Search NASA⌕ Search

SEARCH · Search NASA

Results for “Error Fields”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Comparing field data using Alpert multi-wavelets

In this paper we introduce a method to compare sets of full-field data using Alpert tree-wavelet transforms. The Alpert tree-wavelet methods transform the data into a spectral space allowing the comparison of all points in the fields by comparing spectral amplitudes. The methods are insensitive to translation, scale and discretization and can be applied to arbitrary geometries. This makes them especially well suited for comparison of field data sets coming from two different sources such as when comparing simulation field data to experimental field data. We have developed both global and local error metrics to quantify the error between two fields. Additionally, we verify the methods on two-dimensional and three-dimensional discretizations of analytical functions. Furthermore, we then deploy the methods to compare full-field strain data from a simulation of elastomeric syntactic foam.

42 ENGINEERING↗
NASA NTRS1980

A parametric study of aliasing error for a narrow field of view scanning radiometer

Starting from the general measurement equation, it is shown that a NFOV scanner can be approximated by a spatially invariant system whose point spread function depends on the detector shape and angular characteristics and electrical filter transfer function for given patches at the top of the atmosphere. The radiometer is modeled by a detector, electrical filter, analog to digital converter followed by a reconstruction filter. The errors introduced by aliasing and blurring into a reconstruction of the input radiant exitance are modeled and analyzed for various detector shapes, sampling intervals, electrical filters and scan types. Quantitative results on the errors introduced are presented showing the various tradeoffs between design parameters. The results indicate that proper selection of detector shape coupled with electrical filter can reduce aliasing errors significantly.

Halyo, N.↗
NASA NTRS2002

Overview of SIM external calibration

Like all astrometric instruments, the Space Interferometry Mission (SIM) suffers from field-dependent errors requiring calibration. Diffraction effects in the delay line, polarization rotations on comer cubes, and beam walk across imperfect optics, all contribute to field-distortion that is significantly larger than is acceptable. The bulk of the systematic error is linear across the field - that is, it results in a magnification error. We show that the linear terms are inconsequential to the performance of SIM because they are inseparable from baseline length and orientation errors. One approach to calibrating the higher-order terms is to perform external' calibration; that is, SIM periodically makes differential measurements of a field of bright stars whose positions are not precisely known. We describe the requirements and constraints on the external calibration process and lay the groundwork for a specific procedure detailed in accompanying papers.

Space↗
NASA NTRS1990

Stiffness-matrix condition number and shape sensitivity errors

This paper derives an error magnification index for assessing the sensitivity of the displacement field to errors in the load vector. It is shown that the error magnification index is less conservative than the stiffness-matrix condition number and that, for some cases, no error magnification occurs even when the condition number is very high. The proposed index was used to calculate the derivatives of beam response to changes in the beam structural parameters, using a semianalytical method. It is shown that the proposed index discriminates well between the calculation of the derivative with respect to length, which is very sensitive to errors, and the calculation of the derivative with respect to cross-sectional height, which is not sensitive.

Haftka, Raphael T.↗
NASA NTRS1991

On error sources during airborne measurements of the ambient electric field

The principal sources of errors during airborne measurements of the ambient electric field and charge are addressed. Results of their analysis are presented for critical survey. It is demonstrated that the volume electric charge has to be accounted for during such measurements, that charge being generated at the airframe and wing surface by droplets of clouds and precipitation colliding with the aircraft. The local effect of that space charge depends on the flight regime (air speed, altitude, particle size, and cloud elevation). Such a dependence is displayed in the relation between the collector conductivity of the aircraft discharging circuit - on one hand, and the sum of all the residual conductivities contributing to aircraft discharge - on the other. Arguments are given in favor of variability in the aircraft electric capacitance. Techniques are suggested for measuring from factors to describe the aircraft charge.

Evteev, B. F.↗
NASA NTRS1996

Interpolation Errors in Spectrum Analyzers

To obtain the proper measurement amplitude with a spectrum analyzer, the correct frequency-dependent transducer factor must be added to the voltage measured by the transducer. This report examines how entering transducer factors into a spectrum analyzer can cause significant errors in field amplitude due to the misunderstanding of the analyzer's interpolation methods. It also discusses how to reduce these errors to obtain a more accurate field amplitude reading.

Martin, J. L.↗
NASA NTRS1987

The error associated with use of various forms of the divergence equation to diagnose geopotential and temperature

This study utilizes a model-generated data set to evaluate the errors associated with the diagnosis of geopotential height using three approximate forms of the divergence equation (DE). The DE was solved on the original sigma-coordinate surfaces of the model to exclude any error produced in the process of interpolating the data from observation points to the coordinate surface of the DE. An inviscid, nonlinear, divergent DE produced rms geopotential height errors as large as 3 m and rms temperature errors of over 26 C in the lower planetary boundary layer (PBL), with minimal errors above 800 mb. Elimination of the isobaric divergence in the velocity field caused additional height errors of 5-6 m and temperature errors of 0.4-1.2 C in the free troposphere. Use of a further-degraded DE without nonlinear terms caused height errors of 10-15 m in the upper troposphere with modestly increased temperature errors. Error fields at all levels had synoptic-scale features, with some mesoalpha structure. No spatial noise was apparent. Use of a temporal spectral filter to eliminate high-frequency modes from the model-generated data did not significantly influence the error associated with use of various forms of the DE.

Modica, George M.↗
NASA NTRS1967

Flight research program. VI.

Correlation between heart rate, landing error and field of view for binocular and monocular sphere of vision of jet pilots

VISUAL FIELD↗
NASA NTRS1972

Optimization of multimagnetometer systems on a spacecraft

Magnetometers on a radial boom may be employed to determine the first N-1 multipole contributions to the spacecraft field and improve the total accuracy of a magnetic field experiment. The total error for systems of one to four magnetometers is investigated. The optimal magnetometer locations, for which the total error is a minimum, are found for given boom-length, instrument errors and magnetic field models characteristic for spacecraft with only a restricted or ineffective magnetic cleanliness program.

Neubauer, F. M.↗
NASA NTRS1991

Simplification of the Kalman filter for meteorological data assimilation

The paper proposes a new statistical method of data assimilation that is based on a simplification of the Kalman filter equations. The forecast error covariance evolution is approximated simply by advecting the mass-error covariance field, deriving the remaining covariances geostrophically, and accounting for external model-error forcing only at the end of each forecast cycle. This greatly reduces the cost of computation of the forecast error covariance. In simulations with a linear, one-dimensional shallow-water model and data generated artificially, the performance of the simplified filter is compared with that of the Kalman filter and the optimal interpolation (OI) method. The simplified filter produces analyses that are nearly optimal, and represents a significant improvement over OI.

Dee, Dick P.↗
NASA NTRS1992

Survey Data for Geomagnetic Field Modelling

The survey data discussed here are based on observations made relatively recently at points on land. A special subset of land survey data consists of those made at specially designated sites known as repeat stations. This class of data will be discussed in another part of this document (Barton, 1991b), so only the briefest of references will be made to repeat stations here. This discussion of 'ordinary' land survey data begins with a description of the spatial and temporal distributions of available survey data based on observations made since 1900. (The reason for this rather arbitrary choice of cut-off date is that this was the value used in the production of the computer file of magnetic survey data (land, sea, air, satellite, rocket) that is the primary source of data for geomagnetic main-field modeling). This is followed by a description of the various types of error to which these survey data are, or may be, subject and a discussion of the likely effects of such errors on field models produced from the data. Finally, there is a short section on the availability of geomagnetic survey data, which also describes how the data files are maintained.

Barraclough, D. R.↗
NASA NTRS2010

Single Event Test Methodologies and System Error Rate Analysis for Triple Modular Redundant Field Programmable Gate Arrays

We present a test methodology for estimating system error rates of Field Programmable Gate Arrays (FPGAs) mitigated with Triple Modular Redundancy (TMR). The test methodology is founded in a mathematical model, which is also presented. Accelerator data from 90 nm Xilins Military/Aerospace grade FPGA are shown to fit the model. Fault injection (FI) results are discussed and related to the test data. Design implementation and the corresponding impact of multiple bit upset (MBU) are also discussed.

error rate calculations↗
NASA NTRSDate not supplied

Assessing the Viability of Using GEOS-Forecast Product for Landslides Forecasting: A Step Toward Early Warning System

Landslides across the globe are mostly triggered by extreme rainfall events affecting infrastructure, transportation and livelihoods. The risks are rarely quantified due to lack of data, analytical skills and limited modeling techniques. Knowledge of local to global scale landslide risks provides communities and national agencies the ability to adapt disaster management practices to mitigate and recover from these hazards. In order to minimize the risks and improve characterization of community resilience to landslides, it is vital to have reliable information about the factors triggering landslides such as rainfall, well ahead in time. Forecasting potential landslide activity and impacts can be achieved through reliable precipitation forecast models. However, it is challenging because of the temporal and spatial variability of precipitation, an important factor in triggering landslides. Evaluation of the precipitation field, associated errors, and sampling uncertainties is integral for development of efficient and reliable landslide forecasting and early warning system. This study develops a methodology to assess the viability of using a precipitation field provided by a global model and its potential integration in the landslide forecasting system. The study focuses on the comparison between the IMERG (Integrated Multi-satellitE Retrievals for Global Precipitation Mission) and GEOS (NASA Goddard Earth Observing System)-Forecast product over contiguous United States (CONUS). GEOS model assimilates new observations every 6 hours, at 00, 06, 12, and 18 UTC. The framework is tested on the GEOS-Forecast Model initialized at 00 UTC using daily IMERG early product as reference using both categorical and continuous statistics. The categorical statistics includes the probability of detection (POD), success ratio (SR), critical success index (CSI), and the hit bias. Continuous statistics such as correlation, normalized standard deviation, and root-mean-square error are also evaluated. Overall, GEOS-Forecast precipitation field over the analysis period (~1 year) show underestimation with respect to IMERG early for the daily accumulated rainfall. However, the probability distribution function and cumulative distribution function of both show similar patterns. In terms of correlations, POD, SR, CSI, hit bias, the performance varies with respect to the rainfall threshold used.

Sana Khan↗
DOE OSTI2022

Error metrics for partially coherent wave fields

Lensless imaging methods that account for partial coherence have become very common in the past decade. However, there are no metrics in use for comparing partially coherent light fields, despite the widespread use of such metrics to compare fully coherent objects and wave fields. Here, we show how reformulating the mean squared error and Fourier ring correlation in terms of quantum state fidelity naturally generalizes them to partially coherent wave fields. We report these results fill an important gap in the lensless imaging literature and will enable quantitative assessments of the reliability and resolution of reconstructed partially coherent wave fields.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗