Search NASA⌕ Search

SEARCH · Search NASA

Results for “Local Method”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
NASA NTRS1978

Sound propagation in a duct of periodic wall structure

A boundary condition, which accounts for the coupling in the sections behind the duct boundary, is given for the sound-absorbing duct with a periodic structure of the wall lining and using regular partition walls. The soundfield in the duct is suitably described by the method of differences. For locally active walls this renders an explicit approximate solution for the propagation constant. Coupling may be accounted for by the method of differences in a clear manner. Numerical results agree with measurements and yield information which has technical applications.

Kurze, U.↗
NASA NTRS1993

The theoretical accuracy of Runge-Kutta time discretizations for the initial boundary value problem: A careful study of the boundary error

The conventional method of imposing time dependent boundary conditions for Runge-Kutta (RK) time advancement reduces the formal accuracy of the space-time method to first order locally, and second order globally, independently of the spatial operator. This counter intuitive result is analyzed in this paper. Two methods of eliminating this problem are proposed for the linear constant coefficient case: (1) impose the exact boundary condition only at the end of the complete RK cycle, (2) impose consistent intermediate boundary conditions derived from the physical boundary condition and its derivatives. The first method, while retaining the RK accuracy in all cases, results in a scheme with much reduced CFL condition, rendering the RK scheme less attractive. The second method retains the same allowable time step as the periodic problem. However it is a general remedy only for the linear case. For non-linear hyperbolic equations the second method is effective only for for RK schemes of third order accuracy or less. Numerical studies are presented to verify the efficacy of each approach.

Carpenter, Mark H.↗
DOE OSTI2024

CLimate Impact: Determining Etiology thRough pAthways (CLDERA)

Climate impacts have broad economic, health, political, and national security ramifications. Societally relevant impacts are typically farther downstream, are the product of multiple interacting processes, and can arise over small regions and timeframes because their sources are short-term and localized. Short-term forcings (as can be seen in volcanic eruptions, climatic tipping points (e.g., the collapse of rainforests or the disappearance of sea ice), or in increasingly plausible climate interventions) fundamentally possess low signal-to-noise and could benefit from accounting for the multiple conditional processes through which a downstream impact arises. Under the Grand Challenge LDRD CLDERA (CLimate impacts: Discovering Etiology thRough pAthways), we have developed tools to enable downstream impact attribution from geographically and temporally localized source forcings in the climate. CLDERA developed methods that can distinguish how a localized source drives the climate system to respond with particular impacts. The how is embodied in pathways – the spatio-temporally evolving chain of physical processes that connects a source to a series of increasingly distant impacts. Novel analytic methods in pursuit of downstream impact attribution were developed and demonstrated on simulations and observations of the 1991 eruption of Mt. Pinatubo in the Philippines. As described within this report we have • developed stratospheric expertise and aerosol modeling capabilities in E3SM, • created original methods to detect and model pathways from source-to-impact, and • advanced climate attribution through novel methods, cases, and approaches. Further, CLDERA developed a tiered verification process consisting of controlled datasets to prototype, verify, and refine the original method development. CLDERA increased Sandia’s footprint in the climate analytics community and developed new climate collaborations whilst also creating a cadre of climate analysts at Sandia. The products from CLDERA have been extensive with a total of 9 journal articles published, 12 articles submitted and under review, and an additional 8 articles in preparation. We have produced 1750 simulated years and developed 9 code-bases. This report details these accomplishments and serves as a summary of the work completed during the CLDERA Grand Challenge.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Adaptive Online Multivariate Signal Extraction With Locally Weighted Robust Polynomial Regression

High-frequency, multivariate data collected in real-time and used to control or make decisions regarding a process’ operation often contain some noise and outliers. Thus, a method to extract the signal is needed in order to reduce the number and magnitude of control-based adjustments that are implemented. Such a method must be (i) online, depending only on past and current observations; (ii) fast, producing a smooth value more quickly than the measurement frequency; (iii) robust, ignoring brief bursts of erroneously measured values; (iv) multivariate, ignoring observations that are jointly unusual; (v) adaptive, adjusting to periods of rapid fluctuation in the signal versus periods of stability; and (vi) purely data-driven, not incorporating any information about the process from which the data are collected. Most existing methods are only able to address a subset of these six features. Furthermore, we also require the method to be nonlinear, providing a local nonlinear estimate of the signal. In this work, we propose a novel, real-time signal extraction method based on a local, robust polynomial fit. We demonstrate the performance of our method compared to a state-of-the-art competitor through simulation. For illustration, the methodology is applied to data collected from a reverse osmosis water treatment process.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Automated identification of local contamination in remote atmospheric composition time series

Abstract. Atmospheric observations in remote locations offer a possibility of exploring trace gas and particle concentrations in pristine environments. However, data from remote areas are often contaminated by pollution from local sources. Detecting this contamination is thus a central and frequently encountered issue. Consequently, many different methods exist today to identify local contamination in atmospheric composition measurement time series, but no single method has been widely accepted. In this study, we present a new method to identify primary pollution in remote atmospheric datasets, e.g., from ship campaigns or stations with a low background signal compared to the contaminated signal. The pollution detection algorithm (PDA) identifies and flags periods of polluted data in five steps. The first and most important step identifies polluted periods based on the derivative (time derivative) of a concentration over time. If this derivative exceeds a given threshold, data are flagged as polluted. Further pollution identification steps are a simple concentration threshold filter, a neighboring points filter (optional), a median, and a sparse data filter (optional). The PDA only relies on the target dataset itself and is independent of ancillary datasets such as meteorological variables. All parameters of each step are adjustable so that the PDA can be “tuned” to be more or less stringent (e.g., flag more or fewer data points as contaminated). The PDA was developed and tested with a particle number concentration dataset collected during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the central Arctic. Using strict settings, we identified 62 % of the data as influenced by local contamination. Using a second independent particle number concentration dataset also collected during MOSAiC, we evaluated the performance of the PDA against the same dataset cleaned by visual inspection. The two methods agreed in 94 % of the cases. Additionally, the PDA was successfully applied to a trace gas dataset (CO2), also collected during MOSAiC, and to another particle number concentration dataset, collected at the high-altitude background station Jungfraujoch, Switzerland. Thus, the PDA proves to be a useful and flexible tool to identify periods affected by local contamination in atmospheric composition datasets without the need for ancillary measurements. It is best applied to data representing primary pollution. The user-friendly and open-access code enables reproducible application to a wide suite of different datasets. It is available at https://doi.org/10.5281/zenodo.5761101 (Beck et al., 2021).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1981

Rigorous numerical treatment of the no-slip condition in a vorticity formulation

It is shown that a rigorous mathematical treatment of the boundary conditions for rigid no-slip surfaces requires, in general, that two passes be made in solving Poisson's equation. A Fourier solution procedure was the key to this realization. It is also shown that a corresponding method exists for finite and, for the same local approximation, the usual one step method gives the same result for the geometry considered here. The more fundamental two step method gives a new insight into the physical significance of boundary vorticity.

Gazdag, J.↗
NASA NTRS1990

Mode localization in multi-span beams

The influence of numerous effects on mode localization in multi-span beams is investigated. Finite-element methods are used to study localization as a function of: Timoshenko beam effects; beam end conditions; span length, mass, and stiffness imperfection; viscous damping; axial force; transverse support and rotational coupling stiffness; and modeling resolution. Three configurations are studied, commencing with two different two-span models, and culminating in a ten-span configuration resembling lattice-type large space structures. Results indicate that, in addition to the ratio of imperfection to coupling stiffness being an important localization parameter, transverse support stiffness and Timoshenko beam effects greatly affect the tendency of a structure to exhibit localized modes.

Lust, S. D.↗
NASA NTRS2013

The Effect of Fiber Strength Stochastics and Local Fiber Volume Fraction on Multiscale Progressive Failure of Composites

Continuous fiber unidirectional polymer matrix composites (PMCs) can exhibit significant local variations in fiber volume fraction as a result of processing conditions that can lead to further local differences in material properties and failure behavior. In this work, the coupled effects of both local variations in fiber volume fraction and the empirically-based statistical distribution of fiber strengths on the predicted longitudinal modulus and local tensile strength of a unidirectional AS4 carbon fiber/ Hercules 3502 epoxy composite were investigated using the special purpose NASA Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC); local effective composite properties were obtained by homogenizing the material behavior over repeating units cells (RUCs). The predicted effective longitudinal modulus was relatively insensitive to small (~8%) variations in local fiber volume fraction. The composite tensile strength, however, was highly dependent on the local distribution in fiber strengths. The RUC-averaged constitutive response can be used to characterize lower length scale material behavior within a multiscale analysis framework that couples the NASA code FEAMAC and the ABAQUS finite element solver. Such an approach can be effectively used to analyze the progressive failure of PMC structures whose failure initiates at the RUC level. Consideration of the effect of local variations in constituent properties and morphologies on progressive failure of PMCs is a central aspect of the application of Integrated Computational Materials Engineering (ICME) principles for composite materials.

multiscale analysis↗
DOE OSTI2022

Relativistic Density Functional NMR Tensors Analyzed with Spin–free Localized Molecular Orbitals

The implementation of fast relativistic methods based on density functional theory, in conjunction with localized molecular orbital (LMO) based analysis, allows straightforward interpretations of NMR parameters in terms of contributions from core shells, lone pairs, and bonds, for compounds containing elements from across the periodic table. We present a conceptual review of a frequently used LMO analysis of NMR parameters calculated in the presence of spin-orbit interactions and other relativistic effects. An accompanying example focuses on the 15 N shielding in a heavy metal complex.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1975

A multilevel control system for the large space telescope

A multilevel scheme was proposed for control of Large Space Telescope (LST) modeled by a three-axis-six-order nonlinear equation. Local controllers were used on the subsystem level to stabilize motions corresponding to the three axes. Global controllers were applied to reduce (and sometimes nullify) the interactions among the subsystems. A multilevel optimization method was developed whereby local quadratic optimizations were performed on the subsystem level, and global control was again used to reduce (nullify) the effect of interactions. The multilevel stabilization and optimization methods are presented as general tools for design and then used in the design of the LST Control System. The methods are entirely computerized, so that they can accommodate higher order LST models with both conceptual and numerical advantages over standard straightforward design techniques.

D D Siljak↗
DOE OSTI2021

Probe the Localized Electrochemical Environment Effects and Electrode Reaction Dynamics for Metal Batteries using In Situ 3D Microscopy

Uncontrollable dendrite growth is closely related to non-uniform reaction environments. However, there is a lack of understanding and analysis methods to probe the localized electrochemical environment (LEE). Here the effects of the LEE are investigated, including localized ion concentrations, current density, and electric potential, on metal plating/stripping dynamics and dendrite minimization. A novel in situ 3D microscopy technique is developed to image the morphology dynamics and deposition rate of Zn plating/stripping processes on 3D Zn–Mn anodes. Using the in situ 3D microscope, the electrode morphology changes during the reactions are directly imaged and Zn deposition rate maps at different time points are obtained. It is found that reaction kinetics are highly correlated to LEE and electrode morphology. To further quantify the LEE effects, the digital twin technique is employed that allows the accurate calculation of the electrochemical environments, such as localized ion concentrations, current density, and electric potential, which cannot be directly measured from experiments. We found that the curvature of the 3D electrode surface determines the LEE and significantly influences reaction kinetics. This provides a new strategy to minimize the dendrite formation by designing and optimizing the 3D geometry of the electrode to control the LEE.

36 MATERIALS SCIENCE↗
DOE OSTI2021

In situ and operando force-based atomic force microscopy for probing local functionality in energy storage materials

Electrochemical energy storage is the key enabling component of electric vehicles and solar-/wind-based energy technologies. The enhancement of energy stored requires the detailed understanding of charge storage mechanisms and local electrochemical and electromechanical phenomena over a variety of length scales from atoms to full cells. Classical electrochemical techniques, such as voltammetry, represent the macroscopic electrochemical properties, and consequently do not allow to extract important information about local electrochemical reactions, ions adsorption, intercalations, and transport. Understanding, controlling, and tuning the local electrochemical functionalities in functional energy materials require in situ/operando techniques which limit the use of structural and functional characterization techniques that provide local information. Here, force-based atomic force microscopies (AFMs) have provided novel insights into locally probing electrochemical mechanisms on tens of nanometer and even molecular length scales and provide a viable pathway to probe electrochemical processes in situ/operando. In this review, we highlight the contributions in the development and application of force-based AFM methods to elucidate the local charge storage mechanism in a variety of energy-related materials. We will focus in particular on methods or AFM modalities in a liquid electrolyte environment.

25 ENERGY STORAGE↗
DOE OSTI2022

Realistic magnetic thermodynamics by local quantization of a semiclassical Heisenberg model

Abstract Classical Monte Carlo simulation of the Heisenberg model poorly describes many thermodynamic phenomena due to its neglect of the quantum nature of spins. Alternatively, we discuss how to semiclassically approach the quantum problem and demonstrate a simple method for introducing a locally approximate form of spin quantization. While the procedure underestimates magnetic short-range order, our results suggest a simple correction for recovering realistic spin–spin correlations above the critical temperature. Moreover, ensemble fluctuations are found to provide reasonably accurate thermodynamics, largely reproducing quantum mechanically calculated heat capacities and experimental magnetometry for ferromagnetic Fe and antiferromagnetic RbMnF 3 . Extensions of the method are proposed to address remaining inaccuracies.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A family of independent Variable Eddington Factor methods with efficient preconditioned iterative solvers

We present a family of discretizations for the Variable Eddington Factor (VEF) equations that have high-order accuracy on curved meshes and efficient preconditioned iterative solvers. The VEF discretizations are combined with the Discontinuous Galerkin transport discretization from to form effective high-order, linear transport methods. The VEF discretizations are derived by extending the unified analysis of Discontinuous Galerkin methods for elliptic problems presented by Arnold et al. to the VEF equations. This framework is used to define analogs of the interior penalty, second method of Bassi and Rebay, minimal dissipation local Discontinuous Galerkin, and continuous finite element methods. The analysis of subspace correction preconditioners, which use a continuous operator to iteratively precondition the discontinuous discretization, is extended to the case of the non-symmetric VEF system. Numerical results demonstrate that the VEF discretizations have arbitrary-order accuracy on curved meshes, preserve the thick diffusion limit, and are effective on a proxy problem from thermal radiative transfer in both outer transport iterations and inner preconditioned linear solver iterations. We demonstrate that the VEF solution converges to the S N transport solution as the mesh is refined on both problems with smooth and non-smooth behavior in angle. Parallel performance studies show that the interior penalty VEF discretization's linear solve weak scales out to 1024 processors and strong scales well on a single node. Particular attention is paid to the parallel performance of the VEF algorithm when used in combination with a parallel block Jacobi transport sweep.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

X-ray scattering based scanning tomography for imaging and structural characterization of cellulose in plants

X-ray and neutron scattering have long been used for structural characterization of cellulose in plants. Due to averaging over the illuminated sample volume, these measurements traditionally overlooked the compositional and morphological heterogeneity within the sample. Here, a scanning tomographic imaging method is described, using contrast derived from the X-ray scattering intensity, for virtually sectioning the sample to reveal its internal structure at a resolution of a few micrometres. This method provides a means for retrieving the local scattering signal that corresponds to any voxel within the virtual section, enabling characterization of the local structure using traditional data-analysis methods. This is accomplished through tomographic reconstruction of the spatial distribution of a handful of mathematical components identified by non-negative matrix factorization from the large dataset of X-ray scattering intensity. Joint analysis of multiple datasets, to find similarity between voxels by clustering of the decomposed data, could help elucidate systematic differences between samples, such as those expected from genetic modifications, chemical treatments or fungal decay. The spatial distribution of the microfibril angle can also be analyzed, based on the tomographically reconstructed scattering intensity as a function of the azimuthal angle.

36 MATERIALS SCIENCE↗
NASA NTRS1976

Efficient reanalysis of structures by a direct modification method

A procedure for the local stiffness modifications of large structures is described. It enables structural modifications without an a priori definition of the changes in the original structure and without loss of efficiency due to multiple loading conditions. The solution procedure, implemented in NASTRAN, involved the decomposed stiffness matrix and the displacement vectors of the original structure. It solves the modified structure exactly, irrespective of the magnitude of the stiffness changes. In order to investigate the efficiency of the present procedure and to test its applicability within a design environment, several real and large structures were solved. The results of the efficiency studies indicate that the break-even point of the procedure varies between 8% and 60% stiffness modifications, depending upon the structure's characteristics and the options employed.

Raibstein, A. I.↗
NASA NTRS1980

Grid generation for time dependent problems: Criteria and methods

The problem of generating local mesh refinements when solving time dependent partial differential equations was examined. The problem of creating an appropriate grid, given a mesh function h defined over the spatial domain is discussed. A data structure which permits efficient use of the resulting grid is described. A good choice for h is an estimate of the local truncation error, and several ways to estimate it are discussed. The efficiency and implementation problems of these error estimates were compared.

Berger, M.↗
DOE OSTI2021

A Data-Fusion Method using Bayesian Approach to Enhance Raw Data Accuracy of Position and Distance Measurements for Connected Vehicles

Accurate positioning of vehicles is a critical element of autonomous and connected vehicle systems. Most of other studies heavily focused on enhancing simultaneous localization and mapping (SLAM) methods, i.e., constructing or updating a map of an unknown environment and tracking an object within the map. This paper provides a method that can, in addition to existing SLAM or relevant methods, enhance the raw measurements of position and distance. The basic idea of this study is to identify and update the error distribution of each data source by combining all available information. A Bayesian approach was incorporated to estimate and update the error distribution of individual data sources or sensors. The proposed method can be conducted in real-time environments, and a self-learning scheme determines whether enough data has been collected to further improve the accuracy of such measurements. The simulated experiments show that the proposed model noticeably improves the accuracy of position and distance measurements. Especially, the estimated biases of position coordinates and distance measures are very close to the biases of true error distributions, with the R-squared over 0.98. A similar approach can also be utilized to enhance accuracy of other sensors or measurements in connected vehicle or relevant systems, where multi-data sources are available.

Lim, Hyeonsup↗