Limits on the accuracy of correction of trans-ionospheric propagation errors by using ionospheric models based on solar and magnetic indices and local measurements
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Nisbet, J. S.↗
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The Impact of Truth Surrogate Variance on Quality Assessment/Assurance in Wind Tunnel Testing
Minimum data volume requirements for wind tunnel testing are reviewed and shown to depend on error tolerance, response model complexity, random error variance in the measurement environment, and maximum acceptable levels of inference error risk. Distinctions are made between such related concepts as quality assurance and quality assessment in response surface modeling, as well as between precision and accuracy. Earlier research on the scaling of wind tunnel tests is extended to account for variance in the truth surrogates used at confirmation sites in the design space to validate proposed response models. A model adequacy metric is presented that represents the fraction of the design space within which model predictions can be expected to satisfy prescribed quality specifications. The impact of inference error on the assessment of response model residuals is reviewed. The number of sites where reasonably well-fitted response models actually predict inadequately is shown to be considerably less than the number of sites where residuals are out of tolerance. The significance of such inference error effects on common response model assessment strategies is examined.
DeLoach, Richard↗
Techniques for Down-Sampling a Measured Surface Height Map for Model Validation
This software allows one to down-sample a measured surface map for model validation, not only without introducing any re-sampling errors, but also eliminating the existing measurement noise and measurement errors. The software tool of the current two new techniques can be used in all optical model validation processes involving large space optical surfaces
Sidick, Erkin↗
Calibration of the Diffusivity Predictions of Centipede Using Approximate Bayesian Computation and Applications in Nyx (Engineering Scale) and Xolotl-MARMOT (Meso-Scale) Simulations
Fission gas evolution and release in UO 2 nuclear fuel are important fuel performance metrics and occur in several distinct stages: 1) nucleation, growth and resolution of intra-granular bubbles, 2) diffusion to grain boundaries and 3) nucleation and growth of bubbles at grain boundaries, which eventually form a connected network (percolation) enabling release of gas from grain boundaries through connections to triple junctions, grain edges or free surfaces. The NE-SciDAC project is developing several computational tools to model this problem, which are connected in a hierarchical multi-scale framework. The information transfer in the multi-scale framework is a critical step that, in addition to best-estimates, should include uncertainty quantification. Despite taking a first-principles multi-scale approach, there is a need to perform parameter calibration to ensure consistency with available experimental data. In the present study, uncertainty quantification (UQ) and parameter calibration is demonstrated for one of the lower length scale codes in the multi-scale framework (Centipede) and then the results, including instances of the propagated uncertainties, are used in other codes within the framework, specifically Nyx and Xolotl-MARMOT. We calibrated the model parameters in Centipede, a computer code used to predict diffusivities of uranium (U) and xenon (Xe) in the context of the simulation of fission gas in uranium oxide (UO 2 ) nuclear fuel. The Centipede code depends on 183 parameters, all of which are subject to uncertainty. The three data sets used in our calibration effort are taken from the literature. This data is available as a set of measurements, including measurement errors. Our goal is to calibrate a statistical model that predicts both the value of the measurement and the uncertainty associated with the measurement. We perform a Bayesian calibration of the model parameters using a dedicated approximate Bayesian computation (ABC) likelihood function. To avoid excessive computational costs, we replace the expensive Centipede simulation code by a higher-order surrogate model, constructed using only the 9 most important parameters. These important parameters are identified by a preliminary global sensitivity analysis (GSA) study. Among the important parameters are T0 (the temperature at which UO 2 is perfectly stoichiometric) and Hf_pO2 (the temperature dependence of the oxygen (O) partial pressure) that should be considered as operating conditions to be estimated along with the other parameters. We consider two different cases: one where we define one set of these operating conditions for all data sets, and one where we define distinct operating condition parameters for each data set. The Xe diffusivities predicted by the latter case show distinct features that could not be observed in the former. Next, we use the diffusivity predictions by Centipede as input to Nyx, a reduced order fuel performance code focused on gas behavior alone, in order to estimate quantities associated with inter-granular bubble formation at conditions specified by the experiments. Finally, the diffusivities obtained from the calibrated Centipede runs were used in coupled Xolotl-MARMOT simulations of intra- and inter-granular gas evolution. The results are compared to simulations using the baseline diffusivities from Turnbull et al.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Rotor dynamic state and parameter identification from simulated forward flight transients, part 1
State and parameter identifications from simulated forward flight blade flapping measurements are presented. The transients were excited by progressing cyclic pitch stirring or by hub stirring with constant stirring acceleration. Rotor dynamic inflow models of varying degree of sophistication were used from a one parameter inflow model (equivalent Lock number) to an eight parameter inflow model. The maximum likelihood method with assumed fixed measurement error covariance matrix was applied. The rotor system equations for both fixed hub and tilting hub are given. The identified models were verified by comparing true responses with predicted responses. An optimum utilization of the simulated measurement data can be defined. From the numerical results it can be anticipated that brief periods of either accelerated cyclic pitch stirring or of hub stirring are sufficient to extract with adequate accuracy up to 8 rotor dynamic inflow parameters plus the blade Lock number from the transients.
Hohenemser, K. H.↗
Estimating value of information for heliostat washing operations at solar thermal plants
Concentrating solar power (CSP) plants depend on thousands of heliostats whose reflectance declines as dust accumulates. Operators routinely measure reflectance to estimate soiling and, in turn, inform cleaning schedules, but the value of collecting more frequent or more accurate data has not been formally quantified. This study introduces a Monte Carlo discrete event simulation framework that integrates stochastic models of soiling, weather, and measurement error with a dynamic cleaning dispatch policy to estimate annual energy production and operations costs. Applied to two representative central-receiver field configurations, the results show that both the frequency and accuracy of reflectance measurements can meaningfully impact plant performance. In both case studies, reducing measurement intervals yields significant returns, with the energy gains greatly exceeding the cost of more frequent data collection. The simulation framework serves as a decision-support tool for CSP operators, allowing them to input site-specific soiling conditions, measurement accuracy, and survey frequency to evaluate the tradeoffs between data collection cost and energy recovery, and to identify measurement strategies that maximize plant profit.
14 SOLAR ENERGY↗
Application of New Los Alamos OPLIB Opacities in Solar Modeling Using the Mesa Code
The Sun provides the only local laboratory to test our understanding of stellar physics. The production, then, of valid dynamical models of the Sun is critical to how we think about other stars. Despite improvements in modeling methodologies and abundance measurements, solar models continue to reproduce errors in convection zone depth and surface helium abundance compared to helioseismic observations. Using the 1D stellar evolution code MESAstar, this work first evaluates the effect of changes to timestep resolution and mixing length theory on model outputs. A standard test case is then constructed with both GS98 and AGSS09 abundances using OP and OPAL opacities before implementing the new Los Alamos OPLIB opacities. It is shown that, when using GS98 abundances, OPLIB opacities improve agreement with helioseismic inference of the convection zone base radius, R czb , by 1.68-σ and 1.19-σ compared to OP and OPAL, respectively, while worsening agreement with the inferred envelope helium mass fraction, Y surf , by 0.63-σ and 0.98-σ for OP and OPAL.
14 SOLAR ENERGY↗
Advanced communication system time domain modeling techniques ASYSTD software description. Volume 2: Program support documentation
The theoretical basis for the ASYSTD program is discussed in detail. In addition, the extensive bibliography given in this document illustrates some of the extensive work accomplished in the area of time domain simulation. Additions have been in the areas of modeling and language program enhancements, orthogonal transform modeling, error analysis, general filter models, BER measurements, etc. Several models have been developed which utilize the COMSAT generated orthogonal transform algorithms.
Source record↗
Determination of instrumentation errors from measured data using maximum likelihood method
The maximum likelihood method is used for estimation of unknown initial conditions, constant bias and scale factor errors in measured flight data. The model for the system to be identified consists of the airplane six-degree-of-freedom kinematic equations, and the output equations specifying the measured variables. The estimation problem is formulated in a general way and then, for practical use, simplified by ignoring the effect of process noise. The algorithm developed is first applied to computer generated data having different levels of process noise for the demonstration of the robustness of the method. Then the real flight data are analyzed and the results compared with those obtained by the extended Kalman filter algorithm.
Keskar, D. A.↗
Evaluation of Thompson-type trend and monthly weather data models for corn yields in Iowa, Illinois, and Indiana
An evaluation was made of Thompson-Type models which use trend terms (as a surrogate for technology), meteorological variables based on monthly average temperature, and total precipitation to forecast and estimate corn yields in Iowa, Illinois, and Indiana. Pooled and unpooled Thompson-type models were compared. Neither was found to be consistently superior to the other. Yield reliability indicators show that the models are of limited use for large area yield estimation. The models are objective and consistent with scientific knowledge. Timely yield forecasts and estimates can be made during the growing season by using normals or long range weather forecasts. The models are not costly to operate and are easy to use and understand. The model standard errors of prediction do not provide a useful current measure of modeled yield reliability.
French, V.↗
Structural damage detection using a subspace rotation algorithm
A computationally inexpensive algorithm is developed to provide an insight to the location of structural damage, using the original finite element model and a subset of measured eigenvalues and eigenvectors. The computational requirements of the algorithm may make the technique suitable for real-time implementation. With damage location determined, a second algorithm is developed to determine the extent of damage. The algorithms are demonstrated using two classes of structural models. The effects of eigenvector measurement error is demonstrated and techniques to overcome the effects of noise are discussed.
Zimmerman, David C.↗
Reliability of magnetic inclination angle determinations for pulsars
We compare the recent estimates of the inclination angle alpha between the rotation and magnetic axes of 56 pulsars made by both Lyne and Manchester (1988) and Rankin (1990). Their results agree reasonably well when alpha is less than about 40 deg; however, there is no correlation between the two estimates of alpha if either estimate exceeds 40 deg. The correlation is better for pulsars with beams having more complicated core structure. Nevertheless, the differences between the two sets of estimates are large enough that use of these estimates to investigate pulsar physics is questionable. We discuss the method for determining alpha based on the Radhakrishnan and Cooke (1969) single-vector model, emphasizing its sensitivity to measurement errors. This method complements the approaches of Rankin and Lyne and Manchester and is preferable when accurate polarization data are available.
Miller, M. C.↗
Development of a model protection and dynamic response monitoring system for the national transonic facility
A state-of-the-art, computerized mode protection and dynamic response monitoring system has been developed for the NASA Langley Research Center National Transonic Facility (NTF). This report describes the development of the model protection and shutdown system (MPSS). A technical description of the system is given along with discussions on operation and capabilities of the system. Applications of the system to vibration problems are presented to demonstrate the system capabilities, typical applications, versatility, and investment research return derived from the system to date. The system was custom designed for the NTF but can be used at other facilities or for other dynamic measurement/diagnostic applications. Potential commercial uses of the system are described. System capability has been demonstrated for forced response testing and for characterizing and quantifying bias errors for onboard inertial model attitude measurement devices. The system is installed in the NTF control room and has been used successfully for monitoring, recording and analyzing the dynamic response of several model systems tested in the NTF.
Young, Clarence P., Jr.↗
Systems Engineering Programmatic Estimation Using Technology Variance
Unique and innovative system programmatic estimation is conducted using the variance of the packaged technologies. Covariance analysis is performed on the subsystems and components comprising the system of interest. Technological "return" and "variation" parameters are estimated. These parameters are combined with the model error to arrive at a measure of system development stability. The resulting estimates provide valuable information concerning the potential cost growth of the system under development.
Mog, Robert A.↗
Systems Engineering Programmatic Estimation Using Technology Variance
Unique and innovative system programmatic estimation is conducted using the variance of the packaged technologies. Covariance analysis is performed oil the subsystems and components comprising the system of interest. Technological "returns" and "variation" parameters, are estimated. These parameters are combined with the model error to arrive at a measure of system development stability. The resulting estimates provide valuable information concerning the potential cost growth of the system under development.
Mog, Robert A.↗
Analysis of earth albedo effect on sun sensor measurements based on theoretical model and mission experience
Analysis of flight data from previous missions indicates that anomalous Sun sensor readings could be caused by Earth albedo interference. A previous Sun sensor study presented a detailed mathematical model of this effect. The model can be used to study the effect of both diffusive and specular reflections and to improve Sun angle determination based on perturbed Sun sensor measurements, satellite position, and an approximate knowledge of attitude. The model predicts that diffuse reflected light can cause errors of up to 10 degrees in Coarse Sun Sensor (CSS) measurements and 5 to 10 arc sec in Fine Sun Sensor (FSS) measurements, depending on spacecraft orbit and attitude. The accuracy of these sensors is affected as long as part of the illuminated Earth surface is present in the sensor field of view. Digital Sun Sensors (DSS) respond in a different manner to the Earth albedo interference. Most of the time DSS measurements are not affected, but for brief periods of time the Earth albedo can cause errors which are a multiple of the sensor least significant bit and may exceed one degree. This paper compares model predictions with Tropical Rainfall Measuring Mission (TRMM) CSS measurements in order to validate and refine the model. Methods of reducing and mitigating the impact of Earth albedo are discussed. ne CSS sensor errors are roughly proportional to the Earth albedo coefficient. Photocells that are sensitive only to ultraviolet emissions would reduce the effective Earth albedo by up to a thousand times, virtually eliminating all errors caused by Earth albedo interference.
Brasoveanu, Dan↗
Observations of TOPEX/Poseidon Orbit Errors Due to Gravitational and Tidal Modeling Errors Using the Global Positioning System
Satellite altimetry must measure variations in ocean topography with cm-level accuracy. The TOPEX/Poseidon mission is designed to do this by measuring the radial component of the orbit with an accuracy of 13 cm or better RMS. Recent advances, however, have improved this accuracy by about an order of magnitude.
tidal models↗
Estimation of bias errors in measured airplane responses using maximum likelihood method
A maximum likelihood method is used for estimation of unknown bias errors in measured airplane responses. The mathematical model of an airplane is represented by six-degrees-of-freedom kinematic equations. In these equations the input variables are replaced by their measured values which are assumed to be without random errors. The resulting algorithm is verified with a simulation and flight test data. The maximum likelihood estimates from in-flight measured data are compared with those obtained by using a nonlinear-fixed-interval-smoother and an extended Kalmar filter.
Klein, Vladiaslav↗