Error dynamics and perfect model following with application to flight control
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Anderson, Mark R.↗
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Results for “error models”
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FOCUS - An experimental environment for fault sensitivity analysis
FOCUS, a simulation environment for conducting fault-sensitivity analysis of chip-level designs, is described. The environment can be used to evaluate alternative design tactics at an early design stage. A range of user specified faults is automatically injected at runtime, and their propagation to the chip I/O pins is measured through the gate and higher levels. A number of techniques for fault-sensitivity analysis are proposed and implemented in the FOCUS environment. These include transient impact assessment on latch, pin and functional errors, external pin error distribution due to in-chip transients, charge-level sensitivity analysis, and error propagation models to depict the dynamic behavior of latch errors. A case study of the impact of transient faults on a microprocessor-based jet-engine controller is used to identify the critical fault propagation paths, the module most sensitive to fault propagation, and the module with the highest potential for causing external errors.
Choi, Gwan S.↗
Lander Lighting to Reduce Pilot Approach Errors: Project Design Assumptions & Model Constraints
The south pole lighting environment will have harsh low inclination sunlight, making overhead judgement of surface features difficult. Autonomous solutions are great, however, the need for visual monitoring and independent go/no-go decisions remain. Our project proposes that lunar landing systems will be better served by including a powerful landing light system that improves visibility of surfaces from overhead by illuminating the ground at critical distances for the crew to make last minute decisions regarding an approach.
Toni A. Clark↗
Precision Measurements of the Cluster Red Sequence Using An Error Corrected Gaussian Mixture Model
Abstract Not Provided
Astrophysics,ASTRO↗
A Discrete Error Transport Equation Source Model for Mesh Adaptation.
Abstract not provided.
Franko, Kenneth↗
Ultimate Bifacial Showdown: 75kW Field Results
This work presents one year results for a side-by-side comparison of 5 different bifacial technologies, deployed in a 75-kW single-axis tracked field at Golden, CO. Four PERC (multi and mono) and 1 Silicon Heterojunction manufacturers are represented. Reference strings of equivalent monofacial PV modules are also installed for a direct technology comparison and calculation of bifacial gain. Analysis indicates performance within expectation, with a cumulative model mean error within +/- 2% for both bifacial and monofacial models and cumulative bifacial energy gain between 6-9%. High accuracy string-level DC monitoring and module-level measurements are also presented, showing effects of snow and edge effects in the order of +/- 3% for non-uniform irradiance across the row. Data from a custom-module to measure shading loss from the torque-tube is installed, showing up to 6% irradiance non-uniformity for the month of January.
bifacial field validation↗
Using Direct Error Predictors to Improve Model Safety and Interpretability
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Computer science↗
Modeling tropical Pacific sea surface temperature with satellite-derived solar radiative forcing
Two independent datasets for the solar radiation at the surface derived from satellites are compared. The data derived from the Earth Radiation Budget Experiment (ERBE) is for the net solar radiation at the surface whereas the International Satellite Cloud Climatology Project (ISCCP) data is for the downward flux only and was corrected with a space- and time-varying albedo. The ISCCP net flux is at all times higher than the ERBE flux. The difference can be divided into an offset that decreases with latitude and another component that correlates with high tropical cloud cover. With this latter exception the two datasets provide spatial patterns of solar flux that are very similar. A tropical Pacific Ocean model is forced with these two datasets and observed climatological winds. The upward heat flux is parameterized taking into account separately the longwave radiative, latent, and sensible heat fluxes. Best fit values for the uncertain parameters are found using an optimization procedure that seeks to minimize the difference between model and observed SST by varying the parameters within a reasonable range of uncertainty. The SST field the model produces with the best fit parameters is the best the model can do. If the differences between the model and data are larger than can be accounted for by remaining uncertainties in the heat flux parameterization and forcing data then the ocean model must be held to be at fault. Using this method of analysis, a fundamental model fault is identified. Inadequate treatment of mixed layer/entrainment processes in upwelling regions of the eastern tropical Pacific leads to a large and seasonally varying error in the model SST. Elsewhere the model SST is insufficiently different from observed to be able to identify model errors.
Seager, Richard↗
Atmospheric refractivity corrections in satellite laser ranging
Atmospheric refraction can cause significant errors in satellite laser ranging (SLR) systems. There are two techniques which can be used to correct for these errors. Atmospheric models based upon surface measurements of pressure, temperature, and relative humidity have been shown by ray tracing to be accurate to within a few centimeters at 20 deg elevation angle. The residual errors in the models are thought to be primarily caused by horizontal gradients in the refractivity. Although models have been developed to predict the gradient effects, initial studies show that they can be sensitive to local topographic effects. Atmospheric turbulence can introduce random fluctuations in the refractivity, but only introduces centimeter level errors at elevation angles below 10 deg. Pulsed two-color ranging systems can directly measure the atmospheric delay in satellite ranging. These systems require mode-locked multiple-frequency lasers and streak-camera-based receivers and currently appear capable of measuring the atmospheric delay with an accuracy of 0.5 cm or better.
Abshire, J. B.↗
Characterizing the Impact of Soft Errors Affecting Floating-point ALUs using RTL-level Fault Injection
Strategies to detect, correct, or mitigate the impact of soft errors rely on errors-injection experiments. For efficient evaluation, such experiments typically inject errors in software by sampling errors from a candidate distribution. Most often, these strategies randomly select and flip one bit in the output of an instruction. While single-bit flips might constitute a meaningful model for errors affecting hardware, the appropriateness of this model for software-based errors has not been studied. In this paper, we study the manifestation of errors in the output registers due to errors affecting candidate instructions executed by floating point ALUs. We inject single-bit flips into the RTL descriptions of floating point ALUs and analyze the differences between anticipated and observed outputs when executing floating-point addition, subtraction, multiplication, and division. We choose the operands for these instructions randomly and from operands observed in five benchmarks. We observe a rich distribution of errors in the output and analyze their implications for software-based fault-injection campaigns.
Subasi, Omer↗
Exactly solvable model of light-scattering errors in quantum simulations with metastable trapped-ion qubits
Here, we analytically solve a model for light scattering in Ising dynamics of metastable atomic qubits, generalizing the approach of Foss-Feig et al. to include leakage outside the qubit manifold. We analyze the influence of these fundamental errors in simulations of proposed experiments with metastable levels of 40 Ca + ions in a Penning trap. We find that “effective magnetic fields” generated by leaked qubits have significant impacts on spin-spin correlation functions for Greenberger-Horne-Zeilinger state preparation or for quantum simulations with strong coupling, while spin squeezing uses a much weaker coupling and is largely insensitive to the simulated leakage errors, even with a few hundred ions. Our theory and results are expected to be useful in modeling a variety of metastable qubit experiments in the future.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Uncertainty analysis of correlated parameters in automated reaction mechanism generation
Abstract Uncertainty analysis is a useful tool for inspecting and improving detailed kinetic mechanisms because it can identify the greatest sources of model output error. Owing to the very nonlinear relationship between kinetic and thermodynamic parameters and computed concentrations, model predictions can be extremely sensitive to uncertainties in some parameters while uncertainties in other parameters can be irrelevant. Error propagation becomes even more convoluted in automatically generated kinetic models, where input uncertainties are correlated through kinetic rate rules and thermodynamic group values. Local and global uncertainty analyses were implemented and used to analyze error propagation in Reaction Mechanism Generator (RMG), an open‐source software for generating kinetic models. A framework for automatically assigning parameter uncertainties to estimated thermodynamics and kinetics was created, enabling tracking of correlated uncertainties. Local first‐order uncertainty propagation was implemented using sensitivities computed natively within RMG. Global uncertainty analysis was implemented using adaptive Smolyak pseudospectral approximations as implemented in the MIT Uncertainty Quantification Library to efficiently compute and construct polynomial chaos expansions to approximate the dependence of outputs on a subset of uncertain inputs. Cantera was used as a backend for simulating the reactor system in the global analysis. Analyses were performed for a phenyldodecane pyrolysis model. Local and global methods demonstrated similar trends; however, many uncertainties were significantly overestimated by the local analysis. Both local and global analyses show that correlated uncertainties based on kinetic rate rules and thermochemical groups drastically reduce a model's degrees of freedom and have a large impact on the determination of the most influential input parameters. These results highlight the necessity of incorporating uncertainty analysis in the mechanism generation workflow.
Gao, Connie W.↗
A model study of potential sampling errors due to data scatter around expendable bathythermograph transects in the tropical Pacific
A linear multiple vertical-mode model described by McPhaden et al. (1988) is used to examine potential errors due to data scatter around expendable bathythermograph (XBT) transects in the tropical Pacific. Two methods of sampling are compared. In the first, the model was sampled along approximately straight lines of grid points corresponding to the mean positions of XBT tracks in the eastern, central, and western Pacific; in the second, the model was sampled again at the dates and locations of actual XTB casts for 1979-1983. The model indicates that the data scattered zonally around XBT transects in general can lead to about 2 dyn cm error in dynamic height in composite sections of XBT data. Errors larger than 2 dyn cm occurred in regions where XBT sample spacing in the zonal direction was insufficient to resolve Rossby wave variations in the model.
Mcphaden, Michael J.↗
Verification of optical modelling of sunshape and surface slope error for concentrating solar power systems
Sunshape and reflector surface slope error distributions are significant elements in modelling the optical behaviour of a concentrating solar power system. Different optical modelling tools implement these elements with various approaches. Discrepancies can easily accumulate in simulations of a large optical system as a result of incorrect implementations. This study reviews and verifies the implementations of these two factors in six tools that are widely used for optical modelling in solar energy research: Tonatiuh, SolTrace, Tracer, Solstice, Heliosim and SolarPILOT. The review incorporates three rounds of tests. Firstly, basic tests examine each factor carefully in simplified on-axis reflector-target configurations (round 'A'). Secondly, off-axis effects are introduced (round 'B'). Thirdly, full heliostat field simulations are verified (round 'C'). All of the test cases are simulated with each modelling tool, and results are compared. Discrepancies were observed due to approximations inherent in the cone optics (convolution) methods, incorrect implementation the of pillbox slope errors, different approaches to setting the circumsolar ratio for the Buie sunshape, and different approaches to the calculation of blocking and shading losses in some tools. All issues are discussed fully, and solutions to most issues were implemented within the scope of the present study. Some remaining issues are noted. The study highlights the importance of careful implementation of these aspects of optical modelling and contributes to an improvement in the quality of several widely-used tools.
14 SOLAR ENERGY↗
Organic Photovoltaic Efficiency Predictor: Data-Driven Models for Non-Fullerene Acceptor Organic Solar Cells
In the design of organic solar cells, there has been a need for materials with high power conversion efficiencies. Scharber’s model is commonly used to predict efficiency; however, it exhibits poor performance with new non-fullerene acceptor (NFA) devices, since it was designed for fullerene-based devices. In this work, an empirical model is proposed that can be a more accurate alternative for NFA organic solar cells. Additionally, many screening studies use computationally expensive methods. A model based on using semiempirical simplified time-dependent density functional theory (sTD-DFT) as an alternative method can accelerate the calculations and yield a similar accuracy. The models presented in this paper, termed organic photovoltaic efficiency predictor (OPEP) models, have shown significantly lower errors than previous models, with OPEP/B3LYP yielding errors of 1.53% and OPEP/sTD- DFT of 1.55%. As a result, the proposed computational models can be used for the fast and accurate screening of new high-efficiency NFAs/donor pairs.
14 SOLAR ENERGY↗
Results from a Sting Whip Correction Verification Test at the Langley 16-Foot Transonic Tunnel
In recent years, great strides have been made toward correcting the largest error in inertial Angle of Attack (AoA) measurements in wind tunnel models. This error source is commonly referred to as 'sting whip' and is caused by aerodynamically induced forces imparting dynamics on sting-mounted models. These aerodynamic forces cause the model to whip through an arc section in the pitch and/or yaw planes, thus generating a centrifugal acceleration and creating a bias error in the AoA measurement. It has been shown that, under certain conditions, this induced AoA error can be greater than one third of a degree. An error of this magnitude far exceeds the target AoA goal of 0.01 deg established at NASA Langley Research Center (LaRC) and elsewhere. New sting whip correction techniques being developed at LaRC are able to measure and reduce this sting whip error by an order of magnitude. With this increase of accuracy, the 0.01 deg AoA target is achievable under all but the most severe conditions.
Crawford, B. L.↗
Modeling Ring Current Proton Fluxes Using Artificial Neural Network and Van Allen Probe Measurements
Abstract Terrestrial ring current dynamics are a critical part of the near‐space environment, in that they directly drive geomagnetic field variations that control particle drifts, and define geomagnetic storms. The present study aims to specify a global and time‐varying distribution of ring current proton using geomagnetic indices and solar wind parameters with their history as input. We train an artificial neural network (ANN) model to reproduce proton fluxes measured by the Radiation Belt Storm Probes Ion Composition Experiment instrument onboard Van Allen Probes. By choosing optimal feature parameters and their history length, the model results show a high correlation and a small error between model specifications and satellite measurements. The modeled results well capture energy‐dependent proton dynamics in association with geomagnetic storms, including inward radial diffusion, acceleration and decay. Our ANN model produces proton fluxes with their corresponding 3D spatiotemporal variations, capturing the latitudinal distribution and local time asymmetry that are consistent with observations and that can further inform theory.
Li, Jinxing↗