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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Uncertainty of Observation Impact Estimation in an Adjoint Model Investigated with an Observing System Simulation Experiment

Adjoint models are often used to estimate the impact of different observations on short-term forecast skill. A common difficulty with the evaluation of short term forecast quality is the choice of verification fields. The use of self-analysis fields for verification is typical but incestuous, and introduces uncertainty due to biases and errors in the analysis field. In this study, an observing system simulation experiment (OSSE) is used to explore the uncertainty in adjoint model estimations of observation impact. The availability of the true state for verification in the OSSE framework in the form of the Nature Run allows calculation of the observation impact without the uncertainties present in self-analysis verification. These impact estimates are compared to estimates calculated using self-analysis verification. The Global Earth Observing System version 5 (GEOS-5) forecast model with Gridpoint Statistical Interpolation (GSI) is used with the National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASA/GMAO) OSSE capability. The adjoint model includes moist processes, with total wet energy selected as the norm for evaluation of observation impacts. The results show that there are measurable but small discrepancies in the adjoint model estimation of observation impact. In general, observations of temperature and winds tend to have overestimated impacts with self-analysis verification, while observations of humidity and moisture-affected observations tend to have underestimated impacts. The small magnitude of the differences in impact estimates supports the robustness of the adjoint method of estimating observation impacts.

N C Prive↗
NASA NTRS2017

Pre-Test Assessment of the Upper Bound of the Drag Coefficient Repeatability of a Wind Tunnel Model

A new method is presented that computes a pre{test estimate of the upper bound of the drag coefficient repeatability of a wind tunnel model. This upper bound is a conservative estimate of the precision error of the drag coefficient. For clarity, precision error contributions associated with the measurement of the dynamic pressure are analyzed separately from those that are associated with the measurement of the aerodynamic loads. The upper bound is computed by using information about the model, the tunnel conditions, and the balance in combination with an estimate of the expected output variations as input. The model information consists of the reference area and an assumed angle of attack. The tunnel conditions are described by the Mach number and the total pressure or unit Reynolds number. The balance inputs are the partial derivatives of the axial and normal force with respect to all balance outputs. Finally, an empirical output variation of 1.0 microV/V is used to relate both random instrumentation and angle measurement errors to the precision error of the drag coefficient. Results of the analysis are reported by plotting the upper bound of the precision error versus the tunnel conditions. The analysis shows that the influence of the dynamic pressure measurement error on the precision error of the drag coefficient is often small when compared with the influence of errors that are associated with the load measurements. Consequently, the sensitivities of the axial and normal force gages of the balance have a significant influence on the overall magnitude of the drag coefficient's precision error. Therefore, results of the error analysis can be used for balance selection purposes as the drag prediction characteristics of balances of similar size and capacities can objectively be compared. Data from two wind tunnel models and three balances are used to illustrate the assessment of the precision error of the drag coefficient.

drag coefficient measurement↗
NASA NTRS1984

Error determination of a successive correction type objective analysis scheme

The Purdue Regional Objective Analysis of the Mesoscale (PROAM) is a successive correction type scheme for the analysis of surface meteorological data. The scheme is subjected to a series of experiments to evaluate its performance under a variety of analysis conditions. The tests include use of a known analytic temperature distribution to quantify error bounds for the scheme. Similar experiments were conducted using actual atmospheric data. Results indicate that the multiple pass technique increases the accuracy of the analysis. Furthermore, the tests suggest appropriate values for the analysis parameters in resolving disturbances for the data set used in this investigation.

Smith, D. R.↗
NASA NTRS1975

Geometric theory of horizon scanners

The note presents a general geometrical theory of spacecraft horizon scanners for the purpose of actual attitude determination, as opposed to just attitude stabilization. Analysis is carried out in terms of the scanning angles and three sets of auxiliary axes: the scanner axes, the nonscanning axes, and the orbital axes. Euler angles (yaw, pitch, and roll) transform the orbital axes to the nonscanning axes, and spacecraft attitude is determined directly from the attitude of the nonscanning axes relative to the orbital axes. In most applications the scanning speed is fast, so that it can be assumed that the attitude of the spacecraft does not change during a scan; however, a perturbation analysis is provided for errors committed by neglecting attitude changes. The analysis is valid for all types of scanners; in addition, the case where two scanners with different half-cone angles are used is considered.

Fang, B. T.↗
NASA NTRS1980

Predicting the thermal/structural performance of the atmospheric trace molecules spectroscopy /ATMOS/ Fourier transform spectrometer

ATMOS is a Fourier transform spectrometer to measure atmospheric trace molecules over a spectral range of 2-16 microns. Assessment of the system performance of ATMOS includes evaluations of optical system errors induced by thermal and structural effects. In order to assess the optical system errors induced from thermal and structural effects, error budgets are assembled during system engineering tasks and line of sight and wavefront deformations predictions (using operational thermal and vibration environments and computer models) are subsequently compared to the error budgets. This paper discusses the thermal/structural error budgets, modelling and analysis methods used to predict thermal/structural induced errors and the comparisons that show that predictions are within the error budgets.

Miller, J. M.↗
NASA NTRS1981

Robustness tests utilizing the structure of modelling error

The present investigation is essentially concerned with the extension of results presented by Lehtomaki et al. (1981) on the robustness of multivariable linear time invariant feedback control systems. The work reported by Lehtomaki et al. is based on a multivariable version of Nyquist's theorem from which several robustness theorems were derived. In connection with the current investigation a slightly more general approach based on Nyquist's theorem is given in a fundamental robustness theorem from which various robustness tests may be obtained. A fundamental characterization of robustness is considered, and important tools from matrix theory are introduced. Attention is given to robustness tests and unstructured model error, and a robustness analysis for linear systems with structured model error.

Lehtomaki, N. A.↗
NASA NTRS1985

Generated spiral bevel gears: Optimal machine-tool settings and tooth contact analysis

Geometry and kinematic errors were studied for Gleason generated spiral bevel gears. A new method was devised for choosing optimal machine settings. These settings provide zero kinematic errors and an improved bearing contact. The kinematic errors are a major source of noise and vibration in spiral bevel gears. The improved bearing contact gives improved conditions for lubrication. A computer program for tooth contact analysis was developed, and thereby the new generation process was confirmed. The new process is governed by the requirement that during the generation process there is directional constancy of the common normal of the contacting surfaces for generator and generated surfaces of pinion and gear.

Litvin, F. L.↗
NASA NTRS1985

Generated spiral bevel gears - Optimal machine-tool settings and tooth contact analysis

Geometry and kinematic errors were studied for Gleason generated spiral bevel gears. A new method was devised for choosing optimal machine settings. These settings provide zero kinematic errors and an improved bearing contact. The kinematic errors are a major source of noise and vibration in spiral bevel gears. The improved bearing contact gives improved conditions for lubrication. A computer program for tooth contact analysis was developed, and thereby the new generation process was confirmed. The new process is governed by the requirement that during the generation process there is directional constancy of the common normal of the contacting surfaces for generator and generated surfaces of pinion and gear.

Litvin, F. L.↗
DOE OSTI2024

MFANS 2024 - Dimensional Analysis Made Easy

There is a significant impact of dimensional errors in systems. Dimensional analysis is difficult due to the large size of systems. SA4U and Scalpel are practical programs which can have an impact beyond traditional software as they are able to perform precise dimensional analysis and repair C++ source code.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2017

Human Error Assessment and Reduction Technique (HEART) and Human Factor Analysis and Classification System (HFACS)

Research results have shown that more than half of aviation, aerospace and aeronautics mishaps/incidents are attributed to human error. As a part of Safety within space exploration ground processing operations, the identification and/or classification of underlying contributors and causes of human error must be identified, in order to manage human error. This research provides a framework and methodology using the Human Error Assessment and Reduction Technique (HEART) and Human Factor Analysis and Classification System (HFACS), as an analysis tool to identify contributing factors, their impact on human error events, and predict the Human Error probabilities (HEPs) of future occurrences. This research methodology was applied (retrospectively) to six (6) NASA ground processing operations scenarios and thirty (30) years of Launch Vehicle related mishap data. This modifiable framework can be used and followed by other space and similar complex operations.

human error↗
NASA NTRS1989

Image defects from surface and alignment errors in grazing incidence telescopes

The rigid body motions and low frequency surface errors of grazing incidence Wolter telescopes are studied. The analysis is based on surface error descriptors proposed by Paul Glenn. In his analysis, the alignment and surface errors are expressed in terms of Legendre-Fourier polynomials. Individual terms in the expression correspond to rigid body motions (decenter and tilt) and low spatial frequency surface errors of mirrors. With the help of the Legendre-Fourier polynomials and the geometry of grazing incidence telescopes, exact and approximated first order equations are derived in this paper for the components of the ray intercepts at the image plane. These equations are then used to calculate the sensitivities of Wolter type I and II telescopes for the rigid body motions and surface deformations. The rms spot diameters calculated from this theory and OSAC ray tracing code agree very well. This theory also provides a tool to predict how rigid body motions and surface errors of the mirrors compensate each other.

Saha, Timo T.↗
NASA NTRS2006

Geolocation and Pointing Accuracy Analysis for the WindSat Sensor

Geolocation and pointing accuracy analyses of the WindSat flight data are presented. The two topics were intertwined in the flight data analysis and will be addressed together. WindSat has no unusual geolocation requirements relative to other sensors, but its beam pointing knowledge accuracy is especially critical to support accurate polarimetric radiometry. Pointing accuracy was improved and verified using geolocation analysis in conjunction with scan bias analysis. nvo methods were needed to properly identify and differentiate between data time tagging and pointing knowledge errors. Matchups comparing coastlines indicated in imagery data with their known geographic locations were used to identify geolocation errors. These coastline matchups showed possible pointing errors with ambiguities as to the true source of the errors. Scan bias analysis of U, the third Stokes parameter, and of vertical and horizontal polarizations provided measurement of pointing offsets resolving ambiguities in the coastline matchup analysis. Several geolocation and pointing bias sources were incfementally eliminated resulting in pointing knowledge and geolocation accuracy that met all design requirements.

Meissner, Thomas↗
NASA NTRS1980

Errors in finite-difference computations on curvilinear coordinate systems

Curvilinear coordinate systems were used extensively to solve partial differential equations on arbitrary regions. An analysis of truncation error in the computation of derivatives revealed why numerical results may be erroneous. A more accurate method of computing derivatives is presented.

Mastin, C. W.↗
NASA NTRS2017

Human Error Assessment and Reduction Technique (HEART) and Human Factor Analysis and Classification System (HFACS)

Research results have shown that more than half of aviation, aerospace and aeronautics mishaps incidents are attributed to human error. As a part of Quality within space exploration ground processing operations, the identification and or classification of underlying contributors and causes of human error must be identified, in order to manage human error.This presentation will provide a framework and methodology using the Human Error Assessment and Reduction Technique (HEART) and Human Factor Analysis and Classification System (HFACS), as an analysis tool to identify contributing factors, their impact on human error events, and predict the Human Error probabilities (HEPs) of future occurrences. This research methodology was applied (retrospectively) to six (6) NASA ground processing operations scenarios and thirty (30) years of Launch Vehicle related mishap data. This modifiable framework can be used and followed by other space and similar complex operations.

human error↗
NASA NTRS2017

Human Error Assessment and Reduction Technique (HEART) and Human Factor Analysis and Classification System (HFACS)

Research results have shown that more than half of aviation, aerospace and aeronautics mishaps incidents are attributed to human error. As a part of Safety within space exploration ground processing operations, the identification and/or classification of underlying contributors and causes of human error must be identified, in order to manage human error. This research provides a framework and methodology using the Human Error Assessment and Reduction Technique (HEART) and Human Factor Analysis and Classification System (HFACS), as an analysis tool to identify contributing factors, their impact on human error events, and predict the Human Error probabilities (HEPs) of future occurrences. This research methodology was applied (retrospectively) to six (6) NASA ground processing operations scenarios and thirty (30) years of Launch Vehicle related mishap data. This modifiable framework can be used and followed by other space and similar complex operations.

mishaps↗
NASA NTRS1985

Gamma-ray burster recurrence time scales

In the decade since gamma-ray bursters (GRBs) were discovered by Klebesadel et al. (1973), many models have been proposed to explain the GRB phenomenon. A difficulty is related to the small number of predictions which would make it possible to evaluate the models. One verifiable prediction is the recurrence time scale, tau-gamma. One method to measure tau-gamma is to look for possible cases of recurrence as indicated by overlapping error boxes. The analysis considered in the present investigation is composed of three procedures. One of these involves a search through known error regions for cases where the error regions overlap. In addition, the number of overlaps expected by chance coincidence alone has been determined, and a calculation has been performed regarding the number of overlaps which are expected due to recurrence for various assumed tau-gamma and luminosity functions.

Schaefer, B. E.↗
NASA NTRS2016

Can Aerosol Direct Radiative Effects Account for Analysis Increments of Temperature in the Tropical Atlantic?

In the late 1990's, prior to the launch of the Terra satellite, atmospheric general circulation models (GCMs) did not include aerosol processes because aerosols were not properly monitored on a global scale and their spatial distributions were not known well enough for their incorporation in operational GCMs. At the time of the first GEOS Reanalysis (Schubert et al. 1993), long time series of analysis increments (the corrections to the atmospheric state by all available meteorological observations) became readily available, enabling detailed analysis of the GEOS-1 errors on a global scale. Such analysis revealed that temperature biases were particularly pronounced in the Tropical Atlantic region, with patterns depicting a remarkable similarity to dust plumes emanating from the African continent as evidenced by TOMS aerosol index maps. Yoram Kaufman was instrumental encouraging us to pursue this issue further, resulting in the study reported in Alpert et al. (1998) where we attempted to assess aerosol forcing by studying the errors of a the GEOS-1 GCM without aerosol physics within a data assimilation system. Based on this analysis, Alpert et al. (1998) put forward that dust aerosols are an important source of inaccuracies in numerical weather-prediction models in the Tropical Atlantic region, although a direct verification of this hypothesis was not possible back then. Nearly 20 years later, numerical prediction models have increased in resolution and complexity of physical parameterizations, including the representation of aerosols and their interactions with the circulation. Moreover, with the advent of NASA's EOS program and subsequent satellites, atmospheric aerosols are now monitored globally on a routine basis, and their assimilation in global models are becoming well established. In this talk we will reexamine the Alpert et al. (1998) hypothesis using the most recent version of the GEOS-5 Data Assimilation System with assimilation of aerosols. We will explicitly calculate the impact of aerosols on the temperature analysis increments in the tropical Atlantic and assess the extent to which inclusion of atmospheric aerosols have reduced these increments.

General Circulation Models↗