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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Development of a winter wheat adjustable crop calendar model

The author has identified the following significant results. Least squares techniques were applied for parameter estimation of functions to predict winter wheat phenological stage with daily maximum temperature, minimum temperature, daylength, and precipitation as independent variables. After parameter estimation, tests were conducted using independent data. It may generally be concluded that exponential functions have little advantage over polynomials. Precipitation was not found to significantly affect the fits. The Robertson triquadratic form, in general use for spring wheat, yielded good results, but special techniques and care are required. In most instances, equations with nonlinear effects were found to yield erratic results when utilized with averaged daily environmental values as independent variables.

Baker, J. R.↗
NASA NTRSDate not supplied

Comparison of Corcos-based and experimentally-derived coherence factors for BFFs estimation

In this paper, high-spatial-resolution unsteady Pressure Sensitive Paint (uPSP) data are utilized to compare two methods for panel Buffet Forcing Functions (BFF) estimation for the Space Launch System (SLS). Such methods are based on discrete pressure measurements within a panel but employ coherence factors to account for partially-correlated fluctuating pressures across the whole panel. In one method, coherence factors are derived based on the Corcos model, whereas the second method utilizes experimentally-derived coherence factors. To simulate discrete measurements using uPSP data, suitable subsets of the data are extracted. When full uPSP resolution is retained, uPSP data provide a benchmark to assess discrete-measurements-based methods. The analysis focuses on the peak SLS buffet environment located downstream of the Forward Attachment Hardware (FAH) between the core stage and solid rocket boosters. Trends of Corcos-based and experimentally-derived coherence factors are in reasonable agreement with the benchmark. However, at certain frequencies, experimentally-derived coherence factors are sensitive to the separation distance between pressure measurements utilized to compute coherence lengths. Such sensitivity originates from deviation of the experimental-based coherence function from an exponential decay assumption. On the other hand, the present implementation of the Corcos model fails to capture certain non-turbulent boundary layer related environments, such as a subharmonic of FAH vortex-shedding. For all methods presented in this paper, at near transonic conditions, increased pressure coherence and spatial nonuniformity lead to BFF overestimation and sensitivity to the pressure measurement location within the panel.

transonic buffet↗
NASA NTRS2015

Airborne Doppler Wind Lidar Post Data Processing Software DAPS-LV

Systems, methods, and devices of the present invention enable post processing of airborne Doppler wind LIDAR data. In an embodiment, airborne Doppler wind LIDAR data software written in LabVIEW may be provided and may run two versions of different airborne wind profiling algorithms. A first algorithm may be the Airborne Wind Profiling Algorithm for Doppler Wind LIDAR ("APOLO") using airborne wind LIDAR data from two orthogonal directions to estimate wind parameters, and a second algorithm may be a five direction based method using pseudo inverse functions to estimate wind parameters. The various embodiments may enable wind profiles to be compared using different algorithms, may enable wind profile data for long haul color displays to be generated, may display long haul color displays, and/or may enable archiving of data at user-selectable altitudes over a long observation period for data distribution and population.

Beyon, Jeffrey Y.↗
NASA NTRS1991

Energy functions for regularization algorithms

Regularization techniques are widely used for inverse problem solving in computer vision such as surface reconstruction, edge detection, or optical flow estimation. Energy functions used for regularization algorithms measure how smooth a curve or surface is, and to render acceptable solutions these energies must verify certain properties such as invariance with Euclidean transformations or invariance with parameterization. The notion of smoothness energy is extended here to the notion of a differential stabilizer, and it is shown that to void the systematic underestimation of undercurvature for planar curve fitting, it is necessary that circles be the curves of maximum smoothness. A set of stabilizers is proposed that meet this condition as well as invariance with rotation and parameterization.

Delingette, H.↗
NASA NTRS1977

Parameter estimation in a human operator describing function model for a two-dimensional tracking task

A previously described parameter estimation program was applied to a number of control tasks, each involving a human operator model consisting of more than one describing function. One of these experiments is treated in more detail. It consisted of a two dimensional tracking task with identical controlled elements. The tracking errors were presented on one display as two vertically moving horizontal lines. Each loop had its own manipulator. The two forcing functions were mutually independent and consisted each of 9 sine waves. A human operator model was chosen consisting of 4 describing functions, thus taking into account possible linear cross couplings. From the Fourier coefficients of the relevant signals the model parameters were estimated after alignment, averaging over a number of runs and decoupling. The results show that for the elements in the main loops the crossover model applies. A weak linear cross coupling existed with the same dynamics as the elements in the main loops but with a negative sign.

Vanlunteren, A.↗
NASA NTRS2010

Algorithms for Learning Preferences for Sets of Objects

A method is being developed that provides for an artificial-intelligence system to learn a user's preferences for sets of objects and to thereafter automatically select subsets of objects according to those preferences. The method was originally intended to enable automated selection, from among large sets of images acquired by instruments aboard spacecraft, of image subsets considered to be scientifically valuable enough to justify use of limited communication resources for transmission to Earth. The method is also applicable to other sets of objects: examples of sets of objects considered in the development of the method include food menus, radio-station music playlists, and assortments of colored blocks for creating mosaics. The method does not require the user to perform the often-difficult task of quantitatively specifying preferences; instead, the user provides examples of preferred sets of objects. This method goes beyond related prior artificial-intelligence methods for learning which individual items are preferred by the user: this method supports a concept of setbased preferences, which include not only preferences for individual items but also preferences regarding types and degrees of diversity of items in a set. Consideration of diversity in this method involves recognition that members of a set may interact with each other in the sense that when considered together, they may be regarded as being complementary, redundant, or incompatible to various degrees. The effects of such interactions are loosely summarized in the term portfolio effect. The learning method relies on a preference representation language, denoted DD-PREF, to express set-based preferences. In DD-PREF, a preference is represented by a tuple that includes quality (depth) functions to estimate how desired a specific value is, weights for each feature preference, the desired diversity of feature values, and the relative importance of diversity versus depth. The system applies statistical concepts to estimate quantitative measures of the user s preferences from training examples (preferred subsets) specified by the user. Once preferences have been learned, the system uses those preferences to select preferred subsets from new sets. The method was found to be viable when tested in computational experiments on menus, music playlists, and rover images. Contemplated future development efforts include further tests on more diverse sets and development of a sub-method for (a) estimating the parameter that represents the relative importance of diversity versus depth, and (b) incorporating background knowledge about the nature of quality functions, which are special functions that specify depth preferences for features.

Wagstaff, Kiri L.↗
NASA NTRS1976

Detectability of auditory signals presented without defined observation intervals

Ability to detect tones in noise was measured without defined observation intervals. Latency density functions were estimated for the first response following a signal and, separately, for the first response following randomly distributed instances of background noise. Detection performance was measured by the maximum separation between the cumulative latency density functions for signal-plus-noise and for noise alone. Values of the index of detectability, estimated by this procedure, were approximately those obtained with a 2-dB weaker signal and defined observation intervals. Simulation of defined- and non-defined-interval tasks with an energy detector showed that this device performs very similarly to the human listener in both cases.

Watson, C. S.↗
NASA NTRS1992

Computer program for calculating and fitting thermodynamic functions

A computer program is described which (1) calculates thermodynamic functions (heat capacity, enthalpy, entropy, and free energy) for several optional forms of the partition function, (2) fits these functions to empirical equations by means of a least-squares fit, and (3) calculates, as a function of temperture, heats of formation and equilibrium constants. The program provides several methods for calculating ideal gas properties. For monatomic gases, three methods are given which differ in the technique used for truncating the partition function. For diatomic and polyatomic molecules, five methods are given which differ in the corrections to the rigid-rotator harmonic-oscillator approximation. A method for estimating thermodynamic functions for some species is also given.

Mcbride, Bonnie J.↗
NASA NTRS1996

Modeling of Aircraft Unsteady Aerodynamic Characteristics/Part 3 - Parameters Estimated from Flight Data: Parameters Estimated from Flight Data - Part 3

A nonlinear least squares algorithm for aircraft parameter estimation from flight data was developed. The postulated model for the analysis represented longitudinal, short period motion of an aircraft. The corresponding aerodynamic model equations included indicial functions (unsteady terms) and conventional stability and control derivatives. The indicial functions were modeled as simple exponential functions. The estimation procedure was applied in five examples. Four of the examples used simulated and flight data from small amplitude maneuvers to the F-18 HARV and X-31A aircraft. In the fifth example a rapid, large amplitude maneuver of the X-31 drop model was analyzed. From data analysis of small amplitude maneuvers ft was found that the model with conventional stability and control derivatives was adequate. Also, parameter estimation from a rapid, large amplitude maneuver did not reveal any noticeable presence of unsteady aerodynamics.

Klein, Vladislav↗
NASA NTRS1975

Comparison of some biased estimation methods (including ordinary subset regression) in the linear model

Ridge, Marquardt's generalized inverse, shrunken, and principal components estimators are discussed in terms of the objectives of point estimation of parameters, estimation of the predictive regression function, and hypothesis testing. It is found that as the normal equations approach singularity, more consideration must be given to estimable functions of the parameters as opposed to estimation of the full parameter vector; that biased estimators all introduce constraints on the parameter space; that adoption of mean squared error as a criterion of goodness should be independent of the degree of singularity; and that ordinary least-squares subset regression is the best overall method.

Sidik, S. M.↗
NASA NTRS1992

Near-infrared observations of young stellar objects in the Rho Ophiuchi dark cloud

We have conducted an imaging survey of 1.4 sq pc of the Rho Ophiuchi dark cloud in the J, H, and K near-infrared photometric bands. Approximately 337 of our 481 detected sources are associated with the cloud, and we estimate that 48 percent of these have near-infrared excesses, indicative of disks or circumstellar material surrounding these young stellar objects (YSOs). The K-band luminosity function is significantly different in different regions of our survey area, suggesting that YSOs in these regions have different ages or mass functions. We estimate that the entire survey area has a high star-formation efficiency, at roughly 23 percent. Finally, our many newly detected sources provide a relatively large, uniformly sensitive sample of objects for study at longer wavelengths to better determine true source luminosities and evolutionary lifetimes.

Greene, Thomas P.↗
NASA NTRS1970

Quadratic Liapunov functions

Criteria for estimating errors in quadratic approximations to asymptotic stability involving Popov condition based on existence of quadratic Liapunov functions

Weissenberger, S.↗
NASA NTRS2004

Image-Based Computational Fluid Dynamics in Blood Vessel Models: Toward Developing a Prognostic Tool to Assess Cardiovascular Function Changes in Prolonged Space Flights

One of NASA's objectives is to be able to perform a complete, pre-flight, evaluation of cardiovascular changes in astronauts scheduled for prolonged space missions. Computational fluid dynamics (CFD) has shown promise as a method for estimating cardiovascular function during reduced gravity conditions. For this purpose, MRI can provide geometrical information, to reconstruct vessel geometries, and measure all spatial velocity components, providing location specific boundary conditions. The objective of this study was to investigate the reliability of MRI-based model reconstruction and measured boundary conditions for CFD simulations. An aortic arch model and a carotid bifurcation model were scanned in a 1.5T Siemens MRI scanner. Axial MRI acquisitions provided images for geometry reconstruction (slice thickness 3 and 5 mm; pixel size 1x1 and 0.5x0.5 square millimeters). Velocity acquisitions provided measured inlet boundary conditions and localized three-directional steady-flow velocity data (0.7-3.0 L/min). The vessel walls were isolated using NIH provided software (ImageJ) and lofted to form the geometric surface. Constructed and idealized geometries were imported into a commercial CFD code for meshing and simulation. Contour and vector plots of the velocity showed identical features between the MRI velocity data, the MRI-based CFD data, and the idealized-geometry CFD data, with less than 10% differences in the local velocity values. CFD results on models reconstructed from different MRI resolution settings showed insignificant differences (less than 5%). This study illustrated, quantitatively, that reliable CFD simulations can be performed with MRI reconstructed models and gives evidence that a future, subject-specific, computational evaluation of the cardiovascular system alteration during space travel is feasible.

Chatzimavroudis, George P.↗
NASA NTRS1988

On a useful functional representation of control system structure

An alternative structure for control systems is proposed. The structure is represented by a three-element block diagram and three functional definitions. It is argued that the three functional elements form a canonical set. The set includes the functions description, estimation and control. General overlay of the structure on parallel state and nested-state control systems is discussed. Breakdown of two real nested-state control systems into the proposed functional format is displayed. Application of the process to the mapping of complex control systems R and D efforts is explained with the Mars Rover Sample and Return mission as an example. A previous application of this basic functional structure to Space Station performance requirements organization is discussed.

Malchow, Harvey L.↗
NASA NTRS1981

A function space approach to smoothing with applications to model error estimation for flexible spacecraft control

A function space approach to smoothing is used to obtain a set of model error estimates inherent in a reduced-order model. By establishing knowledge of inevitable deficiencies in the truncated model, the error estimates provide a foundation for updating the model and thereby improving system performance. The function space smoothing solution leads to a specification of a method for computation of the model error estimates and development of model error analysis techniques for comparison between actual and estimated errors. The paper summarizes the model error estimation approach as well as an application arising in the area of modeling for spacecraft attitude control.

Rodriguez, G.↗
NASA NTRS1984

Analysis of subpixel registration

The area of subpixel accuracy in image registration and edge detection was studied. Two main directions of research were pursued, edge detection and matching based on the digital geometry of edges, and random field models for probablistic analysis of registration error. In the edge detection approach, error bounds and error probabilities were computed using theoretical models. Algorithms were developed and tests on simulated imagery. The methods appear promising for high accuracy edge position estimation and registration, though further refinement of the procedures is required. Using random field models, a statistical measure of the quality of the cross correlation peak as an estimate of the offset between a sensed and a reference image was developed. Simulations were performed to determine the validity of this estimte with real imagery and to study the results of interpolating digital correlation functions to estimate the translation offset to subpixel accuracy.

Berenstein, C. A.↗
NASA NTRS2006

Space-Time Error Representation and Estimation in Navier-Stokes Calculations

The mathematical framework for a-posteriori error estimation of functionals elucidated by Eriksson et al. [7] and Becker and Rannacher [3] is revisited in a space-time context. Using these theories, a hierarchy of exact and approximate error representation formulas are presented for use in error estimation and mesh adaptivity. Numerical space-time results for simple model problems as well as compressible Navier-Stokes flow at Re = 300 over a 2D circular cylinder are then presented to demonstrate elements of the error representation theory for time-dependent problems.

Barth, Timothy J.↗