Analysis of dynamic simulation errors for coupled loop models, phase 1 Final report
Dynamic simulation errors for coupled loop models for digital differential and electronic differential analyzers
Jackson, A. S.↗
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Results for “Model error”
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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Assimilation of a knowledge base and physical models to reduce errors in passive-microwave classifications of sea ice
An expert system framework has been developed to classify sea ice types using satellite passive microwave data, an operational classification algorithm, spatial and temporal information, ice types estimated from a dynamic-thermodynamic model, output from a neural network that detects the onset of melt, and knowledge about season and region. The rule base imposes boundary conditions upon the ice classification, modifies parameters in the ice algorithm, determines a `confidence' measure for the classified data, and under certain conditions, replaces the algorithm output with model output. Results demonstrate the potential power of such a system for minimizing overall error in the classification and for providing non-expert data users with a means of assessing the usefulness of the classification results for their applications.
Maslanik, J. A.↗
Software development predictors, error analysis, reliability models and software metric analysis
The use of dynamic characteristics as predictors for software development was studied. It was found that there are some significant factors that could be useful as predictors. From a study on software errors and complexity, it was shown that meaningful results can be obtained which allow insight into software traits and the environment in which it is developed. Reliability models were studied. The research included the field of program testing because the validity of some reliability models depends on the answers to some unanswered questions about testing. In studying software metrics, data collected from seven software engineering laboratory (FORTRAN) projects were examined and three effort reporting accuracy checks were applied to demonstrate the need to validate a data base. Results are discussed.
Basili, Victor↗
Terrestrial Water Mass Load Changes from Gravity Recovery and Climate Experiment (GRACE)
Recent studies show that data from the Gravity Recovery and Climate Experiment (GRACE) is promising for basin- to global-scale water cycle research. This study provides varied assessments of errors associated with GRACE water storage estimates. Thirteen monthly GRACE gravity solutions from August 2002 to December 2004 are examined, along with synthesized GRACE gravity fields for the same period that incorporate simulated errors. The synthetic GRACE fields are calculated using numerical climate models and GRACE internal error estimates. We consider the influence of measurement noise, spatial leakage error, and atmospheric and ocean dealiasing (AOD) model error as the major contributors to the error budget. Leakage error arises from the limited range of GRACE spherical harmonics not corrupted by noise. AOD model error is due to imperfect correction for atmosphere and ocean mass redistribution applied during GRACE processing. Four methods of forming water storage estimates from GRACE spherical harmonics (four different basin filters) are applied to both GRACE and synthetic data. Two basin filters use Gaussian smoothing, and the other two are dynamic basin filters which use knowledge of geographical locations where water storage variations are expected. Global maps of measurement noise, leakage error, and AOD model errors are estimated for each basin filter. Dynamic basin filters yield the smallest errors and highest signal-to-noise ratio. Within 12 selected basins, GRACE and synthetic data show similar amplitudes of water storage change. Using 53 river basins, covering most of Earth's land surface excluding Antarctica and Greenland, we document how error changes with basin size, latitude, and shape. Leakage error is most affected by basin size and latitude, and AOD model error is most dependent on basin latitude.
Seo, K.-W.↗
Feedback control laws for highly maneuverable aircraft
During the first half of the year, the investigators concentrated their efforts on completing the design of control laws for the longitudinal axis of the HARV. During the second half of the year they concentrated on the synthesis of control laws for the lateral-directional axes. The longitudinal control law design efforts can be briefly summarized as follows. Longitudinal control laws were developed for the HARV using mu synthesis design techniques coupled with dynamic inversion. An inner loop dynamic inversion controller was used to simplify the system dynamics by eliminating the aerodynamic nonlinearities and inertial cross coupling. Models of the errors resulting from uncertainties in the principal longitudinal aerodynamic terms were developed and included in the model of the HARV with the inner loop dynamic inversion controller. This resulted in an inner loop transfer function model which was an integrator with the modeling errors characterized as uncertainties in gain and phase. Outer loop controllers were then designed using mu synthesis to provide robustness to these modeling errors and give desired response to pilot inputs. Both pitch rate and angle of attack command following systems were designed. The following tasks have been accomplished for the lateral-directional controllers: inner and outer loop dynamic inversion controllers have been designed; an error model based on a linearized perturbation model of the inner loop system was derived; controllers for the inner loop system have been designed, using classical techniques, that control roll rate and Dutch roll response; the inner loop dynamic inversion and classical controllers have been implemented on the six degree of freedom simulation; and lateral-directional control allocation scheme has been developed based on minimizing required control effort.
Garrard, William L.↗
Contribution of Modeling Differences to Systematic Errors of the Celestial Reference Frame: Modest/Calc/Gloria
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software differences↗
Optical Error Budgeting Using Linearized Ray-Trace Models
The Root-Sum-Squared, or “RSS” wavefront error model is a simple, scalar tool, commonly used for space telescope error budgeting. At the same time, much more detailed models, combining ray-trace and Fourier optics with optical alignments and wavefront controls, can provide accurate, high -resolution simulations for detailed system and subsystem design. This paper makes a connection between the two modeling approaches by deriving RSS model coefficients from ray-trace models, including the effects of wavefront controls, for computing system performance from component error statistics. It is shown that, properly constructed, the simple RSS error budget is a covariance analysis, and can be as accurate as high-resolution wavefront models for statistical wavefront error prediction. A notional segmented-aperture space telescope is used to illustrate this error modeling process.
Wavefront error↗
Effects of vibration on inertial wind-tunnel model attitude measurement devices
Results of an experimental study of a wind tunnel model inertial angle-of-attack sensor response to a simulated dynamic environment are presented. The inertial device cannot distinguish between the gravity vector and the centrifugal accelerations associated with wind tunnel model vibration, this situation results in a model attitude measurement bias error. Significant bias error in model attitude measurement was found for the model system tested. The model attitude bias error was found to be vibration mode and amplitude dependent. A first order correction model was developed and used for estimating attitude measurement bias error due to dynamic motion. A method for correcting the output of the model attitude inertial sensor in the presence of model dynamics during on-line wind tunnel operation is proposed.
Young, Clarence P., Jr.↗
Quantifying the Storm Time Thermospheric Neutral Density Variations Using Model and Observations
Accurate determination of thermospheric neutral density holds crucial importance for satellited rag calculations. The problem is twofold and involves the correct estimation of the quiet time climatology and storm time variations. In this work, neutral density estimations from two empirical and threephysics based models of the ionosphere thermosphere are compared with the neutral densities along the Challenging MicroSatellite Payload satellite track for six geomagnetic storms. Storm time variations are extracted from neutral density by (1) subtracting the mean difference between model and observation (bias),(2) setting climatological variations to zero, and (3) multiplying model data with the quiet time ratio between the model and observation. Several metrics are employed to evaluate the model performances. We find that the removal of bias or climatology reveals actual performance of the model in simulating the storm time variations. When bias is removed, depending on event and model, storm time errors in neutral density can decrease by an amount of 113% or can increase by an amount of 12% with respect to error in models with quiet time bias. It is shown that using only average and maximum values of neutral density to determine the model performances can be misleading since a model can estimate the averages fairly well but may not capture the maximum value or vice versa. Since each of the metrics used for determining model performances provides different aspects of the error, among these, we suggest employing mean absolute error, prediction efficiency, and normalized root mean square error together as a standard set ofmetrics for the neutral density.
Eyiguler, E. Ceren Kalafatoglu↗
Solar maximum mission fine pointing sun sensor dawn and dusk errors flight data and model analysis
SMM flight system control errors occurring at spacecraft dawn and dusk are analyzed. The errors are associated with the fine pointing sun sensor (FPSS), which is a primary component of the SMM attitude control system. It is shown that the source of the FPSS dawn/dusk distortion is the incomplete masking of sunlight reflected off the earth by the optical baffle covering the FPSS sensor heads onboard the SMM during periods of orbit dawn and dusk. For the most part, the modeled behavior of the FPSS under dawn and dusk lighting conditions matches the observed behavior in the SMM flight data.
Kulp, D. R.↗
Mars Entry Atmospheric Data System Modeling, Calibration, and Error Analysis
The Mars Science Laboratory (MSL) Entry, Descent, and Landing Instrumentation (MEDLI)/Mars Entry Atmospheric Data System (MEADS) project installed seven pressure ports through the MSL Phenolic Impregnated Carbon Ablator (PICA) heatshield to measure heatshield surface pressures during entry. These measured surface pressures are used to generate estimates of atmospheric quantities based on modeled surface pressure distributions. In particular, the quantities to be estimated from the MEADS pressure measurements include the dynamic pressure, angle of attack, and angle of sideslip. This report describes the calibration of the pressure transducers utilized to reconstruct the atmospheric data and associated uncertainty models, pressure modeling and uncertainty analysis, and system performance results. The results indicate that the MEADS pressure measurement system hardware meets the project requirements.
Karlgaard, Christopher D.↗
Parameter estimation and error analysis in environmental modeling and computation
A method for the estimation of parameters and error analysis in the development of nonlinear modeling for environmental impact assessment studies is presented. The modular computer program can interactively fit different nonlinear models to the same set of data, dynamically changing the error structure associated with observed values. Parameter estimation techniques and sequential estimation algorithms employed in parameter identification and model selection are first discussed. Then, least-square parameter estimation procedures are formulated, utilizing differential or integrated equations, and are used to define a model for association of error with experimentally observed data.
Kalmaz, E. E.↗
Error-source effects in a high-accuracy optical finite-element processor
High-accuracy optical linear algebra processors are addressed with attention to three new aspects. These include: their application to the solution of finite-element problems; the first error-source models for component errors in such processors; and the first analysis of error sources in such processors.
Taylor, B. K.↗
Can Resilience Assessments Inform Early Design Human Factors Decision-making?
There is a growing call among researchers for tighter coupling between human factors and human reliability assessments. In this research, we explore if early design stage resilience assessments can help bridge some of the gaps between human factors and human reliability assessments. Resilience in systems is their ability to recover reasonably and operate within acceptable bounds during failures and unexpected events. The fmdtools toolkit allows designers to assess the resilience of a system by modeling the human error and machine-related failure propagation in both nominal and faulty scenarios during the early design stages. As a result, the fmdtools toolkit has a low-fidelity dynamic human reliability assessment component built into it. In this paper, we study if the results from the fmdtools simulations can help inform and prioritize human factors design decision-making, resulting in tighter coupling between human factors and human reliability assessments during the design process. Specifically, we explore the results from a rover design example to understand the types of information that can help guide human factor-related decision-making.
Resilience-based Design↗
A framework for simulating map error in ecosystem models
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Sean P. Healey↗
Predicting Pilot Error in Nextgen: Pilot Performance Modeling and Validation Efforts
We review 25 articles presenting 5 general classes of computational models to predict pilot error. This more targeted review is placed within the context of the broader review of computational models of pilot cognition and performance, including such aspects as models of situation awareness or pilot-automation interaction. Particular emphasis is placed on the degree of validation of such models against empirical pilot data, and the relevance of the modeling and validation efforts to Next Gen technology and procedures.
pilot error↗