Spaceborne rainfall Doppler radar measurements: correction of errors induced by pointing uncertainties
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precipitation radar TRMM GPM CAMEX-4↗
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Correction of errors induced by pointing uncertainties in spaceborne rainfall Doppler radar measurments
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Doppler rainfall velocity↗
Correction of errors induced by pointing uncertainties in spaceborne rainfall Doppler measurements
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Doppler rainfall velocity↗
Spaceborne rainfall Doppler radar measurements: correction of errors induced by pointing uncertainties
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precipitation radar TRMM GPM CAMEX-4↗
Detailed Uncertainty Analysis of the ZEM-3 Measurement System
The measurement of Seebeck coefficient and electrical resistivity are critical to the investigation of all thermoelectric systems. Therefore, it stands that the measurement uncertainty must be well understood to report ZT values which are accurate and trustworthy. A detailed uncertainty analysis of the ZEM-3 measurement system has been performed. The uncertainty analysis calculates error in the electrical resistivity measurement as a result of sample geometry tolerance, probe geometry tolerance, statistical error, and multi-meter uncertainty. The uncertainty on Seebeck coefficient includes probe wire correction factors, statistical error, multi-meter uncertainty, and most importantly the cold-finger effect. The cold-finger effect plagues all potentiometric (four-probe) Seebeck measurement systems, as heat parasitically transfers through thermocouple probes. The effect leads to an asymmetric over-estimation of the Seebeck coefficient. A thermal finite element analysis allows for quantification of the phenomenon, and provides an estimate on the uncertainty of the Seebeck coefficient. The thermoelectric power factor has been found to have an uncertainty of +9-14 at high temperature and 9 near room temperature.
Seebeck effect↗
Uncertainty of in-flight thrust determination
Methods for estimating the measurement error or uncertainty of in-flight thrust determination in aircraft employing conventional turbofan/turbojet engines are reviewed. While the term 'in-flight thrust determination' is used synonymously with 'in-flight thrust measurement', in-flight thrust is not directly measured but is determined or calculated using mathematical modeling relationships between in-flight thrust and various direct measurements of physical quantities. The in-flight thrust determination process incorporates both ground testing and flight testing. The present text is divided into the following categories: measurement uncertainty methodoogy and in-flight thrust measurent processes.
Abernethy, Robert B.↗
Study of geopotential error models used in orbit determination error analysis
The uncertainty in the geopotential model is currently one of the major error sources in the orbit determination of low-altitude Earth-orbiting spacecraft. The results of an investigation of different geopotential error models and modeling approaches currently used for operational orbit error analysis support at the Goddard Space Flight Center (GSFC) are presented, with emphasis placed on sequential orbit error analysis using a Kalman filtering algorithm. Several geopotential models, known as the Goddard Earth Models (GEMs), were developed and used at GSFC for orbit determination. The errors in the geopotential models arise from the truncation errors that result from the omission of higher order terms (omission errors) and the errors in the spherical harmonic coefficients themselves (commission errors). At GSFC, two error modeling approaches were operationally used to analyze the effects of geopotential uncertainties on the accuracy of spacecraft orbit determination - the lumped error modeling and uncorrelated error modeling. The lumped error modeling approach computes the orbit determination errors on the basis of either the calibrated standard deviations of a geopotential model's coefficients or the weighted difference between two independently derived geopotential models. The uncorrelated error modeling approach treats the errors in the individual spherical harmonic components as uncorrelated error sources and computes the aggregate effect using a combination of individual coefficient effects. This study assesses the reasonableness of the two error modeling approaches in terms of global error distribution characteristics and orbit error analysis results. Specifically, this study presents the global distribution of geopotential acceleration errors for several gravity error models and assesses the orbit determination errors resulting from these error models for three types of spacecraft - the Gamma Ray Observatory, the Ocean Topography Experiment, and the Cosmic Background Explorer.
Yee, C.↗
An error covariance model for sea surface topography and velocity derived from TOPEX/POSEIDON altimetry
In order to facilitate the use of satellite-derived sea surface topography and velocity oceanographic models, methodology is presented for deriving the total error covariance and its geographic distribution from TOPEX/POSEIDON measurements. The model is formulated using a parametric model fit to the altimeter range observations. The topography and velocity modeled with spherical harmonic expansions whose coefficients are found through optimal adjustment to the altimeter range residuals using Bayesian statistics. All other parameters, including the orbit, geoid, surface models, and range corrections are provided as unadjusted parameters. The maximum likelihood estimates and errors are derived from the probability density function of the altimeter range residuals conditioned with a priori information. Estimates of model errors for the unadjusted parameters are obtained from the TOPEX/POSEIDON postlaunch verification results and the error covariances for the orbit and the geoid, except for the ocean tides. The error in the ocean tides is modeled, first, as the difference between two global tide models and, second, as the correction to the present tide model, the correction derived from the TOPEX/POSEIDON data. A formal error covariance propagation scheme is used to derive the total error. Our global total error estimate for the TOPEX/POSEIDON topography relative to the geoid for one 10-day period is found tio be 11 cm RMS. When the error in the geoid is removed, thereby providing an estimate of the time dependent error, the uncertainty in the topography is 3.5 cm root mean square (RMS). This level of accuracy is consistent with direct comparisons of TOPEX/POSEIDON altimeter heights with tide gauge measurements at 28 stations. In addition, the error correlation length scales are derived globally in both east-west and north-south directions, which should prove useful for data assimilation. The largest error correlation length scales are found in the tropics. Errors in the velocity field are smallest in midlatitude regions. For both variables the largest errors caused by uncertainty in the geoid. More accurate representations of the geoid await a dedicated geopotential satellite mission. Substantial improvements in the accuracy of ocean tide models are expected in the very near future from research with TOPEX/POSEIDON data.
Tsaoussi, Lucia S.↗
Dynamics of hypersonic flight vehicles exhibiting significant aeroelastic and aeropropulsive interactions
With analytic expressions previously developed for the forces and moments acting on a generic hypersonic vehicle, it is of interest to investigate the relative importance of the aerodynamic and propulsive effects on the vehicle dynamics. It is shown that the vehicle's aerodynamics and propulsive forces are both very significant in the evaluation of key stability derivatives which dictate the vehicle's dynamic characteristics. It is also shown that the vehicle model selected is unstable in pitch and exhibits strong airframe/engine/elastic coupling. With the use of literal expressions for both the systems poles and zeros, as well as the stability derivatives, key vehicle dynamic characteristics are investigated. For small errors, or uncertainties, in either the aerodynamic or propulsive forces, significant errors in the frequency and damping of the dominant modes and zero locations will arise.
Chavez, Frank R.↗
What the UV SED Tells us About Stellar Populations and Galaxies
The UV SED parameter b as in f(sub 1) ~ 1(sup b), is commonly used to estimate fundamental properties of high-redshift galaxies including age and metallicity. However, sources and processes other than age and metallicity can influence the value of b. We use the local starforming dwarf galaxy, I Zw 18, in a case study to investigate uncertainties in age and metallicity inferred from b due errors or uncertainties in: mode of star formation (instantaneous starburst vs. continuous SF), dust extinction, nebular continuous emission (2-photon emission, Balmer continuum flux), and presence of older stars.
Heap, Sara R.↗
Assessment of NASA's Aircraft Noise Prediction Capability
A goal of NASA s Fundamental Aeronautics Program is the improvement of aircraft noise prediction. This document provides an assessment, conducted from 2006 to 2009, on the current state of the art for aircraft noise prediction by carefully analyzing the results from prediction tools and from the experimental databases to determine errors and uncertainties and compare results to validate the predictions. The error analysis is included for both the predictions and the experimental data and helps identify where improvements are required. This study is restricted to prediction methods and databases developed or sponsored by NASA, although in many cases they represent the current state of the art for industry. The present document begins with an introduction giving a general background for and a discussion on the process of this assessment followed by eight chapters covering topics at both the system and the component levels. The topic areas, each with multiple contributors, are aircraft system noise, engine system noise, airframe noise, fan noise, liner physics, duct acoustics, jet noise, and propulsion airframe aeroacoustics.
Dahl, Milo D.↗
Calibration of a stack of NaI scintillators at the Berkeley Bevalac
An analysis of the carbon and argon data reveals that essentially all of the charge-changing fragmentation reactions within the stack can be identified and removed by imposing the simple criteria relating the observed energy deposition profiles to the expected Bragg curve depositions. It is noted that these criteria are even capable of identifying approximately one-third of the expected neutron-stripping interactions, which in these cases have anomalous deposition profiles. The contribution of mass error from uncertainty in delta E has an upper limit of 0.25 percent for Mn; this produces an associated mass error for the experiment of about 0.14 amu. It is believed that this uncertainty will change little with changing gamma. Residual errors in the mapping produce even smaller mass errors for lighter isotopes, whereas photoelectron fluctuations and delta-ray effects are approximately the same independent of the charge and energy deposition.
Schindler, S. M.↗
Impact of Pilot Delay and Non-Responsiveness on the Safety Performance of Airborne Separation
Assessing the safety effects of prediction errors and uncertainty on automationsupported functions in the Next Generation Air Transportation System concept of operations is of foremost importance, particularly safety critical functions such as separation that involve human decision-making. Both ground-based and airborne, the automation of separation functions must be designed to account for, and mitigate the impact of, information uncertainty and varying human response. This paper describes an experiment that addresses the potential impact of operator delay when interacting with separation support systems. In this study, we evaluated an airborne separation capability operated by a simulated pilot. The experimental runs are part of the Safety Performance of Airborne Separation (SPAS) experiment suite that examines the safety implications of prediction errors and system uncertainties on airborne separation assistance systems. Pilot actions required by the airborne separation automation to resolve traffic conflicts were delayed within a wide range, varying from five to 240 seconds while a percentage of randomly selected pilots were programmed to completely miss the conflict alerts and therefore take no action. Results indicate that the strategicAirborne Separation Assistance System (ASAS) functions exercised in the experiment can sustain pilot response delays of up to 90 seconds and more, depending on the traffic density. However, when pilots or operators fail to respond to conflict alerts the safety effects are substantial, particularly at higher traffic densities.
Consiglio, Maria↗
Uncertainty Analysis of the CE-22 Advanced Nozzle Test Facility
This paper presents methods and results of a detailed measurement uncertainty analysis that was performed for the Advanced Nozzle Test Facility, CE-22, located at the NASA Glenn Research Center. Results for the uncertainty in thrust and flow coefficients, in addition to other variables of interest, are provided. Results are presented separately as random uncertainty (characterizing errors inherent to instrument or measurement environment, impacting repeatability), systematic uncertainty (capturing inaccuracies due to measurement process, calibration, installation effects or other sources which may introduce bias), and total combined uncertainty. The statistical methods and engineering judgments used to estimate elemental uncertainties are described. The analysis tool MANTUS (Measurement Analysis Tool for Uncertainty in Systems) was used to quantify instrumentation system uncertainty, and statistical analysis and engineering judgment were used to quantify other random and systematic uncertainty sources. The Monte Carlo method was used to propagate systematic and random elemental uncertainties to determine the uncertainties of various calculated variables of interest.
data quality↗
Health Management and Prognostics for Electric Aircraft Powertrain
W and c Any air borne vehicle needs incorporating safety as key parameter of measure, and inclusion of autonomy raises the critical need for safety under autonomous operations. Management of faults and component degradation is key as complexity in autonomous operations grow over the period of time. Therefore, in addition to basic operational requirements, an autonomous electric vehicle should be able to make accurate estimates of its current system health and take the correct decisions to complete its mission successfully. Real-time safety and state-awareness tools are therefore essential for the vehicle to be able to reach its destination in a safe and successful manner. The need for safety assurance and health management capabilities is particularly relevant for aircraft electric propulsion systems, which are relatively new and with limited historical to learn. They are critical systems requiring high power density along with reliability, resilience, efficient management of weight, and operational costs. A model- based fault diagnosis and prognostics approach of complex critical systems can successfully accomplish the safety and state awareness goal for such electric propulsion systems, enabling autonomous decision making capability for safe and efficient operation. To identify critical components in the system a Qualitative Bayesian approach using FMECA is implemented. This requires the assessment of some quantities representing the state of the electric unmanned aerial systems (e-UAS), as well as look-ahead forecasts of such states during the entire flight, presented in form of safety metrics (SM). In-service data and performance data gathered from degraded components sup- ports diagnostic and prognostic methods for these systems, but this data can be difficult to obtain as weight and packaging restrictions reduce redundancy and instrumentation on-board the vehicle. Therefore, an model-based framework should be capable or operating with limited data. In addition to data scarcity, the variability of such complex critical systems re- quires the model-based framework to reason in the presence of uncertainty, such as sensor noise, and modeling imperfections. Quantification of errors and uncertainties in the measured states and quantities is therefore a fundamental step for a precise estimation of such SMs; un-modeled uncertainty may result in erroneous state assessment and un- reliable predictions of future states of e-UAVs. Typical, centralized model-based schemes suffer from inherent disadvantages such as computational complexity, single point of failure, and scalability issues, and therefore may fail in such a complex scenario. This paper presents a methodology for developing a system level diagnostics and prognostics approach using a Qualitative Bayesian FMECA approach along with a formal uncertainty management framework for an e-UAS. In this work we demonstrate the efficacy of the framework to predict effects of sub-system level degradation on vehicle operation incorporating uncertainty management to predict future behavior under different operating conditions.
Kulkarni, Chetan↗
Benchmarking the performance of uncertainty quantification methods for neural network-based interatomic potentials
Machine-learned interatomic potentials (ML-IAPs) continue to gain popularity as accurate, computationally efficient replacements for traditional, physics-based interatomic potentials and expensive ab initio methods. Uncertainty quantification (UQ) of ML-IAPs is a growing area of research as UQ is critical in many applications of IAPs, such as developing curated datasets, active learning-based data augmentation, self-improving models, and estimating the uncertainty of molecular dynamics simulations. In this paper, we construct and benchmark a series of different neural network potentials (NNPs) with varying network architectures to determine the performance of these models with respect to both the mean and uncertainty calibration error. Each NNP method is specifically designed to predict either epistemic or aleatoric uncertainty with particular focus on the differences in behavior between the epistemic and aleatoric uncertainty estimates. We benchmark these methods using multiple datasets common in the ML-IAP literature. The results show that the aleatoric uncertainty from single-shot model architectures is a competitive alternative to ensemble-based epistemic uncertainty predictions in regions of sufficient data-density. However, in regions where the representative data is sparse, aleatoric uncertainty models tend to overpredict and epistemic methods tend to underpredict the actual model error. We conclude that the type of UQ is crucial when discussing performance of probabilistic model results as different methods have different performance characteristics depending on the regime in which they are evaluated. Therefore, the type of UQ method should be carefully evaluated against both the data characteristics and requirements for the intended application.
97 MATHEMATICS AND COMPUTING↗
Global and regional kinematics with GPS
The inherent precision of the doubly differenced phase measurement and the low cost of instrumentation made GPS the space geodetic technique of choice for regional surveys as soon as the constellation reached acceptable geometry in the area of interest: 1985 in western North America, the early 1990's in most of the world. Instrument and site-related errors for horizontal positioning are usually less than 3 mm, so that the dominant source of error is uncertainty in the reference frame defined by the satellites orbits and the tracking stations used to determine them. Prior to about 1992, when the tracking network for most experiments was globally sparse, the number of fiducial sites or the level at which they could be tied to an SLR or VLBI reference frame usually, set the accuracy limit. Recently, with a global network of over 30 stations, the limit is set more often by deficiencies in models for non-gravitational forces acting on the satellites. For regional networks in the northern hemisphere, reference frame errors are currently about 3 parts per billion (ppb) in horizontal position, allowing centimeter-level accuracies over intercontinental distances and less than 1 mm for a 100 km baseline. The accuracy of GPS measurements for monitoring height variations is generally 2-3 times worse than for horizontal motions. As for VLBI, the primary source of error is unmodeled fluctuations in atmospheric water vapor, but both reference frame uncertainties and some instrument errors are more serious for vertical than horizontal measurements. Under good conditions, daily repeatabilities at the level of 10 mm rms were achieved. This paper will summarize the current accuracy of GPS measurements and their implication for the use of SLR to study regional kinematics.
King, Robert W.↗
Computational Fluid Dynamics Uncertainty Analysis for Payload Fairing Spacecraft Environmental Control Systems
Spacecraft thermal protection systems are at risk of being damaged due to airflow produced from Environmental Control Systems. There are inherent uncertainties and errors associated with using Computational Fluid Dynamics to predict the airflow field around a spacecraft from the Environmental Control System. This proposal describes an approach to validate the uncertainty in using Computational Fluid Dynamics to predict airflow speeds around an encapsulated spacecraft. The research described here is absolutely cutting edge. Quantifying the uncertainty in analytical predictions is imperative to the success of any simulation-based product. The method could provide an alternative to traditional"validation by test only'' mentality. This method could be extended to other disciplines and has potential to provide uncertainty for any numerical simulation, thus lowering the cost of performing these verifications while increasing the confidence in those predictions. Spacecraft requirements can include a maximum airflow speed to protect delicate instruments during ground processing. Computationaf Fluid Dynamics can be used to veritY these requirements; however, the model must be validated by test data. The proposed research project includes the following three objectives and methods. Objective one is develop, model, and perform a Computational Fluid Dynamics analysis of three (3) generic, non-proprietary, environmental control systems and spacecraft configurations. Several commercially available solvers have the capability to model the turbulent, highly three-dimensional, incompressible flow regime. The proposed method uses FLUENT and OPEN FOAM. Objective two is to perform an uncertainty analysis of the Computational Fluid . . . Dynamics model using the methodology found in "Comprehensive Approach to Verification and Validation of Computational Fluid Dynamics Simulations". This method requires three separate grids and solutions, which quantify the error bars around Computational Fluid Dynamics predictions. The method accounts for all uncertainty terms from both numerical and input variables. Objective three is to compile a table of uncertainty parameters that could be used to estimate the error in a Computational Fluid Dynamics model of the Environmental Control System /spacecraft system. Previous studies have looked at the uncertainty in a Computational Fluid Dynamics model for a single output variable at a single point, for example the re-attachment length of a backward facing step. To date, the author is the only person to look at the uncertainty in the entire computational domain. For the flow regime being analyzed (turbulent, threedimensional, incompressible), the error at a single point can propagate into the solution both via flow physics and numerical methods. Calculating the uncertainty in using Computational Fluid Dynamics to accurately predict airflow speeds around encapsulated spacecraft in is imperative to the success of future missions.
Groves, Curtis E.↗