compared with known components. The experimental EMG data was obtained using a custom linear electrode array designed for this study.

Wheeler, Kevin R.↗
NASA NTRS2005

Coping with Trial-to-Trial Variability of Event Related Signals: A Bayesian Inference Approach

In electro-neurophysiology, single-trial brain responses to a sensory stimulus or a motor act are commonly assumed to result from the linear superposition of a stereotypic event-related signal (e.g. the event-related potential or ERP) that is invariant across trials and some ongoing brain activity often referred to as noise. To extract the signal, one performs an ensemble average of the brain responses over many identical trials to attenuate the noise. To date, h s simple signal-plus-noise (SPN) model has been the dominant approach in cognitive neuroscience. Mounting empirical evidence has shown that the assumptions underlying this model may be overly simplistic. More realistic models have been proposed that account for the trial-to-trial variability of the event-related signal as well as the possibility of multiple differentially varying components within a given ERP waveform. The variable-signal-plus-noise (VSPN) model, which has been demonstrated to provide the foundation for separation and characterization of multiple differentially varying components, has the potential to provide a rich source of information for questions related to neural functions that complement the SPN model. Thus, being able to estimate the amplitude and latency of each ERP component on a trial-by-trial basis provides a critical link between the perceived benefits of the VSPN model and its many concrete applications. In this paper we describe a Bayesian approach to deal with this issue and the resulting strategy is referred to as the differentially Variable Component Analysis (dVCA). We compare the performance of dVCA on simulated data with Independent Component Analysis (ICA) and analyze neurobiological recordings from monkeys performing cognitive tasks.

Ding, Mingzhou↗
NASA NTRS2006

Effectively Transforming IMC Flight into VMC Flight: An SVS Case Study

A flight-test experiment was conducted using the NASA LaRC Cessna 206 aircraft. Four primary flight and navigation display concepts, including baseline and Synthetic Vision System (SVS) concepts, were evaluated in the local area of Roanoke Virginia Airport, flying visual and instrument approach procedures. A total of 19 pilots, from 3 pilot groups reflecting the diverse piloting skills of the GA population, served as evaluation pilots. Multi-variable Discriminant Analysis was applied to three carefully selected and markedly different operating conditions with conventional instrumentation to provide an extension of traditional analysis methods as well as provide an assessment of the effectiveness of SVS displays to effectively transform IMC flight into VMC flight.

Glaab, Louis J.↗
NASA NTRS2011

Future Multiwavelength Studies with the Fermi Large Area Telescope

With two and a half years of experience, Fermi LAT contributions to multiwavelength studies have become an integral part of many astrophysical research projects. Future efforts will benefit from (1) Deeper LAT exposures} resulting in more sources; (2) More high-energy, high-angular resolution photons, giving better source locations and imaging; (3) Faster analysis of variability and announcements to the community; and (4) Longer time series for studies of variable source properties in comparison to other wavelengths.

Thompson, David J.↗
NASA NTRS2003

Aerodynamic Design Using Neural Networks

The design of aerodynamic components of aircraft, such as wings or engines, involves a process of obtaining the most optimal component shape that can deliver the desired level of component performance, subject to various constraints, e.g., total weight or cost, that the component must satisfy. Aerodynamic design can thus be formulated as an optimization problem that involves the minimization of an objective function subject to constraints. A new aerodynamic design optimization procedure based on neural networks and response surface methodology (RSM) incorporates the advantages of both traditional RSM and neural networks. The procedure uses a strategy, denoted parameter-based partitioning of the design space, to construct a sequence of response surfaces based on both neural networks and polynomial fits to traverse the design space in search of the optimal solution. Some desirable characteristics of the new design optimization procedure include the ability to handle a variety of design objectives, easily impose constraints, and incorporate design guidelines and rules of thumb. It provides an infrastructure for variable fidelity analysis and reduces the cost of computation by using less-expensive, lower fidelity simulations in the early stages of the design evolution. The initial or starting design can be far from optimal. The procedure is easy and economical to use in large-dimensional design space and can be used to perform design tradeoff studies rapidly. Designs involving multiple disciplines can also be optimized. Some practical applications of the design procedure that have demonstrated some of its capabilities include the inverse design of an optimal turbine airfoil starting from a generic shape and the redesign of transonic turbines to improve their unsteady aerodynamic characteristics.

Rai, Man Mohan↗
NASA NTRS2016

Human Influence on Tropical Cyclone Intensity

Recent assessments agree that tropical cyclone intensity should increase as the climate warms. Less agreement exists on the detection of recent historical trends in tropical cyclone intensity.We interpret future and recent historical trends by using the theory of potential intensity, which predicts the maximum intensity achievable by a tropical cyclone in a given local environment. Although greenhouse gas-driven warming increases potential intensity, climate model simulations suggest that aerosol cooling has largely canceled that effect over the historical record. Large natural variability complicates analysis of trends, as do poleward shifts in the latitude of maximum intensity. In the absence of strong reductions in greenhouse gas emissions, future greenhouse gas forcing of potential intensity will increasingly dominate over aerosol forcing, leading to substantially larger increases in tropical cyclone intensities.

Human influence on climate↗
NASA NTRS2016

Craters of the Pluto-Charon System

NASA's New Horizons flyby mission of the Pluto-Charon binary system and its four moons provided humanity with its first spacecraft-based look at a large Kuiper Belt Object beyond Triton. Excluding this system, multiple Kuiper Belt Objects (KBOs) have been observed for only 20 years from Earth, and the KBO size distribution is unconstrained except among the largest objects. Because small KBOs will remain beyond the capabilities of ground-based observatories for the foreseeable future, one of the best ways to constrain the small KBO population is to examine the craters they have made on the Pluto-Charon system. The first step to understanding the crater population is to map it. In this work, we describe the steps undertaken to produce a robust crater database of impact features on Pluto, Charon, and their two largest moons, Nix and Hydra. These include an examination of different types of images and image processing, and we present an analysis of variability among the crater mapping team, where crater diameters were found to average +/-10% uncertainty across all sizes measured (approx.0.5-300 km). We also present a few basic analyses of the crater databases, finding that Pluto's craters' differential size-frequency distribution across the encounter hemisphere has a power-law slope of approximately -3.1 +/- 0.1 over diameters D approx. = 15-200 km, and Charon's has a slope of -3.0 +/- 0.2 over diameters D approx. = 10-120 km; it is significantly shallower on both bodies at smaller diameters. We also better quantify evidence of resurfacing evidenced by Pluto's craters in contrast with Charon's. With this work, we are also releasing our database of potential and probable impact craters: 5287 on Pluto, 2287 on Charon, 35 on Nix, and 6 on Hydra.

Robbins, Stuart J.↗
NASA NTRS2016

Taxi-Out Time Prediction for Departures at Charlotte Airport Using Machine Learning Techniques

Predicting the taxi-out times of departures accurately is important for improving airport efficiency and takeoff time predictability. In this paper, we attempt to apply machine learning techniques to actual traffic data at Charlotte Douglas International Airport for taxi-out time prediction. To find the key factors affecting aircraft taxi times, surface surveillance data is first analyzed. From this data analysis, several variables, including terminal concourse, spot, runway, departure fix and weight class, are selected for taxi time prediction. Then, various machine learning methods such as linear regression, support vector machines, k-nearest neighbors, random forest, and neural networks model are applied to actual flight data. Different traffic flow and weather conditions at Charlotte airport are also taken into account for more accurate prediction. The taxi-out time prediction results show that linear regression and random forest techniques can provide the most accurate prediction in terms of root-mean-square errors. We also discuss the operational complexity and uncertainties that make it difficult to predict the taxi times accurately.

Safe and efficient surface operations↗
NASA NTRS2021

Interpretation of Spectral LiDAR Backscattering off the Florida Coast

A multispectral backscattering LiDAR (Light detection and range) system (hereafter Oculus) was integrated into a wave glider and used to estimate the scattering order (i.e., single vs multiple collisions), inherent optical properties (IOPs) and characteristics of particulate scatterers (i.e., relative size, composition and motion) on shelf waters of South East Florida. Oculus has a dual-wavelength configuration (473 and 532 nm) and two detection geometries (off- and on-axis). Characteristics of scatterers were investigated based on two complementary LiDAR-derived proxies (the Structural Dissimilarity Index and the spectral slope of LiDAR backscattering). In March 2017, field measurements showed a covariation between direct and diffuse backscattering contributions during morning hours and away from shore. LiDAR attenuation coefficients explained up to 57% of IOPs variability. The analysis of LiDAR-derived proxies suggested higher turbidity and larger particulates near the coast.

LiDAR↗
NASA NTRS1976

Analysis and testing of two-dimensional vented Coanda ejectors with asymmetric variable area mixing sections

The analysis of asymmetric, curved (Coanda) ejector flow has been completed using a finite difference technique and a quasi-orthogonal streamline coordinate system. The boundary layer type jet mixing analysis accounts for the effect of streamline curvature in pressure gradients normal to the streamlines and on eddy viscosities. The analysis assured perfect gases, free of pressure discontinuities and flow separation and treated three compound flows of supersonic and subsonic streams. Flow parameters and ejector performance were measured in a vented Coanda flow geometry for the verification of the computer analysis. A primary converging nozzle with a discharge geometry of 0.003175 m x 0.2032 m was supplied with 0.283 cu m/sec of air at about 241.3 KPa absolute stagnation pressure and 82 C stagnation temperature. One mixing section geometry was used with a 0.127 m constant radius Coanda surface. Eight tests were run at spacing between the Coanda surface and primary nozzle 0.01915 m and 0.318 m and at three angles of Coanda turning: 22.5 deg, 45.0 deg, and 75.0 deg. The wall static pressures, the loci of maximum stagnation pressures, and the stagnation pressure profiles agree well between analytical and experimental results.

Maroti, L. A.↗
NASA NTRS1989

Variability of X-ray emission from OB stars

The variability in soft X-ray emission of 12 OB stars is studied. Two different methods of analysis, one more suitable for detecting short-term variations, the other aimed at detecting long time-scale variations, are applied to all stars in the sample. The long-term variability analysis shows that Cyg-OB2 8A Zeta Pup and Delta Ori exhibit significant count rate variations between different data sections. Similar variations are marginally detected in 15 Mon; the count rate variations for the other eight stars are consistent with statistical fluctuations. The light curve of Cyg-OB2 8A suggests the existence of two different emission levels. The short-term variability analysis detects marginal variability in Tau Sco with an effective amplitude of about 30 percent and a time scale of about 50 s. The upper limits to the effective short-term variability amplitude for all other sample stars are in the 10-30 percent range.

Collura, A.↗