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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

NREPS Applications for Water Supply and Management in California and Tennessee

Management of water resources is a balancing act between temporally and spatially limited sources and competitive needs which can often exceed the supply. In order to manage water resources over a region such as the San Joaquin Valley or the Tennessee River Valley, it is pertinent to know the amount of water that has fallen in the watershed and where the water is going within it. Since rain gauge networks are typically sparsely spaced, it is typical that the majority of rainfall on the region may not be measured. To mitigate this under-sampling of rainfall, weather radar has long been employed to provide areal rainfall estimates. The Next-Generation Weather Radars (NEXRAD) make it possible to estimate rainfall over the majority of the conterminous United States. The NEXRAD Rainfall Estimation Processing System (NREPS) was developed specifically for the purpose of using weather radar to estimate rainfall for water resources management. The NREPS is tailored to meet customer needs on spatial and temporal scales relevant to the hydrologic or land-surface models of the end-user. It utilizes several techniques to mitigate artifacts in the NEXRAD data from contaminating the rainfall field. These techniques include clutter filtering, correction for occultation by topography as well as accounting for the vertical profile of reflectivity. This presentation will focus on improvements made to the NREPS system to map rainfall in the San Joaquin Valley for NASA s Water Supply and Management Project in California, but also ongoing rainfall mapping work in the Tennessee River watershed for the Tennessee Valley Authority and possible future applications in other areas of the continent.

Gatlin, P.↗
NASA NTRS2014

Robust Modal Filtering and Control of the X-56A Model with Simulated Fiber Optic Sensor Failures

The X-56A aircraft is a remotely-piloted aircraft with flutter modes intentionally designed into the flight envelope. The X-56A program must demonstrate flight control while suppressing all unstable modes. A previous X-56A model study demonstrated a distributed-sensing-based active shape and active flutter suppression controller. The controller relies on an estimator which is sensitive to bias. This estimator is improved herein, and a real-time robust estimator is derived and demonstrated on 1530 fiber optic sensors. It is shown in simulation that the estimator can simultaneously reject 230 worst-case fiber optic sensor failures automatically. These sensor failures include locations with high leverage (or importance). To reduce the impact of leverage outliers, concentration based on a Mahalanobis trim criterion is introduced. A redescending M-estimator with Tukey bisquare weights is used to improve location and dispersion estimates within each concentration step in the presence of asymmetry (or leverage). A dynamic simulation is used to compare the concentrated robust estimator to a state-of-the-art real-time robust multivariate estimator. The estimators support a previously-derived mu-optimal shape controller. It is found that during the failure scenario, the concentrated modal estimator keeps the system stable.

Modal Filtering↗
NASA NTRS2016

Robust Modal Filtering and Control of the X-56A Model with Simulated Fiber Optic Sensor Failures

The X-56A aircraft is a remotely-piloted aircraft with flutter modes intentionally designed into the flight envelope. The X-56A program must demonstrate flight control while suppressing all unstable modes. A previous X-56A model study demonstrated a distributed-sensing-based active shape and active flutter suppression controller. The controller relies on an estimator which is sensitive to bias. This estimator is improved herein, and a real-time robust estimator is derived and demonstrated on 1530 fiber optic sensors. It is shown in simulation that the estimator can simultaneously reject 230 worst-case fiber optic sensor failures automatically. These sensor failures include locations with high leverage (or importance). To reduce the impact of leverage outliers, concentration based on a Mahalanobis trim criterion is introduced. A redescending M-estimator with Tukey bisquare weights is used to improve location and dispersion estimates within each concentration step in the presence of asymmetry (or leverage). A dynamic simulation is used to compare the concentrated robust estimator to a state-of-the-art real-time robust multivariate estimator. The estimators support a previously-derived mu-optimal shape controller. It is found that during the failure scenario, the concentrated modal estimator keeps the system stable.

Modal Filtering↗
NASA NTRSDate not supplied

A Multivibrational Mode Relaxation Scheme for Two-Temperature Thermochemical State Models

An approach to estimate the effective vibrational relaxation time for polyatomic molecules under the context of two-temperature thermochecmial state model is proposed. Landau-Teller vibrational relaxation equation is used as a basis, and vibrational energies are estimated with partition energy functions assuming harmonic oscillator model. A special weighting procedure is presented, and effective vibrational relaxation time is derived. A series of numerical experiments with CO2 and NH3 mixtures is performed, and the aeroheating results are presented. The results of CO2 environment simulations are compared with the vibrational relaxation model of Park et al. [JTHT, 8(1994), pp. 9–23]. The simulations are also conducted with a modified Landau-Teller expression.

Vibrational relaxation time↗
NASA NTRS1977

Large Area Crop Inventory Experiment (LACIE). Phase 2 evaluation report

Documentation of the activities of the Large Area Crop Inventory Experiment during the 1976 Northern Hemisphere crop year is presented. A brief overview of the experiment is included as well as phase two area, yield, and production estimates for the United States Great Plains, Canada, and the Union of Soviet Socialist Republics spring winter wheat regions. The accuracies of these estimates are compared with independent government estimates. Accuracy assessment of the United States Great Plains yardstick region based on a through blind sight analysis is given, and reasons for variations in estimating performance are discussed. Other phase two technical activities including operations, exploratory analysis, reporting, methods of assessment, phase three and advanced system design, technical issues, and developmental activities are also included.

Source record↗
NASA NTRS1980

Use of multiblade sensors for on-line rotor tip-path plane estimation

Techniques are investigated for on-line estimation of rotor states in the nonrotating frame from multiple, simultaneous measurements in the rotating frame. The multiblade coordinate transformation is first applied to transform both flapping and flapping rate measurements into the nonrotating frame. The 'observer' approach is then used to generate algorithms for estimating tip-path plane rate and attitude from transformed flapping and flapping rate measurements. A numerical evaluation using simulated measurements is conducted to evaluate the performance of the algorithms and recommendations are made.

Du Val, R. W.↗
NASA NTRS2006

Aluminum Effect on the Calibration of the Eu Oxybarometer for Nakhlites

Recent studies of Martian meteorites have shown that Martian magma had wide range of oxygen fugacity. In order to estimate the redox state of the Martian crust and mantle, the partitioning coefficient of Eu in the shergottite pyroxene has been extensively studied. Nakhlite, a cumulate clinopyroxenite, is another important group of Martian meteorites. We have studied synthetic compositions (NT, NL, NJ, NJ2 and NJ4) in order to estimate the Nakhla parent melt composition. In our previous work, we calibrated the Eu oxybarometer for nakhlite using the NJ4 composition which we believe is the closest to the Nakhla parent melt. Consequently, we concluded that Nakhla may have crystallized under fairly reducing condition. However, we also found that the partition coefficient is strongly affected by Al contents in melt and in pyroxene. In this abstract we report the correlation between the D values and Al contents in melt and in pyroxene from our Nakhla experimental studies. Also we check the reliability of our previous calibration of Eu oxybarometer, because Rare Earth Elements (REEs) are easily affected by Al content in melt and in pyroxene and Nakhla pyroxene shows unusual patchy Al zoning.

Makishima, J.↗
NASA NTRS1975

Electron spectroscopic studies related to solar-wind darkening of the lunar surface

Improved instrumentation in the X-ray photoelectron spectrometer allowed the first direct observation of the change of valence state of iron in the silicate Fayalite under helium-ion bombardment. From the observed ion dosage necessary to reduce the iron in the topmost atomic layers to the metallic state it is estimated that similar reduction on the lunar surface under solar-wind proton bombardment would occur between 700 to 1000 years. Within such a time scale, it seems likely that all surface iron in the iron-containing lunar fines should have been reduced to the metallic state. Implications of these experimental observations in terms of various proposed darkening mechanisms are discussed.

Yin, L. I.↗
NASA NTRS1989

Model and simulation development for turbopump health monitoring by parameter estimation

The nonlinear equations describing the flow, pressure and temperature dynamics of the High Pressure Fuel Turbopump of the Space Shuttle Main Engine are summarized and implemented in a digital simulation. Some closed form approximations to the operating curves of the turbopump are made so that closed form derivatives exist. These equations and approximations are then used to develop an extended Kalman filter that estimates the dynamic states of the turbopump and a parameter that can reflect turbopump degradation. The filter is implemented as a digital computer program and applied to data generated by the digital simulation of the turbopump with substantial noise added to the output signals. The results indicate that the parameter estimate converges quickly and accurately. This suggests that the parameter estimate can be used to monitor for turbopump degradations affecting its value.

Walker, Bruce K.↗
NASA NTRS1976

A method of distortion pattern synthesis for high response data screening

An empirically derived method of estimating maximum levels of instantaneous inlet total pressure distortion from steady state measurements is presented. The estimation procedure uses steady state total pressure and root mean square turbulent pressure data measurements to synthesize instantaneous distortion patterns. The synthesis method is tailored to intensify distortion patterns in a manner consistent with the characteristics of the particular index to be used in evaluating inlet/engine compatability. The maximum expected value of distortion, a statistically determined function of the length of time of inlet operation, is used to constrain the amount of pattern intensification. Comparison with an independent set of data is presented for verification of the synthesis method.

King, R. W.↗
NASA NTRS1975

Analysis and application of minimum variance discrete time system identification

An on-line minimum variance parameter identifier is developed which embodies both accuracy and computational efficiency. The formulation results in a linear estimation problem with both additive and multiplicative noise. The resulting filter which utilizes both the covariance of the parameter vector itself and the covariance of the error in identification is proven to be mean square convergent and mean square consistent. The MV parameter identification scheme is then used to construct a stable state and parameter estimation algorithm.

Kaufman, H.↗
NASA NTRS1976

Analysis and application of minimum variance discrete time system identification

An on-line minimum variance parameter identifier is developed which embodies both accuracy and computational efficiency. The formulation results in a linear estimation problem with both additive and multiplicative noise. The resulting filter which utilizes both the covariance of the parameter vector itself and the covariance of the error in identification is proven to be mean square convergent and mean square consistent. The MV parameter identification scheme is then used to construct a stable state and parameter estimation algorithm.

Kotob, S.↗
NASA NTRS1982

The adaptation of a strap down formulation for processing inertial platform data

An estimator propagation formulation which ultilizes dynamic data (attitude and sensed acceleration information) from a gimballed inertial platform has been developed to aid in the Shuttle post-flight trajectory reconstruction process and aerodynamic coefficient determination studies. Unlike the classical inertial algorithms, this formulation yields a six degree-of-freedom fully coupled state and attitude estimate. Furthermore, this inertial version is shown to be independent of initial unknown platform misalignments. Results obtained using actual Inertial Measurement Unit (IMU) data and Aerodynamic Coefficient Identification Package (ACIP) strap down data from Shuttle flights are presented.

Heck, M. L.↗
NASA NTRS1977

Analysis and application of minimum variance discrete linear system identification

An on-line minimum variance (MV) parameter identifier is developed which embodies both accuracy and computational efficiency. The formulation results in a linear estimation problem with both additive and multiplicative noise (AMN). The resulting filter which utilizes both the covariance of the parameter vector itself and the covariance of the error in identification is proven to be mean-square convergent and mean-square consistent. The MV parameter identification scheme is then used to construct a stable state and parameter estimation algorithm.

Kotob, S.↗
NASA NTRS1985

An efficient algorithm for estimating noise covariances in distributed systems

An efficient computational algorithm for estimating the noise covariance matrices of large linear discrete stochatic-dynamic systems is presented. Such systems arise typically by discretizing distributed-parameter systems, and their size renders computational efficiency a major consideration. The proposed adaptive filtering algorithm is based on the ideas of Belanger, and is algebraically equivalent to his algorithm. The earlier algorithm, however, has computational complexity proportional to p to the 6th, where p is the number of observations of the system state, while the new algorithm has complexity proportional to only p-cubed. Further, the formulation of noise covariance estimation as a secondary filter, analogous to state estimation as a primary filter, suggests several generalizations of the earlier algorithm. The performance of the proposed algorithm is demonstrated for a distributed system arising in numerical weather prediction.

Dee, D. P.↗
NASA NTRS2014

Online Prediction of Battery Discharge and Estimation of Parasitic Loads for an Electric Aircraft

Predicting whether or not vehicle batteries contain sufficient charge to support operations over the remainder of a given flight plan is critical for electric aircraft. This paper describes an approach for identifying upper and lower uncertainty bounds on predictions that aircraft batteries will continue to meet output power and voltage requirements over the remainder of a flight plan. Battery discharge prediction is considered here in terms of the following components; (i) online battery state of charge estimation; (ii) prediction of future battery power demand as a function of an aircraft flight plan; (iii) online estimation of additional parasitic battery loads; and finally, (iv) estimation of flight plan safety. Substantial uncertainty is considered to be an irremovable part of the battery discharge prediction problem. However, high-confidence estimates of flight plan safety or lack of safety are shown to be generated from even highly uncertain prognostic predictions.

Battery Discharge Prediction↗