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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

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↗
NASA NTRS2024

Summary and Annotated Bibliography of Measurement Error Corrections with Potential Application in Future Quesst Mission Community Noise Studies

This document is motivated by likely needs of the Quesst mission community response tests, which will culminate in data collection and estimation of dose-response regression relationships for consideration by domestic and international aviation regulators. Furthermore, basic research questions evaluating interactions between rates of community annoyance, dose levels, and indicators of the presence of rattle, vibration, and startle hinge on hypothesis testing in the context of regression models. For a variety of reasons, noise doses may be known only imprecisely and may not reflect the actual level experienced by responding subjects. These differences between true dose and estimated dose, be they systematic or random, constitute covariate measurement error. Available statistics literature speaks to the impacts of measurement error on regression models, both in terms of bias in estimated coefficients and predicted values, and in terms of the loss of statistical power for hypothesis testing. Given the particulars of a categorical annoyance response variable and a continuous noise dose predictor variable subject to measurement error during testing, the emphasis of this report is on findings and methods pertinent to generalized linear (and mixed) models likely to be employed during the Quesst mission community tests. We reach the following conclusions: 1. Of four reviewed methods, structural Bayesian measurement error models and simulation extrapolation (SIMEX) may be the most readily applicable to Quesst mission community noise study objectives. 2. If warranted, a linear measurement model can help model systematic sources of measurement error that the classical measurement error does not. 3. For its ready implementation and small additional input requirements, simulation extrapolation may be ideally suited for addressing secondary research questions involving interactions between annoyance, noise dose, and other factors through hypothesis testing. 4. For their flexibility and ability to propagate uncertainty, structural Bayesian hierarchical models have great appeal for mission purposes; some care may be needed in developing appropriate probability models describing actual noise exposure during testing. An annotated bibliography logs additional papers and resources that may be of value to analysts in other projects and disciplines.

Dose-Response Model↗
NASA NTRS1974

Error control in the GCF: An information-theoretic model for error analysis and coding

The structure of data-transmission errors within the Ground Communications Facility is analyzed in order to provide error control (both forward error correction and feedback retransmission) for improved communication. Emphasis is placed on constructing a theoretical model of errors and obtaining from it all the relevant statistics for error control. No specific coding strategy is analyzed, but references to the significance of certain error pattern distributions, as predicted by the model, to error correction are made.

Adeyemi, O.↗
NASA NTRS1988

Measurement of the de Sitter precession of the moon - A relativistic three-body effect

Lunar laser-ranging data, accumulated between 1970 and 1986, are analyzed to estimate the deviation of the precession of the moon's orbit from the predictions of general relativity. No deviation from this predicted de Sitter precession rate of nearly 2 angular sec per century (sec/cy) is found, to within an estimated standard error of 0.04 sec/cy. This standard error, 2 percent of the predicted effect, incorporates an assessment of the likely contributions of systematic errors, and is about threefold larger than the statistical standard error.

Shapiro, I. I.↗
NASA NTRS1981

Tidal dissipation in the moon

Euler's equations of motion, modified to include elasticity and solid friction, were used to study the rotation of the moon. Two heuristic models for the anelasticity were considered: Q independent of frequency and Q inversely proportional to the frequency and Q inversely proportional to the frequency of the strain oscillation. Parameters in each model were estimated by weighted least squares from 9 years of lunar laser range observations. The root mean square of the postfit range residuals was 19 cm in each case. For a strain period of 1 month, the estimates of Q obtained with the two models were similar and surprisingly low: 23 + or - 6. The range of uncertaintly, + or - 6, represents our estimate of the true standard deviation of the estimate of Q, as affected by systematic errors; it is 3 times larger than the formal, statistical, standard error.

Cappallo, R. J.↗
NASA NTRS1978

Statistical considerations in design of spacelab experiments

After making an analysis of experimental error sources, statistical models were developed for the design and analysis of potential Space Shuttle experiments. Guidelines for statistical significance and/or confidence limits of expected results were also included. The models were then tested out on the following proposed Space Shuttle biomedical experiments: (1) bone density by computer tomography; (2) basal metabolism; and (3) total body water. Analysis of those results and therefore of the models proved inconclusive due to the lack of previous research data and statistical values. However, the models were seen as possible guides to making some predictions and decisions.

Robinson, J.↗
NASA NTRS1990

The spin vector of Venus

Analysis of radar observations from 1964 through 1983 yields the following values for the components of the spin vector of Venus: P = 243.026 + or - 0.006 d (retrograde); alpha = 272.75 + or - 0.09 deg; and delta = 67.10 + or - 0.09 deg, where the standard errors quoted are three- to five-fold larger than the statistical standard errors and encompass the changes in results obtained by various tests designed to expose possible systematic errors. These values demonstrate conclusively that the spin state of Venus is not in resonance with the relative orbital motions of Venus and earth.

Shapiro, I. I.↗
NASA NTRS2000

Evaluation of the Applicability of Solar and Lamp Radiometric Calibrations of a Precision Sun Photometer Operating Between 300 and 1025 nm

Over a period of 3 year a precision Sun photometer (SPM) operating between 300 and 1025 nm was calibrated four times at three different high-mountain sites in Switzerland, Germany, and the United States by means of the Langley-plot technique. We found that for atmospheric window wavelengths the total error (2 sigma-statistical plus systematic errors) of the calibration constants V(sub 0)(lambda), the SPM voltage in the absence of any attenuating atmosphere, can be kept below 1.60% in the UV-A and blue, 0.9% in the mid-visible, and 0.6% in the near-infra red spectral region. For SPM channels within strong water-vapor or ozone absorption bands a modified Langley-plot technique was used to determine V(sub 0)(lambda) with a lower accuracy. Within the same period of time, we calibrated the SPM five times using irradiance standard lamps in the optical labs of the Physikalisch-Meteorologisches Observatorium Davos and World Radiation Center, Switzerland, and of the Remote Sensing Group of the Optical Sciences Center, University of Arizona, Tucson, Arizona. The lab calibration method requires knowledge of the extraterrestrial spectral irradiance. When we refer the standard lamp results to the World Radiation Center extraterrestrial solar irradiance spectrum, they agree with the Langley results within 2% at 6 or 13 SPM wavelengths. The largest disagreement (4.4%) is found for the channel centered at 610 nm. The results of these intercomparisons change significantly when the lamp results are referred to two different extraterrestrial solar irradiance spectra that have become recently available.

Schmid, Beat↗
NASA NTRS2003

Estimation of Model Error Variances During Data Assimilation

Data assimilation is all about understanding the error characteristics of the data and models that are used in the assimilation process. Reliable error estimates are needed to implement observational quality control, bias correction of observations and model fields, and intelligent data selection. Meaningful covariance specifications are obviously required for the analysis as well, since the impact of any single observation strongly depends on the assumed structure of the background errors. Operational atmospheric data assimilation systems still rely primarily on climatological background error covariances. To obtain error estimates that reflect both the character of the flow and the current state of the observing system, it is necessary to solve three problems: (1) how to account for the short-term evolution of errors in the initial conditions; (2) how to estimate the additional component of error caused by model defects; and (3) how to compute the error reduction in the analysis due to observational information. Various approaches are now available that provide approximate solutions to the first and third of these problems. However, the useful accuracy of these solutions very much depends on the size and character of the model errors and the ability to account for them. Model errors represent the real-world forcing of the error evolution in a data assimilation system. Clearly, meaningful model error estimates and/or statistics must be based on information external to the model itself. The most obvious information source is observational, and since the volume of available geophysical data is growing rapidly, there is some hope that a purely statistical approach to model error estimation can be viable. This requires that the observation errors themselves are well understood and quantifiable. We will discuss some of these challenges and present a new sequential scheme for estimating model error variances from observations in the context of an atmospheric data assimilation system.

Dee, Dick↗
NASA NTRS1971

Navigation analysis for Viking 1979, option B

A parametric study performed for 48 trans-Mars reference missions in support of the Viking program is reported. The launch dates cover several months in the year 1979, and each launch date has multiple arrival dates in 1980. A plot of launch versus arrival dates with case numbers designated for reference purposes is included. The analysis consists of the computation of statistical covariance matrices based on certain assumptions about the ground-based tracking systems. The error model statistics are listed in tables. Tracking systems were assumed at three sites: Goldstone, California; Canberra, Australia; and Madrid, Spain. The tracking data consisted of range and Doppler measurements taken during the tracking intervals starting at E-30(d) and ending at E-10(d) for the control data and ending at E-18(h) for the knowledge data. The control and knowledge covariance matrices were delivered to the Planetary Mission Analysis Branch for inputs into a delta V dispersion analysis.

Mitchell, P. H.↗
NASA NTRS1995

Model studies of the beam-filling error for rain-rate retrieval with microwave radiometers

Low-frequency (less than 20 GHz) single-channel microwave retrievals of rain rate encounter the problem of beam-filling error. This error stems from the fact that the relationship between microwave brightness temperature and rain rate is nonlinear, coupled with the fact that the field of view is large or comparable to important scales of variability of the rain field. This means that one may not simply insert the area average of the brightness temperature into the formula for rain rate without incurring both bias and random error. The statistical heterogeneity of the rain-rate field in the footprint of the instrument is key to determining the nature of these errors. This paper makes use of a series of random rain-rate fields to study the size of the bias and random error associated with beam filling. A number of examples are analyzed in detail: the binomially distributed field, the gamma, the Gaussian, the mixed gamma, the lognormal, and the mixed lognormal ('mixed' here means there is a finite probability of no rain rate at a point of space-time). Of particular interest are the applicability of a simple error formula due to Chiu and collaborators and a formula that might hold in the large field of view limit. It is found that the simple formula holds for Gaussian rain-rate fields but begins to fail for highly skewed fields such as the mixed lognormal. While not conclusively demonstrated here, it is suggested that the notionof climatologically adjusting the retrievals to remove the beam-filling bias is a reasonable proposition.

Ha, Eunho↗
NASA NTRS1976

LACIE performance predictor final operational capability program description, volume 1

The program EPHEMS computes the orbital parameters for up to two vehicles orbiting the earth for up to 549 days. The data represents a continuous swath about the earth, producing tables which can be used to determine when and if certain land segments will be covered. The program GRID processes NASA's climatology tape to obtain the weather indices along with associated latitudes and longitudes. The program LUMP takes substrata historical data and sample segment ID, crop window, crop window error and statistical data, checks for valid input parameters and generates the segment ID file, crop window file and the substrata historical file. Finally, the System Error Executive (SEE) Program checks YES error and truth data, CAMS error data, and signature extension data for validity and missing elements. A message is printed for each error found.

Source record↗
NASA NTRS1990

Imaging other planetary systems from the moon

This paper studies the problem of using a telescope like the HST, only larger and sensitive to a wider range of wavelengths, to image systems of planets like the solar system around other stars. Both reflected starlight and thermal radiation from the planets are treated. The instrumental effects of aperture diffraction, scattering due to the power spectral density of telescope mirror surface errors, and telescope thermal emission are included. The integration time required to achieve a signal-to-noise ratio is computed at 5 for photon-statistical random errors only, which is a necessary but not sufficient criterion for detection at a confidence level of five standard deviations. A cold telescope on the moon with 16m aperture and the optical quality of HST could detect and characterize planets around nearby stars.

Brown, Robert A.↗
NASA NTRS1986

Cosmic ray records in Antarctic meteorites

The cosmogenic radionuclides Be(10), Al(26), and Mn(53) and noble gases were determined in more than 28 meteorites from Antarctica by nuclear analytical techniques and static mass spectrometry, respectively. The summarized results are listed. The concentrations of Al(26) and Mn(53) are normalized to the repective main target elements and given in dpm/kg Si sub eq and dpm/kg Fe. The errors stated include statistical as well as systematical errors. For noble gas concentrations estimated errors are 5% and for isotopic ratios 1.5%. Cosmic ray exposure ages T sub 21 were calculated by the noble gas concentrations and the terrestrial residence time (T) on the basis of the spallogenic nuclide Al(26). The suggested pairing of the LL6 chondrite RKPA 80238 and RKPA 80248 and the eucrites ALHA 76005 and ALHA 79017 is confirmed not only by the noble gas data but also by the concentrations of the spallation produced radionuclides. Futhermore, ALHA 80122, clasified as an H6 chondrite, has a noble gas pattern which suggest that this meteorite belongs to the ALHA 80111 shower.

Vogt, S.↗
NASA NTRS2015

Method for Real-Time Model Based Structural Anomaly Detection

A system and methods for real-time model based vehicle structural anomaly detection are disclosed. A real-time measurement corresponding to a location on a vehicle structure during an operation of the vehicle is received, and the real-time measurement is compared to expected operation data for the location to provide a modeling error signal. A statistical significance of the modeling error signal to provide an error significance is calculated, and a persistence of the error significance is determined. A structural anomaly is indicated, if the persistence exceeds a persistence threshold value.

Smith, Timothy A.↗
NASA NTRS1992

A search for the dipole anisotropy of the Cosmic x ray background

X ray data was analyzed which was obtained by the HEAO-1 A2 satellite in order to look for large scale structure in the Cosmic X ray Background. The dipole moment of the x ray background is deltaI/I = (1.87 + or - .34)x 10(exp -2) in a direction, declination = 3.6 + or - 9.4 deg and right ascension = 15.9 + or - .2 hr. This implies a velocity of the Earth with respect to the background of 409.2 + or - 74.4 km/s in the same direction. Comparatively, measurements of the dipole anisotropy of the Cosmic Microwave Background imply a velocity of 369.2 + or - 4 km/s in a direction, declination = 6 + or - 1 deg and right ascension = 11.2 + or - .1 hr. Quoted errors are statistical only. The disparity between the velocities of the x ray dipole and microwave dipole may be due to residual structure in the x ray sky or as yet undiscovered systematic errors.

Evans, Tom↗
NASA NTRS2022

How Well do Multisatellite Products Capture the Space-Time Dynamics of Precipitation? Part II: Building an Error Model Through Spectral System Identification

Satellite precipitation products, as all quantitative estimates, come with some inherent degree of uncertainty. To associate a quantitative value of the uncertainty to each individual estimate, error modeling is necessary. Most of the error models proposed so far compute the uncertainty as a function of precipitation intensity only, and only at one specific spatio-temporal scale. We propose a spectral error model which accounts for the neighboring space-time dynamics of precipitation into the uncertainty quantification. Systematic distortions of the precipitation signal and random errors are characterized distinctively in every frequency-wavenumber band in the Fourier domain, to accurately characterize error across scales. The systematic distortions are represented as a deterministic space-time linear filtering term. The random errors are represented as a non-stationary additive noise. The spectral error model is applied to the IMERG multi satellite precipitation product and its parameters are estimated empirically through a system identification approach using the GV-MRMS gauge-radar measurements as reference (“truth”) over the eastern United States. The filtering term is found to be essentially low-pass. While traditional error models attribute most of the error variance to random errors, it is found here that the systematic filtering term explains 48% of the error variance at the native resolution of IMERG. This fact confirms that, at high resolution, filtering effects in satellite precipitation products cannot be ignored, and that the error cannot be represented as a purely random additive or multiplicative term. An important consequence is that precipitation estimates derived from totally different sources shall not be expected to automatically have statistically independent errors.

Precipitation↗