Statistically Predicting Maneuver Loads from Eight-channel Flight Data Final Report
Statistical prediction of aircraft maneuver fatigue loads from eight-channel oscillograph flight data
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Statistical prediction of aircraft maneuver fatigue loads from eight-channel oscillograph flight data
Two methods are discussed for constructing a design curve on the safe side of fatigue data. Both the tolerance interval and equivalent prediction interval (EPI) concepts provide such a curve while accounting for both the distribution of the estimators in small samples and the data scatter. The EPI is also useful as a mechanism for providing necessary statistics on S-N data for a full reliability analysis which includes uncertainty in all fatigue design factors. Examples of statistical analyses of the general strain life relationship are presented. The tolerance limit and EPI techniques for defining a design curve are demonstrated. Examples usng WASPALOY B and RQC-100 data demonstrate that a reliability model could be constructed by considering the fatigue strength and fatigue ductility coefficients as two independent random variables. A technique given for establishing the fatigue strength for high cycle lives relies on an extrapolation technique and also accounts for "runners." A reliability model or design value can be specified.
In this paper we relate the statistical processes that are involved in multispectral data acquisition and classification to a simple radiometric model of the earth surface and atmosphere. If generalized, these formulations could provide an analytical link between the steadily improving models of our environment and the performance characteristics of rapidly advancing device technology. This link is needed to bring system analysis tools to the task of optimizing remote sensing and (real-time) signal processing systems as a function of target and atmospheric properties, remote sensor spectral bands and system topology (e.g., image-plane processing), radiometric sensitivity and calibration accuracy, compensation for imaging conditions (e.g., atmospheric effects), and classification rates and errors.
A statistical analysis of runway incursion (RI) events was conducted to ascertain relevance to the top ten challenges of the National Aeronautics and Space Administration Aviation Safety Program (AvSP). The information contained in the RI database was found to contain data that may be relevant to several of the AvSP top ten challenges. When combined with other data from the FAA documenting air traffic volume from calendar year 2000 through 2011, the structure of a predictive model emerges that can be used to forecast the frequency of RI events at various airports for various classes of aircraft and under various environmental conditions.
Statistical examination of animal response data obtained using Procedure B of the USF toxicity screening test method indicates that the data deviate only slightly from a normal or Gaussian distribution. This slight departure from normality is not expected to invalidate conclusions based on theoretical statistics. Comparison of times to staggering, convulsions, collapse, and death as endpoints shows that time to death appears to be the most reliable endpoint because it offers the lowest probability of missed observations and premature judgements.
The statistical calculations of the mean and potential bias errors are considered with respect to their applicability to the randomly sampled velocity data obtained from a laser velocimeter. Techniques for displaying the resulting data in the form of arrow plots, flow streamline plots, and contour maps are also discussed. A description is presented of the operation of a new hardware interface between the signal processing electronics and the computer. The interface has been constructed to make it possible to use recently developed data processing techniques for obtaining turbulent power spectra from laser velocimeter data. Additional capabilities which were built into the interface allow the measurement of the velocity vector for each particle passing through the laser velocimeter sample window. By processing the data with extended versions of the turbulent power spectra techniques, cross spectra, interactions between velocity magnitude fluctuations, and flow angle fluctuations may be investigated.
A three-dimensional, multivariate, statistical analysis method, optimal interpolation (OI) is described for modeling meteorological data from widely dispersed sites. The model was developed to analyze FGGE data at the NASA-Goddard Laboratory of Atmospherics. The model features a multivariate surface analysis over the oceans, including maintenance of the Ekman balance and a geographically dependent correlation function. Preliminary comparisons are made between the OI model and similar schemes employed at the European Center for Medium Range Weather Forecasts and the National Meteorological Center. The OI scheme is used to provide input to a GCM, and model error correlations are calculated for forecasts of 500 mb vertical water mixing ratios and the wind profiles. Comparisons are made between the predictions and measured data. The model is shown to be as accurate as a successive corrections model out to 4.5 days.
Ground tests have been made of an instrument which, when assembled in a more compact form for flight installation, could be used to obtain statistical flight data on the liquid-water content of icing clouds and to provide an indication of icing severity. The sensing element of the instrument consists of an electrically heated wire which is mounted in the air stream. The degree of cooling of the wire resulting from evaporation of the impinging water droplets is a measure. of the liquid-water content of the cloud. Determination of the value of the liquid-water content from the wire temperature at any instant requires a knowledge of the airspeed, altitude, and air temperature. An analysis was made of the temperature response of a heated wire exposed to an air stream containing water drops. Comparisons were made of the liquid-water content as measured with several heated wires and absorbent cylinders in an artificially produced cloud. For one of the wires, comparative tests were made with a rotating-disk icing-rate meter in an icing wind tunnel. From the test results, it was shown that an instrument for measuring the concentration of liquid water in an air stream can be built using an electrically heated wire of known temperatureresistance characteristics, and that the performance of such a device can be predicted using appropriate theory. Although an instrument in a form suitable for gathering statistical data in flight was not built, the practicability of constructing such an instrument was illustrated. The ground-test results indicated that a flight heated-wire instrument would be simple and durable, would respond rapidly to variations in liquid-water content, and could be used for the measurement of water content in clouds which are above freezing temperature, as well as in icing clouds.
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A new statistic is proposed for the analysis of circular data. The statistic is designed specifically for situations where a test of uniformity is required which is powerful against alternatives in which a small fraction of the observations is grouped in a small range of directions, or phases.
Crucial to many measurements at the LHC is the use of correlated multi-dimensional information to distinguish rare processes from large backgrounds, which is complicated by the poor modeling of many of the crucial backgrounds in Monte Carlo simulations. In this work, we introduce HI-SIGMA, a method to perform unbinned high-dimensional statistical inference with data-driven background distributions. In contradistinction to many applications of Simulation Based Inference in High Energy Physics, HI-SIGMA relies on generative ML models, rather than classifiers, to learn the signal and background distributions in the high-dimensional space. These ML models allow for interpretable inference while also incorporating model errors and other sources of systematic uncertainties. We showcase this methodology on a simplified version of a di-Higgs measurement in the bbγγ final state, where the di-photon resonance allows for background interpolation from sidebands into the signal region. We demonstrate that HI-SIGMA provides improved sensitivity as compared to standard classifier-based methods, and that systematic uncertainties can be straightforwardly incorporated by extending methods which have been used for histogram based analyses.
An approach to the analysis of a very large elemental concentration data set. The particular data considered was generated by instrumental neutron activation and emission spectroscopy analyses of over 750 24-hour ambient air particulate samples collected at 16 sites in Cleveland, Ohio, during the 15 months from August 1971 thru October 1972. Examples are presented that show the use of multiple approaches to interpreting the data, including pairwise correlation statistics, selective data plotting and cluster analysis.
The total ozone amount over Oslo has been measured with the Dobson spectrophotometer No 56. The instrument was modified, calibrated, and intercompared in 1977 in Boulder. A new intercomparison was made in 1986 in Arosa. Much work has been done to make the zenith charts reliable. A new method has been introduced where one takes into account the change in the shape of the zenith chart curves which is caused by a change of the ozone profile when the ozone amount changes. According to the conclusion derived from the intercomparison in Arosa 1986, the instrument has not been stable. The R-N tables had to be altered, but not the Q-tables. We have tried to account for this change in our handling of the observation data. No statistical analyses of these data has yet been made, but the monthly averages of the raw data show a negative linear trend of about 4 percent for the whole period.
Empirical probability distributions derived from the data are the signatures of physical processes generating the data. Distributions defined on different space-time windows can be compared and differences or changes can be attributed to physical processes. This presentation discusses on ways to reduce remote sensing data in a way that preserves information, focusing on the rate-distortion theory and using the entropy-constrained vector quantization algorithm.
Several statistical and information criteria need to be considered when selecting an adequate model. Incorrect stability and control derivates result from inadequate aerodynamic model structure. Stepwise regression is used to determine the structure for an adequate model. Flight data which covers a nonlinear aerodynamic model range may be analyzed as a single data set or partitioned into several distinct sets. Stepwise regression for model structure detemination and parameter estimation was successfully applied to three aircraft types (single engine general aviation, unaugmented modern jet fighter, jet transport).
Statistical properties of atmospheric turbulence near the Earth's surface are presented. Emphasis is placed on the probability density distribution two point spatial correlation, length scale, and two point and single point spectrum. Comparison of the data with isotropic homogeneous models is made. In general, agreement with the models is poor. For the design of aircraft during operations in the lower levels associated with approach, takeoff, and terrain following, it appears necessary to improve existing models or develop new nonisotropic turbulence models.
The statistics of tropical rain system structure are studied, focusing on the division between convective and stratiform rainfall over the GARP Atlantic Tropical Experiment B-scale array. The satellite IR convective/stratiform technique of Adler and Negri (1988) is used to produce hourly estimates for two day of the GATE. The estimates are verified against the radar data. The results are compared with the results of Houze and Rappaport (1984) and Cheng and Houze (1979). The possible application of the results for estimating the vertical profile of latent heating is discussed.
Statistical procedures taken from the field of survival analysis have been adapted to astronomical usage and have been applied to a sample of stars in the B-V color range between 0.1 and 0.5 with measured soft X-ray luminosities and projected equatorial velocities. The two-sample problem and linear regression problem with arbitrarily censored data were studied. A new method for determining the linear regression between two random variables in the presence of arbitrary censoring has been developed which can also be used for a likelihood-ratio test for the independence of two random variables and for principal-component analysis in the presence of arbitrary censoring. The required numerical computations can be carried out straightforwardly and rapidly.