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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Development of Segregated Thermal-Hydraulics Solvers in MOOSE

The simulation of fluid flows is an essential part of the design and analysis of nuclear systems. Algorithms able to simulate flows at different fidelity levels are available in the Multiphysics Object-Oriented Simulation Environment (MOOSE) and MOOSE-based applications such as Pronghorn \cite{novak2018pronghorn}, Pronghorn-Subchannel, RELAP-7, and SAM. Currently, significant effort is being invested in the development of coarse-mesh Computational Fluid Dynamics (CFD) capabilities within MOOSE and Pronghorn for the simulation of Generation IV nuclear reactors. Traditionally, the solution algorithms in MOOSE have relied on Newton or quasi-Newton methods (such as the preconditioned Jacobian-free Newton-Krylov method) where residuals and Jacobians (or approximations thereof) are constructed. Both Newton and quasi-Newton methods require the solution of a linear system at each nonlinear Newton iteration with the Jacobian as the system matrix. The Jacobian contains blocks originating from all variables in the problem (i.e., for thermal-hydraulics at least pressure, velocities, and temperature). Due to the formulation of the problem in a general multiphysics setting on unstructured mesh, creating a good preconditioner for the linear system can be challenging, thus many fluid applications have utilized direct solver-based methods such as LU factorization. However, with increasing system size and complexity in multi-dimensional problems, the direct solution of linear systems becomes computationally expensive both in execution time and and memory. For this reason, recent effort has focused on adapting segregated solution algorithms for CFD problems in MOOSE. These algorithms use fixed-point iteration between segregated systems whose assembly and preconditioning are easier those of the monolithic system. Initial results show that the segregated solution algorithm outperforms the monolithic approach in terms of memory usage and for large 3D problems in terms of CPU time as well.

42 ENGINEERING↗
NASA NTRS2016

Applicability and Limitations of Reliability Allocation Methods

Reliability allocation process may be described as the process of assigning reliability requirements to individual components within a system to attain the specified system reliability. For large systems, the allocation process is often performed at different stages of system design. The allocation process often begins at the conceptual stage. As the system design develops, more information about components and the operating environment becomes available, different allocation methods can be considered. Reliability allocation methods are usually divided into two categories: weighting factors and optimal reliability allocation. When properly applied, these methods can produce reasonable approximations. Reliability allocation techniques have limitations and implied assumptions that need to be understood by system engineers. Applying reliability allocation techniques without understanding their limitations and assumptions can produce unrealistic results. This report addresses weighting factors, optimal reliability allocation techniques, and identifies the applicability and limitations of each reliability allocation technique.

Reliability allocation↗
NASA NTRS1997

Defining Factors, Goals and Criteria for Reusable Component Evaluation

This paper presents an approach for defining evaluation criteria for reusable software components. We introduce a taxonomy of factors that influence selection, describe each of them, and present a hierarchical decomposition method for deriving reuse goals from factors and formulating the goals into an evaluation criteria hierarchy. We present some highlights from two case studies in which the approach was applied. The approach presented in this paper is a part of the Off-The-Shelf Option (OTSO) method that has been developed for reuseable component selection process.

Kontio, Jyrki↗
DOE OSTI2020

Calculation of the C 12 + C 12 sub-barrier fusion cross section in an imaginary-time-dependent mean field theory

The 12 C + 12 C sub-barrier fusion cross section is calculated within the framework of a time-dependent Hartree-Fock-based classical model using the Feynman path-integral method. The modified astrophysical S* factor is compared to direct and indirect experimental results. A good agreement with the direct data is found. In the lower-energy region where recent analyses of experimental data obtained with the Trojan horse method (THM) lead to contrasting results, the model predicts a nonresonant S* factor half-way between those results. Low-energy resonances revealed in the THM data are added to the calculation, and the relative reaction rate in the Gamow region is calculated. In particular, including 0 + resonances result in some agreement with the THM data. Here, the role of different resonances is discussed in detail, and their influence on the reaction rate at temperatures relevant to stellar evolution is investigated.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1984

Advanced reliability method for fatigue analysis

When design factors are considered as random variables and the failure condition cannot be expressed by a closed form algebraic inequality, computations of risk (or probability of failure) may become extremely difficult or very inefficient. This study suggests using a simple and easily constructed second degree polynomial to approximate the complicated limit state in the neighborhood of the design point; a computer analysis relates the design variables at selected points. Then a fast probability integration technique (i.e., the Rackwitz-Fiessler algorithm) can be used to estimate risk. The capability of the proposed method is demonstrated in an example of a low cycle fatigue problem for which a computer analysis is required to perform local strain analysis to relate the design variables. A comparison of the performance of this method is made with a far more costly Monte Carlo solution. Agreement of the proposed method with Monte Carlo is considered to be good.

Wu, Y.-T.↗
NASA NTRS1993

On the prediction of multigrid efficiency through local mode analysis

A single grid local mode analysis is used to predict the smoothing properties of numerical schemes for solving the Navier-Stokes equations with factorization based on Stone's Strongly Implicit Method. Four difference approximations for the convection terms are considered, namely, hybrid, central, second-order upwind, and third-order upwind. Smoothing factors from the analysis are compared with practical convergence factors in a multigrid method for flow over a backward facing step and it is found that the local mode analysis correctly predicts the effects of Reynolds number and higher-order schemes.

Wilson, R. V.↗
DOE OSTI2025

Factors That Influence Variability in Stress-Drop Measurements Using Spectral Decomposition and Spectral-Ratio Methods for the 2019 Ridgecrest Earthquake Sequence

Stress drop is a fundamental parameter related to earthquake source physics, but is hard to measure accurately. To better understand how different factors influence stress-drop measurements, we compare two different methods using the Ridgecrest stress-drop validation data set: spectral decomposition (SD) and spectral ratio (SR), each with different processing options. Here, we also examine the influence of spectral complexity on source parameter measurement. Applying the SD method, we find that frequency bandwidth and time-window length could influence spectral magnitude calibration, while depth-dependent attenuation is important to correctly map stress-drop variations. For the SR method, we find that the selected source model has limited influence on the measurements; however, the Boatwright model tends to produce smaller standard deviation and larger magnitude dependence than the Brune model. Variance reduction threshold, frequency bandwidth, and time-window length, if chosen within an appropriate parameter range, have limited influence on source parameter measurement. For both methods, wave type, attenuation correction, and spectral complexity strongly influence the result. The scale factor that quantifies the magnitude dependence of stress drop show large variations with different processing options, and earthquakes with complex source spectra deviating from the Brune-type source models tend to have larger scale factor than earthquakes without complexity. Based on these detailed comparisons, we make a few specific suggestions for data processing workflows that could help future studies of source parameters and interpretations.

58 GEOSCIENCES↗
NASA NTRS1978

Satellite Power System (SPS) student participation

A assessment of methods which are appropriate to initiate student participation in the discussion of a satellite power system (SPS) is presented. Methods which are incorporated into the campus environment and the on-going learning experience are reported. The discussion of individual methods for student participation includes a description of the technique, followed by comments on its enhancing and limiting factors, references to situations where the method has been demonstrated, and a brief consideration of cost factors. The two categories of recommendations presented are: an outline of fourteen recommendations addressing specific activities related to student participation in the discussion of SPS, and three recommendations pertaining to student participation activities in general.

Ladwig, A.↗
DOE OSTI2024

Decomposing causality into its synergistic, unique, and redundant components

Causality lies at the heart of scientific inquiry, serving as the fundamental basis for understanding interactions among variables in physical systems. Despite its central role, current methods for causal inference face significant challenges due to nonlinear dependencies, stochastic interactions, self-causation, collider effects, and influences from exogenous factors, among others. While existing methods can effectively address some of these challenges, no single approach has successfully integrated all these aspects. Here, we address these challenges with SURD: Synergistic-Unique-Redundant Decomposition of causality. SURD quantifies causality as the increments of redundant, unique, and synergistic information gained about future events from past observations. The formulation is non-intrusive and applicable to both computational and experimental investigations, even when samples are scarce. We benchmark SURD in scenarios that pose significant challenges for causal inference and demonstrate that it offers a more reliable quantification of causality compared to previous methods.

applied mathematics↗
DOE OSTI2020

Beyond integration: modeling every pixel to obtain better structure factors from stills

Most crystallographic data processing methods use pixel integration. In serial femtosecond crystallography (SFX), the intricate interaction between the reciprocal lattice point and the Ewald sphere is integrated out by averaging symmetrically equivalent observations recorded across a large number (10 4 -10 6 ) of exposures. Although sufficient for generating biological insights, this approach converges slowly, and using it to accurately measure anomalous differences has proved difficult. This report presents a novel approach for increasing the accuracy of structure factors obtained from SFX data. A physical model describing all observed pixels is defined to a degree of complexity such that it can decouple the various contributions to the pixel intensities. Model dependencies include lattice orientation, unit-cell dimensions, mosaic structure, incident photon spectra and structure factor amplitudes. Maximum likelihood estimation is used to optimize all model parameters. The application of prior knowledge that structure factor amplitudes are positive quantities is included in the form of a reparameterization. The method is tested using a synthesized SFX dataset of ytterbium(III) lysozyme, where each X-ray laser pulse energy is centered at 9034 eV. This energy is 100 eV above the Yb 3+ L -III absorption edge, so the anomalous difference signal is stable at 10 electrons despite the inherent energy jitter of each femtosecond X-ray laser pulse. This work demonstrates that this approach allows the determination of anomalous structure factors with very high accuracy while requiring an order-of-magnitude fewer shots than conventional integration-based methods would require to achieve similar results.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1988

Strain intensity factor approach for predicting the strength of continuously reinforced metal matrix composites

A method was previously developed to predict the fracture toughness (stress intensity factor at failure) of composites in terms of the elastic constants and the tensile failing strain of the fibers. The method was applied to boron/aluminum composites made with various proportions of 0 to + or - 45 deg plies. Predicted values of fracture toughness were in gross error because widespread yielding of the aluminum matrix made the compliance very nonlinear. An alternate method was developed to predict the strain intensity factor at failure rather than the stress intensity factor because the singular strain field was not affected by yielding as much as the stress field. Strengths of specimens containing crack-like slits were calculated from predicted failing strains using uniaxial stress-strain curves. Predicted strengths were in good agreement with experimental values, even for the very nonlinear laminates that contained only + or - 45 deg plies. This approach should be valid for other metal matrix composites that have continuous fibers.

Poe, C. C., Jr.↗
NASA NTRS1989

Strain intensity factor approach for predicting the strength of continuously reinforced metal matrix composites

A method was previously developed to predict the fracture toughness (stress intensity factor at failure) of composites in terms of the elastic constants and the tensile failing strain of the fibers. The method was applied to boron/aluminum composites made with various proportions of 0 deg and +/- 45 deg plies. Predicted values of fracture toughness were in gross error because widespread yielding of the aluminum matrix made the compliance very nonlinear. An alternate method was develolped to predict the strain intensity factor at failure rather than the stress intensity factor because the singular strain field was not affected by yielding as much as the stress field. Far-field strains at failure were calculated from the strain intensity factor, and then strengths were calculated from the far-field strains using uniaxial stress-strain curves. The predicted strengths were in good agreement with experimental values, even for the very nonlinear laminates that contained only +/- 45 deg plies. This approach should be valid for other metal matrix composites that have continuous fibers.

Poe, Clarence C., Jr.↗
DOE OSTI2022

General-Purpose Unsupervised Cyber Anomaly Detection via Non-Negative Tensor Factorization

Distinguishing malicious anomalous activities from unusual but benign activities is a fundamental challenge for cyber defenders. Prior studies have shown that statistical user behavior analysis yields accurate detections by learning behavior profiles from observed user activity. These unsupervised models are able to generalize to unseen types of attacks by detecting deviations from normal behavior, without knowledge of specific attack signatures. However, approaches proposed to date based on probabilistic matrix factorization are limited by the information conveyed in a two-dimensional space. Non-negative tensor factorization, on the other hand, is a powerful unsupervised machine learning method that naturally models multi-dimensional data, capturing complex and multi-faceted details of behavior profiles. Herein, our new unsupervised statistical anomaly detection methodology matches or surpasses state-of-the-art supervised learning baselines across several challenging and diverse cyber application areas, including detection of compromised user credentials, botnets, spam e-mails, and fraudulent credit card transactions.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2021

Deconvolution of SNPP VIIRS Solar Diffuser Bidirectional Reflectance Distribution Function On-orbit Change Factor

The Earth-observing Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership satellite regularly calibrates its reflective solar bands (RSBs), primarily through observing an onboard sunlit solar diffuser (SD). The on-orbit change of the value of the SD bidirectional reflectance distribution function (BRDF) is quantified by a numerical factor, called the H-factor, and is determined by the onboard SD stability monitor (SDSM). Because the spectral response function of an SDSM detector spreads in wavelength, the directly measured H-factor is the true H-factor convolved with the spectral response function. To find the true H-factor, we use the traditional direct method and an innovative iterative approach to separately deconvolve the measured H-factor. Our iterative approach relies on two properties of the SDSM detector spectral response function: the central peak width is narrow enough so that the H-factor does not change much over the peak width, and the dominance of the spectral response function’s integral with respect to the wavelength over the width. The iterative approach is more accurate, of a smaller noise impact, much more flexible in terms of interpolation and extrapolation of function values, and faster. We have used deconvolved H-factors to calibrate the NASA SNPP VIIRS RSB Collections 1 and 2 Level-1B products.

SNPP VIIRS↗
NASA NTRS1996

Further evaluation of traditional icing scaling methods

This report provides additional evaluations of two methods to scale icing test conditions; it also describes a hybrid technique for use when scaled conditions are outside the operating envelope of the test facility. The first evaluation is of the Olsen method which can be used to scale the liquid-water content in icing tests, and the second is the AEDC (Ruff) method which is used when the test model is less than full size. Equations for both scaling methods are presented in the paper, and the methods were evaluated by performing icing tests in the NASA Lewis Icing Research Tunnel (IRT). The Olsen method was tested using 53 cm diameter NACA 0012 airfoils. Tests covered liquid-water-contents which varied by as much as a factor of 1.8. The Olsen method was generally effective in giving scale ice shapes which matched the reference shapes for these tests. The AEDC method was tested with NACA 0012 airfoils with chords from 18 cm to 53 cm. The 53 cm chord airfoils were used in reference tests, and 1/2 and 1/3 scale tests were made at conditions determined by applying the AEDC scaling method. The scale and reference airspeeds were matched in these tests. The AEDC method was found to provide fairly effective scaling for 1/2 size tests, but for 1/3 size models, scaling was generally less effective. In addition to these two scaling methods, a hybrid approach was also tested in which the Olsen method was used to adjust the LWC after size was scaled using the constant Weber number method. This approach was found to be an effective way to test when scaled conditions would otherwise be outside the capability of the test facility.

Anderson, David N.↗
DOE OSTI2021

Passive method to measure strength of turbulence

Disclosed is a method to passively measure and calculate the strength of turbulence via the index of refraction structure constant Cn2 from video imagery gathered by an imaging device, such as a video camera. Processing may occur with any type computing device utilizing a processor executing machine executable code stored on memory. This method significantly simplifies instrumentation requirements, reduces cost, and provides rapid data output. This method combines an angle of arrival methodology, which provides scale factors, with a new spatial/temporal frequency domain method. As part of the development process, video imagery from high speed cameras was collected and analyzed. The data was decimated to video rates such that statistics could be computed and used to confirm that this passive method accurately characterizes the atmospheric turbulence. Cn2 accuracy from this method compared well with scintillometer data through two full orders of magnitude and more capability is expected beyond this verification.

O'Neill, Mary Morabito↗
NASA NTRS1979

An implicit factored scheme for the compressible Navier-Stokes equations. II - The numerical ODE connection

An attempt is made to establish a connection between linear multistep methods for applications to ordinary differential equations and their extension (by approximate factorization) to alternating direction implicit methods for partial differential equations. An earlier implicit factored scheme for the compressible Navier-Stokes equations is generalized by innovations that (1) increase the class of temporal difference schemes to include all linear multistep methods, (2) optimize the class of unconditionally stable factored schemes by a new choice of unknown variable, and (3) improve the computational efficiency by the introduction of quasi-one-leg methods.

Beam, R. M.↗
DOE OSTI2024

GPU Accelerated Sparse Cholesky Factorization

The solution of sparse symmetric positive definite linear systems is an important computational kernel in large-scale scientific and engineering modeling and simulation. We will solve the linear systems using a direct method, in which a Cholesky factorization of the coefficient matrix is performed using a right-looking approach and the resulting triangular factors are used to compute the solution. Sparse Cholesky factorization is compute intensive. In this work we investigate techniques for reducing the factorization time in sparse Cholesky factorization by offloading some of the dense matrix operations on a GPU. We will describe the techniques we have considered. We achieved up to 4x speedup compared to the CPU-only version.

Karsavuran, M Ozan↗