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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 577 records · Page 32

Solution Irregularity Remediation for Spatial Discretization Error Estimation for S N Transport Solutions

The discrete ordinates linear Boltzmann transport equation is typically solved in its spatially discretized form, incurring spatial discretization error. Quantification of this error for purposes such as adaptive mesh refinement or error analysis requires an a posteriori estimator, which utilizes the numerical solution to the spatially discretized equation to compute an estimate. Because the quality of the numerical solution informs the error estimate, irregularities, present in the true solution for any realistic problem configuration, tend to cause the largest deviation in the error estimate vis-a-vis the true error. In this paper, an analytical partial singular characteristic tracking (pSCT) procedure for reducing the estimator’s error is implemented within our novel residual source estimator for a zeroth-order discontinuous Galerkin scheme, at the additional cost of a single inner iteration. Here, a metric-based evaluation of the pSCT scheme versus the standard residual source estimator is performed over the parameter range of a Method of Manufactured Solutions test suite. The pSCT scheme generates near-ideal accuracy in the estimate in problems where the dominant source of the estimator’s error is the solution irregularity, namely, problems where the true solution is discontinuous and problems where the true solution’s first derivative is discontinuous and the scattering ratio is low. In problems where the scattering ratio is high and the true solution is discontinuous in the first derivative, the error in the scattering source, which is not converged by the pSCT scheme, is greater than the error incurred due to the irregularity. Ultimately, a pSCT scheme is judged to be useful for error estimation in problems where the computational cost of the scheme is justified. In the presence of many irregularities, such a scheme may be intractable for general use, but in benchmarks, as an analytical tool, or in problems that have nondissipative discontinuities, the scheme may prove invaluable.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Comparison of SAGE II ozone measurements and ozone soundings at Uccle (Belgium) during the period February 1985 to January 1986

The ozone profiles obtained from 24 balloon soundings at Uccle (50 deg 48 min N, 4 deg 21 min E) made with electrochemical ozonesondes were used as correlative data for SAGE II ozone profiles retrieved within a distance of at most 600 km from Uccle. The agreement between the two data sets is in general quite good, especially for profiles nearly coincident in time and space, and during periods of little dynamic activity over the area considered. The percent difference between the ozone column density of the mean balloon and SAGE profile is 4.4 percent (-3.3) percent in the altitude region between 10 and 26 km. From a statistical analysis it appears that there is a small but meaningful difference between the mean profiles at the level of the ozone maximum and around the 30-km level. An error analysis of both data sets give similar results, leading to the conclusion that these differences are instrumentally induced. However, differences between the mean profiles in the lower stratosphere are probably real and due to the high ozone variability in time and space in that altitude region.

De Muer, D.↗

Single Event Analysis and Fault Injection Techniques Targeting Complex Designs Implemented in Xilinx-Virtex Family Field Programmable Gate Array (FPGA) Devices

An informative session regarding SRAM FPGA basics. Presenting a framework for fault injection techniques applied to Xilinx Field Programmable Gate Arrays (FPGAs). Introduce an overlooked time component that illustrates fault injection is impractical for most real designs as a stand-alone characterization tool. Demonstrate procedures that benefit from fault injection error analysis.

Single Event Upset Testing↗

Spectral partitioning with blends of eigenvectors

We report many common methods for data analysis rely on linear algebra. We provide new results connecting data analysis error to numerical accuracy in the context of spectral graph partitioning. We provide pointwise convergence guarantees so that spectral blends (linear combinations of eigenvectors) can be employed to solve data analysis problems with confidence in their accuracy. We apply this theory to an accessible model problem, the ring of cliques, by deriving the relevant eigenpairs and finding necessary and sufficient solver tolerances. Analysis of the ring of cliques provides an upper bound on eigensolver tolerances for graph partitioning problems. These results bridge the gap between linear algebra based data analysis methods and the convergence theory of iterative approximation methods. These results explain how the combinatorial structure of a problem can be recovered much faster than numerically accurate solutions to the associated linear algebra problem.

97 MATHEMATICS AND COMPUTING↗

Objective sea-level pressure analysis for data-sparse areas.

A computer procedure, described in an earlier study, uses the wind speed field near the ocean surface in combination with a small number of observations of pressure and wind velocity to specify the maritime sea-level pressure field. An improved version was used to analyze the pressure distribution over the North Pacific Ocean for eleven synoptic times in February 1967. Independent knowledge of the central pressures of lows is shown to reduce the analysis errors for very sparse data coverage. The application of planned remote sensing of sea-level wind speeds is shown to make a significant contribution to the quality of the analysis especially in the high gradient midlatitudes and for sparse coverage of conventional observations (such as over Southern Hemisphere oceans). Uniform distribution of the available observations of sea-level pressure and wind velocity yields results far superior to those derived from a random distribution.

Druyan, L. M.↗

An NDE Approach for Characterizing Quality Problems in Polymer Matrix Composites

Polymer matrix composite (PMC) materials are periodically identified appearing optically uniform but containing a higher than normal level of global nonuniformity as indicated from preliminary ultrasonic scanning. One such panel was thoroughly examined by nondestructive (NDE) and destructive methods to quantitatively characterize the nonuniformity. The NDE analysis of the panel was complicated by the fact that the panel was not uniformly thick. Mapping of ultrasonic velocity across a region of the panel in conjunction with an error analysis was necessary to (1) characterize properly the porosity gradient that was discovered during destructive analyses and (2) account for the thickness variation effects. Based on this study, a plan for future NDE characterization of PMC's is presented to the PMC community.

Roth, Don J.↗

Comparison of Response Surface and Kriging Models for Multidisciplinary Design Optimization

In this paper, we compare and contrast the use of second-order response surface models and kriging models for approximating non-random, deterministic computer analyses. After reviewing the response surface method for constructing polynomial approximations, kriging is presented as an alternative approximation method for the design and analysis of computer experiments. Both methods are applied to the multidisciplinary design of an aerospike nozzle which consists of a computational fluid dynamics model and a finite-element model. Error analysis of the response surface and kriging models is performed along with a graphical comparison of the approximations, and four optimization problems m formulated and solved using both sets of approximation models. The second-order response surface models and kriging models-using a constant underlying global model and a Gaussian correlation function-yield comparable results.

Simpson, Timothy W.↗

Delta V errors due to attitude correction maneuvers of a spinning spacecraft

A statistical error analysis has been performed to evaluate the change in velocity of a spin stabilized spacecraft due to thruster induced attitude correction maneuvers. Analytical expressions were developed to determine the mean and variance of the velocity in terms of the nominal values and uncertainties of key spacecraft parameters. These parameters include thrust, thruster timing, thruster alignment, plume impingement force and estimated spacecraft mass. Typical values of these parameters and their uncertainties for NASA's Galileo spacecraft were used to evaluate these expressions. The results of the analysis allow the effect of attitude correction maneuvers to be evaluated with respect to the functional requirements on nongravitational acceleration. Other results include the identification of major sources of delta V error and studies of the sensitivity of delta V to variations in the error sources.

Zipursky, H. J.↗

Comparison of SAGE 2 ozone measurements and ozone soundings at Uccle (Belgium) during the period February 1985 to January 1986

The ozone profiles obtained from 24 balloon soundings, at 50 deg 48 min N, 4 deg 21 min E, carried out with the electro-chemical ozonesondes are discussed. The data were used as correlative data to the ozone profiles acquired by the Stratospheric Aerosol and Gas Experiment (SAGE 2). Good agreement was obtained between the two data sets. The difference of percentage between the ozone column density of the mean balloon and SAGE profile is 4.4% in the altitude region between 10 to 26 km. From the statistical analysis it seems that there is a difference between the mean profiles at the level of the ozone maximum and around the 30 km level. Similar results are obtained with an error analysis of both data. The differences between the mean profiles in the lower stratosphere are probably real, and are due to the presence of ozone.

Debacker, Hugo↗

Uncertainty Analysis of Slug Calorimeters in the HyMETS Arc-Jet Facility

The objective of this work is to perform an uncertainty analysis of the deduced stagnation heat flux environment on a slug calorimeter for conditions that span the performance envelope of the Hypersonic Materials Environmental Test System arc-jet facility located at NASA Langley Research Center. Analytical solutions are developed for boundary-value problems on the slug element accounting for non-ideal effects, including spatial variation in the slug heat flux, multi-dimensional thermal conduction, and back-face losses, which departs from the state-of-the-art method derived from the American Society of Testing and Materials. Boundary-value problem definitions are informed by preliminary finite element thermal analysis of the slug calorimeter assembly (including both slug and housing) and just the slug element. The analytical solutions are presented in a general sense and in a truncated form from error analysis. Results are shown in optimizing and validating the analytical models against available slug back-face thermal data. The optimization results indicate that the appropriate epistemic uncertainty of the deduced stagnation heat flux on the slug calorimeter is at most±2.5% for both a high-and low-enthalpy test condition. In addition, a numerical approach is used to determine the aleatory (probabilistic) uncertainty component in the slug stagnation heat flux by applying a marching least-squares slope routine through the steady-state portion of the slug back-face thermal response. Results indicate a compromise between the number of samples and the filter frequency of slug back-face thermal data points when evaluating the standard deviation of the deduced stagnation heat flux statistics. When combining the mixed uncertainty, both aleatory and epistemic, the interval of uncertainty in the deduced stagnation heat flux is determined to be up to ±4%, which is at least a 60% reduction from the standard uncertainty used in the state-of-the-art method.

uncertainty↗

Comparison and Application of Battery Modeling Methods for Conceptual Electric Aircraft

Growing interest in design and optimization of electrified aircraft propulsion concepts prompts the need for accurate, flexible, and efficient methods to model battery systems. Presented in this paper are three battery modeling methods that have been used at NASA’s Glenn Research Center, each representing different mathematical or electrical approaches. Thévenin equivalent circuit, normalization, and curve-fitting methods are compared against battery cell test data for the X-57 Maxwell electric aircraft technology demonstrator. The methods are then applied in a simple multidisciplinary optimization context using NASA’s Six-Passenger Electric Quadrotor concept to determine their applicability and performance. The normalization method achieves the highest accuracy for steady and unsteady discharge rates with a voltage mean error percentage of 0.423% and 1.186%, respectively. Optimal quadrotor mission range between the models varies up to 0.5 nmi, identifying current battery modeling methods as a potentially significant contributor to mission analysis error. A set of relevant tools and techniques for conceptual battery modeling are identified in this paper, with conclusions made on the utility of each modeling approach for various design challenges.

power↗

Sources of error in the graphical analysis of CFD results

Errors inherent to the graphic analysis of CFD solutions are discussed. Consideration is given to contouring, plotting of vector fields, particle tracing, and the computation of flow functions involving integration or differentiation. Many of the problems addressed are the direct result of knowing the function values only at grid points, not in the interior of the grid cells.

Buning, Pieter G.↗

Comparative Analysis of Soft-Error Detection Strategies: A Case Study with Iterative Methods

Undetected soft errors caused by transient bit flips can lead to silent data corruption (SDC), an undesirable outcome where invalid results pass for valid ones. This has motivated the design of soft error detectors to minimize SDCs. However, the detectors have been studied under different contexts, making comparative evaluation difficult. In this paper, we present the first comprehensive evaluation of four online soft error detection techniques in detecting the adverse impact of soft errors on iterative methods. We observe that, across five iterative methods, the detectors studied achieve high but not perfect detection rates. To understand the potential for improved detection, we evaluate a machine-learning based detector that takes as features that are the runtime features observed by the individual detectors to arrive at their conclusions. Our evaluation demonstrates improved but still far from perfect detection accuracy for the machine learning based detectors. This extensive evaluation demonstrates the need for designing error detectors to handle the evolutionary behavior exhibited by iterative solvers.

Silent data corruption, Soft error detection, Iter↗

Poisson-response Tensor-on-Tensor Regression and Applications

We introduce Poisson-response tensor-on-tensor regression (PToTR), a novel regression framework designed to handle tensor responses composed element-wise of random Poisson-distributed counts. Tensors, or multi-dimensional arrays, composed of counts are common data in fields such as inter national relations, social networks, epidemiology, and medical imaging, where events occur across multiple dimensions like time, location, and dyads. PToTR accommodates such tensor responses alongside tensor covariates, providing a versatile tool for multi dimensional data analysis. We propose algorithms for maximum likelihood estimation under a canonical polyadic (CP) structure on the regression coefficient tensor that satisfy the positivity of Poisson parameters and then provide an initial theoretical error analysis for PToTR estimators. We also demonstrate the utility of PToTR through three concrete applications: longitudinal data analysis of the Integrated Crisis Early Warning System database, positron emission tomography (PET) image reconstruction, and change-point detection of communication patterns in longitudinal dyadic data. These applications highlight the versatility of PToTR in addressing complex, structured count data across various domains.

97 MATHEMATICS AND COMPUTING↗

Estimation of spectral reflectance signatures from spectral radiance profiles

This paper presents a technique for converting spectral radiance to the more fundamental quantity of interest, spectral reflectance. A full implementation of the technique requires the availability of radiative transfer software. However, a set of tables (which allows an approximate derivation of reflectance) is included herein, and covers a representative range of environmental parameter values. An error analysis is performed which gives, for an uncertainty in each of the input parameters (solar zenith angle, visibility, sensor altitude, off-nadir viewing angle, background reflectance and surface elevation), the resulting error in derived reflectance. As a demonstration of the technique, several sets of spectral radiance data from the Imperial Valley, California, are presented as spectral reflectances.

Bowker, D. E.↗

Measurements of mantle wave velocities and inversion for lateral heterogeneity and anisotropy. II - Analysis by the single-station method

In the present investigation, the single-station method reported by Brune et al. (1960) is utilized for an analysis of long-period Love(G) and Rayleigh(R) waves recorded on digital seismic networks. The analysis was conducted to study the lateral heterogeneity of surface wave velocities. The data set is examined, and a description is presented of the single-station method. Attention is given to an error analysis for velocity measurements, the estimation of geographical distribution of surface wave velocities, the global distribution of surface wave velocities, and the correlation between the surface wave velocities and the heat flow on the geoid. The conducted measurements and inversions of surface wave velocities are used as a basis to derive certain conclusions. It is found that the application of the single-station method to long-period surface waves recorded on digital networks makes it possible to reach an accuracy level comparable to great circle velocity measurements.

Nakanishi, I.↗