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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 235 records · Page 13

Crew decision making under stress

Flight crews must make decisions and take action when systems fail or emergencies arise during flight. These situations may involve high stress. Full-missiion flight simulation studies have shown that crews differ in how effectively they cope in these circumstances, judged by operational errors and crew coordination. The present study analyzed the problem solving and decision making strategies used by crews led by captains fitting three different personality profiles. Our goal was to identify more and less effective strategies that could serve as the basis for crew selection or training. Methods: Twelve 3-member B-727 crews flew a 5-leg mission simulated flight over 1 1/2 days. Two legs included 4 abnormal events that required decisions during high workload periods. Transcripts of videotapes were analyzed to describe decision making strategies. Crew performance (errors and coordination) was judged on-line and from videotapes by check airmen. Results: Based on a median split of crew performance errors, analyses to date indicate a difference in general strategy between crews who make more or less errors. Higher performance crews showed greater situational awareness - they responded quickly to cues and interpreted them appropriately. They requested more decision relevant information and took into account more constraints. Lower performing crews showed poorer situational awareness, planning, constraint sensitivity, and coordination. The major difference between higher and lower performing crews was that poorer crews made quick decisions and then collected information to confirm their decision. Conclusion: Differences in overall crew performance were associated with differences in situational awareness, information management, and decision strategy. Captain personality profiles were associated with these differences, a finding with implications for crew selection and training.

Orasanu, J.↗

Symbology Development for General Aviation Synthetic Vision Primary Flight Displays for the Approach and Missed-Approach Modes of Flight

Spatial disorientation induced by inadvertent flight into instrument meteorological conditions (IMC) continues to be a leading cause of fatal accidents in general aviation. The Synthetic Vision Systems General Aviation (SVS-GA) research element, an integral part of NASA s Aviation Safety and Security Program (AvSSP), is investigating a revolutionary display technology designed to mitigate low visibility events such as controlled flight into terrain (CFIT) and low-visibility loss of control (LVLoC). The integrated SVS Primary Flight Display (SVS-PFD) utilizes computer generated 3-dimensional imagery of the surrounding terrain augmented with flight path guidance symbology. This unique combination will provide GA pilots with an accurate representation of their environment and projection of their flight path, regardless of time of day or out-the-window (OTW) visibility. The initial Symbology Development for Head-Down Displays (SD-HDD) simulation experiment examined 16 display configurations on a centrally located high-resolution PFD installed in NASA s General Aviation Work Station (GAWS) flight simulator. The results of the experiment indicate that situation awareness (SA) can be enhanced without having a negative impact on flight technical error (FTE), by providing a general aviation pilot with an integrated SVS display to use when OTW visibility is obscured.

Bartolone, Anthony P.↗

Performance of convolutionally encoded noncoherent MFSK modem in fading channels

The performance of a convolutionally encoded noncoherent multiple-frequency shift-keyed (MFSK) modem utilizing Viterbi maximum-likelihood decoding and operating on a fading channel is described. Both the lognormal and classical Rician fading channels are considered for both slow and time-varying channel conditions. Primary interest is in the resulting bit error rate as a function of the ratio between the energy per transmitted information bit and noise spectral density, parameterized by both the fading channel and code parameters. Fairly general upper bounds on bit error probability are provided and compared with simulation results in the two extremes of zero and infinite channel memory. The efficacy of simple block interleaving in combatting channel memory effects are thoroughly explored. Both quantized and unquantized receiver outputs are considered.

Modestino, J. W.↗

Satellite interferometer as an advanced navigation/communication system

An orthogonal system of interferometry baselines aboard a geostationary satellite is proposed to be used for navigation, surveillance, and traffic control. Position determination is based on the relationship between the measured phase differences, the known and unknown transmitter locations, and other systematic error model parameters using a generalized least-squares estimation procedure. It is shown that position accuracy is critically dependent on the baseline length and on the magnitude of the random component of the measuring errors. Several trade-offs with respect to the system accuracies, the number of users, data rates, hardware costs, etc., are examined. Simultaneous use of the same channels for navigation and data transfer is found feasible and five candidate or 'strawman' interferometer system proposals are presented. It is concluded that the system's performance is excellent in comparison with present or planned systems, and that it is viable in meeting potential user's requirements.

Gopalapillai, G. S.↗

Data and results of a laboratory investigation of microprocessor upset caused by simulated lightning-induced analog transients

Advanced composite aircraft designs include fault-tolerant computer-based digital control systems with thigh reliability requirements for adverse as well as optimum operating environments. Since aircraft penetrate intense electromagnetic fields during thunderstorms, onboard computer systems maya be subjected to field-induced transient voltages and currents resulting in functional error modes which are collectively referred to as digital system upset. A methodology was developed for assessing the upset susceptibility of a computer system onboard an aircraft flying through a lightning environment. Upset error modes in a general-purpose microprocessor were studied via tests which involved the random input of analog transients which model lightning-induced signals onto interface lines of an 8080-based microcomputer from which upset error data were recorded. The application of Markov modeling to upset susceptibility estimation is discussed and a stochastic model development.

Belcastro, C. M.↗

The implementation and use of ADA on distributed systems with high reliability requirements

The use and implementation of Ada in distributed environments in which reliability is the primary concern is investigated. Emphasis is placed on the possibility that a distributed system may be programmed entirely in Ada so that the individual tasks of the system are unconcerned with which processors they are executing on, and that failures may occur in the software or underlying hardware. A new linguistic construct, the colloquy, is introduced which solves the problems identified in an earlier proposal, the conversation. It was shown that the colloquy is at least as powerful as recovery blocks, but it is also as powerful as all the other language facilities proposed for other situations requiring backward error recovery: recovery blocks, deadlines, generalized exception handlers, traditional conversations, s-conversations, and exchanges. The major features that distinguish the colloquy are described. Sample programs that were written, but not executed, using the colloquy show that extensive backward error recovery can be included in these programs simply and elegantly. These ideas are being implemented in an experimental Ada test bed.

Knight, J. C.↗

Error correction in adders using systematic subcodes.

A generalized theory is presented for the construction of a systematic subcode for a given AN code in such a way that error control properties of the AN code are preserved in this new code. The 'systematic weight' and 'systematic distance' functions in this new code depend not only on its number representation system but also on its addition structure. Finally, to illustrate this theory, a simple error-correcting adder organization using a systematic subcode of 29 N code is sketched in some detail.

Rao, T. R. N.↗

Tropical forecasting - Predictability perspective

Results are presented of classical predictability studies and forecast experiments with observed initial conditions to show the nature of initial error growth and final error equilibration for the tropics and midlatitudes, separately. It is found that the theoretical upper limit of tropical circulation predictability is far less than for midlatitudes. The error growth for a complete general circulation model is compared to a dry version of the same model in which there is no prognostic equation for moisture, and diabatic heat sources are prescribed. It is found that the growth rate of synoptic-scale errors for the dry model is significantly smaller than for the moist model, suggesting that the interactions between dynamics and moist processes are among the important causes of atmospheric flow predictability degradation. Results are then presented of numerical experiments showing that correct specification of the slowly varying boundary condition of SST produces significant improvement in the prediction of time-averaged circulation and rainfall over the tropics.

Shukla, J.↗

2004: Finite-Difference Time Domain Solution of Light Scattering by an Infinite Dielectric Column Immersed in an Absorbing Medium

The two-dimensional (2-D) finite-difference time domain (FDTD) method is applied to calculate light scattering and absorption by an arbitrarily shaped infinite column embedded in an absorbing dielectric medium. A uniaxial perfectly matched layer (UPML) absorbing boundary condition (ABC) is used to truncate the computational domain. The single-scattering properties of the infinite column embedded in the absorbing medium, including scattering phase functions, extinction and absorption efficiencies, are derived using an area integration of the internal field. An exact solution for light scattering and absorption by a circular cylinder in an absorbing medium is used to examine the accuracy of the 2-D UPML FDTD code. With use of a cell size of 1/120 incident wavelength in the FDTD calculations, the errors in the extinction and absorption efficiencies and asymmetry factors from the 2-D UPML FDTD are generally smaller than approx .1%. The errors in the scattering phase functions are typically smaller than approx .4%. Using the 2-D UPML FDTD technique, light scattering and absorption by long noncircular columns embedded in absorbing media can be accurately solved.

Sun, W.↗

Performance of quadrature overlapped raised-cosine modulation over nonlinear satellite channels

This paper considers the performance evaluation of Staggered Quadrature Overlapped Raised Cosine (SQORC) signal transmission through wideband nonlinear satellite channels in the presence of uplink and downlink additive Gaussian noise. Expressions for the bit error rate are derived for a general transponder model with AM-AM and AM-PM conversion. It is shown that the bit error rate of SQORC is one-half of the sum of the bit error rate of MSK at 2/3 of the uplink signal-to-noise ratio and the bit error rate of Quadriphase Phase-Shift Keying QPSK at 4/3 of the uplink signal-to-noise ratio, whereas the spectrum of SQROC is the product of MSK and QPSK spectra. Numerical results are presented for a transponder which is modelled as a hard limiter.

Divsalar, D.↗

Artificial neural network implementation of a near-ideal error prediction controller

A theory has been developed at the University of Virginia which explains the effects of including an ideal predictor in the forward loop of a linear error-sampled system. It has been shown that the presence of this ideal predictor tends to stabilize the class of systems considered. A prediction controller is merely a system which anticipates a signal or part of a signal before it actually occurs. It is understood that an exact prediction controller is physically unrealizable. However, in systems where the input tends to be repetitive or limited, (i.e., not random) near ideal prediction is possible. In order for the controller to act as a stability compensator, the predictor must be designed in a way that allows it to learn the expected error response of the system. In this way, an unstable system will become stable by including the predicted error in the system transfer function. Previous and current prediction controller include pattern recognition developments and fast-time simulation which are applicable to the analysis of linear sampled data type systems. The use of pattern recognition techniques, along with a template matching scheme, has been proposed as one realizable type of near-ideal prediction. Since many, if not most, systems are repeatedly subjected to similar inputs, it was proposed that an adaptive mechanism be used to 'learn' the correct predicted error response. Once the system has learned the response of all the expected inputs, it is necessary only to recognize the type of input with a template matching mechanism and then to use the correct predicted error to drive the system. Suggested here is an alternate approach to the realization of a near-ideal error prediction controller, one designed using Neural Networks. Neural Networks are good at recognizing patterns such as system responses, and the back-propagation architecture makes use of a template matching scheme. In using this type of error prediction, it is assumed that the system error responses be known for a particular input and modeled plant. These responses are used in the error prediction controller. An analysis was done on the general dynamic behavior that results from including a digital error predictor in a control loop and these were compared to those including the near-ideal Neural Network error predictor. This analysis was done for a second and third order system.

Mcvey, Eugene S.↗

A Generalized Approach to Aircraft Trajectory Prediction via Supervised Deep Learning

As research advances diverse forms and missions of aircraft, the National Airspace System (NAS) will become increasingly crowded, limiting current communications resources to accommodate aviation operations. Ongoing research proposes a paradigm of airspace communications, such that resources are autonomously and dynamically allocated via intelligent agents; this allocation requires accurate representations of the NAS, including the predicted positions of aircraft. State-of-the-art research emphasizes the importance of a hybrid-recurrent framework for trajectory prediction and compares the impact of commonly considered weather data on prediction accuracy. However, current research has been limited in its scope of efforts, frequently utilizing a unique flight route, architecture, set of weather data, and date range. This article considers the challenges of generalizing hybrid-recurrent predictive models for flight trajectories. Results illustrate an increase in error variance when identical models are trained over a generalized set of flights; this may be mitigated with careful tuning of hyperparameters, both in the network structure and optimization algorithms. Even so, an irreducible vertical error was identified, resulting from the complex takeoff and landing procedures which can not be correlated to functions of weather or additional assumptions of aircraft behavior. Finally, the use of a test route indicates that generalized models still do not possess sufficient knowledge for general aircraft predictions, with mean error increases ranging from 70-500%. These results illustrate the need for continued efforts on improving model versatility, as well as potential limitations for spectrum allocation near airports and other centers.

Nathan Schimpf↗

Predicting Pilot Error in Nextgen: Pilot Performance Modeling and Validation Efforts

We review 25 articles presenting 5 general classes of computational models to predict pilot error. This more targeted review is placed within the context of the broader review of computational models of pilot cognition and performance, including such aspects as models of situation awareness or pilot-automation interaction. Particular emphasis is placed on the degree of validation of such models against empirical pilot data, and the relevance of the modeling and validation efforts to Next Gen technology and procedures.

pilot error↗

Visual tracking in stereo

A method is described for visual object tracking by a computer vision system using TV cameras and special low-level image processing hardware. The tracker maintains an internal model of the location, orientation, and velocity of the object in three-dimensional space. This model is used to predict where features of the object will lie on the two-dimensional images produced by stereo TV cameras. The differences in the locations of features in the two-dimensional images as predicted by the internal model and as actually seen create an error signal in the two-dimensional representation. This is multiplied by a generalized inverse Jacobian matrix to deduce the error in the internal model. The procedure repeats to update the internal model of the object's location, orientation and velocity continuously.

Saund, E.↗

Distortion Representation of Forecast Errors for Model Skill Assessment and Objective Analysis

We proposed a novel characterization of errors for numerical weather predictions. A general distortion representation allows for the displacement and amplification or bias correction of forecast anomalies. Characterizing and decomposing forecast error in this way has several important applications, including the model assessment application and the objective analysis application. In this project, we have focused on the assessment application, restricted to a realistic but univariate 2-dimensional situation. Specifically, we study the forecast errors of the sea level pressure (SLP), the 500 hPa geopotential height, and the 315 K potential vorticity fields for forecasts of the short and medium range. The forecasts are generated by the Goddard Earth Observing System (GEOS) data assimilation system with and without ERS-1 scatterometer data. A great deal of novel work has been accomplished under the current contract. In broad terms, we have developed and tested an efficient algorithm for determining distortions. The algorithm and constraints are now ready for application to larger data sets to be used to determine the statistics of the distortion as outlined above, and to be applied in data analysis by using GEOS water vapor imagery to correct short-term forecast errors.

Hoffman, Ross N.↗

Cascade Error Projection Learning Algorithm

A detailed mathematical analysis is presented for a new learning algorithm termed cascade error projection (CEP) and a general learning frame work. This frame work can be used to obtain the cascade correlation learning algorithm by choosing a particular set of parameters.

learning algorithm neural network cascade error pr↗

Polynominal Interpolation Methods for Viscous Flow Calculations

Higher-order collocation procedures resulting in tridiagonal matrix systems are derived from polynomial spline interpolation and by Hermitian (Taylor series) finite-difference discretization. The similarities and special features of these different developments are discussed. The governing systems apply for both uniform and variable meshes. Hybrid schemes resulting from two different polynomial approximations for the first and second derivatives lead to a nonuniform mesh extension of the so-called compact or Pad? difference technique (Hermite 4). A variety of fourth-order methods are described and the Hermitian approach is extended to sixth-order (Hermite 6). The appropriate spline boundary conditions are derived for all procedures. For central finite differences, this leads to a two-point, second-order accurate generalization of the commonly used three-point end-difference formula. Solutions with several spline and Hermite procedures are presented for the boundary layer equations, with and without mass transfer, and for the incompressible viscous flow in a driven cavity. Divergence and nondivergence equations are considered for the cavity. Among the fourth-order techniques, it is shown that spline 4 has the smallest truncation error. The spline 4 procedure generally requires one-quarter the number of mesh points in a given coordinate direction as a central finite-difference calculation of equal accuracy. The Hermite 6 procedure leads to remarkably accurate boundary layer solutions.

Rubin, S. G.↗

A Comparison of Two Balance Calibration Model Building Methods

Simulated strain-gage balance calibration data is used to compare the accuracy of two balance calibration model building methods for different noise environments and calibration experiment designs. The first building method obtains a math model for the analysis of balance calibration data after applying a candidate math model search algorithm to the calibration data set. The second building method uses stepwise regression analysis in order to construct a model for the analysis. Four balance calibration data sets were simulated in order to compare the accuracy of the two math model building methods. The simulated data sets were prepared using the traditional One Factor At a Time (OFAT) technique and the Modern Design of Experiments (MDOE) approach. Random and systematic errors were introduced in the simulated calibration data sets in order to study their influence on the math model building methods. Residuals of the fitted calibration responses and other statistical metrics were compared in order to evaluate the calibration models developed with different combinations of noise environment, experiment design, and model building method. Overall, predicted math models and residuals of both math model building methods show very good agreement. Significant differences in model quality were attributable to noise environment, experiment design, and their interaction. Generally, the addition of systematic error significantly degraded the quality of calibration models developed from OFAT data by either method, but MDOE experiment designs were more robust with respect to the introduction of a systematic component of the unexplained variance.

DeLoach, Richard↗