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At least 487 records · Page 27

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NASA NTRS2009

Simulating and Detecting Radiation-Induced Errors for Onboard Machine Learning

Spacecraft processors and memory are subjected to high radiation doses and therefore employ radiation-hardened components. However, these components are orders of magnitude more expensive than typical desktop components, and they lag years behind in terms of speed and size. We have integrated algorithm-based fault tolerance (ABFT) methods into onboard data analysis algorithms to detect radiation-induced errors, which ultimately may permit the use of spacecraft memory that need not be fully hardened, reducing cost and increasing capability at the same time. We have also developed a lightweight software radiation simulator, BITFLIPS, that permits evaluation of error detection strategies in a controlled fashion, including the specification of the radiation rate and selective exposure of individual data structures. Using BITFLIPS, we evaluated our error detection methods when using a support vector machine to analyze data collected by the Mars Odyssey spacecraft. We found ABFT error detection for matrix multiplication is very successful, while error detection for Gaussian kernel computation still has room for improvement.

data analysis↗

NASA NTRS2015

Radiative Flux and Forcing Parameterization Error in Aerosol-Free Clear Skies

This article reports on the accuracy in aerosol- and cloud-free conditions of the radiation parameterizations used in climate models. Accuracy is assessed relative to observationally validated reference models for fluxes under present-day conditions and forcing (flux changes) from quadrupled concentrations of carbon dioxide. Agreement among reference models is typically within 1 W/m2, while parameterized calculations are roughly half as accurate in the longwave and even less accurate, and more variable, in the shortwave. Absorption of shortwave radiation is underestimated by most parameterizations in the present day and has relatively large errors in forcing. Error in present-day conditions is essentially unrelated to error in forcing calculations. Recent revisions to parameterizations have reduced error in most cases. A dependence on atmospheric conditions, including integrated water vapor, means that global estimates of parameterization error relevant for the radiative forcing of climate change will require much more ambitious calculations.

Climate↗

NASA NTRS2016

Characterizing background error with the NASA GMAO OSSE

Understanding the characteristics of background error is vital to the design and performance of data assimilation systems. However, the true state of the atmosphere is unknown, and qualitative determination of background error is thus a challenge. We present an exploration of background error characteristics using the NASA Global Modeling and Assimilation Office Observing System Simulation Experiment framework, where the presence of the Nature Run allows direct calculation of the background error. The behavior of the data assimilation system (DAS) can be compared with the character of the background error, and performance of the DAS will be investigated in a series of both idealized and realistic experiments.

Nature Run↗

NASA NTRS2015

Effect of DM Actuator Errors on the WFIRST/AFTA Coronagraph Contrast Performance

The WFIRST/AFTA 2.4 m space telescope currently under study includes a stellar coronagraph for the imaging and the spectral characterization of extrasolar planets. The coronagraph employs two sequential deformable mirrors (DMs) to compensate for phase and amplitude errors in creating dark holes. DMs are critical elements in high contrast coronagraphs, requiring precision and stability measured in picometers to enable detection of Earth-like exoplanets. Working with a low-order wavefront-sensor the DM that is conjugate to a pupil can also be used to correct low-order wavefront drift during a scientific observation. However, not all actuators in a DM have the same gain. When using such a DM in low-order wavefront sensing and control subsystem, the actuator gain errors introduce high-spatial frequency errors to the DM surface and thus worsen the contrast performance of the coronagraph. We have investigated the effects of actuator gain errors and the actuator command digitization errors on the contrast performance of the coronagraph through modeling and simulations, and will present our results in this paper.

adaptive optics↗

NASA NTRS2018

Combined Error and Uncertainty Estimates for CFD Problems

Given input sources of uncertainty, non-intrusive uncertainty propagation methods quantify the uncertainty in output quantities of interest (QoI) by performing a nite number of CFD (Computational Fluid Dynamics) instance realizations needed in the calculation of output statistics. It is well known that this introduces multiple sources of error. CFD codes often utilize finite-dimensional approximation (grids, basis functions, etc.) thus incurring CFD numerical errors often approximately reinterpreted as a statistical bias. Uncertainty propagation methods calculate uncertainty statistics for output quantities of interest using a numerical method (e.g. deterministic quadrature, sampling, etc.) thus incurring UQ (Uncertainty Quantification) numerical errors. Importance of quantifying these errors in large scale scientific computing: How accurate is an output statistic?; How should additional computational resources be invested to further reduce the error in a statistic?

Posteriori↗

NASA NTRS2018

Spatial Representativeness Error in the Ground-Level Observation Networks for Black Carbon Radiation Absorption

There is high uncertainty in the direct radiative forcing of black carbon (BC), an aerosol that strongly absorbs solar radiation. The observation-constrained estimate, which is several times larger than the bottom-up estimate, is influenced by the spatial representativeness error due to the mesoscale inhomogeneity of the aerosol fields and the relatively low resolution of global chemistry-transport models. Here we evaluated the spatial representativeness error for two widely used observational networks (AErosol RObotic NETwork and Global Atmosphere Watch) by downscaling the geospatial grid in a global model of BC aerosol absorption optical depth to 0.1° × 0.1°. Comparing the models at a spatial resolution of 2° × 2° with BC aerosol absorption at AErosol RObotic NETwork sites (which are commonly located near emission hot spots) tends to cause a global spatial representativeness error of 30%, as a positive bias for the current top-down estimate of global BC direct radiative forcing. By contrast, the global spatial representativeness error will be 7% for the Global Atmosphere Watch network, because the sites are located in such a way that there are almost an equal number of sites with positive or negative representativeness error.

Wang, Rong↗

NASA NTRS2018

Introduction to CAUSES: Description of Weather and Climate Models and Their Near‐Surface Temperature Errors in 5 Day Hindcasts near the Southern Great Plains

We introduce the Clouds Above the United States and Errors at the Surface (CAUSES) project with its aim of better understanding the physical processes leading to warm screen temperature biases over the American Midwest in many numerical models. In this first of four companion papers, 11 different models, from nine institutes, perform a series of 5 day hindcasts, each initialized from reanalyses. After describing the common experimental protocol and detailing each model configuration, a gridded temperature data set is derived from observations and used to show that all the models have a warm bias over parts of the Midwest. Additionally, a strong diurnal cycle in the screen temperature bias is found in most models. In some models the bias is largest around midday, while in others it is largest during the night. At the Department of Energy Atmospheric Radiation Measurement Southern Great Plains (SGP) site, the model biases are shown to extend several kilometers into the atmosphere. Finally, to provide context for the companion papers, in which observations from the SGP site are used to evaluate the different processes contributing to errors there, it is shown that there are numerous locations across the Midwest where the diurnal cycle of the error is highly correlated with the diurnal cycle of the error at SGP. This suggests that conclusions drawn from detailed evaluation of models using instruments located at SGP will be representative of errors that are prevalent over a larger spatial scale.

Morcrette, C. J.↗

NASA NTRS2019

Polar Coding For Forward Error Correction In Space Communications With LDPC Comparisons

With the surging development of optical telecommunicationsfor space applications, the importance of errorcorrection has become more apparent than ever. Specifically,the exploration of forward error correction code (FEC) methodologieswill be instrumental in developing the standards foroptical communications in space. Despite the widespread useof low-density parity-check (LDPC) codes, alternate FEC codessuch as polar codes have shown immense promise in assistingspace communications error correction with their ability tobypass the error floors that plague LDPC codes. Extremelypromising techniques including cyclic redundancy checks (CRC),successive cancellation (SC), and successive cancellation lists(SCL) that assist polar coding in achieving the Shannon limitin a timely manner are evaluated. MATLAB simulations areconducted with AWGN and burst noise to test each technique'sability to handle noise typically encountered in space and eachtechnique's ability to correct unexpected errors. Results ofsimulations for different rates and message lengths are alsoreported to determine each technique's ability to handle largedata volumes and fix errors. Similar simulations are conductedfor LDPC codes with additional tests for convolutional and nointerleavers. Finally, a discussion regarding the future ability ofpolar codes to satisfy current missions in the place of, or inconjunction with, LDPC codes along with the merits of eachFEC technique's ability to process data efficiently and handledata while maintaining adequate performance will be provided.Preliminary recommendations will be made for each technique'seffectiveness for GEO related missions along with discussionsregarding each technique's ability to fit within the CCSDS standards for optical communications.

Polar Coding↗

NASA NTRS2004

Scientific impacts of wind direction errors

An assessment on the scientific impact of random errors in wind direction (< 45°) retrieved from space-based observations under weak wind (< 7 m/s) conditions was made. Half of the winds over global oceans are below 7 m/s, in their long-term averages, and these weak winds cover most of the tropical, sub-tropical, and coastal oceans. Introduction of these errors in the semi-daily winds causes, on average, 5% changes of the yearly mean Ekman and Sverdrup volume transports computed directly from the winds, respectively. These poleward movements of water are the main mechanisms to redistribute heat from the warmer tropical region to the colder highlatitude regions, and they are the major manifestations of the ocean’s function in modifying Earth’s climate. Simulation by an ocean general circulation model shows that the wind errors introduce a 5% error in the meridional heat transport at tropical latitudes. The simulation also shows that the erroneous winds cause a pile-up of warm surface water in the eastern tropical Pacific, similar to the conditions during El Niño episode. Similar wind directional errors cause significant change in sea-surface temperature and sea-level patterns in coastal oceans in a coastal model simulation. Previous studies have shown that assimilation of scatterometer winds improves 3–5 day weather forecasts in the Southern Hemisphere. When directional information below 7 m/s was withheld, approximately 40% of the improvement was lost.

Atlas, Robert↗

NASA NTRSDate not supplied

Goal-Oriented Discretization Error Control in Coupled Nearfield-Farfield Low-Boom Simulations

The method of adjoint weighted residuals is used to determine the level of discretization error in loudness predictions of sonic booms on the ground. We analyze the standard nearfied-farfield domain decomposition approach. In the nearfield domain, the three-dimensional Euler equations are solved to obtain a pressure signature generated by the aircraft. In the farfield, this waveform is propagated through the atmosphere to the ground by solving the augmented Burgers’ equation. Loudness is characterized using weighted sound-exposure-level metrics. We formulate discretization error estimates for the ground signature and loudness metrics for this one-way coupled system. Although the nearfield solution is independent of the farfield, the adjoint formulation for the coupled system provides feedback from the farfield to identify high-error regions in the nearfield. The results demonstrate that the discrete adjoint implementation is asymptotically consistent and provides reliable error estimates. Furthermore, we show how the error can be controlled through adaptive refinement of the nearfield mesh. The approach is evaluated on two- and three-dimensional problems, including the X-59 flight demonstration aircraft.

CST↗

NASA NTRSDate not supplied

Systematic Errors in Simulated L-Band Brightness Temperature in the SMAP Level-4 Soil Moisture Analysis

The NASA Soil Moisture Active Passive (SMAP) mission has been providing L-band (1.4 GHz) brightness temperature (Tb) observations since April 2015. By assimilating the Tb observations into the NASA Catchment land surface model using a spatially distributed ensemble Kalman filter (EnKF), the SMAP Level-4 Soil Moisture (L4_SM) product provides global, 3-hourly, 9-km resolution estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture with ~2.5-day latency for use in research and applications. The EnKF-based L4_SM analysis assumes unbiased forecast errors. Consequently, the seasonally varying bias between the model forecast Tb and the observed values is removed prior to the assimilation of the SMAP Tb observations. The L4_SM system is thus designed to only correct errors in synoptic-scale and interannual variations from the long-term mean seasonal cycle while maintaining the model’s (possibly wrong) climatology. In this paper, we examine the Tb observation-minus-forecast (O-F) residuals from the L4_SM Version 7 product (computed after rescaling the Tb observations to the mean seasonal cycle of the simulated Tb). The long-term average of the Tb O-F residuals has a global mean of only 0.13 K and locally small values, ranging from -1 to 3 K. The model forecast Tb, however, still exhibits undesirable systematic errors relative to the (rescaled) Tb observations. At some locations, the time-average Tb O-F values strongly depend on surface soil moisture (SM). At the Yanco SMAP core validation site, for example, the Tb O-F residuals typically range from 5 to 15 K under dry soil moisture conditions (SM < 0.15 m3 m-3) yet are predominantly negative under wet soil moisture conditions (SM > 0.25 m3 m-3), with values ranging from 0 to -40 K. This results in soil moisture analysis increments that persistently make the soil drier under dry SM conditions and persistently make the soil wetter under wet SM conditions, suggesting an error in the dynamic range of the simulated Tb, soil moisture or soil temperature. In this paper, we describe the higher-order systematic Tb forecast errors in more detail, examine their impact on the L4_SM product quality, and explore potential avenues to improve the L4_SM algorithm.

Rolf Reichle↗

NASA NTRSDate not supplied

Discretization Error Estimation and Control for Farfield Acoustic Signatures

We investigate the utility of adjoint-based error estimates for sonic boom farfield simulations governed by solutions of the augmented Burgers’ equation. Solution of this nonlinear system uses operator splitting with a second-order finite volume discretization in space and second-order Runge-Kutta time marching, while the absorption and molecular relaxation are solved using second-order central differencing. The discretization error in selected ground sonic boom cost functionals is estimated using the method of adjoint-weighted residuals. Key elements of the implementation process are emphasized with details provided on the practical aspects as appliedto the sonic boom farfield propagation. We establish the accuracy of the adjoint solutions usingcomplex step and finite difference approaches, and examine the accuracy of the error estimates using analytical N-wave solutions. We then apply it to a pressure waveform corresponding to the X-59 research aircraft. The investigations demonstrate that the method of adjoint-weighted residuals accurately predicts the level of discretization error present in sonic boom farfield simulations while offering insight into which features of the near field signal are the primary drivers of ground noise metrics. The numerical results indicate that at sampling frequencies as low as50kHz, discretization error in the propagation is under 0.01 dB[A] for realistically complex examples.

CST↗

NASA NTRS2011

Effects of Correlated Errors on the Analysis of Space Geodetic Data

As thermal errors are reduced instrumental and troposphere correlated errors will increasingly become more important. Work in progress shows that troposphere covariance error models improve data analysis results. We expect to see stronger effects with higher data rates. Temperature modeling of delay errors may further reduce temporal correlations in the data.

thermal errors↗

DOE OSTI2025

Error field measurements and correction on MUSE permanent magnet stellarator

The magnetic field topology and error fields are measured in the MUSE permanent magnet stellarator with an electron beam and fluorescent rod. The effective magnetization of the magnets is determined by measuring rational flux surface locations. Electron magnetic drift effects must be considered self-consistently due to the small magnetic shear on MUSE. Error fields are characterized by flux surface shape deviation and magnetic island chain width and phase. Error fields are then corrected by adjusting the permanent magnet (PM) holders as rigid bodies. Resonant error fields are on the order of or smaller than 3 x 10 -6 of the toroidal field after correction and surface shape matches well with the design. Resonant components of the quasi-symmetry deviation are estimated, using a novel magnetic drift measurement, to be in the 10 −4 range. The PM approach is validated as a low-cost and precise way to build optimized stellarators.

electron beam mapping↗

DOE OSTI2024

Behavior and mechanisms of Doppler wind lidar error in complex terrain: stable flow case study at Perdigão

A numerical experiment is carried out investigating the magnitude of biases in ground-based lidar measurements in complex flow conditions. Biases assessed include those arising from flow curvature and from the interaction of turbulence with the wind field reconstruction (WFR) algorithms used by a WindCube lidars and anemometers. RANS-CFD and WRF-LES simulations were performed for the Perdig˜ao Field Experiment site for a range of atmospheric conditions. Virtual anemometer and lidar data were generated for four locations: two near exposed ridge tops and two in low-speed regions in the valley. The LES data at these four locations show that the scalar inflation terms (the relation between scalar and vector averaged wind speed) for virtual lidar and virtual cups agree very well with predictions using perturbation theory. While the lidar errors vary greatly with location and height, the contribution from the flow curvature tends to be larger than the differences arising from scalar inflation. For one lidar/mast pair near the ridge top, comparisons between simulations and measurements are carried out for a resonant mountain wave event on June 14th, 2017, and for the whole duration of the Perdigão campaign for winds perpendicular to the ridges. The lidar error during the mountain wave, a period of strong stability and low inversion height, is significantly larger than the campaign average. The sensitivity of the lidar error to atmospheric stability is confirmed by the RANS simulations, which suggests strong sensitivity of flow curvature error to stability conditions and to the shape of the wind speed profile near the top of the boundary layer.

17 WIND ENERGY↗

DOE OSTI2024

Single-shot quantum error correction in intertwined toric codes

We construct a subsystem code in three dimensions that exhibits single-shot error correction in a user-friendly and transparent way. As this code is a subsystem version of coupled toric codes, we call it the intertwined toric code (ITC). Although previous codes share the property of single-shot error correction, the ITC is distinguished by its physically motivated origin, geometrically straightforward logical operators and errors, and a simple phase diagram. The code arises from three-dimensional (3D) stabilizer toric codes in a way that emphasizes the physical origin of the single-shot property. In particular, starting with two copies of the 3D toric code, we add check operators that provide for the confinement of pointlike excitations without condensing the loop excitations. Geometrically, the bare and dressed logical operators in the ITC derive from logical operators in the underlying toric codes, creating a clear relationship between errors and measurement outcomes. The syndromes of the ITC resemble the syndromes of the single-shot code by Kubica and Vasmer, allowing us to use their decoding schemes. We also extract the phase diagram corresponding to ITC and show that it contains the phases found in the Kubica-Vasmer code. Lastly, we suggest various connections to Walker-Wang models and measurement-based quantum computation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Quantum error thresholds for gauge-redundant digitizations of lattice field theories

In the quantum simulation of lattice gauge theories, gauge symmetry can be either fixed or encoded as a redundancy of the Hilbert space. While gauge-fixing reduces the number of qubits, keeping the gauge redundancy can provide code space to mitigate and correct quantum errors by checking and restoring Gauss’s law. In this work, we consider the correctable errors for generic finite gauge groups and design the quantum circuits to detect and correct them. We calculate the error thresholds below which the gauge-redundant digitization with Gauss’s law error correction has better fidelity than the gauge-fixed digitization involving only gauge-invariant states. Our results provide guidance for fault-tolerant quantum simulations of lattice gauge theories. Published by the American Physical Society 2024

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Estimating the Contributions to Human Error Probability from the Convolution of the Distribution of Time Available and Time Required

As part of their duties, Human Reliability Analysis must often evaluate if crews in nuclear power plants (NPPs) can complete tasks associated with a human-failure event within time limits. For example, the time required in NPP scenarios is determined by systematic and structured walkthroughs, feasibility studies, recorded times from training exercises, and interviews with experienced operators and experts. Typically, a point estimate is derived for the estimate (mean, maximum, or 95th percentile of time required). Using point-estimate values can mask the risk associated with variability among crews, plant conditions and set-up, environmental conditions, and other impact factors under which these actions are executed. While point estimates for time required and time available have served the industry well, without considering the uncertainty they could lead to biased understanding about the risk. The Integrated Human Event Analysis System - General Methodology (IDHEAS-G) model (developed by the US Nuclear Regulatory Commission, NRC) for human error probability calculates human error probability by summing two probabilities: insufficient time and cognitive error. As such, the model takes a more holistic approach by considering the full distributions for time required and time available to calculate the human error probability because the time available to complete the task is insufficient. In this study, we expand on the work of the NRC and discuss methods for estimating these time considerations. For example, for the time required, the impact of Performance Influencing Factors (PIFs) on the distribution was divided into impacts that are aleatory in nature, such as crew-to-crew variability, and those that are epistemic (i.e., the PIFs). Starting with the factors that introduce aleatory uncertainty, a first-order distribution was developed from a large set of time required (i.e., NPP task completion times) data for the range of operator actions that occur in the NPP control room under simulated accident conditions. The first-order distribution can then be adjusted to account for epistemic uncertainty using research associated with the impact of applicable PIFs on the time required. We also develop guidance for analysts to address the probability distributions for the time available. The guidance we developed on how to estimate time required and time available distributions is based on the identification of pertinent research and data, data analyses, and expert knowledge elicitation.

human error probability, human performance, time e↗