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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Measurement Error and Resolution in Quantitative Stable Isotope Probing: Implications for Experimental Design

Quantitative stable isotope probing (qSIP) estimates isotope tracer incorporation into DNA of individual microbes and can link microbial biodiversity and biogeochemistry in complex communities. As with any quantitative estimation technique, qSIP involves measurement error, and a fuller understanding of error, precision, and statistical power benefits qSIP experimental design and data interpretation. We used several qSIP data sets—from soil and seawater microbiomes—to evaluate how variance in isotope incorporation estimates depends on organism abundance and resolution of the density fractionation scheme. We assessed statistical power for replicated qSIP studies, plus sensitivity and specificity for unreplicated designs. As a taxon’s abundance increases, the variance of its weighted mean density declines. Nine fractions appear to be a reasonable trade-off between cost and precision for most qSIP applications. Increasing the number of density fractions beyond that reduces variance, although the magnitude of this benefit declines with additional fractions. Our analysis suggests that, if a taxon has an isotope enrichment of 10 atom% excess, there is a 60% chance that this will be detected as significantly different from zero (with alpha 0.1). With five replicates, isotope enrichment of 5 atom% could be detected with power (0.6) and alpha (0.1). Finally, we illustrate the importance of internal standards, which can help to calibrate per sample conversions of %GC to mean weighted density. These results should benefit researchers designing future SIP experiments and provide a useful reference for metagenomic SIP applications where both financial and computational limitations constrain experimental scope.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1979

Flight test of navigation and guidance sensor errors measured on STOL approaches

Navigation and guidance sensor error characteristics were measured during STOL approach-flight investigations. Data from some of the state sensors of a digital avionics system were compared to corresponding outputs from an inertial navigation system. These sensors include the vertical gyro, compass, and accelerometers. Barometric altimeter data were compared to altitude measured by a tracking radar. Data were recorded with the Augmentor Wing Jet STOL Research Aircraft parked and in flight.

Warner, D. N.↗
NASA NTRS1993

Strain gage measurement errors in the transient heating of structural components

Significant strain-gage errors may exist in measurements acquired in transient thermal environments if conventional correction methods are applied. Conventional correction theory was modified and a new experimental method was developed to correct indicated strain data for errors created in radiant heating environments ranging from 0.6 C/sec (1 F/sec) to over 56 C/sec (100 F/sec). In some cases the new and conventional methods differed by as much as 30 percent. Experimental and analytical results were compared to demonstrate the new technique. For heating conditions greater than 6 C/sec (10 F/sec), the indicated strain data corrected with the developed technique compared much better to analysis than the same data corrected with the conventional technique.

Richards, W. Lance↗
NASA NTRSDate not supplied

Spectral Measurement Errors due to CCD Serial Pixel-to-Pixel Readout Interference in the Ocean Color Instrument of the NASA PACE Mission

The Ocean Color Instrument on NASA’s PACE mission is a hyperspectral imager with a spatial resolution of 1km x 1km and spectral resolution of 5nm in 2.5nm steps over 320-890nm. The detection system is based on two Charge-Coupled Devices (CCDs) operating in Time Delay Integration (TDI) mode to achieve high signal-to-noise ratio. The front-end optical imager is a rotating mirror-based system that images the ground-scene onto a slit with a field of view of 16km x 1km. The slit-image is re-imaged and wavelength dispersed on the CCDs. As the ground-scene moves through the slit, it moves along the CCD columns as charge is moved along with it. The accumulated charge at the end of each column is collected in a serial pixel. Each of the 16 CCD outputs read out 32 columns of the same ground scene spaced 0.625nm apart. The 32-pixel serial register is swiftly read out before the next TDI cycle. The telescope is spinning at 5.77Hz to achieve the required spatial resolution. This results in a serial pixel readout speed of 8.5MHz. Each serial read-cycle goes through a reset and video period that are each sampled to create a low-noise correlated double sample value. This only allows 59ns for the reset and video to be asserted and settled before sampling. Due to the short time period, the response of the CCD exhibits serial pixel-to-pixel readout interference as the reset and video signals do not have time to fully settle before sampling. Each serial pixel value therefore has a dependence on the value of the preceding pixel value. This leads to a spectral measurement error of up to 0.3%. We explain the operation of the detection system, the behavior of the interference and the resulting wavelength error with results from ground testing and on-orbit characterization.

Ulrik B Gliese↗
NASA NTRS2018

Wave-Front Error Measurements and Alignment of CLASP2 Telescope with a Dual-Band Pass Cold Mirror Coated Primary Mirror

"Chromospheric LAyer Spectro-Polarimeter (CLASP2)" is the next sounding rocket experiment of the "Chromospheric Lyman-Alpha Spectro-Polarimeter (CLASP)" that succeeded in observing for the first time the linear polarization spectra in the hydrogen Lyman- line (121.6 nm) and is scheduled to be launched in 2019. In CLASP2, we will carry out full Stokes-vector spectropolarimetric observations in the Mg II h & k lines near 280 nm with the spectro-polarimeter (SP), while imaging observations in the Lyman- line will be conducted with the slitjaw optics (SJ). For the wavelength selection of CLASP2, the primary mirror of the telescope uses a new dual-band pass cold mirror coating targeting both at 121.6 nm and 280 nm. Therefore, we have to perform again the alignment of the telescope after the installation of the recoated primary mirror. Before unmounting the primary mirror from the telescope structure, we measured the wave-front error (WFE) of the telescope. The measured WFE map was consistent with what we had before the CLASP flight, clearly indicating that the telescope alignment has been maintained even after the flight. After the re-coated primary mirror was installed the WFE was measured, and coma aberration was found to be larger. Finally, the secondary mirror shim adjustments were carried out based on the WFE measurements. In CLASP2 telescope, we improved a fitting method of WFE map (applying 8th terms circular Zernike polynomial tting instead of 37th terms circular Zernike fitting) and the improved method enables to achieve better performance than CLASP telescope. Indeed, WFE map obtained after the final shim adjustment indicated that the required specification (< 5:5 m RMS spot radius) that is more stringent than CLASP telescope was met.

chromosphere; polarimetry; sounding rocket↗
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.↗
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↗
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.↗
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.↗