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Error Propagation Analysis in the SAE Architecture Analysis and Design Language (AADL) and the EDICT Tool Framework

This report documents the capabilities of the EDICT tools for error modeling and error propagation analysis when operating with models defined in the Architecture Analysis & Design Language (AADL). We discuss our experience using the EDICT error analysis capabilities on a model of the Scalable Processor-Independent Design for Enhanced Reliability (SPIDER) architecture that uses the Reliable Optical Bus (ROBUS). Based on these experiences we draw some initial conclusions about model based design techniques for error modeling and analysis of highly reliable computing architectures.

LaValley, Brian W.↗

Error Propagation in Microwave Soil Moisture and Vegetation Optical Depth Retrievals

Satellite soil moisture and vegetation optical depth (VOD; related to the total vegetation water mass per unit area) are increasingly being used to study water relations in the soil-plant continuum across the globe. However, soil moisture and VOD are typically jointly estimated, where errors in the optimization approach can cause compensation between both variables and confound such studies. It is thus critical to quantify how satellite microwave measurement errors propagate into soil moisture and VOD. Such a study is especially important for VOD given limited investigations of whether VOD reflects in-situ plant physiology. Furthermore, despite new approaches that constrain (or regularize) VOD dynamics to reduce soil moisture errors, there is limited study of whether regularization reduces VOD errors without obscuring true vegetation temporal dynamics. Here, we find that, across the globe, VOD is less robust to measurement error (more difficult for optimization methods to find the true solution) than soil moisture in their joint estimation. However, a moderate degree of regularization (via time-constrained VOD) reduces errors in VOD to a greater degree than soil moisture and reduces spurious soil moisture-VOD coupling. Furthermore, despite constraining VOD time dynamics, regularized VOD variations on sub-weekly scales are both closer to simulated true VOD time series and have global VOD post-rainfall responses with reduced error signatures compared to VOD retrievals without regularization. Ultimately, we recommend moderately regularized VOD for use in large scale studies of soil-plant water relations because it suppresses noise and spurious soil moisture-VOD coupling without removing the physical signal.

Vegetation optical depth↗

Cross Section Sensitivity and Propagated Errors in HZE Exposures

It has long been recognized that galactic cosmic rays are of such high energy that they tend to pass through available shielding materials resulting in exposure of astronauts and equipment within space vehicles and habitats. Any protection provided by shielding materials result not so much from stopping such particles but by changing their physical character in interaction with shielding material nuclei forming, hopefully, less dangerous species. Clearly, the fidelity of the nuclear cross-sections is essential to correct specification of shield design and sensitivity to cross-section error is important in guiding experimental validation of cross-section models and database. We examine the Boltzmann transport equation which is used to calculate dose equivalent during solar minimum, with units (cSv/yr), associated with various depths of shielding materials. The dose equivalent is a weighted sum of contributions from neutrons, protons, light ions, medium ions and heavy ions. We investigate the sensitivity of dose equivalent calculations due to errors in nuclear fragmentation cross-sections. We do this error analysis for all possible projectile-fragment combinations (14,365 such combinations) to estimate the sensitivity of the shielding calculations to errors in the nuclear fragmentation cross-sections. Numerical differentiation with respect to the cross-sections will be evaluated in a broad class of materials including polyethylene, aluminum and copper. We will identify the most important cross-sections for further experimental study and evaluate their impact on propagated errors in shielding estimates.

Heinbockel, John H.↗

Error Propagation in a System Model

Embodiments of the present subject matter can enable the analysis of signal value errors for system models. In an example, signal value errors can be propagated through the functional blocks of a system model to analyze possible effects as the signal value errors impact incident functional blocks. This propagation of the errors can be applicable to many models of computation including avionics models, synchronous data flow, and Kahn process networks.

Schloegel, Kirk↗

Scout trajectory error propagation computer program

Since 1969, flight experience has been used as the basis for predicting Scout orbital accuracy. The data used for calculating the accuracy consists of errors in the trajectory parameters (altitude, velocity, etc.) at stage burnout as observed on Scout flights. Approximately 50 sets of errors are used in Monte Carlo analysis to generate error statistics in the trajectory parameters. A covariance matrix is formed which may be propagated in time. The mechanization of this process resulted in computer program Scout Trajectory Error Propagation (STEP) and is described herein. Computer program STEP may be used in conjunction with the Statistical Orbital Analysis Routine to generate accuracy in the orbit parameters (apogee, perigee, inclination, etc.) based upon flight experience.

Myler, T. R.↗

A neural fuzzy controller learning by fuzzy error propagation

In this paper, we describe a procedure to integrate techniques for the adaptation of membership functions in a linguistic variable based fuzzy control environment by using neural network learning principles. This is an extension to our work. We solve this problem by defining a fuzzy error that is propagated back through the architecture of our fuzzy controller. According to this fuzzy error and the strength of its antecedent each fuzzy rule determines its amount of error. Depending on the current state of the controlled system and the control action derived from the conclusion, each rule tunes the membership functions of its antecedent and its conclusion. By this we get an unsupervised learning technique that enables a fuzzy controller to adapt to a control task by knowing just about the global state and the fuzzy error.

Nauck, Detlef↗

Error propagation in the numerical solutions of the differential equations of orbital mechanics

The relationship between the eigenvalues of the linearized differential equations of orbital mechanics and the stability characteristics of numerical methods is presented. It is shown that the Cowell, Encke, and Encke formulation with an independent variable related to the eccentric anomaly all have a real positive eigenvalue when linearized about the initial conditions. The real positive eigenvalue causes an amplification of the error of the solution when used in conjunction with a numerical integration method. In contrast an element formulation has zero eigenvalues and is numerically stable.

Bond, V. R.↗

GeoCarb L2 Validation- Albedo Error Propagation into XCO2 in the Near Infrared

GeoCarb validation activities Pre-launch validation •Thermovac: Nov-Jan, 2022/3: Edwards/Dryden will move to Palo Alto Nov-March 2022/3 •Day-in-the life simulation-2022 •Simulations near Dallas, TX •Validation of TROPOMI in GeoCarb domain-2022 2GeoCarb post-launch GeoCarb will have gas precision of: •0.3% (1.2 ppm) for XCO2 •0.6% (11 ppb) for XCH4 •10% or 12 ppb for XCO GeoCarb SIF with precision of better than 0.75 W/m2/um/sr GeoCarb will utilize TCCON, GML/DOE aircraft, AirCore, and any validation site with systematic errors better than GeoCarb’s

GeoCarb↗

Optimal control of quaternion propagation errors in spacecraft navigation

Optimal control techniques are used to drive the numerical error (truncation, roundoff, commutation) in computing the quaternion vector to zero. The normalization of the quaternion is carried out by appropriate choice of a performance index, which can be optimized. The error equations are derived from Friedland's (1978) theoretical development, and a matrix Riccati equation results for the computation of the gain matrix. Simulation results show that a high precision of the order of 10 to the -12th can be obtained using this technique in meeting the q(T)q=1 constraint. The performance of the estimator in the presence of the feedback control that maintains the normalization, is studied.

Vathsal, S.↗

Implications of cross section errors for cosmic ray propagation

Errors in nuclear interaction cross sections are the single most important limitation on the analysis of cosmic ray composition data. At the 18th International Cosmic Ray Conference, the potential importance of correlations in cross section errors in determining cosmic ray source abundances was demonstrated. In this paper the magnitude of cross section error correlation is estimated. Analysis suggests that cross section errors are essentially uncorrelated for nuclei with Z 29 and that the actual errors may be less than the nominal 35%.

Letaw, J. R.↗

Location of a faulty module in a computing system

Considering the interplay between different phases of fault tolerance, a new problem of locating a faulty module in a computing system is formulated and solved. First, the probability of each module being faulty, or faulty probability, is calculated using the likelihood principle from the model parameters for fault detection, diagnostics, error propagation, and error detection. Then, based on the faulty probabilities and a given required diagnostic coverage, the order in which modules are to be diagnosed and the maximum time allotted to diagnose each module are determined by minimizing the average total diagnostic time. An example is presented and analyzed to answer the question of whether or not a system should delay the diagnosis upon detection of an error until more errors are detected.

Lin, Tein-Hsiang↗

A Computational Intelligence (CI) Approach to the Precision Mars Lander Problem

A Mars precision landing requires a landed footprint of no more than 100 meters. Obstacles to reducing the landed footprint include trajectory dispersions due to initial atmospheric entry conditions such as entry angle, parachute deployment height, environment parameters such as wind, atmospheric density, parachute deployment dynamics, unavoidable injection error or propagated error from launch, etc. Computational Intelligence (CI) techniques such as Artificial Neural Nets and Particle Swarm Optimization have been shown to have great success with other control problems. The research period extended previous work on investigating applicability of the computational intelligent approaches. The focus of this investigation was on Particle Swarm Optimization and basic Neural Net architectures. The research investigating these issues was performed for the grant cycle from 5/15/01 to 5/15/02. Matlab 5.1 and 6.0 along with NASA's POST were the primary computational tools.

Birge, Brian↗

Mathematical analysis study for radar data processing and enchancement. Part 2: Modeling of propagation path errors

A study is performed under NASA contract to evaluate data from an AN/FPS-16 radar installed for support of flight programs at Dryden Flight Research Facility of NASA Ames Research Center. The purpose of this study is to provide information necessary for improving post-flight data reduction and knowledge of accuracy of derived radar quantities. Tracking data from six flights are analyzed. Noise and bias errors in raw tracking data are determined for each of the flights. A discussion of an altitude bias error during all of the tracking missions is included. This bias error is defined by utilizing pressure altitude measurements made during survey flights. Four separate filtering methods, representative of the most widely used optimal estimation techniques for enhancement of radar tracking data, are analyzed for suitability in processing both real-time and post-mission data. Additional information regarding the radar and its measurements, including typical noise and bias errors in the range and angle measurements, is also presented. This report is in two parts. This is part 2, a discussion of the modeling of propagation path errors.

James, R.↗

Study of a co-designed decision feedback equalizer, deinterleaver, and decoder

A technique that promises better quality data from band limited channels at lower received power in digital transmission systems is presented. Data transmission, in such systems often suffers from intersymbol interference (ISI) and noise. Two separate techniques, channel coding and equalization, have caused considerable advances in the state of communication systems and both concern themselves with removing the undesired effects of a communication channel. Equalizers mitigate the ISI whereas coding schemes are used to incorporate error-correction. In the past, most of the research in these two areas has been carried out separately. However, the individual techniques have strengths and weaknesses that are complementary in many applications: an integrated approach realizes gains in excess to that of a simple juxtaposition. Coding schemes have been successfully used in cascade with linear equalizers which in the absence of ISI provide excellent performance. However, when both ISI and the noise level are relatively high, nonlinear receivers like the decision feedback equalizer (DFE) perform better. The DFE has its drawbacks: it suffers from error propagation. The technique presented here takes advantage of interleaving to integrate the two approaches so that the error propagation in DFE can be reduced with the help of error correction provided by the decoder. The results of simulations carried out for both, binary, and non-binary, channels confirm that significant gain can be obtained by codesigning equalizer and decoder. Although, systems with time-invariant channels and simple DFE having linear filters were looked into, the technique is fairly general and can easily be modified for more sophisticated equalizers to obtain even larger gains.

Peile, Robert E.↗