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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Goal-oriented a-posteriori estimation of model error as an aid to parameter estimation

In this work, a Bayesian model calibration framework is presented that utilizes goal-oriented a-posterior error estimates in quantities of interest (QoIs) for classes of high-fidelity models characterized by PDEs. It is shown that for a large class of computational models, it is possible to develop a computationally inexpensive procedure for calibrating parameters of high-fidelity models of physical events when the parameters of low-fidelity (surrogate) models are known with acceptable accuracy. The main ingredients in the proposed model calibration scheme are goal-oriented a-posteriori estimates of error in QoIs computed using a so-called lower fidelity model compared to those of an uncalibrated higher fidelity model. The estimates of error in QoIs are used to define likelihood functions in Bayesian inversion analysis. A standard Bayesian approach is employed to compute the posterior distribution of model parameters of high-fidelity models. As applications, parameters in a quasi-linear second-order elliptic boundary-value problem (BVP) are calibrated using a second-order linear elliptic BVP. In a second application, parameters of a tumor growth model involving nonlinear time-dependent PDEs are calibrated using a lower fidelity linear tumor growth model with known parameter values.

A-posterior estimates↗
NASA NTRS1979

Short-term solar pressure effect and GM uncertainty on TDRS orbital accuracy: A study of the interaction of modeling error with tracking and orbit determination

The TDRS was modeled as a combination of a sun-pointing solar panel and earth-pointing plate. Based on this model, explanations are given for the following orbit determination error characteristics: inherent limits in orbital accuracy, the variation of solar pressure induced orbital error with time of the day of epoch, the insensitivity of range-rate orbits to GM error, and optimum bilateration baseline.

Fang, B. T.↗
DOE OSTI2021

Analytical Bit-Error Model of NAND Flash Memories for Dosimetry Application

In this work, we provide an analytical model for the total ionizing dose (TID) effects on the bit error statistics of commercial flash memory chips. We have validated the model with experimental data collected by irradiating several commercial NAND flash memory chips from different technology nodes. We find that our analytical model can project bit errors at higher TID values (~ 20 krad(Si)) from measured data at lower TID values (<1 krad(Si)). Based on our model and the measured data, we have formulated basic design rules for using a commercial flash memory chip as a dosimeter. We discuss the impact of NAND chip-to-chip variability, noise margin and the intrinsic errors on the dosimeter design using detailed experimentation.

3-D NAND↗
NASA NTRS1987

Antenna pointing systematic error model derivations

The pointing model used to represent and correct systematic errors for the Deep Space Network (DSN) antennas is presented. Analytical expressions are given in both azimuth-elevation (az-el) and hour angle-declination (ha-dec) mounts for RF axis collimation error, encoder offset, nonorthogonality of axes, axis plane tilt, and structural flexure due to gravity loading. While the residual pointing errors (rms) after correction appear to be within the ten percent of the half-power beamwidth criterion commonly set for good pointing accuracy, the DSN has embarked on an extensive pointing improvement and modeling program aiming toward an order of magnitude higher pointing precision.

Guiar, C. N.↗
DOE OSTI2013

A Bayesian Measurment Error Model for Misaligned Radiographic Data

An understanding of the inherent variability in micro-computed tomography (micro-CT) data is essential to tasks such as statistical process control and the validation of radiographic simulation tools. The data present unique challenges to variability analysis due to the relatively low resolution of radiographs, and also due to minor variations from run to run which can result in misalignment or magnification changes between repeated measurements of a sample. Positioning changes artificially inflate the variability of the data in ways that mask true physical phenomena. We present a novel Bayesian nonparametric regression model that incorporates both additive and multiplicative measurement error in addition to heteroscedasticity to address this problem. We also use this model to assess the effects of sample thickness and sample position on measurement variability for an aluminum specimen. Supplementary materials for this article are available online.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Multiple indicators, multiple causes measurement error models

Multiple indicators, multiple causes (MIMIC) models are often employed by researchers studying the effects of an unobservable latent variable on a set of outcomes, when causes of the latent variable are observed. There are times, however, when the causes of the latent variable are not observed because measurements of the causal variable are contaminated by measurement error. The objectives of this study are as follows: (i) to develop a novel model by extending the classical linear MIMIC model to allow both Berkson and classical measurement errors, defining the MIMIC measurement error (MIMIC ME) model; (ii) to develop likelihood-based estimation methods for the MIMIC ME model; and (iii) to apply the newly defined MIMIC ME model to atomic bomb survivor data to study the impact of dyslipidemia and radiation dose on the physical manifestations of dyslipidemia. Finally, as a by-product of our work, we also obtain a data-driven estimate of the variance of the classical measurement error associated with an estimate of the amount of radiation dose received by atomic bomb survivors at the time of their exposure.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2011

Improved Systematic Pointing Error Model for the DSN Antennas

New pointing models have been developed for large reflector antennas whose construction is founded on elevation over azimuth mount. At JPL, the new models were applied to the Deep Space Network (DSN) 34-meter antenna s subnet for corrections of their systematic pointing errors; it achieved significant improvement in performance at Ka-band (32-GHz) and X-band (8.4-GHz). The new models provide pointing improvements relative to the traditional models by a factor of two to three, which translate to approximately 3-dB performance improvement at Ka-band. For radio science experiments where blind pointing performance is critical, the new innovation provides a new enabling technology. The model extends the traditional physical models with higher-order mathematical terms, thereby increasing the resolution of the model for a better fit to the underlying systematic imperfections that are the cause of antenna pointing errors. The philosophy of the traditional model was that all mathematical terms in the model must be traced to a physical phenomenon causing antenna pointing errors. The traditional physical terms are: antenna axis tilts, gravitational flexure, azimuth collimation, azimuth encoder fixed offset, azimuth and elevation skew, elevation encoder fixed offset, residual refraction, azimuth encoder scale error, and antenna pointing de-rotation terms for beam waveguide (BWG) antennas. Besides the addition of spherical harmonics terms, the new models differ from the traditional ones in that the coefficients for the cross-elevation and elevation corrections are completely independent and may be different, while in the traditional model, some of the terms are identical. In addition, the new software allows for all-sky or mission-specific model development, and can utilize the previously used model as an a priori estimate for the development of the updated models.

Rochblatt, David J.↗
NASA NTRS1992

Spacecraft-spacecraft very long baseline interferometry. Part 1: Error modeling and observable accuracy

In Part 1 of this two-part article, an error budget is presented for Earth-based delta differential one-way range (delta DOR) measurements between two spacecraft. Such observations, made between a planetary orbiter (or lander) and another spacecraft approaching that planet, would provide a powerful target-relative angular tracking data type for approach navigation. Accuracies of better than 5 nrad should be possible for a pair of spacecraft with 8.4-GHz downlinks, incorporating 40-MHz DOR tone spacings, while accuracies approaching 1 nrad will be possible if the spacecraft incorporate 32-GHz downlinks with DOR tone spacing on the order of 250 MHz; these accuracies will be available for the last few weeks or months of planetary approach for typical Earth-Mars trajectories. Operational advantages of this data type are discussed, and ground system requirements needed to enable spacecraft-spacecraft delta DOR observations are outlined. This tracking technique could be demonstrated during the final approach phase of the Mars '94 mission, using Mars Observer as the in-orbit reference spacecraft, if the Russian spacecraft includes an 8.4-GHz downlink incorporating DOR tones. Part 2 of this article will present an analysis of predicted targeting accuracy for this scenario.

Edwards, C. D., Jr.↗
DOE OSTI2018

Cyclops I: Modeling Error Study for Inertially Confined Detonation of Insensitive High Explosive (IHE) PBX-9502

A validation study is performed using the hydrodynamics code PAGOSA to assess the accuracy of reflected shock, burn front propagation, and Photon Doppler Velocimetry (PDV) predictions using several burn models and strength models. Experimental data collected from proton radiography (pRad) is compared to burn front propagation times and reflected shock patterns. Burn front isochrones are computed and the lag time for the burn front is quantified for a given burn model. The effect of strength models and damage are assessed by comparison of simulations to experimental PDV data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Effects of head modeling errors on the spatial frequency representation of MEG

Abstract Objectives. We aim to investigate the effects of head model inaccuracies on signal and source reconstruction accuracies for various sensor array distances to the head. This allows for the assessment of the importance of head modeling for next-generation magnetoencephalography (MEG) sensors, optically-pumped magnetometers (OPM). Approach. A 1-shell boundary element method (BEM) spherical head model with 642 vertices of radius 9 cm and conductivity of 0.33 S m −1 was defined. The vertices were then randomly perturbed radially up to 2%, 4%, 6%, 8% and 10% of the radius. For each head perturbation case, the forward signal was calculated for dipolar sources located at 2 cm, 4 cm, 6 cm and 8 cm from the origin (center of the sphere), and for a 324 sensor array located at 10 cm to 15 cm from the origin. Equivalent current dipole (ECD) source localization was performed for each of these forward signals. The signal for each perturbed spherical head case was then analyzed in the spatial frequency domain, and the signal and ECD errors were quantified relative to the unperturbed case. Main results. In the noiseless and high signal-to-noise ratio (SNR) case of approximately ≥6 dB, inaccuracies in our spherical BEM head conductor models lead to increased signal and ECD inaccuracies when sensor arrays are placed closer to the head. This is true especially in the case of deep and superficial sources. In the noisy case however, the higher SNR for closer sensor arrays allows for an improved ECD fit and outweighs the effects of head geometry inaccuracies. Significance. OPMs may be placed directly on the head, as opposed to the more commonly used superconducting quantum interference device sensors which must be placed a few centimeters away from the head. OPMs thus allow for signals of higher spatial resolution to be captured, resulting in potentially more accurate source localizations. Our results suggest that an increased emphasis on accurate head modeling for OPMs may be necessary to fully realize its improved source localization potential.

Yeo, Wan-Jin (ORCID:0000000241417123)↗
NASA NTRS2011

Toward a Framework for Systematic Error Modeling of NASA Spaceborne Radar with NOAA/NSSL Ground Radar-Based National Mosaic QPE

Characterization of the error associated to satellite rainfall estimates is a necessary component of deterministic and probabilistic frameworks involving space-born passive and active microwave measurement") for applications ranging from water budget studies to forecasting natural hazards related to extreme rainfall events. We focus here on the error structure of NASA's Tropical Rainfall Measurement Mission (TRMM) Precipitation Radar (PR) quantitative precipitation estimation (QPE) at ground. The problem is addressed by comparison of PR QPEs with reference values derived from ground-based measurements using NOAA/NSSL ground radar-based National Mosaic and QPE system (NMQ/Q2). A preliminary investigation of this subject has been carried out at the PR estimation scale (instantaneous and 5 km) using a three-month data sample in the southern part of US. The primary contribution of this study is the presentation of the detailed steps required to derive trustworthy reference rainfall dataset from Q2 at the PR pixel resolution. It relics on a bias correction and a radar quality index, both of which provide a basis to filter out the less trustworthy Q2 values. Several aspects of PR errors arc revealed and quantified including sensitivity to the processing steps with the reference rainfall, comparisons of rainfall detectability and rainfall rate distributions, spatial representativeness of error, and separation of systematic biases and random errors. The methodology and framework developed herein applies more generally to rainfall rate estimates from other sensors onboard low-earth orbiting satellites such as microwave imagers and dual-wavelength radars such as with the Global Precipitation Measurement (GPM) mission.

Kirstettier, Pierre-Emmanual↗
NASA NTRS1989

A discussion of observation model, error sources and signal size for spaceborne gravitational gradiometry

Various space concepts were discussed during the past 20 years for a global improvement of the knowledge of the earth's gravity field. The concepts reach from high-low and low-low satellite-to-satellite tracking via tethered satellite gradiometers to sophisticated superconducting gradiometers. The purpose is to show that starting from one basic equation three criteria are sufficient to typify the various concepts and define the underlying observation model. Furthermore the different error sources, in particular, the time varying part of self-gravitation, and the expected signal size of all six gravity gradient components shall be discussed.

Rummel, R.↗
NASA NTRS2004

Error Modeling of Multibaseline Optical Truss: Part 1: Modeling of System Level Performance

Global astrometry is the measurement of stellar positions and motions. These are typically characterized by five parameters, including two position parameters, two proper motion parameters, and parallax. The Space Interferometry Mission (SIM) will derive these parameters for a grid of approximately 1300 stars covering the celestial sphere to an accuracy of approximately 4uas, representing a two orders of magnitude improvement over the most precise current star catalogues. Narrow angle astrometry will be performed to a 1uas accuracy. A wealth of scientific information will be obtained from these accurate measurements encompassing many aspects of both galactic (and extragalactic science. SIM will be subject to a number of instrument errors that can potentially degrade performance. Many of these errors are systematic in that they are relatively static and repeatable with respect to the time frame and direction of the observation. This paper and its companion define the modeling of the, contributing factors to these errors and the analysis of how they impact SIM's ability to perform astrometric science.

meterology modeling↗
NASA NTRS1984

GP-B error modeling and analysis

The analysis and modeling for the Gravity Probe B (GP-B) experiment is reported. The finite-wordlength induced errors in Kalman filtering computation were refined. Errors in the crude result were corrected, improved derivation steps are taken, and better justifications are given. The errors associated with the suppression of the 1-noise were analyzed by rolling the spacecraft and then performing a derolling operation by computation.

Source record↗
DOE OSTI2025

Reducing model error using optimized galaxy selection: weak lensing cluster mass estimation

Galaxy clusters are one of the most powerful probes to study extensions of General Relativity and the Standard Cosmological Model. Upcoming surveys like the Vera Rubin Observatory’s Legacy Survey of Space and Time are expected to revolutionise the field, by enabling the analysis of cluster samples of unprecedented size and quality. To reach this era of high-precision cluster cosmology, the mitigation of sources of systematic error is crucial. A particularly important challenge is bias in cluster mass measurements induced by the mismodelling of photometric redshift estimates of source galaxies. This work proposes a method to optimise the source sample selection in cluster weak lensing analyses drawn from wide-field survey lensing catalogs to reduce the bias on reconstructed cluster masses. We use a combinatorial optimisation scheme and methods from variational inference to select galaxies in latent space to produce a probabilistic galaxy source sample catalog for highly accurate cluster mass estimation. We show that our method reduces the critical surface mass density Σ crit relative modelling bias on the 60-70% level, while maintaining up to 90% of galaxies. We highlight that our methodology has applications beyond cluster mass estimation as an approach to jointly combine galaxy selection and model inference under sources of systematics.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1986

Analysis of modeling errors in system identification

This paper is concerned with the identification of a system in the presence of several error sources. Following some basic definitions, the notion of 'near-equivalence in probability' is introduced using the concept of near-equivalence between a model and process. Necessary and sufficient conditions for the identifiability of system parameters are given. The effect of structural error on the parameter estimates for both deterministic and stochastic cases are considered.

Hadaegh, F. Y.↗