Search NASA⌕ Search

SEARCH · Search NASA

Results for “prediction error”

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 163 records · Page 9

Galilean satellite ephemeris improvement using Galileo tour encounter information

Accurate navigation of the satellite tour portion of the Galileo mission requires an accurate ephemeris of the Galilean satellites. The ephemeris is updated using radiometric and optical tracking data acquired during the satellite tour. The improved accuracy of the satellite ephemeris leads to improved targeting accuracy at subsequent encounters. The Galileo mission will benefit from improved targeting accuracy through reduced propellant costs and improved pointing accuracy. The predicted error in the updated ephemeris can be less than approximations inherent in the analytical theory used for the ephemeris, so an alternate numerical representation is applied. This alternate description shows promise but also raises questions of numerical stability.

Murrow, D. W.↗

Averaging analysis of adaptive control algorithms

The method of averaging is used to analyze discrete-time indirect adaptive control. The analysis focuses on various prediction-error-driven identification algorithms coupled with a general linear control law. The plant is not required to be in the model set of the identifier, which accounts for systems with unmodeled plant dynamics. Exogenous input signals including known command signals and unknown disturbances are also included. Both gradient and Newton-based algorithms are considered.

Phillips, Stephen M.↗

On the Wiener-Masani algorithm for finding the generating function of multivariate stochastic processes

The algorithms developed by Wiener and Masani (1957 and 1958) and Masani (1960) for the characterization of a class of multivariate stationary stochastic processes are investigated analytically. The algorithms permit the determination of (1) the generating function, (2) the prediction-error matrix, and (3) an autoregressive representation of the linear least-squares predictor. A number of theorems and lemmas are proved, and it is shown that the range of validity of the algorithms can be extended significantly beyond that given by Wiener and Masani.

Miamee, A. G.↗

Multiple weather regimes over the North Atlantic - Analysis of precursors and successors

Four weather regimes occurring over the Atlantic area and their preferred precursors and successors are identified. The first pattern exhibits the typical European blocking dipole, the second one represents an enhanced zonal flow, the third one consists of a positive anomaly over Greenland, and the last one is characterized by a ridge over the eastern Atlantic Ocean. The backward and forward memory times of the different regimes are established. Preferred precursor and successor patterns are identified as the maxima of the composite probability densities of the anomalies occurring before the onsets and after the breaks. The preferred transitions between regimes are also examined. The systematic aspect of this study gives rise to multiple applications, especially for case and composite studies on model prediction errors.

Vautard, R.↗

Flat plate at incidence as a waverider in rarefied hypersonic flow

The physical validity of continuum models and their ability to predict the critical aerothermodynamic properties of a waverider at high altitudes are examined using a flat plate at angle of attack as a generic hypersonic lifting vehicle. For a shock layer far from local translational equilibrium, a theoretical study based on Grad's thirteen-moment equations shows that the Navier-Stokes based solutions can correctly predict the drag, lift, and surface heat transfer rate, with the prediction error comparable to that of the standard shock-layer theory. The conclusion is supported by a comparison with direct simulation Monte Carlo calculations.

Cheng, H. K.↗

Fundamental parameters of brightest cluster galaxies

Photometry and spectroscopy of a sample of the brightest cluster galaxies (BCGs) are presented, and the relationships between scale length, surface brightness, velocity dispersion, and line strength are determined and compared with the relations determined for lower luminosity ellipticals (LLEs). It is found that the relation between log r(e), log sigma, and mean surface brightness reported by Dressler et al. for LLEs also describes the relation for BCGs fairly well. Fundamental plane solutions for BCGs are derived which can be used as distance indicators with a predicted error of about 21 percent per galaxy. Only a weak correlation is found between the Na D 5893 line strength and velocity dispersion for BCGs, in contrast to the significant correlation between these quantities reported for LLEs. It is found that the mean mass-to-light ratio for BCGs is a factor of about two greater than for the LLEs in the Virgo and Coma sample of Dressler et al.

Oegerle, William R.↗

Acoustic results of the Boeing model 360 whirl tower test

An evaluation is presented for whirl tower test results of the Model 360 helicopter's advanced, high-performance four-bladed composite rotor system intended to facilitate over-200-knot flight. During these performance measurements, acoustic data were acquired by seven microphones. A comparison of whirl-tower tests with theory indicate that theoretical prediction accuracies vary with both microphone position and the inclusion of ground reflection. Prediction errors varied from 0 to 40 percent of the measured signal-to-peak amplitude.

Watts, Michael E.↗

Precise tracking of the Magellan and Pioneer Venus orbiters by same-beam interferometry

Results of a demonstration of same-beam interferometry, the simultaneous tracking of two spacecraft in orbit about a distant planet by widely separated earth-based radio antennas, are presented with regard to the Magellan and Pioneer 12 orbiters at Venus. Signals from both spacecraft fall within the same beamwidth of the tracking antennas. The plane-of-sky position difference between spacecraft is precisely determined by double-differenced phase measurements. This data type complements line-of-sight Doppler and improves orbital accuracy by up to an order of magnitude. The predicted error is dominated by solar plasma fluctuations, and is 15.1 psec for a 5-min integration. The rms of the residuals is less than this by about 25 percent. The shape of the spectrum computed from residuals is consistent with that derived from a model of solar plasma fluctuations. Same-beam interferometry is expected to enhance tracking accuracy and efficiency for proposed multiple missions to Mars.

Border, James S.↗

Optimal experiment design for on-orbit identification

An optimal on-orbit experiment is designed to extract the most information from an on-orbit test, subject to the constraints of the testing environment. However, simply jumping in and optimizing standard measures of information with respect to the experiment design can cause severe problems if attention is not paid to the specific needs and properties of the problem at hand. The actual criteria to be optimized depends on (among other things) the particular ID algorithm and parametrization being used. Two parametric techniques are the focus of this presentation: recursive prediction error method (RPEM) and maximum likelihood estimation (MLE).

Bayard, David S.↗

Optimal gains for a single polar orbiting satellite

Gains are the spatial weighting of an observation in its neighborhood versus the local values of a model prediction. They are the key to data assimilation, as they are the direct measure of how the data are used to guide the model. As derived in the broad context of data assimilation by Kalman and in the context of meteorology, for example, by Rutherford, the optimal gains are functions of the prediction error covariances between the observation and analysis points. Kalman introduced a very powerful technique that allows one to calculate these optimal gains at the time of each observation. Unfortunately, this technique is both computationally expensive and often numerically unstable for dynamical systems of the magnitude of meteorological models, and thus is unsuited for use in PMIRR data assimilation. However, the optimal gains as calculated by a Kalman filter do reach a steady state for regular observing patterns like that of a satellite. In this steady state, the gains are constants in time, and thus could conceivably be computed off-line. These steady-state Kalman gains (i.e., Wiener gains) would yield optimal performance without the computational burden of true Kalman filtering. We proposed to use this type of constant-in-time Wiener gain for the assimilation of data from PMIRR and Mars Observer.

Banfield, Don↗

Neural network prediction of aluminum-lithium weld strengths from acoustic emission amplitude data

AE flaw growth activity was monitored in aluminum-lithium weld specimens from the onset of tensile loading to failure. Data on actual ultimate strengths together with AE data from the beginning of loading up to 25 percent of the expected ultimate strength were used to train a backpropagation neural network to predict ultimate strengths. Architecturally, the fully interconnected network consisted of an input layer for the AE amplitude data, a hidden layer to accommodate failure mechanism mapping, and an output layer for ultimate strength prediction. The trained network was then applied to the prediction of ultimate strengths in the remaining six specimens. The worst case prediction error was found to be +2.6 percent.

Hill, Eric V. K.↗

A steady-state Kalman filter for assimilating data from a single polar orbiting satellite

A steady-state scheme for data assimilation in the context of a single, short period (relative to a day), sun-synchronous, polar-orbiting satellite is examined. If the satellite takes observations continuously, the gains, which are the weights for blending observations and predictions together, are steady in time. For a linear system forced by random noise, the optimal steady-state gains (Wiener gains) are equivalent to those of a Kalman filter. Computing the Kalman gains increases the computational cost of the model by a large factor, but computing the Wiener gains does not. The latter are computed by iteration using prior estimates of the gains to assimilate simulated observations of one run of the model, termed 'truth' into another run termed 'prediction'. At each stage, the prediction errors form the basis for the next estimate of the gains. Steady state is achieved after three or four iterations. Further simplification is achieved by making the gains depend on longitudinal distance from the observation point, not on absolute longitude. For a single-layer primitive equation model, the scheme works well even if only the mass field is observed but not the velocity field. Although the scheme was developed for Mars Observer, it should be applicable to data retrieved from Earth atmosphere satellites, for example, UARS.

Banfield, Don↗

Conflict Probability Estimation for Free Flight

The safety and efficiency of free flight will benefit from automated conflict prediction and resolution advisories. Conflict prediction is based on trajectory prediction and is less certain the farther in advance the prediction, however. An estimate is therefore needed of the probability that a conflict will occur, given a pair of predicted trajectories and their levels of uncertainty. A method is developed in this paper to estimate that conflict probability. The trajectory prediction errors are modeled as normally distributed, and the two error covariances for an aircraft pair are combined into a single equivalent covariance of the relative position. A coordinate transformation is then used to derive an analytical solution. Numerical examples and Monte Carlo validation are presented.

Paielli, Russell A.↗

Nonlinear ARMA models for the D(st) index and their physical interpretation

Time series models successfully reproduce or predict geomagnetic activity indices from solar wind parameters. A method is presented that converts a type of nonlinear filter, the nonlinear Autoregressive Moving Average (ARMA) model to the nonlinear damped oscillator physical model. The oscillator parameters, the growth and decay, the oscillation frequencies and the coupling strength to the input are derived from the filter coefficients. Mathematical methods are derived to obtain unique and consistent filter coefficients while keeping the prediction error low. These methods are applied to an oscillator model for the Dst geomagnetic index driven by the solar wind input. A data set is examined in two ways: the model parameters are calculated as averages over short time intervals, and a nonlinear ARMA model is calculated and the model parameters are derived as a function of the phase space.

Vassiliadis, D.↗

Neural Network Prediction of Aluminum-Lithium Weld Strengths from Acoustic Emission Amplitude Data

Acoustic Emission (AE) flaw growth activity was monitored in aluminum-lithium weld specimens from the onset tensile loading to failure. Data on actual ultimate strengths together with AE data from the beginning of loading up to 25 percent of the expected ultimate strength were used to train a backpropagation neural network to predict ultimate strengths. Architecturally, the fully interconnected network consisted of an input layer for the AE amplitude data, a hidden layer to accommodate failure mechanism mapping, and an output layer for ultimate strength prediction. The trained network was the applied to the prediction of ultimate strengths in the remaining six specimens. The worst case prediction error was found to be +2.6 percent.

Hill, Eric v. K.↗

The Role of Computational Fluid Dynamics at Marshall Space Flight Center

The Marshall Space Flight Center (MSFC) is the Center of Excellence for Space Propulsion Technology within NASA. One of MSFC's goals is to lower the cost of access to space. MSFC's Fluid Dynamics Division, a part of the Structures and Dynamics Lab, assists in accomplishing this goal. This division is divided into two branches: experimental and analytical, whose work is complimentary and integrated. In the analysis branch, the emphasis is to apply, rather than develop computational fluid dynamics (CFD), to reduce the cost of design and development of: (1) pump and turbine feedlines and feed manifolds; (2) all primary and secondary flow paths in pumps; (3) all primary and secondary flow paths in turbines; (4) combustion chambers; (5) rocket engine nozzles and plumes; and (6) launch vehicles ascent. The broad range of applications imposes unique constraints on the software. The use of CFD in evaluating rocket engine hardware, specifically, is of value due to several reasons: (1) Rocket engine hardware is extremely expensive to build and test; (2) high engineering and development cost is due to limited production; (3) the cost of one engine test is greater than the average yearly hardware and software cost; (4) CFD represents a relatively small investment relative to the impact it has on the engine development; and (5) computing costs are continuously decreasing. In terms of accuracy the predictable error is more useful than the inconsistent accuracy. The achievable accuracy varies from application to application. The lack of accuracy is often caused by improper analyses: such as improperly applied or located boundary conditions, or attempting steady analysis of unsteady flows. This report is in viewgraph format.

Garcia, Roberto↗

Evaluation of the Linear Aerospike SR-71 Experiment (LASRE) Oxygen Sensor

The Linear Aerospike SR-71 Experiment (LASRE) was a propulsion flight experiment for advanced space vehicles such as the X-33 and reusable launch vehicle. A linear aerospike rocket engine was integrated into a semi-span of an X-33-like lifting body shape (model), and carried on top of an SR-71 aircraft at NASA Dryden Flight Research Center. Because no flight data existed for aerospike nozzles, the primary objective of the LASRE flight experiment was to evaluate flight effects on the engine performance over a range of altitudes and Mach numbers. Because it contained a large quantity of energy in the form of fuel, oxidizer, hypergolics, and gases at very high pressures, the LASRE propulsion system posed a major hazard for fire or explosion. Therefore, a propulsion-hazard mitigation system was created for LASRE that included a nitrogen purge system. Oxygen sensors were a critical part of the nitrogen purge system because they measured purge operation and effectiveness. Because the available oxygen sensors were not designed for flight testing, a laboratory study investigated oxygen-sensor characteristics and accuracy over a range of altitudes and oxygen concentrations. Laboratory test data made it possible to properly calibrate the sensors for flight. Such data also provided a more accurate error prediction than the manufacturer's specification. This predictive accuracy increased confidence in the sensor output during critical phases of the flight. This paper presents the findings of this laboratory test.

Ennix, Kimberly A.↗

Evaluation of the Linear Aerospike SR-71 Experiment (LASRE) Oxygen Sensor

The Linear Aerospike SR-71 Experiment (LASRE) was a propulsion flight experiment for advanced space vehicles such as the X-33 and reusable launch vehicle. A linear aerospike rocket engine was integrated into a semi-span of an X-33-like lifting body shape (model), and carried on top of an SR-71 aircraft at NASA Dryden Flight Research Center. Because no flight data existed for aerospike nozzles, the primary objective of the LASRE flight experiment was to evaluate flight effects on the engine performance over a range of altitudes and Mach numbers. Because it contained a large quantity of energy in the form of fuel, oxidizer, hypergolics, and gases at very high pressures, the LASRE propulsion system posed a major hazard for fire or explosion. Therefore, a propulsion-hazard mitigation system was created for LASRE that included a nitrogen purge system. Oxygen sensors were a critical part of the nitrogen purge system because they measured purge operation and effectiveness. Because the available oxygen sensors were not designed for flight testing, a laboratory study investigated oxygen-sensor characteristics and accuracy over a range of altitudes and oxygen concentrations. Laboratory test data made it possible to properly calibrate the sensors for flight. Such data also provided a more accurate error prediction than the manufacturer's specification. This predictive accuracy increased confidence in the sensor output during critical phases of the flight. This paper presents the findings of this laboratory test.

Ennix, Kimberly A.↗