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Results for “ERROR FUNCTION”

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 343 records · Page 19

All sources NASA NTRS DOE OSTI

NASA NTRS1996

Computerized Design and Analysis of Face-Milled, Uniform Tooth Height, Low-Noise Spiral Bevel Gear Drives

A new method for design and generation of spiral bevel gears of uniform tooth depth with localized bearing contact and low level of transmission errors is considered. The main features of the proposed approach are as follows: (1) the localization of the bearing contact is achieved by the mismatch of the generating surfaces. The bearing contact may be provided in the longitudinal direction, or in the direction across the surface; and (2) the low level of transmission errors is achieved due to application of nonlinear relations between the motions of the gear and the gear head-cutter. Such relations may be provided by application of a CNC machine. The generation of the pinion is based on application of linear relations between the motions of the tool and the pinion being generated. The relations described above permit a parabolic function of transmission errors to be obtained that is able to absorb almost linear functions caused by errors of gear alignment. A computer code has been written for the meshing and contact of the spiral bevel gears with the proposed geometry. The effect of misalignment on the proposed geometry has also been determined. Numerical examples for illustration of the proposed theory have been provided.

Litvin, F. L.↗

NASA NTRS1996

Computerized Design and Analysis of Face-Milled, Uniform Tooth Height, Low-Noise Spiral Bevel Gear Drives

A new method for design and generation of spiral bevel gears of uniform tooth depth with localized bearing contact and low level of transmission errors is considered. The main features of the proposed approach are as follows: (1) The localization of the bearing contact is achieved by the mismatch of the generating surfaces. The bearing contact may be provided in the longitudinal direction, or in the direction across the surface; and (2) The low level of transmission errors is achieved due to application of nonlinear relations between the motions of the gear and the gear head-cutter. Such relations may be provided by application of a CNC machine. The generation of the pinion is based on application of linear relations between the motions of the tool and the pinion being generated. The relations described above permit a parabolic function of transmission errors to be obtained that is able to absorb almost linear functions caused by errors of gear alignment. A computer code has been written for the meshing and contact of the spiral bevel gears with the proposed geometry. The effect of misalignment on the proposed geometry has also been determined. Numerical examples for illustration of the proposed theory have been provided.

Litvin, F. L.↗

NASA NTRS2003

Characteristics of Single-Event Upsets in a Fabric Switch (ADS151)

Abstract-Two types of single event effects - bit errors and single event functional interrupts - were observed during heavy-ion testing of the AD8151 crosspoint switch. Bit errors occurred in bursts with the average number of bits in a burst being dependent on both the ion LET and on the data rate. A pulsed laser was used to identify the locations on the chip where the bit errors and single event functional interrupts occurred. Bit errors originated in the switches, drivers, and output buffers. Single event functional interrupts occurred when the laser was focused on the second rank latch containing the data specifying the state of each switch in the 33x17 matrix.

Buchner, Stephen↗

DOE OSTI2022

The effect of quasar redshift errors on Lyman-α forest correlation functions

ABSTRACT Using synthetic Lyman-α forests from the Dark Energy Spectroscopic Instrument (DESI) survey, we present a study of the impact of errors in the estimation of quasar redshift on the Lyman-α correlation functions. Estimates of quasar redshift have large uncertainties of a few hundred km s−1 due to the broadness of the emission lines and the intrinsic shifts from other emission lines. We inject Gaussian random redshift errors into the mock quasar catalogues, and measure the auto-correlation and the Lyman-α-quasar cross-correlation functions. We find a smearing of the BAO feature in the radial direction, but changes in the peak position are negligible. However, we see a significant unphysical correlation for small separations transverse to the line of sight which increases with the amplitude of the redshift errors. We interpret this contamination as a result of the broadening of emission lines in the measured mean continuum, caused by quasar redshift errors, combined with the unrealistically strong clustering of the simulated quasars on small scales.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

A moment-conserving discontinuous Galerkin representation of the relativistic Maxwellian distribution

Kinetic simulations of relativistic gases and plasmas are critical for understanding diverse astrophysical and terrestrial systems, but the accurate construction of the relativistic Maxwellian, the Maxwell–Jüttner distribution, on a discrete simulation grid is challenging. Difficulties arise from the finite velocity bounds of the domain, which may not capture the entire distribution function, as well as errors introduced by projecting the function onto a discrete grid. Here, we present a novel scheme for iteratively correcting the moments of the projected distribution applicable to all grid-based discretizations of the relativistic kinetic equation. In addition, we describe how to compute the needed nonlinear quantities, such as Lorentz boost factors, in a discontinuous Galerkin scheme through a combination of numerical quadrature and weak operations. The resulting method accurately captures the distribution function and ensures that the moments match the desired values to machine precision.

astrophysical plasmas↗

DOE OSTI2023

Recommendations for Minimum Required Error Codes for Electric Vehicle Charging Infrastructure

OCPP protocol manages the interaction between the EVSE and its respective back-end communication network. It plays a pivotal role in both error reporting and troubleshooting, carried out primarily through the CSMS. OCPP defines both standard error codes and a flexible framework for creating and communicating custom error codes. The OCPI protocol orchestrates the communication between different backhaul communication networks, incorporating the exchange of error codes. These error codes are instrumental in pinpointing and rectifying issues that can surface prior to, during, or after charging operations, fortifying the reliability and resilience of the EV charging infrastructure. The flexibility offered by the OCPP and OCPI frameworks through the introduction of custom error codes also creates its own set of challenges. While the integration of custom error codes allows for enhanced granularity, it also introduces inconsistencies and fragmentation within the overarching diagnostic reporting system. To address the challenges with custom error codes this report proposes a set of Minimum Required Error Codes (MRECs) for streamlined error reporting, interpretability, and diagnostics. Recommendations in this report are based on independent analysis of custom error codes from multiple stakeholders within the EV charging ecosystem. For better error resolution, this report also assigns one or more entities responsible for the resolution of every mentioned error code. Finally, a functional classification for each mentioned error code is also identified to describe the nature of the error. In summary, the purpose of this document is to simplify the troubleshooting process and increase charging reliability for all EV users. This report serves as a recommendation for industry stakeholders, encouraging a unified methodology to define, transmit, and interpret common error codes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1989

A performance comparison of integration algorithms in simulating flexible structures

Asymptotic formulas for the characteristic root errors as well as transfer function gain and phase errors are presented for a number of traditional and new integration methods. Normalized stability regions in the lambda h plane are compared for the various methods. In particular, it is shown that a modified form of Euler integration with root matching is an especially efficient method for simulating lightly-damped structural modes. The method has been used successfully for structural bending modes in the real-time simulation of missiles. Performance of this algorithm is compared with other special algorithms, including the state-transition method. A predictor-corrector version of the modified Euler algorithm permits it to be extended to the simulation of nonlinear models of the type likely to be obtained when using the discretized structure approach. Performance of the different integration methods is also compared for integration step sizes larger than those for which the asymptotic formulas are valid. It is concluded that many traditional integration methods, such as RD-4, are not competitive in the simulation of lightly damped structures.

Howe, R. M.↗

NASA NTRS1993

Specification-based software sizing: An empirical investigation of function metrics

For some time the software industry has espoused the need for improved specification-based software size metrics. This paper reports on a study of nineteen recently developed systems in a variety of application domains. The systems were developed by a single software services corporation using a variety of languages. The study investigated several metric characteristics. It shows that: earlier research into inter-item correlation within the overall function count is partially supported; a priori function counts, in themself, do not explain the majority of the effort variation in software development in the organization studied; documentation quality is critical to accurate function identification; and rater error is substantial in manual function counting. The implication of these findings for organizations using function based metrics are explored.

Jeffery, Ross↗

NASA NTRS2013

Simultaneous Estimation of Model State Variables and Observation and Forecast Biases Using a Two-Stage Hybrid Kalman Filter

In this paper, we present a two-stage hybrid Kalman filter to estimate both observation and forecast bias in hydrologic models, in addition to state variables. The biases are estimated using the discrete Kalman filter, and the state variables using the ensemble Kalman filter. A key issue in this multi-component assimilation scheme is the exact partitioning of the difference between observation and forecasts into state, forecast bias and observation bias updates. Here, the error covariances of the forecast bias and the unbiased states are calculated as constant fractions of the biased state error covariance, and the observation bias error covariance is a function of the observation prediction error covariance. In a series of synthetic experiments, focusing on the assimilation of discharge into a rainfall-runoff model, it is shown that both static and dynamic observation and forecast biases can be successfully estimated. The results indicate a strong improvement in the estimation of the state variables and resulting discharge as opposed to the use of a bias-unaware ensemble Kalman filter. Furthermore, minimal code modification in existing data assimilation software is needed to implement the method. The results suggest that a better performance of data assimilation methods should be possible if both forecast and observation biases are taken into account.

Data Assimilation↗

DOE OSTI2015

Accuracy of maximum likelihood estimates of a two-state model in single-molecule FRET

Photon sequences from single-molecule Förster resonance energy transfer (FRET) experiments can be analyzed using a maximum likelihood method. Parameters of the underlying kinetic model (FRET efficiencies of the states and transition rates between conformational states) are obtained by maximizing the appropriate likelihood function. In addition, the errors (uncertainties) of the extracted parameters can be obtained from the curvature of the likelihood function at the maximum. We study the standard deviations of the parameters of a two-state model obtained from photon sequences with recorded colors and arrival times. The standard deviations can be obtained analytically in a special case when the FRET efficiencies of the states are 0 and 1 and in the limiting cases of fast and slow conformational dynamics. These results are compared with the results of numerical simulations. The accuracy and, therefore, the ability to predict model parameters depend on how fast the transition rates are compared to the photon count rate. In the limit of slow transitions, the key parameters that determine the accuracy are the number of transitions between the states and the number of independent photon sequences. In the fast transition limit, the accuracy is determined by the small fraction of photons that are correlated with their neighbors. The relative standard deviation of the relaxation rate has a “chevron” shape as a function of the transition rate in the log-log scale. The location of the minimum of this function dramatically depends on how well the FRET efficiencies of the states are separated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

The Good, the Bad, and the Ugly: Pseudopotential Inconsistency Errors in Molecular Applications of Density Functional Theory

The pseudopotential (PP) approximation is one of the most common techniques in computational chemistry. Despite its long history, the development of custom PPs has not tracked with the explosion of different density functional approximations (DFAs). As a result, the use of PPs with exchange/correlation models for which they were not developed is widespread, although this practice is known to be theoretically unsound. The extent of PP inconsistency errors (PPIEs) associated with this practice has not been systematically explored across the types of energy differences commonly evaluated in chemical applications. Here, we evaluate PPIEs for a number of PPs and DFAs across 196 chemically relevant systems of both transition-metal and main-group elements, as represented by the W4-11, TMC34, and S22 data sets. Near the complete basis set limit, these PPs are found to cleanly approach all-electron (AE) results for noncovalent interactions but introduce root-mean-squared errors (RMSEs) upwards of 15 kcal mol –1 into predictions of covalent bond energies for a number of popular DFAs. We achieve significant improvements through the use of empirical atom- and DFA-specific PP corrections, indicating considerable systematicity of the PPIEs. The results of this work have implications for chemical modeling in both molecular contexts and for DFA design, which we discuss.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Assessing the predictive impact of factor fixing with an adaptive uncertainty-based approach .

Despite widespread use of factor fixing in environmental modeling, its effect on model predictions has received little attention and is instead commonly presumed to be negligible. We propose a proof-of-concept adaptive method for systematically investigating the impact of factor fixing. The method uses Global Sensitivity Analysis methods to identify groups of sensitive parameters, then quantifies which groups can be safely fixed at nominal values without exceeding a maximum acceptable error, demonstrated using the 21-dimensional Sobol’ G-function. Furthermore, three error measures are considered for quantities of interest, namely Relative Mean Absolute Error, Pearson Product-Moment Correlation and Relative Variance. Results demonstrate that factor fixing may cause large errors in the model results unexpectedly, when preliminary analysis suggests otherwise, and that the default value selected affects the number of factors to fix. To improve the applicability and methodological development of factor fixing, a new research agenda encompassing five opportunities is discussed for further attention.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1978

Gravitational experiments on solar probe

A covariance analysis was performed for a solar probe trajectory which encounters the sun at four solar radii. The unknown parameters in the analysis are the six initial cartesian coordinates for the probe, six initial cartesian coordinates for the earth, the astronomical unit, the solar gravitational quadrupole coefficient and two post Newtonian meters (beta, gamma). Errors in the unknown parameters were computed as a function of standard errors on the radio tracking data and on the nongravitational forces which act on the probe. Results were obtained for several tracking geometries and for several orbital inclinations to the ecliptic. The analysis shows that the principal scientific result from the radio tracking of a solar probe would be the determination of the quadrupole moment, which would place a constraint on models of the solar interior.

Anderson, J. D.↗

NASA NTRS1991

Test functions for the moment method which yield the minimum mean square error

The method of moments has found extensive applications in the solution of a wide class of electromagnetic problems. Additionally, there are a number of basis functions which have found favor and with them different types of testing methods. This work examines the selection of test functions, given a selected set of basis functions, which serve to minimize the mean square error. These test functions will guarantee equal or lesser error compared with any other test function. Additionally, these test functions provide a monotonic improvement of the approximation as the increase in the order of the system. Hence while these test functions require the application of the differential or integral operator one additional time, they provide an absolute lower bound to the mean square error in the approximation and a means to systematically improve accuracy with each increase in the order of the unknowns.

Shamansky, H.↗

DOE OSTI2024

Machine learning for accuracy in density functional approximations

Machine learning techniques have found their way into computational chemistry as indispensable tools to accelerate atomistic simulations and materials design. In addition, machine learning approaches hold the potential to boost the predictive power of computationally efficient electronic structure methods, such as density functional theory, to chemical accuracy and to correct for fundamental errors in density functional approaches. In this paper, recent progress in applying machine learning to improve the accuracy of density functional and related approximations is reviewed. Promises and challenges in devising machine learning models transferable between different chemistries and materials classes are discussed with the help of examples applying promising models to systems far outside their training sets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Interactive tools for functional annotation of bacterial genomes

Automated annotations of protein functions are error-prone because of our lack of knowledge of protein functions. For example, it is often impossible to predict the correct substrate for an enzyme or a transporter. Furthermore, much of the knowledge that we do have about the functions of proteins is missing from the underlying databases. We discuss how to use interactive tools to quickly find different kinds of information relevant to a protein’s function. Many of these tools are available via PaperBLAST (http://papers.genomics.lbl.gov). Combining these tools often allows us to infer a protein’s function. Ideally, accurate annotations would allow us to predict a bacterium’s capabilities from its genome sequence, but in practice, this remains challenging. We describe interactive tools that infer potential capabilities from a genome sequence or that search a genome to find proteins that might perform a specific function of interest.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1984

Estimation of parameters in linear structural relationships: Sensitivity to the choice of the ratio of error variances

Maximum likelihood estimation of parameters in linear structural relationships under normality assumptions requires knowledge of one or more of the model parameters if no replication is available. The most common assumption added to the model definition is that the ratio of the error variances of the response and predictor variates is known. The use of asymptotic formulae for variances and mean squared errors as a function of sample size and the assumed value for the error variance ratio is investigated.

Lakshminarayanan, M. Y.↗

NASA NTRS1984

Estimation of parameters in linear structural relationships Sensitivity to the choice of the ratio of error variances

Maximum likelihood estimation of parameters in linear structural relationships under normality assumptions requires knowledge of one or more of the model parameters if no replication is available. The most common assumption added to the model definition is that the ratio of the error variances of the response and predictor variates is known. This paper investigates the use of asymptotic formulae for variances and mean squared errors as a function of sample size and the assumed value for the error variance ratio.

Lakshminarayanan, M. Y.↗