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At least 469 records · Page 26

Lagged average forecasting, an alternative to Monte Carlo forecasting

A 'lagged average forecast' (LAF) model is developed for stochastic dynamic weather forecasting and used for predictions in comparison with the results of a Monte Carlo forecast (MCF). The technique involves the calculation of sample statistics from an ensemble of forecasts, with each ensemble member being an ordinary dynamical forecast (ODF). Initial conditions at a time lagging the start of the forecast period are used, with varying amounts of time for the lags. Forcing by asymmetric Newtonian heating of the lower layer is used in a two-layer, f-plane, highly truncated spectral model in a test forecasting run. Both the LAF and MCF are found to be more accurate than the ODF due to ensemble averaging with the MCF and the LAF. When a regression filter is introduced, all models become more accurate, with the LAF model giving the best results. The possibility of generating monthly or seasonal forecasts with the LAF is discussed.

Hoffman, R. N.↗

LANDSAT instruments characterization

Work performed for the LANDSAT instrument characterization task in the areas of absolute radiometry, coherent noise analysis, and between-date smoothing is reported. Absolute radiometric calibration for LANDSAT-5 TM under ambient conditions was performed. The TM Radiometric Algorithms and Performance Program (TRAPP) was modified to create optional midscan data files and to match the TM Image Processing System (TIPS) algorithm for pulse determination. Several data reduction programs were developed, including a linear regression and its plotted result. A fast Fourier transformation study was conducted on the resequenced TM data. Subscenes of homogeneous water within scenes over Pensacola, Florida were used for testing the FFT on the resequenced data. Finally, a gain and pulse height stability study of LANDSAT 5 TM spectral bands was performed.

Lee, Y.↗

Cosmic ray secular variations in terrestrial records and aurorae

The rediscovery that the Sun and the solar wind can undergo important changes on historical time scales has brought into question the stability of the cyclic behavior of past time series of solar and solar-terrestrial origin. It was found by Vector Fourier analysis that the solar 11 year cycle is present in the series of 10Be, delta 180, in ice cores and of thermoluminescence (TL) in sea sediments during the last Millennia with a frequency modulation, related to the Sun behavior, as tested by comparison with the Sunspot number R sub z series. It was shown that the cyclogram of the series of yearly Aurorae from 1721 to 1979 linear-regression-corrected-for-R sub z is straight for the periodicity zeta=11,1y, which indicates that such periodicity is constant in time corresponding to the only line present in the 11y band. The maxima of this component appear at the same time together with the high speed solar wind streams taking place in coronal holes situated in high heliolatitudes. It is evidenced that the 11 year cycle has undergone frequency oscillations on a time scale of two centuries, although it is very difficult to determine the periodicities with high accuracy.

Attolini, M. R.↗

STEP and STEPSPL: Computer programs for aerodynamic model structure determination and parameter estimation

The successful parametric modeling of the aerodynamics for an airplane operating at high angles of attack or sideslip is performed in two phases. First the aerodynamic model structure must be determined and second the associated aerodynamic parameters (stability and control derivatives) must be estimated for that model. The purpose of this paper is to document two versions of a stepwise regression computer program which were developed for the determination of airplane aerodynamic model structure and to provide two examples of their use on computer generated data. References are provided for the application of the programs to real flight data. The two computer programs that are the subject of this report, STEP and STEPSPL, are written in FORTRAN IV (ANSI l966) compatible with a CDC FTN4 compiler. Both programs are adaptations of a standard forward stepwise regression algorithm. The purpose of the adaptation is to facilitate the selection of a adequate mathematical model of the aerodynamic force and moment coefficients of an airplane from flight test data. The major difference between STEP and STEPSPL is in the basis for the model. The basis for the model in STEP is the standard polynomial Taylor's series expansion of the aerodynamic function about some steady-state trim condition. Program STEPSPL utilizes a set of spline basis functions.

Batterson, J. G.↗

Data Analysis & Statistical Methods for Command File Errors

This paper explains current work on modeling for managing the risk of command file errors. It is focused on analyzing actual data from a JPL spaceflight mission to build models for evaluating and predicting error rates as a function of several key variables. We constructed a rich dataset by considering the number of errors, the number of files radiated, including the number commands and blocks in each file, as well as subjective estimates of workload and operational novelty. We have assessed these data using different curve fitting and distribution fitting techniques, such as multiple regression analysis, and maximum likelihood estimation to see how much of the variability in the error rates can be explained with these. We have also used goodness of fit testing strategies and principal component analysis to further assess our data. Finally, we constructed a model of expected error rates based on the what these statistics bore out as critical drivers to the error rate. This model allows project management to evaluate the error rate against a theoretically expected rate as well as anticipate future error rates.

Correlation Analysis↗

Comparison of Two Load Prediction Methods for Strain-Gage Balances

Data from a five-component semi-span balance is used to perform a systematic comparison of the load prediction accuracy of two load prediction methods. Both methods independently obtain the load prediction equations from multivariate least squares fits of balance calibration data. The first method is called the Non-Iterative Method. This approach directly uses regression models of the individual load components of a balance for the load prediction. The second method is called the Iterative Method. This alternate approach uses a load iteration equation for the load prediction that is constructed from the regression coefficients of the gage outputs of the balance. Basic characteristics of the two methods are reviewed. Afterwards, both methods are applied to calibration, check load, and wind tunnel test data of a five-component semi-span balance. Selected analysis results are compared. These comparisons confirm that the accuracy of the two methods is the same for all practical purposes.

strain-gage balance↗

Irrigated lands assessment for water management: Technique test

A procedure for estimating irrigated land using full frame LANDSAT imagery was demonstrated. Relatively inexpensive interpretation of multidate LANDSAT photographic enlargements was used to produce a map of irrigated land in California. The LANDSAT and ground maps were then linked by regression equations to enable precise estimation of irrigated land area by county, basin, and statewide. Land irrigated at least once in California in 1979 was estimated to be 9.86 million acres, with an expected error of less than 1.75% at the 99% level of confidence. To achieve the same level of error with a ground-only sample would have required 3 to 5 times as many ground sample units statewide. A procedure for relatively inexpensive computer classification of LANDSAT digital data to irrigated land categories was also developed. This procedure is based on ratios of MSS band 7 and 5, and gave good results for several counties in the Central Valley.

Wall, S. L.↗

Reduction in peak oxygen uptake after prolonged bed rest

The hypothesis that the magnitude of the reduction in peak oxygen uptake (VO2) after bed rest is directly proportional to the level of pre-bed rest peak VO2 is tested. Complete pre and post-bed rest working capacity and body weight data were obtained from studies involving 24 men (19-24 years old) and 8 women (23-34 years old) who underwent bed rest for 14-20 days with no remedial treatments. Results of regression analyses of the present change in post-bed rest peak VO2 on pre-bed rest peak VO2 with 32 subjects show correlation coefficients of -0.03 (NS) for data expressed in 1/min and -0.17 for data expressed in ml/min-kg. In addition, significant correlations are found that support the hypothesis only when peak VO2 data are analyzed separately from studies that utilized the cycle ergometer, particularly with subjects in the supine position, as opposed to data obtained from treadmill peak VO2 tests. It is concluded that orthostatic factors, associated with the upright body position and relatively high levels of physical fitness from endurance training, appear to increase the variability of pre and particularly post-bed rest peak VO2 data, which would lead to rejection of the hypothesis.

Greenleaf, J. E.↗

Aeroelastic Model Structure Computation for Envelope Expansion

Structure detection is a procedure for selecting a subset of candidate terms, from a full model description, that best describes the observed output. This is a necessary procedure to compute an efficient system description which may afford greater insight into the functionality of the system or a simpler controller design. Structure computation as a tool for black-box modeling may be of critical importance in the development of robust, parsimonious models for the flight-test community. Moreover, this approach may lead to efficient strategies for rapid envelope expansion that may save significant development time and costs. In this study, a least absolute shrinkage and selection operator (LASSO) technique is investigated for computing efficient model descriptions of non-linear aeroelastic systems. The LASSO minimises the residual sum of squares with the addition of an l(Sub 1) penalty term on the parameter vector of the traditional l(sub 2) minimisation problem. Its use for structure detection is a natural extension of this constrained minimisation approach to pseudo-linear regression problems which produces some model parameters that are exactly zero and, therefore, yields a parsimonious system description. Applicability of this technique for model structure computation for the F/A-18 (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) Active Aeroelastic Wing project using flight test data is shown for several flight conditions (Mach numbers) by identifying a parsimonious system description with a high percent fit for cross-validated data.

Kukreja, Sunil L.↗

Crop status evaluations and yield predictions

A model was developed for predicting the day 50 percent of the wheat crop is planted in North Dakota. This model incorporates location as an independent variable. The Julian date when 50 percent of the crop was planted for the nine divisions of North Dakota for seven years was regressed on the 49 variables through the step-down multiple regression procedure. This procedure begins with all of the independent variables and sequentially removes variables that are below a predetermined level of significance after each step. The prediction equation was tested on daily data. The accuracy of the model is considered satisfactory for finding the historic dates on which to initiate yield prediction model. Growth prediction models were also developed for spring wheat.

Haun, J. R.↗

Traction behavior of two traction lubricants

In the analysis of rolling-sliding concentrated contacts, such as gears, bearings and traction drives, the traction characteristics of the lubricant are of prime importance. The elastic shear modulus and limiting shear stress properties of the lubricant dictate the traction/slip characteristics and power loss associated with an EHD contact undergoing slip and/or spin. These properties can be deducted directly from the initial slope m and maximum traction coefficient micron of an experimental traction curve. In this investigation, correlation equations are presented to predict m and micron for two modern traction fluids based on the regression analysis of 334 separate traction disk machine experiments. The effects of contact pressure, temperature, surface velocity, ellipticity ratio are examined. Problems in deducing lubricant shear moduli from disk machine tests are discussed.

Loewenthal, S. H.↗

Elastic model of the traction behavior of two traction lubricants

In the analysis of rolling-sliding concentrated contacts, such as gears, bearings and traction drives, the traction characteristics of the lubricant are of prime importance. The elastic shear modulus and limiting shear stress properties of the lubricant dictate the traction/slip characteristics and power loss associated with an EHD contact undergoing slip and/or spin. These properties can be deducted directly from the initial slope m and maximum traction coefficient micron of an experimental traction curve. In this investigation, correlation equations are presented to predict m and micron for two modern traction fluids based on the regression analysis of 334 separate traction disk machine experiments. The effects of contact pressure, temperature, surface velocity, ellipticity ratio are examined. Problems in deducing lubricant shear moduli from disk machine tests are discussed. Previously announced in STAR as N83-20116

Loewenthal, S. H.↗

Sensitivity of C-Band Polarimetric Radar-Based Drop Size Distribution Measurements to Maximum Diameter Assumptions

The estimation of rain drop size distribution (DSD) parameters from polarimetric radar observations is accomplished by first establishing a relationship between differential reflectivity (Z(sub dr)) and the central tendency of the rain DSD such as the median volume diameter (D0). Since Z(sub dr) does not provide a direct measurement of DSD central tendency, the relationship is typically derived empirically from rain drop and radar scattering models (e.g., D0 = F[Z (sub dr)] ). Past studies have explored the general sensitivity of these models to temperature, radar wavelength, the drop shape vs. size relation, and DSD variability. Much progress has been made in recent years in measuring the drop shape and DSD variability using surface-based disdrometers, such as the 2D Video disdrometer (2DVD), and documenting their impact on polarimetric radar techniques. In addition to measuring drop shape, another advantage of the 2DVD over earlier impact type disdrometers is its ability to resolve drop diameters in excess of 5 mm. Despite this improvement, the sampling limitations of a disdrometer, including the 2DVD, make it very difficult to adequately measure the maximum drop diameter (D(sub max)) present in a typical radar resolution volume. As a result, D(sub max) must still be assumed in the drop and radar models from which D0 = F[Z(sub dr)] is derived. Since scattering resonance at C-band wavelengths begins to occur in drop diameters larger than about 5 mm, modeled C-band radar parameters, particularly Z(sub dr), can be sensitive to D(sub max) assumptions. In past C-band radar studies, a variety of D(sub max) assumptions have been made, including the actual disdrometer estimate of D(sub max) during a typical sampling period (e.g., 1-3 minutes), D(sub max) = C (where C is constant at values from 5 to 8 mm), and D(sub max) = M*D0 (where the constant multiple, M, is fixed at values ranging from 2.5 to 3.5). The overall objective of this NASA Global Precipitation Measurement Mission (GPM/PMM Science Team)-funded study is to document the sensitivity of DSD measurements, including estimates of D0, from C-band Z(sub dr) and reflectivity to this range of D(sub max) assumptions. For this study, GPM Ground Validation 2DVD's were operated under the scanning domain of the UAHuntsville ARMOR C-band dual-polarimetric radar. Approximately 7500 minutes of DSD data were collected and processed to create gamma size distribution parameters using a truncated method of moments approach. After creating the gamma parameter datasets the DSD's were then used as input to a T-matrix model for computation of polarimetric radar moments at C-band. All necessary model parameterizations, such as temperature, drop shape, and drop fall mode, were fixed at typically accepted values while the D(sub max) assumption was allowed to vary in sensitivity tests. By hypothesizing a DSD model with D(sub max) (fit) from which the empirical fit to D0 = F[Z(sub dr)] was derived via non-linear least squares regression and a separate reference DSD model with D(sub max) (truth), bias and standard error in D0 retrievals were estimated in the presence of Z(sub dr) measurement error and hypothesized mismatch in D(sub max) assumptions. Although the normalized standard error for D0 = F[Z(sub dr)r] can increase slightly (as much as from 11% to 16% for all 7500 DSDs) when the D(sub max) (fit) does not match D(sub max) (truth), the primary impact of uncertainty in D(sub max) is a potential increase in normalized bias error in D0 (from 0% to as much as 10% over all 7500 DSDs, depending on the extent of the mismatch between D(sub max) (fit) and D(sub max) (truth)). For DSDs characterized by large Z(sub dr) (Z(sub dr) > 1.5 to 2.0 dB), the normalized bias error for D0 estimation at C-band is sometimes unacceptably large (> 10%), again depending on the extent of the hypothesized D(sub max) mismatch. Modeled errors in D0 retrievals from Z(sub dr) at C-band are demonstrated in detail and comparedo similar modeled retrieval errors at S-band and X-band where the sensitivity to D(sub max) is expected to be less. The impact of D(sub max) assumptions to the retrieval of other DSD parameters such as Nw, the liquid water content normalized intercept parameter, are also explored. Likely implications for DSD retrievals using C-band polarimetric radar for GPM are assessed by considering current community knowledge regarding D(sub max) and quantifying the statistical distribution of Z(sub dr) from ARMOR over a large variety of meteorological conditions. Based on these results and the prevalence of C-band polarimetric radars worldwide, a call for more emphasis on constraining our observational estimate of D(sub max) within a typical radar resolution volume is made

Carey, Lawrence D.↗

Analysis and Evaluation of NASA's MK40B Six-Component TASK Balance

The paper discusses the physical characteristics NASA's MK40B TASK balance. It is NASA's newest TASK balance that was optimized for the testing of wind tunnel models in the NASA Ames 11-ft Transonic Wind Tunnel. The calibration data of the MK40B balance was obtained in Calspan's Automatic Balance Calibration System. A machine load schedule design was used for the calibration that was developed at the NASA Ames Balance Calibration Laboratory. The calibration data was analyzed using both the Non-Iterative Method and the Iterative Method. Then, the chosen regression models of the calibration data were assessed and compared using the percent contribution, the variance inflation factor, and the calibration load residuals. Interactions of single-component loads were also quantified. In addition, the bi-directional characteristics of the six gage outputs of the balance were assessed by applying a semi-empirical test that was developed at the Ames Balance Calibration Laboratory. It was concluded that four of the six gages of the balance have bi-directional characteristics. Finally, the accuracy of the load prediction equations of the balance was tested by applying the equations to independent check load data that was obtained at the NASA Ames Balance Calibration Laboratory. The standard deviation of the check load residuals met expectations. The check load data also confirmed that the interactions of the forward and aft normal forces on the axial force gage output are very small. - This paper is to be presented in the invited special session titled: "65 Years of TASK Wind Tunnel Balances - Past, Present, and Future".

wind tunnel balance↗

A Subsonic Aircraft Design Optimization With Neural Network and Regression Approximators

The Flight-Optimization-System (FLOPS) code encountered difficulty in analyzing a subsonic aircraft. The limitation made the design optimization problematic. The deficiencies have been alleviated through use of neural network and regression approximations. The insight gained from using the approximators is discussed in this paper. The FLOPS code is reviewed. Analysis models are developed and validated for each approximator. The regression method appears to hug the data points, while the neural network approximation follows a mean path. For an analysis cycle, the approximate model required milliseconds of central processing unit (CPU) time versus seconds by the FLOPS code. Performance of the approximators was satisfactory for aircraft analysis. A design optimization capability has been created by coupling the derived analyzers to the optimization test bed CometBoards. The approximators were efficient reanalysis tools in the aircraft design optimization. Instability encountered in the FLOPS analyzer was eliminated. The convergence characteristics were improved for the design optimization. The CPU time required to calculate the optimum solution, measured in hours with the FLOPS code was reduced to minutes with the neural network approximation and to seconds with the regression method. Generation of the approximators required the manipulation of a very large quantity of data. Design sensitivity with respect to the bounds of aircraft constraints is easily generated.

Patnaik, Surya N.↗

Evaluation, Analysis, and Application of Internal Strain-Gage Balance Data

Experimental processes, analytical methods, and numerical algorithms are described that may be used to predict the forces and moments of an internal strain–gage balance during a wind tunnel test. First, the control volume model of a strain–gage balance and the concepts of load state, load space, and output space are introduced. These important abstractions provide a better understanding of fundamental characteristics of different balance load prediction approaches. Then, the description of strain–gage balance data and the definition of the primary bridge sensitivity are discussed. Afterwards, basic elements of the calibration of a typical six–component balance are reviewed. Two fundamentally different balance load prediction methods, the processing of check loads, and related topics are also discussed. Three real–world balance data examples are reviewed in great detail to illustrate typical analysis results for a variety of strain–gage balance designs. Finally, important observations are summarized and recommendations are provided. – Additional information and detailed mathematical derivations can be found in the appendices of the document. They include the following topics: balance terminology, definitions of important statistical metrics, balance axis system conventions, balance load transformations, the combined load diagram, electrical output format options, bi–directional output characteristics, determination of the natural zeros, derivation of two balance load prediction methods, description of two tare load iteration algorithms, modeling of balance temperature effects, basics of three–component moment balances, definition of the percent contribution, detection of linear and near–linear dependencies in balance calibration data, a regression model search algorithm, balance interactions, and other related information.

strain-gage balance↗

Two biased estimation techniques in linear regression: Application to aircraft

Several ways for detection and assessment of collinearity in measured data are discussed. Because data collinearity usually results in poor least squares estimates, two estimation techniques which can limit a damaging effect of collinearity are presented. These two techniques, the principal components regression and mixed estimation, belong to a class of biased estimation techniques. Detection and assessment of data collinearity and the two biased estimation techniques are demonstrated in two examples using flight test data from longitudinal maneuvers of an experimental aircraft. The eigensystem analysis and parameter variance decomposition appeared to be a promising tool for collinearity evaluation. The biased estimators had far better accuracy than the results from the ordinary least squares technique.

Klein, Vladislav↗

The effects of pressure sensor acoustics on airdata derived from a high-angle-of-attack flush airdata sensing (HI-FADS) system

The accuracy of a prototype nonintrusive airdata system derived for high-angle-of-attack measurements was demonstrated for quasi-steady maneuvers as great as 55 degrees during phase one of the F-18 high alpha research vehicle flight test program. This system consists of a matrix of nine pressure ports arranged in annular rings on the aircraft nose, and estimates the complete airdata set utilizing flow modeling and nonlinear regression. Particular attention is paid to the effects of acoustical distortions within the individual pressure sensors of the HI-FADS pressure matrix. A dynamic model to quantify these effects which describes acoustical distortion is developed and solved in closed form for frequency response.

Whitmore, Stephen R.↗