A method of treating the non-grey error in total emittance measurements
Calculating non-grey errors in total emittance measurements as function of temperature control coating thickness
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Calculating non-grey errors in total emittance measurements as function of temperature control coating thickness
Human error is a significant contributing factor in a very high proportion of civil transport, general aviation, and rotorcraft accidents. The technical details of a variety of proven approaches for the measurement of human errors in the context of the national airspace system are presented. Unobtrusive measurements suitable for cockpit operations and procedures in part of full mission simulation are emphasized. Procedure, system performance, and human operator centered measurements are discussed as they apply to the manual control, communication, supervisory, and monitoring tasks which are relevant to aviation operations.
A prototype balance study was conducted on earth prior to the balance studies conducted in Skylab itself. Collected were daily dietary intake data of 6 minerals and nitrogen, and fecal and urinary outputs on each of three astronauts. Essential statistical issues show what quantities need to be estimated and establish the scope of inference associated with alternative variance estimates. The procedures for obtaining the final variability due both to errors of measurement and total error (total = measurement and biological variability) are exhibited.
This paper examines filter tuning techniques for a sequential orbit determination (OD) covariance analysis. Recently, there has been a renewed interest in sequential OD, primarily due to the successful flight qualification of the Tracking and Data Relay Satellite System (TDRSS) Onboard Navigation System (TONS) using Doppler data extracted onboard the Extreme Ultraviolet Explorer (EUVE) spacecraft. TONS computes highly accurate orbit solutions onboard the spacecraft in realtime using a sequential filter. As the result of the successful TONS-EUVE flight qualification experiment, the Earth Observing System (EOS) AM-1 Project has selected TONS as the prime navigation system. In addition, sequential OD methods can be used successfully for ground OD. Whether data are processed onboard or on the ground, a sequential OD procedure is generally favored over a batch technique when a realtime automated OD system is desired. Recently, OD covariance analyses were performed for the TONS-EUVE and TONS-EOS missions using the sequential processing options of the Orbit Determination Error Analysis System (ODEAS). ODEAS is the primary covariance analysis system used by the Goddard Space Flight Center (GSFC) Flight Dynamics Division (FDD). The results of these analyses revealed a high sensitivity of the OD solutions to the state process noise filter tuning parameters. The covariance analysis results show that the state estimate error contributions from measurement-related error sources, especially those due to the random noise and satellite-to-satellite ionospheric refraction correction errors, increase rapidly as the state process noise increases. These results prompted an in-depth investigation of the role of the filter tuning parameters in sequential OD covariance analysis. This paper analyzes how the spacecraft state estimate errors due to dynamic and measurement-related error sources are affected by the process noise level used. This information is then used to establish guidelines for determining optimal filter tuning parameters in a given sequential OD scenario for both covariance analysis and actual OD. Comparisons are also made with corresponding definitive OD results available from the TONS-EUVE analysis.
Instrument errors, error reduction, and elements of measurements for measurement systems with feedback instrumentation
The magnitude and variation of the static-pressure error for various distances ahead of sharp-nose bodies and open-nose air inlets and for a distance of 1 chord ahead of the wing tip of a swept wing are defined by a combination of experiment and theory. The mechanism of the error is discussed in some detail to show the contributing factors that make up the error. The information presented provides a useful means for choosing a proper location for measurement of static pressure for most purposes.
Potential sources of error in the use of heated surface gages for separated-skin-friction measurement are studied. Emphasis is placed on the interpretation of local skin-friction measurements in two- and three-dimensional separated turbulent-shear flows before they are used to test the validity of current and proposed computer codes.
Due to their unpredictable nature, many impact events (e.g., overheight vehicles striking on bridges) go unnoticed or get reported many hours later. However, they can induce structural failures or hidden damage that accelerates the structure’s long-term degradation. Therefore, prompt impact detection and localization strategies are essential for early warning of impact events and rapid maintenance of structures. Most existing impact detection strategies are developed for aircraft composite panels utilizing high-rate synchronized measurement from densely deployed sensors. Limited efforts have been made for infrastructure or human habitats which generally require large-scale but low-rate measurement. In particular, due to harsh environments (e.g., deep space habitats under meteoroids), structural impact localization must be robust to limited sensors (e.g., sensor damage during impacts) and multi-source errors (e.g., measurement errors). In this study, an effective impact detection and localization strategy is proposed using a limited number of vibration measurements, especially in harsh environments (e.g. in deep space). Convolutional neural networks are trained for each sensor node and are fused using Bayesian theory to improve the accuracy of impact localization. Special considerations are paid to evaluate the effect of both measurement error and modeling error in the analysis. The proposed strategy is illustrated using 1D structure, and further validated in 3D geodesic dome structure numerically. The results demonstrate that it can detect and localize impact events accurately and robustly on structures.
Why do we need time series of ozone and water vapor profiles at low altitude? The degradation of air quality is a very serious environmental problem that affects urban and industrial areas worldwide. Air pollution injures human health and ecosystems, diminishes crop yield, and spoils patrimony and materials. The phenomena involved in air pollution are very complex. Once emitted into the atmosphere, (primary) pollutants are transported, dispersed, transformed by gas/solid phase change and chemical reaction, and finally removed by dry and wet deposition. Most challenging is the fact that the health and environmental impacts of secondary pollutants (formed in the atmosphere) are frequently more severe than those of their precursors (primary pollutants). This is the case of ozone and other photochemical pollutants, such as peroxyacetil nitrate (PAN) and secondary particles, produced in the atmosphere by the photo-oxidation volatile organic compounds (VOC) catalyzed by nitrogen oxides (NO(sub x)). Photochemical air pollution is a complex science because of the non-linearity of its response to changes in primary emission.
An error analysis has been made of a Shuttle postflight entry trajectory reconstruction process to obtain trajectory state estimation errors and to assess the impact of these errors on Shuttle aerodynamic force coefficient extraction. In this analysis, the entry trajectory is assumed to be reconstructed via numerical integration of onboard accelerometer and gyro measurements and constrained to satisfy ground-based radio tracking. The trajectory state estimation errors are calculated using a Kalman-Schmidt sequential filter assuming various measurement error models and combinations of ground-based tracking. The resultant trajectory estimation errors are analyzed in a simplified perturbation process to establish the accuracy to which postflight aerodynamic force coefficients can be determined. Results are presented which show that the principal error sources affecting the trajectory reconstruction and thus the force coefficient extraction, assuming perfect atmospheric density knowledge, are the accelerometer and gyro resolution, acceleration-sensitive gyro drifts, and the alignment uncertainties associated with integration on the Shuttle.
The scientific usefulness of satellite measurements of ocean topography for the study of ocean circulation was investigated. The following topics were studied: (1) scientific problems which use altimetric measurements of ocean topography; (2) the extent in which in situ measurements are complementary or required; (3) accuracy, precision, and spatial and temporal resolutions which are required of the topographic measurements; (4) errors associated with measurement techniques; and (5) influences of these errors on scientific problems. An operational system for measuring ocean topography, was defined and the cost of conducting such a topographic experiment, was estimated.
A generalized least squares method for deducing both total ozone and aerosol extinction spectrum parameters from Dobson spectrophotometer measurements was developed. An error analysis applied to this system indicates that there is little advantage to additional measurements once a sufficient number of line pairs have been employed to solve for the selected detail in the attenuation model. It is shown that when there is a predominance of small particles (less than about 0.35 microns in diameter) the total ozone from the standard AD system is too high by about one percent. When larger particles are present the derived total ozone may be an overestimate or an underestimate but serious errors occur only for narrow polydispersions.
The overall errors of the service altimeter installations of a variety of civil transport, military, and general-aviation airplanes have been experimentally determined during normal landing-approach and take-off operations. The average height above the runway at which the data were obtained was about 280 feet for the landings and about 440 feet for the take-offs. An analysis of the data obtained from 196 airplanes during 415 landing approaches and from 70 airplanes during 152 take-offs showed that: 1. The overall error of the altimeter installations in the landing- approach condition had a probable value (50 percent probability) of +/- 36 feet and a maximum probable value (99.7 percent probability) of +/- 159 feet with a bias of +10 feet. 2. The overall error in the take-off condition had a probable value of +/- 47 feet and a maximum probable value of +/- 207 feet with a bias of -33 feet. 3. The overall errors of the military airplanes were generally larger than those of the civil transports in both the landing-approach and take-off conditions. In the landing-approach condition the probable error and the maximum probable error of the military airplanes were +/- 43 and +/- 189 feet, respectively, with a bias of +15 feet, whereas those for the civil transports were +/- 22 and +/- 96 feet, respectively, with a bias of +1 foot. 4. The bias values of the error distributions (+10 feet for the landings and -33 feet for the take-offs) appear to represent a measure of the hysteresis characteristics (after effect and recovery) and friction of the instrument and the pressure lag of the tubing-instrument system.
When a sensor is embedded in a solid body to measure its internal temperature, any conduction to or from its sensing element may cause the indicated temperature to be different from the true temperature. This paper describes an analysis of the error caused by conduction when there is an arbitrary temperature distribution in the body along the sensor. The sensor is modeled as a cylindrical fin and the appropriate conduction equation is solved. The solution gives a correction for the error which depends on such parameters as, depth of immersion, thermocouple wire and insulation properties, contact between the sensor and the body, and temperature distribution in the body. The latter may not be known, but the measured temperature distribution can be used as a first approximation. The corrected value can then be used to obtain a better estimate of the error. The results show good agreement with experimental observations.
Attention is given to a general derivation of the fractional standard deviation (FSD) of any integrated property X such that X(D) = cD to the n. This work extends that of Joss and Waldvogel (1969). The equation is applicable to measuring integrated properties of cloud, rain or hail populations (such as water content, precipitation rate, kinetic energy, or radar reflectivity) which are subject to statistical sampling errors due to the Poisson distributed fluctuations of particles sampled in each particle size interval and the weighted sum of the associated variances in proportion to their contribution to the integral parameter to be measured. Universal curves are presented which are applicable to the exponential size distribution permitting FSD estimation of any parameters from n = 0 to n = 6. The equations and curves also permit corrections for finite upper limits in the size spectrum and a realistic fall speed law.
Several previous studies highlight pressure (or equivalently, pressure altitude) discrepancies between the radiosonde pressure sensor and that derived from a GPS flown with the radiosonde. The offsets vary during the ascent both in absolute and percent pressure differences. To investigate this problem further, a total of 731 radiosonde-ozonesonde launches from the Southern Hemisphere subtropics to Northern mid-latitudes are considered, with launches between 2005 - 2013 from both longer-term and campaign-based intensive stations. Five series of radiosondes from two manufacturers (International Met Systems: iMet, iMet-P, iMet-S, and Vaisala: RS80-15N and RS92-SGP) are analyzed to determine the magnitude of the pressure offset. Additionally, electrochemical concentration cell (ECC) ozonesondes from three manufacturers (Science Pump Corporation; SPC and ENSCI-Droplet Measurement Technologies; DMT) are analyzed to quantify the effects these offsets have on the calculation of ECC ozone (O3) mixing ratio profiles (O3MR) from the ozonesonde-measured partial pressure. Approximately half of all offsets are 0.6 hPa in the free troposphere, with nearly a third 1.0 hPa at 26 km, where the 1.0 hPa error represents 5 persent of the total atmospheric pressure. Pressure offsets have negligible effects on O3MR below 20 km (96 percent of launches lie within 5 percent O3MR error at 20 km). Ozone mixing ratio errors above 10 hPa (30 km), can approach greater than 10 percent ( 25 percent of launches that reach 30 km exceed this threshold). These errors cause disagreement between the integrated ozonesonde-only column O3 from the GPS and radiosonde pressure profile by an average of +6.5 DU. Comparisons of total column O3 between the GPS and radiosonde pressure profiles yield average differences of +1.1 DU when the O3 is integrated to burst with addition of the McPeters and Labow (2012) above-burst O3 column climatology. Total column differences are reduced to an average of -0.5 DU when the O3 profile is integrated to 10 hPa with subsequent addition of the O3 climatology above 10 hPa. The RS92 radiosondes are superior in performance compared to other radiosondes, with average 26 km errors of -0.12 hPa or +0.61 percent O3MR error. iMet-P radiosondes had average 26 km errors of -1.95 hPa or +8.75 percent O3MR error. Based on our analysis, we suggest that ozonesondes always be coupled with a GPS-enabled radiosonde and that pressure-dependent variables, such as O3MR, be recalculated-reprocessed using the GPS-measured altitude, especially when 26 km pressure offsets exceed 1.0 hPa 5 percent.
As satellite communications systems become both more complex and reliant with respect to their operating environment, it has become imperative to be able to identify, during real-time operation, the onset of one or more impairments to the quality of overall communications system integrity. One of the most important aspects to monitor of a satellite link operating within the Earth's atmosphere is the signal fading due to the occurrence of rain and/or phase scintillations. This, of course, must be done in the presence of the associated measurement uncertainty or potentially faulty measurement equipment such as in the Advanced Communication Technology Satellite (ACTS) experiment. In the present work, an approach originally suggested in 1991, and apparently still considered iconoclastic, will be significantly developed and applied to the satellite communications link on which the deleterious composite signal fade is the result of one or many component fade mechanisms. Through the measurement (with the attendant uncertainty or 'error' in the measurement) of such a composite fading satellite signal, it is desired to extract the level of each of the individual fading mechanisms so they can be appropriately mitigated before they impact the overall performance of the communications network. Rather than employing simple-minded deterministic filtering to the real-time fading, the present approach is built around all the models and/or descriptions used to describe the individual fade components, including their dynamic evolution. The latter is usually given by a first-order Langevin equation. This circumstance allows the description of the associated temporal transition probability densities of each of the component processes. By using this description, along with the real-time measurements of the composite fade (along with the measurement errors), one can obtain statistical estimates of the levels of each of the component fading mechanisms as well as their predicted values into the future. This is all accomplished by the use of the well-known Stratonovich integro-differential equation that results from the model of the measured signal fade that is also tailored to adaptively adjust the values of the parameters used in the statistical models of the individual fade mechanisms. Three examples of increasing complexity are addressed and solved for the iterative determination of fade component levels from the measured composite signal fade in the presence of measurement error and, in the last case, with uncertainty in the model parameters.
Inertial measurement units (IMUs) with very low mass and power can be manufactured using micromachined accelerometers and gyroscopes. Six degree of freedom packages which require a few watts of power and have less than a kg of mass are available commercially, greatly expanding the potential applications of IMUs in guidance and navigation. Recent advances in small sensor design and fabrication have pushed the performance limits of these small devices. However, the limitations on the precision of small IMUs are not entirely due to the performance of the individual sensors.