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Results for “error bound”

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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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Galileo EM-2 contributions to the lunar control network

A local control network is being developed using Galileo images that cover the region north of the Apollo area and lie between 10 and 100 degrees east longitude. This network is tied to the Apollo control network and will have a positional accuracy of approximately 500-1500 m. This region has been photographed by Earth-based telescopes and the Mariner 10 and Lunar Orbiter spacecraft, but the Gallileo images are preferred for control because of their superior viewing angles, resolution, and Galileo's geometrically stable sensor. Based on Davies et al., 1987, the potential accuracy of the near-side Apollo network is estimated to be between 50 and 300 m. The laser ranging retroreflector locations at the Apollo 11, 14, and 15 sites and the Lunikhod 2 site have been determined with an accuracy of about 10 m. The locations of the ALSEP transmitters relative to the retroreflectors have also been measured. These known coordinates are used to estimate errors in the Apollo network. The telescopic control is approximately bounded by 75 degrees north and south latitude and 75 degrees east and west longitudes. The accuracy of the telescopic network is thought to be about one to two km. Thus, the Galileo network might improve coordinates in the telescopic area as well as north and east of it.

Davies, M. E.↗
DOE OSTI2022

Evaluation of dynamic testing of full-scale wind turbine drivetrains with hardware-in-the-loop

Dynamometer testing of full-scale wind turbine drivetrains involves subjecting integrated components to extreme static loads, fatigue loads, or dynamic loads to replicate field conditions. This paper provides a detailed evaluation of the uncertainty and errors in applied loads and measured responses, and their magnitude relative to established repeatability bounds for a drivetrain subjected to static and dynamic loads on the 7.5 MW test bench at the Clemson University Wind Turbine Drivetrain Testing Facility. An ideal drivetrain simulation model is utilized to isolate the influence of load tracking errors on test article responses. It is shown that the test article response variations are mainly driven by run out and clearances inherent to the drivetrain. For the dynamic profiles, the load tracking errors are within acceptable limits. Furthermore, a frequency analysis is used to show that the test bench controller tracking performance is acceptable for profiles with frequency content up to 1.5 Hz.

17 WIND ENERGY↗
DOE OSTI2025

A new upper bound for the growth factor in Gaussian elimination with complete pivoting

Abstract The growth factor in Gaussian elimination measures how large the entries of an LU factorization can be relative to the entries of the original matrix. It is a key parameter in error estimates, and one of the most fundamental topics in numerical analysis. We produce an upper bound of for the growth factor in Gaussian elimination with complete pivoting — the first improvement upon Wilkinson's original 1961 bound of .

Bisain, Ankit [Department of Mathematics Massachus↗
DOE OSTI2022

Characterizing the Reproducibility of Noisy Quantum Circuits

The ability of a quantum computer to reproduce or replicate the results of a quantum circuit is a key concern for verifying and validating applications of quantum computing. Statistical variations in circuit outcomes that arise from ill-characterized fluctuations in device noise may lead to computational errors and irreproducible results. While device characterization offers a direct assessment of noise, an outstanding concern is how such metrics bound the reproducibility of a given quantum circuit. Here, we first directly assess the reproducibility of a noisy quantum circuit, in terms of the Hellinger distance between the computational results, and then we show that device characterization offers an analytic bound on the observed variability. We validate the method using an ensemble of single qubit test circuits, executed on a superconducting transmon processor with well-characterized readout and gate error rates. The resulting description for circuit reproducibility, in terms of a composite device parameter, is confirmed to define an upper bound on the observed Hellinger distance, across the variable test circuits. This predictive correlation between circuit outcomes and device characterization offers an efficient method for assessing the reproducibility of noisy quantum circuits.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Benchmarking quantum logic operations relative to thresholds for fault tolerance

Contemporary methods for benchmarking noisy quantum processors typically measure average error rates or process infidelities. However, thresholds for fault-tolerant quantum error correction are given in terms of worst-case error rates—defined via the diamond norm—which can differ from average error rates by orders of magnitude. One method for resolving this discrepancy is to randomize the physical implementation of quantum gates, using techniques like randomized compiling (RC). In this work, we use gate set tomography to perform precision characterization of a set of two-qubit logic gates to study RC on a superconducting quantum processor. We find that, under RC, gate errors are accurately described by a stochastic Pauli noise model without coherent errors, and that spatially correlated coherent errors and non-Markovian errors are strongly suppressed. We further show that the average and worst-case error rates are equal for randomly compiled gates, and measure a maximum worst-case error of 0.0197(3) for our gate set. Our results show that randomized benchmarks are a viable route to both verifying that a quantum processor’s error rates are below a fault-tolerance threshold, and to bounding the failure rates of near-term algorithms, if—and only if—gates are implemented via randomization methods which tailor noise.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1977

Retransmission error control with memory

In this paper, an error control technique that is a basic improvement over automatic-repeat-request ARQ is presented. Erroneously received blocks in an ARQ system are used for error control. The technique is termed ARQ-with-memory (MRQ). The general MRQ system is described, and simple upper and lower bounds are derived on the throughput achievable by MRQ. The performance of MRQ with respect to throughput, message delay and probability of error is compared to that of ARQ by simulating both systems using error data from a VHF satellite channel being operated in the ALOHA packet broadcasting mode.

Sindhu, P. S.↗
NASA NTRS1977

Flight-test measurements of ground effect - STOL airplanes

Powered-lift STOL aircraft exhibit special aerodynamic characteristics that necessitate changes in established procedures of flight testing. Methods used in ground-effect flight testing of STOL-configured aircraft are described, with special emphasis on results obtained from tests of the YC-15 AMST prototype aircraft. Ground effect on lift and on drag is theoretically analyzed in terms of trailing vortices, bound vortex, and flight-path angle. Airspeed static source position errors are induced by ground constraint and must be considered in the data reduction. Flight-test results show a positive lift increment due to ground proximity.

Parks, E. K.↗
NASA NTRS1982

Reassessment of net radiation measurements in the atmosphere of Venus

An analysis was performed of the possible error mechanisms which degraded the IR net flux measurements made by the three small atmospheric probes dispatched from the Pioneer Venus spacecraft. The larger errors began below 30 km, and caused the data to be inconsistent with previous estimates of the atmospheric opacity. Evaluations were made of the possible radiation field perturbations behind each probe, cloud particle deposition on the sensor windows, and thermal disturbances within the sensors because of gas flow through the window retainers. The gas flow through the retainers was identified as the most likely error source, and was demonstrated in laboratory tests. A strong Reynolds number dependence was also found. Radiative transfer calculations were performed to account for the errors, using the constraints defined by the tests. Upper and lower bounds were calculated for the true net flux for both day and night conditions.

Revercomb, H. E.↗
NASA NTRS1985

New short constraint length, rate 1/N convolutional codes which minimize the required SNR for given desired bit error rates

It is pointed out that for a convolutional coding system, the Bit Error Rate (BER) at the Viterbi decoder output is upper-bounded by the transfer function bound. A large number of rate 1/N convolutional codes have been reported. The criteria used for determining the quality of a code in code search procedures, however, may not be very suited for cases in which the required BER is in the moderate range. For this reason, it may be best to select the code with the aim to minimize the required SNR for a given disired BER. Partial code searching techniques are presented, and a table listing the code search results is provided.

Lee, P. J.↗
NASA NTRS2012

Uncertainty Quantification for Polynomial Systems via Bernstein Expansions

This paper presents a unifying framework to uncertainty quantification for systems having polynomial response metrics that depend on both aleatory and epistemic uncertainties. The approach proposed, which is based on the Bernstein expansions of polynomials, enables bounding the range of moments and failure probabilities of response metrics as well as finding supersets of the extreme epistemic realizations where the limits of such ranges occur. These bounds and supersets, whose analytical structure renders them free of approximation error, can be made arbitrarily tight with additional computational effort. Furthermore, this framework enables determining the importance of particular uncertain parameters according to the extent to which they affect the first two moments of response metrics and failure probabilities. This analysis enables determining the parameters that should be considered uncertain as well as those that can be assumed to be constants without incurring significant error. The analytical nature of the approach eliminates the numerical error that characterizes the sampling-based techniques commonly used to propagate aleatory uncertainties as well as the possibility of under predicting the range of the statistic of interest that may result from searching for the best- and worstcase epistemic values via nonlinear optimization or sampling.

Crespo, Luis G.↗
NASA NTRS2013

Powered Descent Guidance with General Thrust-Pointing Constraints

The Powered Descent Guidance (PDG) algorithm and software for generating Mars pinpoint or precision landing guidance profiles has been enhanced to incorporate thrust-pointing constraints. Pointing constraints would typically be needed for onboard sensor and navigation systems that have specific field-of-view requirements to generate valid ground proximity and terrain-relative state measurements. The original PDG algorithm was designed to enforce both control and state constraints, including maximum and minimum thrust bounds, avoidance of the ground or descent within a glide slope cone, and maximum speed limits. The thrust-bound and thrust-pointing constraints within PDG are non-convex, which in general requires nonlinear optimization methods to generate solutions. The short duration of Mars powered descent requires guaranteed PDG convergence to a solution within a finite time; however, nonlinear optimization methods have no guarantees of convergence to the global optimal or convergence within finite computation time. A lossless convexification developed for the original PDG algorithm relaxed the non-convex thrust bound constraints. This relaxation was theoretically proven to provide valid and optimal solutions for the original, non-convex problem within a convex framework. As with the thrust bound constraint, a relaxation of the thrust-pointing constraint also provides a lossless convexification that ensures the enhanced relaxed PDG algorithm remains convex and retains validity for the original nonconvex problem. The enhanced PDG algorithm provides guidance profiles for pinpoint and precision landing that minimize fuel usage, minimize landing error to the target, and ensure satisfaction of all position and control constraints, including thrust bounds and now thrust-pointing constraints.

Carson, John M., III↗
NASA NTRS1987

Cyclic unequal error protection codes constructed from cyclic codes of composite length

The distance structure of cyclic codes of composite length was investigated. A lower bound on the minimum distance for this class of codes is derived. In many cases, the lower bound gives the true minimum distance of a code. Then the distance structure of the direct sum of two cyclic codes of composite length were investigated. It was shown that, under certain conditions, the direct-sum code provides two levels of error correcting capability, and hence is a two-level unequal error protection (UEP) code. Finally, a class of two-level UEP cyclic direct-sum codes and a decoding algorithm for a subclass of these codes are presented.

Lin, Shu↗
DOE OSTI2021

Uncertainty bounds for multivariate machine learning predictions on high-strain brittle fracture

Simulation of the crack network evolution on high strain rate impact experiments performed in brittle materials is very compute-intensive. The cost increases even more if multiple simulations are needed to account for the randomness in crack length, location, and orientation, which is inherently found in real-world materials. Constructing a machine learning emulator can make the process faster by orders of magnitude. There has been little work, however, on assessing the error associated with their predictions. Estimating these errors is imperative for meaningful overall uncertainty quantification. In this work, we extend the heteroscedastic uncertainty estimates to bound a multiple output machine learning emulator. Overall, we find that the response prediction is accurate within its predicted errors, but with a somewhat conservative estimate of uncertainty.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Multi-parametric analysis for mixed integer linear programming: An application to transmission upgrade and congestion management

Upgrading the capacity of existing transmission lines is essential for meeting the growing energy demands, facilitating the integration of renewable energy, and ensuring the security of the transmission system. This study focuses on the selection of lines whose capacities and by how much should be expanded from the perspective of the Independent System Operators (ISOs) to minimize the total system cost. We employ advanced multi-parametric programming and an enhanced branch-and-bound algorithm to address complex mixed-integer linear programming (MILP) problems, considering multi-period time constraints and physical limitations of generators and transmission lines. To characterize the various decisions in transmission expansion, we model the increased capacity of existing lines as parameters within a specified range. This study first relaxes the binary variables to continuous variables and applies the Lagrange method and Karush-Kuhn-Tucker (KKT) conditions to obtain optimal solutions and identify critical regions associated with active and inactive constraints. Moreover, we extend the traditional branch-and-bound (B&B) method by determining the problem’s upper and lower bounds at each node of the B&B decision tree, helping to manage computational challenges in large-scale MILP problems. Here, we compare the difference between the upper and lower bounds to obtain an approximate optimal solution within the decision-makers’ tolerable error range. In addition, the first derivative of the objective function on the parameters of each line is used to inform the selection of lines for easing congestion and maximizing social welfare. Finally, the capacity upgrades are selected by weighing the reductions in system costs against the expense of upgrading line capacities. The findings are supported by numerical simulations and provide transmission-line planners with decision-making guidance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Enhancing quantum clocks and sensors with randomization and decoherence

This letter shows how incoherent dynamics can lead to metrological advantages in quantum sensing. The results rely on the fact that incoherent dynamics lead to an additive contribution to the quantum Fisher information about time. Such an additive contribution can reduce the error of optimal estimation protocols, as implied by the quantum Cramér–Rao bound. I characterize regimes in which the estimation of a time interval or a frequency is enhanced by decoherence, thereby identifying cases in which incoherent dynamics serve as a metrological resource. The decoherence processes that yield enhanced precision of quantum sensors can be engineered by randomized Hamiltonian dynamics. I illustrate the results with protocols that display improved sensing of time intervals or global fields by qubit and photonic sensors. Enhanced precision of time intervals is achieved with Hamiltonians that include randomized global parameters. Enhanced precision in field estimation is obtained by randomized sensing times.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1997

Estimating Surface Radiation Fluxes in the Arctic from TOVS Brightness Temperatures

A new method for estimating downwelling shortwave and longwave radiation fluxes in the Arctic from TOVS brightness temperatures has been developed. The method employs a neural network to bypass computationally intensive inverse and for-ward radiative transfer calculations, Results from two drifting ice camps (CEAREX, LeadEx) and from one coastal station show that downwelling fluxes can be estimated with r.m.s. errors of 20 W/sq m for longwave radiation and 35 W/sq m for shortwave radiation. Mean errors are less than 4 W/sq m and are well within the bounds required for many climate process studies.

Schweiger, A. J.↗
NASA NTRS2012

Spacecraft Thermal and Optical Modeling Impacts on Estimation of the GRAIL Lunar Gravity Field

We summarize work performed involving thermo-optical modeling of the two Gravity Recovery And Interior Laboratory (GRAIL) spacecraft. We derived several reconciled spacecraft thermo-optical models having varying detail. We used the simplest in calculating SRP acceleration, and used the most detailed to calculate acceleration due to thermal re-radiation. For the latter, we used both the output of pre-launch finite-element-based thermal simulations and downlinked temperature sensor telemetry. The estimation process to recover the lunar gravity field utilizes both a nominal thermal re-radiation accleration history and an apriori error model derived from that plus an off-nominal history, which bounds parameter uncertainties as informed by sensitivity studies.

thermal modeling↗