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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

New Gear Transmission Error Measurement System Designed

The prime source of vibration and noise in a gear system is the transmission error between the meshing gears. Transmission error is caused by manufacturing inaccuracy, mounting errors, and elastic deflections under load. Gear designers often attempt to compensate for transmission error by modifying gear teeth. This is done traditionally by a rough "rule of thumb" or more recently under the guidance of an analytical code. In order for a designer to have confidence in a code, the code must be validated through experiment. NASA Glenn Research Center contracted with the Design Unit of the University of Newcastle in England for a system to measure the transmission error of spur and helical test gears in the NASA Gear Noise Rig. The new system measures transmission error optically by means of light beams directed by lenses and prisms through gratings mounted on the gear shafts. The amount of light that passes through both gratings is directly proportional to the transmission error of the gears. A photodetector circuit converts the light to an analog electrical signal. To increase accuracy and reduce "noise" due to transverse vibration, there are parallel light paths at the top and bottom of the gears. The two signals are subtracted via differential amplifiers in the electronics package. The output of the system is 40 mV/mm, giving a resolution in the time domain of better than 0.1 mm, and discrimination in the frequency domain of better than 0.01 mm. The new system will be used to validate gear analytical codes and to investigate mechanisms that produce vibration and noise in parallel axis gears.

Oswald, Fred B.↗
DOE OSTI2015

Sinusoidal Siemens star spatial frequency response measurement errors due to misidentified target centers

Numerous methods are available to measure the spatial frequency response (SFR) of an optical system. A recent change to the ISO 12233 photography resolution standard includes a sinusoidal Siemens star test target. We take the sinusoidal Siemens star proposed by the ISO 12233 standard, measure system SFR, and perform an analysis of errors induced by incorrectly identifying the center of a test target. We show a closed-form solution for the radial profile intensity measurement given an incorrectly determined center and describe how this error reduces the measured SFR of the system. As a result, using the closed-form solution, we propose a two-step process by which test target centers are corrected and the measured SFR is restored to the nominal, correctly centered values.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2012

Cumulative Measurement Errors for Dynamic Testing of Space Flight Hardware

Located at the NASA Johnson Space Center in Houston, TX, the Six-Degree-of-Freedom Dynamic Test System (SDTS) is a real-time, six degree-of-freedom, short range motion base simulator originally designed to simulate the relative dynamics of two bodies in space mating together (i.e., docking or berthing). The SDTS has the capability to test full scale docking and berthing systems utilizing a two body dynamic docking simulation for docking operations and a Space Station Remote Manipulator System (SSRMS) simulation for berthing operations. The SDTS can also be used for nonmating applications such as sensors and instruments evaluations requiring proximity or short range motion operations. The motion base is a hydraulic powered Stewart platform, capable of supporting a 3,500 lb payload with a positional accuracy of 0.03 inches. The SDTS is currently being used for the NASA Docking System testing and has been also used by other government agencies. The SDTS is also under consideration for use by commercial companies. Examples of tests include the verification of on-orbit robotic inspection systems, space vehicle assembly procedures and docking/berthing systems. The facility integrates a dynamic simulation of on-orbit spacecraft mating or de-mating using flight-like mechanical interface hardware. A force moment sensor is used for input during the contact phase, thus simulating the contact dynamics. While the verification of flight hardware presents unique challenges, one particular area of interest involves the use of external measurement systems to ensure accurate feedback of dynamic contact. The measurement systems for the test facility have two separate functions. The first is to take static measurements of facility and test hardware to determine both the static and moving frames used in the simulation and control system. The test hardware must be measured after each configuration change to determine both sets of reference frames. The second function is to take dynamic measurements during hardware motion and contact. While performing dynamic testing of an active docking system, researchers found that the data from the motion platform, test hardware and two external measurement systems exhibited frame offsets and rotational errors. While the errors were relatively small when considering the motion scale overall, they substantially exceeded the individual accuracies for each component. After evaluating both the static and dynamic measurements, researchers found that the static measurements introduced significantly more error into the system than the dynamic measurements even though, in theory, the static measurement errors should be smaller than the dynamic. In several cases, the magnitude of the errors varied widely for the static measurements. Upon further investigation, researchers found the larger errors to be a consequence of hardware alignment issues, frame location and measurement technique whereas the smaller errors were dependent on the number of measurement points. This paper details and quantifies the individual and cumulative errors of the docking system and describes methods for reducing the overall measurement error. The overall quality of the dynamic docking tests for flight hardware verification was improved by implementing these error reductions.

Winnitoy, Susan↗
DOE OSTI2021

Estimation of sensor measurement errors in reactor coolant systems using multi-sensor fusion

A nuclear power plant is typically instrumented with a variety of sensors to continually monitor its variables, and their sensor’s measurements may be used to assess the plant state and initiate safety actions, if needed. Errors in sensor measurements, due to factors such as calibration drifts, critically affect such state assessments. Here, we address a problem of estimating sensor errors using physics-informed machine learning methods that use measurements collected under known plant conditions. For a given sensor, we propose an information fusion method that uses measurements from other sensors to estimate its output assuming it is error-free and provides its difference from an actual measurement as an error estimate. We present the ensemble of trees and support vector machine fusers, and evaluate their performance using measurements collected over an emulated test loop of a pressurized water reactor. The plant variables are related to each other through the underlying physical laws under inertial constraints that place bounds on their derivatives, which analytically justify the applicability of machine learning methods for computing these fusers. Under twenty scenarios, we assess their sensor error estimates for pressure sensors of the heat exchanger of a reactor’s primary coolant system. Multiple types of errors are captured by both fusers under externally induced calibration drifts, blockages, minor leaks and air gaps in sensing lines, and electromagnetic interference; the root mean square error of the estimation of error is under 2.2% percent of the maximum measurement. We present generalization equations, in the framework of statistical learning theory, for these methods that characterize the confidence probability that the estimation error is bounded by a specified parameter in future test scenarios.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2003

On the Measurement Errors of the Joss-Waldvogel Disdrometer

The Joss-Waldvogel (JW) disdrometer is considered to be a reference instrument for drop size distribution measurements. It has been widely used in many field campaigns as part of validation efforts of radar rainfall estimation. It has also been incorporated in radar rain gauge rainfall observation networks at several ground validation sites for NASA s Tropical Rainfall Measuring Mission (TRMM). It is anticipated that the Joss-Waldvogel disdrometer will be one of the key instruments for ground validation for the upcoming Global Precipitation Measurement (GPM) mission. The JW is an impact type disdrometer and has several shortcomings. One such shortcoming is that it underestimates the number of small drops in heavy rain due to the disdrometer dead time. The detection of smaller drops is also suppressed in the presence of background noise. Further, drops larger than 5.0 to 5.5 mm diameter cannot be distinguished by the disdrometer. The JW assumes that all raindrops fall at their terminal fall speed. Ignoring the influence of vertical air motion on raindrop fall speed results in errors in determining the raindrop size. Also, the bulk descriptors of rainfall that requires the fall speed of the drops will be overestimated or underestimated due to errors in measured size and assumed fall velocity. Long-term observations from a two-dimensional video disdrometer are employed to simulate the JW disdrometer and assess how it s shortcomings affect radar rainfall estimation. Data collected from collocated JW disdrometers were also incorporated in this study.

Tokay, Ali↗
DOE OSTI2021

Reynolds stress tensor measurements using magnetic resonance velocimetry: expansion of the dynamic measurement range and analysis of systematic measurement errors

This study presents magnetic resonance velocimetry (MRV) Reynolds Stress measurements in a periodic hill channel with a hill Reynolds number of Re = 29,500. The velocity encoding scheme is based on the ICOSA6 method with six icosahedral encoding directions and multiple encoding values are measured to increase the dynamic range. The full Reynolds stress tensor is obtained from a voxel-wise three-dimensional Gaussian fit using the magnitude data of all acquisitions. The MRV results are compared to a wall-resolved large eddy simulation and laser Doppler velocimetry measurements conducted in the same channel. It is shown that the MRV Reynolds stress data have excellent precision and agree qualitatively with the reference data. However, there are apparent systematic deviations. One of the most prominent error contributions is the signal attenuation caused by higher orders of motion, which leads to an overestimation of the turbulence level. Another fundamental error is identified in the assumption that the turbulence is Gaussian distributed. With the presented reconstruction technique, the MRV data are fitted to a statistical model, and depending on the examined flow setup, the Gaussian model can lead to considerable errors. Possible ways of how to reduce all identified errors are presented. In summary, this technique enables Reynolds stress tensor measurements in complex internal flows with high dynamic range and excellent precision. However, several issues need to be resolved to make the turbulence quantification more accurate.

42 ENGINEERING↗
DOE OSTI2018

Assessment of Gamma-Ray-Spectra Analysis Method Utilizing the Fireworks Algorithm for Various Error Measures

The analysis of measured data plays a significant role in enhancing nuclear nonproliferation mainly by inferring the presence of patterns associated with special nuclear materials. Among various types of measurements, gamma-ray spectra is the widest utilized type of data in nonproliferation applications. In this paper, a method that employs the fireworks algorithm (FWA) for analyzing gamma-ray spectra aiming at detecting gamma signatures is presented. In particular, FWA is utilized to fit a set of known signatures to a measured spectrum by optimizing an objective function, where non-zero coefficients express the detected signatures. FWA is tested on a set of experimentally obtained measurements optimizing various objective functions—MSE, RMSE, Theil-2, MAE, MAPE, MAP—with results exhibiting its potential in providing highly accurate and precise signature detection. Finally and furthermore, FWA is benchmarked against genetic algorithms and multiple linear regression, showing its superiority over those algorithms regarding precision with respect to MAE, MAPE, and MAP measures.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1999

Investigation of Measurement Errors in Doppler Global Velocimetry

While the initial development phase of Doppler Global Velocimetry (DGV) has been successfully completed, there remains a critical next phase to be conducted, namely the determination of an error budget to provide quantitative bounds for measurements obtained by this technology. This paper describes a laboratory investigation that consisted of a detailed interrogation of potential error sources to determine their contribution to the overall DGV error budget. A few sources of error were obvious; e.g., iodine vapor adsorption lines, optical systems, and camera characteristics. However, additional non-obvious sources were also discovered; e.g., laser frequency and single-frequency stability, media scattering characteristics, and interference fringes. This paper describes each identified error source, its effect on the overall error budget, and where possible, corrective procedures to reduce or eliminate its effect.

Meyers, James F.↗
NASA NTRS2006

The Importance of Measurement Errors for Deriving Accurate Reference Leaf Area Index Maps for Validation of Moderate-Resolution Satellite LAI Products

The validation of moderate-resolution satellite leaf area index (LAI) products such as those operationally generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor data requires reference LAI maps developed from field LAI measurements and fine-resolution satellite data. Errors in field measurements and satellite data determine the accuracy of the reference LAI maps. This paper describes a method by which reference maps of known accuracy can be generated with knowledge of errors in fine-resolution satellite data. The method is demonstrated with data from an international field campaign in a boreal coniferous forest in northern Sweden, and Enhanced Thematic Mapper Plus images. The reference LAI map thus generated is used to assess modifications to the MODIS LAI/fPAR algorithm recently implemented to derive the next generation of the MODIS LAI/fPAR product for this important biome type.

Huang, Dong↗
NASA NTRS1986

Assessment of measurement error due to sampling perspective in the space-based Doppler lidar wind profiler

A Multipair Algorithm (MPA) has been developed to minimize the contribution of the sampling error in the simulated Doppler lidar wind profiler measurements (due to angular and spatial separation between shots in a shot pair) to the total measurement uncertainty. Idealized wind fields are used as input to the profiling model, and radial wind estimates are passed through the MPA to yield a wind measurement for 300 x 300 sq km areas. The derived divergence fields illustrate the gradient patterns that are particular to the Doppler lidar sampling strategy and perspective.

Houston, S. H.↗
NASA NTRSDate not supplied

Sequential Filtering in the Presence of Uniform Measurement Errors

This paper presents a sequential filtering strategy using observations corrupted with uniform measurement noise. While the Kalman filter remains the best linear estimator of the state, other filtering techniques provide minimum variance optimal estimates, a trait only enjoyed by the Kalman filter when the underlying noises are, in fact, Gaussian. This work develops a new approximate optimal estimator for uniform measurement noises. The resulting recursion requires just slightly more computational time to complete a measurement update than the Kalman filter, which generally cannot be claimed by other optimal strategies such as the particle or Gaussian mixture filters.

James S. McCabe↗
NASA NTRSDate not supplied

Sequential Filtering in the Presence of Uniform Measurement Errors

This paper presents a sequential filtering strategy using observations corrupted with uniform measurement noise. While the Kalman filter remains the best linear estimator of the state, other filtering techniques provide minimum variance optimal estimates, a trait only enjoyed by the Kalman filter when the underlying noises are, in fact, Gaussian. This work develops a new approximate optimal estimator for uniform measurement noises. The resulting recursion requires just slightly more computational time to complete a measurement update than the Kalman filter, which generally cannot be claimed by other optimal strategies such as the particle or Gaussian mixture filters.

James S McCabe↗
NASA NTRS2001

Characterization of Measurement Error Sources in Doppler Global Velocimetry

Doppler global velocimetry uses the absorption characteristics of iodine vapor to provide instantaneous three-component measurements of flow velocity within a plane defined by a laser light sheet. Although the technology is straightforward, its utilization as a flow diagnostics tool requires hardening of the optical system and careful attention to detail during data acquisition and processing if routine use in wind tunnel applications is to be achieved. A development program that reaches these goals is presented. Theoretical and experimental investigations were conducted on each technology element to determine methods that increase measurement accuracy and repeatability. Enhancements resulting from these investigations included methods to ensure iodine vapor calibration stability, single frequency operation of the laser and image alignment to sub-pixel accuracies. Methods were also developed to improve system calibration, and eliminate spatial variations of optical frequency in the laser output, spatial variations in optical transmissivity and perspective and optical distortions in the data images. Each of these enhancements is described and experimental examples given to illustrate the improved measurement performance obtained by the enhancement. The culmination of this investigation was the measured velocity profile of a rotating wheel resulting in a 1.75% error in the mean with a standard deviation of 0.5 m/s. Comparing measurements of a jet flow with corresponding Pitot measurements validated the use of these methods for flow field applications.

Meyers, James F.↗
DOE OSTI2019

Measurement Error Variance Estimation in Gamma-Spectroscopy Data using FRAM

The FRAM gamma-ray isotopic analysis code has recently been applied to four Pu data sets and four U data sets, each with relatively well-characterized standard items, in order to estimate the variances of random errors and of item-specific systematic errors. Assay results are available for Pu238, Pu239, Pu240, Pu241, Pu242 (operator entered, not independently measured), Am241, Specific Power, and Pu240eff. For the four U data sets, results are available for the measurands U234, U235, U236 (operator entered, not independently measured), and U238. For example, in Pu data set 1, there are 33 standard reference Pu items, which have well-known nominal/true values (except for a few items). FRAM was used to make approximately 15 repeat measurements for each of the 33 items, so empirical standard deviations can be calculated. In addition, FRAM internally estimates its random error variance using propagation of variance. This paper applies analysis of variance (ANOVA) to separately estimate the repeatability standard deviation and the standard deviation of the item-specific biases δ s in each of the 8 data sets.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1982

Horizon sensor errors calculated by computer models compared with errors measured in orbit

Using a computer program to model the earth's horizon and to duplicate the signal processing procedure employed by the ESA (Earth Sensor Assembly), errors due to radiance variation have been computed for a particular time of the year. Errors actually occurring in flight at the same time of year are inferred from integrated rate gyro data for a satellite of the TIROS series of NASA weather satellites (NOAA-A). The predicted performance is compared with actual flight history.

Ward, K. A.↗
NASA NTRS1971

Aerial measurement error with a dot planimeter: Some experimental estimates

A shape analysis is presented which utilizes a computer to simulate a multiplicity of dot grids mathematically. Results indicate that the number of dots placed over an area to be measured provides the entire correlation with accuracy of measurement, the indices of shape being of little significance. Equations and graphs are provided from which the average expected error, and the maximum range of error, for various numbers of dot points can be read.

Yuill, R. S.↗
NASA NTRS1974

Measurement error analysis in determination of small-body gravity fields

We consider analytically the use of existing instrumentation in determining asteroid gravity fields from orbiting spacecraft. Asteroids (Eros as an example) are modeled as homogeneous triaxial ellipsoids, with gravitational potential given by a sperical-harmonic expansion. Mass concentrations are modeled as point masses. The character of spacecraft orbits about asteroids is discussed, along with detectibility of gravitational coefficients and of mass concentrations. A Kalman-filtering treatment of the observation process, for Eros as example, shows that using DSN tracking and onboard gravity gradiometry, radar altimetry, and celestial angle measurements, a single orbit yields asteroid mass to 0.03% and coefficients C20 to C44 to 1% accuracies.

Friedlander, A. L.↗
NASA NTRS1984

Altimeter height measurement errors introduced by the presence of variable cloud and rain attenuation

It has recently been recognized that spatially inhomogeneous clouds and rain can substantially affect the height precision obtainable from a spaceborne radar altimeter system. Through computer simulation, it has been found that typical levels of cloud and rain intensities and associated spatial variabilities may degrade altimeter precision at 13.5 GHz and, in particular, cause severe degradation at 35 GHz. This degradation in precision is a result of radar signature distortion caused by variable attenuation over the beam limited altimeter footprint. Because attenuation effects increase with frequency, imprecision caused by them will significantly impact on the frequency selection of future altimeters. In this paper the degradation of altimeter precision introduced by idealized cloud and rain configurations as well as for a realistic rain configuration as measured with a ground based radar is examined.

Monaldo, F. M.↗