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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
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NASA NTRS2011

Optimal Tuner Selection for Kalman-Filter-Based Aircraft Engine Performance Estimation

An emerging approach in the field of aircraft engine controls and system health management is the inclusion of real-time, onboard models for the inflight estimation of engine performance variations. This technology, typically based on Kalman-filter concepts, enables the estimation of unmeasured engine performance parameters that can be directly utilized by controls, prognostics, and health-management applications. A challenge that complicates this practice is the fact that an aircraft engine s performance is affected by its level of degradation, generally described in terms of unmeasurable health parameters such as efficiencies and flow capacities related to each major engine module. Through Kalman-filter-based estimation techniques, the level of engine performance degradation can be estimated, given that there are at least as many sensors as health parameters to be estimated. However, in an aircraft engine, the number of sensors available is typically less than the number of health parameters, presenting an under-determined estimation problem. A common approach to address this shortcoming is to estimate a subset of the health parameters, referred to as model tuning parameters. The problem/objective is to optimally select the model tuning parameters to minimize Kalman-filterbased estimation error. A tuner selection technique has been developed that specifically addresses the under-determined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine that seeks to minimize the theoretical mean-squared estimation error of the Kalman filter. This approach can significantly reduce the error in onboard aircraft engine parameter estimation applications such as model-based diagnostic, controls, and life usage calculations. The advantage of the innovation is the significant reduction in estimation errors that it can provide relative to the conventional approach of selecting a subset of health parameters to serve as the model tuning parameter vector. Because this technique needs only to be performed during the system design process, it places no additional computation burden on the onboard Kalman filter implementation. The technique has been developed for aircraft engine onboard estimation applications, as this application typically presents an under-determined estimation problem. However, this generic technique could be applied to other industries using gas turbine engine technology.

Simon, Donald L.↗
NASA NTRS2011

Lessons Learned from Assimilating Altimeter Data into a Coupled General Circulation Model with the GMAO Augmented Ensemble Kalman Filter

Satellite altimetry measurements have provided global, evenly distributed observations of the ocean surface since 1993. However, the difficulties introduced by the presence of model biases and the requirement that data assimilation systems extrapolate the sea surface height (SSH) information to the subsurface in order to estimate the temperature, salinity and currents make it difficult to optimally exploit these measurements. This talk investigates the potential of the altimetry data assimilation once the biases are accounted for with an ad hoc bias estimation scheme. Either steady-state or state-dependent multivariate background-error covariances from an ensemble of model integrations are used to address the problem of extrapolating the information to the sub-surface. The GMAO ocean data assimilation system applied to an ensemble of coupled model instances using the GEOS-5 AGCM coupled to MOM4 is used in the investigation. To model the background error covariances, the system relies on a hybrid ensemble approach in which a small number of dynamically evolved model trajectories is augmented on the one hand with past instances of the state vector along each trajectory and, on the other, with a steady state ensemble of error estimates from a time series of short-term model forecasts. A state-dependent adaptive error-covariance localization and inflation algorithm controls how the SSH information is extrapolated to the sub-surface. A two-step predictor corrector approach is used to assimilate future information. Independent (not-assimilated) temperature and salinity observations from Argo floats are used to validate the assimilation. A two-step projection method in which the system first calculates a SSH increment and then projects this increment vertically onto the temperature, salt and current fields is found to be most effective in reconstructing the sub-surface information. The performance of the system in reconstructing the sub-surface fields is particularly impressive for temperature, but not as satisfactory for salt.

Keppenne, Christian↗
NASA NTRS1979

Nonresonance rotation of Venus

Radar observations accumulated over the past 14 yr are used to make a precise estimate of the spin vector of Venus. The results obtained show that the spin vector of Venus may be adequately described in the standard 1950.0 coordinate system by a period of 243.01 + or - 0.03 days (retrograde) and a north pole direction corresponding to alpha = 272.8 + or - 0.5 deg and delta = 67.2 + or - 0.3 deg; the quoted errors represent estimates of 70% confidence intervals. The angular separations between the spin vector and those vectors representing the unit normals to the invariable plane of the solar system and the orbital plane of Venus are found to be 0.5 deg and 2.6 deg, respectively. It is concluded that Venus is not rotating with a resonance spin period relative to the orbit of earth and that the spin of Venus may be in a generalized Cassini state.

Shapiro, I. I.↗
NASA NTRS1978

Vector space methods of photometric analysis - Applications to O stars and interstellar reddening

A multivariate vector-space formulation of photometry is developed which accounts for error propagation. An analysis of uvby and H-beta photometry of O stars is presented, with attention given to observational errors, reddening, general uvby photometry, early stars, and models of O stars. The number of observable parameters in O-star continua is investigated, the way these quantities compare with model-atmosphere predictions is considered, and an interstellar reddening law is derived. It is suggested that photospheric expansion affects the formation of the continuum in at least some O stars.

Massa, D.↗
NASA NTRS1985

The Use of a Laser Doppler Velocimeter in a Standard Flammability Tube

The use of the Laser Doppler Velocimeter, (LDV), to measure the flow associated with the passage of a flame through a standard flammability limit tube (SFLT) was studied. Four major results are presented: (1) it is shown that by using standard ray tracing calculations, the displacement of the LDV volume and the fringe rotation within the experimental error of measurement can be predicted; (2) the flow velocity vector field associated with passage of an upward propagating flame in an SFLT is determined; (3) it is determined that the use of a light interruption technique to track particles is not feasible; and (4) it is shown that a 25 mW laser is adequate for LDV measurements in the Shuttle or Spacelab.

Strehlow, R. A.↗
NASA NTRS1985

Two locations, two times, and the element set

A robust analytical formulation is developed to apply classical initial orbital determination to artificial satellites whose locations are uncertain to about 1 cu km and separated in time by no more than 30 min. An analytical simplification reduces Gauss's method, iteration on the semilatus rectum, iteration on the true anomaly, and the Lambert-Euler technique, to the solution of a single equation in one unknown, instead of the usual coupled triplet of three equations in three unknowns. The method is demonstrated for all common artificial satellite orbits over a variety of time intervals between the two location vectors, and for a varied set of position and distance errors.

Taff, L. G.↗
NASA NTRS1989

A multidomain spectral collocation method for the Stokes problem

A multidomain spectral collocation scheme is proposed for the approximation of the two-dimensional Stokes problem. It is shown that the discrete velocity vector field is exactly divergence-free and we prove error estimates both for the velocity and the pressure.

Landriani, G. Sacchi↗
NASA NTRS1990

Computational enhancement of an unsymmetric block Lanczos algorithm

An unsymmetric block Lanczos algorithm has been employed for the dynamic analysis of a large system which has arbitrary damping and/or repeated (or closely spaced) eigenvalues. In the algorithm development, the right and left Lanczos vectors are all theoretically biorthogonal to each other. However, these vectors may lose the biorthogonality owing to cancellation and roundoff errors. For the unsymmetric case there can be a breakdown, even without numerical errors. This paper describes computational techniques which have led to a robust unsymmetric block Lanczos algorithm.

Kim, Hyoung M.↗
NASA NTRS2001

Effects of the Ionosphere on Passive Microwave Remote Sensing of Ocean Salinity from Space

Among the remote sensing applications currently being considered from space is the measurement of sea surface salinity. The salinity of the open ocean is important for understanding ocean circulation and for modeling energy exchange with the atmosphere. Passive microwave remote sensors operating near 1.4 GHz (L-band) could provide data needed to fill the gap in current coverage and to complement in situ arrays being planned to provide subsurface profiles in the future. However, the dynamic range of the salinity signal in the open ocean is relatively small and propagation effects along the path from surface to sensor must be taken into account. In particular, Faraday rotation and even attenuation/emission in the ionosphere can be important sources of error. The purpose or this work is to estimate the magnitude of these effects in the context of a future remote sensing system in space to measure salinity in L-band. Data will be presented as a function of time location and solar activity using IRI-95 to model the ionosphere. The ionosphere presents two potential sources of error for the measurement of salinity: Rotation of the polarization vector (Faraday rotation) and attenuation/emission. Estimates of the effect of these two phenomena on passive remote sensing over the oceans at L-band (1.4 GHz) are presented.

LeVine, D. M.↗
NASA NTRS1998

A Numerical Optimization Approach for Tuning Fuzzy Logic Controllers

This paper develops a method to tune fuzzy controllers using numerical optimization. The main attribute of this approach is that it allows fuzzy logic controllers to be tuned to achieve global performance requirements. Furthermore, this approach allows design constraints to be implemented during the tuning process. The method tunes the controller by parameterizing the membership functions for error, change-in-error and control output. The resulting parameters form a design vector which is iteratively changed to minimize an objective function. The minimal objective function results in an optimal performance of the system. A spacecraft mounted science instrument line-of-sight pointing control is used to demonstrate results.

Woodard, Stanley E.↗
NASA NTRS1991

On state estimation for an orbiting single tether system

The effects of instrumentation accuracy and configuration on estimation error are studied for the small expendable-tether deployment system (SEDS) using a continuous-discrete extended Kalman filter (CDEKF) state estimator. A twelfth order model that incorporates the rigid body modes of the tether as well as the satellite attitude dynamics is developed. Simulation results using the model and the estimator indicate that the originally planned instrumentation package could not estimate the state vector adequately. Recommendations are made and results presented that reduce the estimation error by adding instruments and increasing selected measurement accuracies.

Greene, Michael E.↗
NASA NTRS1971

Principles of error detection and error correction codes

Report is reviewed which considers theoretical basis of groups, rings, fields, and vector spaces, and their relationship to algebraic coding theory. Report serves as summary for engineers and scientists involved in data handling and processing systems.

Perlman, M.↗
NASA NTRS2004

AveBoost2: Boosting for Noisy Data

AdaBoost is a well-known ensemble learning algorithm that constructs its constituent or base models in sequence. A key step in AdaBoost is constructing a distribution over the training examples to create each base model. This distribution, represented as a vector, is constructed to be orthogonal to the vector of mistakes made by the pre- vious base model in the sequence. The idea is to make the next base model's errors uncorrelated with those of the previous model. In previous work, we developed an algorithm, AveBoost, that constructed distributions orthogonal to the mistake vectors of all the previous models, and then averaged them to create the next base model s distribution. Our experiments demonstrated the superior accuracy of our approach. In this paper, we slightly revise our algorithm to allow us to obtain non-trivial theoretical results: bounds on the training error and generalization error (difference between training and test error). Our averaging process has a regularizing effect which, as expected, leads us to a worse training error bound for our algorithm than for AdaBoost but a superior generalization error bound. For this paper, we experimented with the data that we used in both as originally supplied and with added label noise-a small fraction of the data has its original label changed. Noisy data are notoriously difficult for AdaBoost to learn. Our algorithm's performance improvement over AdaBoost is even greater on the noisy data than the original data.

Oza, Nikunj C.↗
NASA NTRS1974

Short-range forecasts with the GISS model of the global atmosphere

A nine-layer, primitive equation (PE) model of the global atmosphere developed at the Goddard Institute for Space Studies (GISS) has been used to generate six 48-hr forecasts during December 1972 and January 1973. Operational analyses north of 18 N and experimental global analyses made available by the National Meteorological Center (NMC), NOAA, were used as the initial conditions; the operational analyses were used to verify the forecasts at 12-hr intervals over the Northern Hemisphere north of 22 N. The combined analyses were used to verify the forecasts in the global domain. RMS errors of the sea-level pressure, 1000-mb heights, and vector geostrophic winds, and 500-mb heights and vector geostrophic winds indicate that the GISS forecasts have skill comparable to those made by operational PE models.

Druyan, L. M.↗
NASA NTRS1982

Determination of intercontinental baselines and Earth orientation using VLBI

A series of experiments was conducted during the last decade to explore the capability of very long baseline interferometry (VLBI) to measure the crustal and rotational motions of the Earth with accuracies at the centimeter level. The observing stations are those of NASA's Deep Space Network in California, Spain and Australia. A multiparameter fit to the observed values of delay and delay rate yields radio source positions, polar motion, universal time, the precession constant, baseline vectors, and solid Earth tides. Source positions are obtained with formal errors of the order of 0''.01. UT1-UTC and polar motion are determined at 49 epochs, with formal error estimates for the more recent data of 0.5 msec for UT1-UTC and 2 to 6 mas for polar motion. Intercontinental baseline lengths are determined with formal errors of 5 to 10 cm. The Love numbers and Earth tide phase lag agree with the commonly accepted values.

Sovers, O. J.↗
NASA NTRS1984

Analysis of lidar, radar and satellite measurements on severe thunderstorms and their environments

Intercomparison of wind data from the airborne Doppler lidar, ground-based Doppler radars, the 444 m NSSL-KTVY tower, and rawinsonde were completed. The vertical profile of wind in the PBL measured by the radars compared favorably with the profiles measured by the tower and rawinsonde while the one obtained from lidar data differed from the other three by as much as 3m/sec in wind speed and 38 degrees in direction. The time dependence of differences in wind estimates from radar and lidar suggested that these discrepencies could be attributed to a Schuler resonance in the aircraft's inertial navigation system which caused an erroneous component of the aircraft's velocity vector to be subtracted from the lidar radial velocities, thus creating errors in the synthesized wind speed and direction. The vertical profile of turbulent fluctuations of the horizontal wind detected by the different systems compared well. Also, spectra from the different sensing systems compared well in both magnitude and shape, suggesting that the lidar and radar detected similar turbulent structure.

Bluestein, H.↗