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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Coherent Optical Receiver for PPM Signals under Atmospheric Turbulence

Adaptive combining of experimentally obtained heterodyned pulse position modulated (PPM) signals with pulse-to-pulse coherence in the presence of simulated spatial distortions resembling atmospheric turbulence is demonstrated. The adaptively combined PPM signals are phased up via an LMS algorithm suitably optimized to operate with PPM in the presence of additive shot-noise. A convergence analysis of the algorithm is presented, and results with both, computer simulated and experimentally obtained PPM signals are analyzed.

coherent detection↗
NASA NTRS2011

A Record-High Ocean Bottom Pressure in the South Pacific Observed by GRACE

In late 2009 to early 2010, the Gravity Recovery and Climate Experiment (GRACE) satellite pair observed a record increase in ocean bottom pressure (OBP) over a large mid-latitude region of the South East Pacific. Its magnitude is substantially larger than other oceanic events in the Southern Hemisphere found in the entire GRACE data records (2003-2010) on multi-month time scales. The OBP data help to understand the nature of a similar signal in sea surface height (SSH) anomaly observed by altimetry: the SSH increase is mainly due to mass convergence. Analysis of the barotropic vorticity equation using scatterometer data, atmospheric reanalysis product, and GRACE and altimeter an atmospheric reanalysis product observations suggests that the observed OBP/SSH signal was primarily caused by wind stress curl associated with a strong and persistent anticyclone in late 2009 in combination with effects of planetary vorticity gradient, bottom topography, and friction

Gravity Recovery and Climate Experiment (GRACE)↗
NASA NTRSDate not supplied

History and Status of the CDISC Aerodynamic Design Method

This paper will review the development and application of the CDISC aerodynamic design method that began in the early 1980s and continues in active use today. The method uses an iterative, knowledge-based approach that has been coupled with numerous flow solvers utilizing a variety of grid types and levels of flow physics. It has been applied to configurations varying in complexity from 2-D airfoils to full 3-D aircraft at flow conditions ranging from low-speed, high-lift to supersonic cruise. The knowledge-based approach provides a very rapid design process, with designs typically completed in approximately 1-2x the time required for an initial converged analysis of the baseline. The evolution of the method as it tracked the expansive growth of grid and flow solver technology, along with some major applications over 5 decades, are given, followed by a description of the philosophy and process used in design. Finally, an example of its use in a preliminary design environment is given.

CDISC↗
NASA NTRSDate not supplied

History and Status of the CDISC Aerodynamic Design Method

This paper will review the development and application of the CDISC aerodynamic design method that began in the early 1980s and continues in active use today. The method uses an iterative, knowledge-based approach that has been coupled with numerous flow solvers utilizing a variety of grid types and levels of flow physics. It has been applied to configurations varying in complexity from 2-D airfoils to full 3-D aircraft at flow conditions ranging from low-speed, high-lift to supersonic cruise. The knowledge-based approach provides a very rapid design process, with designs typically completed in approximately 1-2x the time required for an initial converged analysis of the baseline. The evolution of the method as it tracked the expansive growth of grid and flow solver technology, along with some major applications over 5 decades, are given, followed by a description of the philosophy and process used in design. Finally, an example of its use in a preliminary design environment is given.

CDISC↗
NASA NTRS2026

Development and Experimental Validation of a Path-Dependent Spin Forming Finite Element Model

Spin forming is an advanced manufacturing process widely used in the aerospace and defense sectors to produce lightweight, high-strength cylindrical components with tight dimensional tolerances. This study explores the applicability of the path-dependent Mechanical Threshold Stress (MTS) constitutive model by simulating the evolution of geometry, machining forces, and plastic deformation during the spin forming of a 10-mm thick 6061-O aluminum cylinder. While numerical modeling of spin forming has advanced substantially over the past decade, systematic verification and experimental validation of material models remain limited, particularly in predicting through-thickness process evolution. The MTS model, incorporating a Voce hardening rule, is employed for its ability to represent cyclic loading, rapidly varying temperature fields, and strain rates characteristic of spin forming. Numerical convergence analysis indicates discretization uncertainties between 0.3% and 9.2% for key quantities of interest. Experimental validation demonstrates that the MTS model, when implemented with a verified mesh, accurately reproduces both elastic and plastic behavior of 6061-O aluminum, predicting peak roller loads within 11–18% of measurements, geometric tolerances within 3%, and plastic strain distributions within 10% of experimental values. Collectively, these results establish a validated computational framework for predictive spin-forming simulations with quantified confidence, providing a foundation for extension to other alloys, geometries, and forming conditions.

Spin forming↗
DOE OSTI2020

Experimental Validation of Approximate Dynamic Programming Based Optimization and Convergence on Microgrid Applications

Stochastic optimization can better address uncertainties in power system problems. However, when state space and action space become large, many existing approaches become computationally expensive and even infeasible. Approximate dynamic programming (ADP) attracts researchers’ attention as a powerful tool for solving power system optimization problems with reduced computational cost. In this paper, in light of the existing literature, we investigate how the ADP approach with post-decision value function approximation converges to the nearly optimal solution with improved computational speed and experimentally validate the performance of the approach for a microgrid energy optimization problem. The approximation error versus the number of iteration is studied for convergence analysis of the post-decision ADP. A flowchart is provided to illustrate the proposed ADP algorithm for a microgrid energy optimization problem. The performance of ADP and dynamic programming (DP) is compared in terms of optimization error and computational time. It has found that the post-decision ADP approach can achieve competitive optimality with improved computational speed compared to the traditional DP.

Das, Avijit↗
NASA NTRS1988

Analysis of the convergence history of flow through nozzles with shocks

Acceleration techniques such as Wynn's (1986) epsilon algorithm and analysis techiques such as eigensystem analysis are used here to study numerically the convergence properties of an iterative scheme applied to the quasi-one-dimensional Euler and Navier-Stokes equations for flow through nozzles with shocks. The convergence and stability properties are studied by analyzing the dependence of convergence of the code on the discretization technique, boundary conditions, time-step, number of grid points, and the physics of the problem.

Cheer, A. Y.↗
NASA NTRS2008

Nonstandard Analysis and Jump Conditions for Converging Shock Waves

Nonstandard analysis is an area of modern mathematics which studies abstract number systems containing both infinitesimal and infinite numbers. This article applies nonstandard analysis to derive jump conditions for one-dimensional, converging shock waves in a compressible, inviscid, perfect gas. It is assumed that the shock thickness occurs on an infinitesimal interval and the jump functions in the thermodynamic and fluid dynamic parameters occur smoothly across this interval. Predistributions of the Heaviside function and the Dirac delta measure are introduced to model the flow parameters across a shock wave. The equations of motion expressed in nonconservative form are then applied to derive unambiguous relationships between the jump functions for the flow parameters.

Baty, Roy S.↗
DOE OSTI2024

Convergent ab initio analysis of the multi-channel HOBr + H reaction

High-level potential energy surfaces for three reactions of hypobromous acid with atomic hydrogen were computed at the CCSDTQ/CBS//CCSDT(Q)/complete basis set level of theory. Focal point analysis was utilized to extrapolate energies and gradients for energetics and optimizations, respectively. The H attack at Br and subsequent Br–O cleavage were found to proceed barrierlessly. The slightly submerged transition state lies −0.2 kcal mol−1 lower in energy than the reactants and produces OH and HBr. The two other studied reaction paths are the radical substitution to produce H2O and Br with a 4.0 kcal mol−1 barrier and the abstraction at hydrogen to produce BrO and H2 with an 11.2 kcal mol−1 barrier. The final product energies lie −37.2, −67.9, and −7.3 kcal mol−1 lower in energy than reactants, HOBr + H, for the sets of products OH + HBr, H2O + Br, and H2 + BrO, respectively. Additive corrections computed for the final energetics, particularly the zero-point vibrational energies and spin–orbit corrections, significantly impacted the final stationary point energies, with corrections up to 6.2 kcal mol−1.

Chemistry↗
DOE OSTI2020

Analysis into Asymptotic Convergence to Full Nonlinear Solutions and Exploration of the Implication of Numerical Operator Mutation of Differential Systems

A robust, sufficiently accurate and practical hydrodynamic simulation toolset is required as a key component of the modeling and simulation of air-gap electrostatic discharge events. This work was performed to complement these ongoing efforts. In particular, hydrodynamic simulations must be vetted to ensure they are robust and sufficiently accurate over relevant characteristic scales. Verification models were generated in order to cultivate the technical knowledge and expertise needed to properly create, implement and execute numerical simulations. Furthermore, this effort was utilized extensively to educate students on the mathematical and numerical principles underlying hydrodynamic simulations. This education opportunity, provided in a holistic and rigorous manner, has greatly benefited developing scientists and engineers with the necessary understandings and toolsets required to excel at accomplishing the task at hand, and, more generally, it has enabled them to generate key programmatic deliverables. This report articulates several subtilties; specifically, how perturbations, nonlinear behavior, and dissipative mechanisms influence numerical stability, how to properly structure mathematical and numerical solutions, and how to properly generate error estimation/assignment. A more rigorous discussion of the consequences of such topics can be found in the body of this report in Chapters 2 and 3 with qualitative findings discussed in Chapter 4.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2005

A Study of Multigrid Preconditioners Using Eigensystem Analysis

The convergence properties of numerical schemes for partial differential equations are studied by examining the eigensystem of the discrete operator. This method of analysis is very general, and allows the effects of boundary conditions and grid nonuniformities to be examined directly. Algorithms for the Laplace equation and a two equation model hyperbolic system are examined.

Roberts, Thomas W.↗
DOE OSTI2023

Turbulence Modeling with Nek5000/RS, SOD2D and Alya

We present Validation and Verification (V & V) study of two high-order spectral element method (SEM) based Computational Fluid Dyanimcs (CFD) codes that we will utilize for work on turbulence modeling: Nek5000 and SOD2D. While the former solves the incompressible form of Navier-Stokes equation, the latter works with compressible set of equations and uses an entropy-viscosity formulation to account for the discontinuities for high Mach number flows. We demonstrate the accuracy of these codes for two benchmark sub-sonic turbulent flows: periodic channel and pipe flow, by carrying out first and second order statistical analysis, grid convergence and turbulent structure analysis using wall-resolved large eddy simulations (WRLES). Later, we report on the implementation and testing of various wall-modeling strategies for large eddy simulation of turbulent flows in Nek5000. These include both classical log-law based and decision-tree based machine-learning models. Accuracy of these closure strategies are analyzed and necessary future work is outlined.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1997

Convergence Estimates for Multidisciplinary Analysis and Optimization

A quantitative analysis of coupling between systems of equations is introduced. This analysis is then applied to problems in multidisciplinary analysis, sensitivity, and optimization. For the sensitivity and optimization problems both multidisciplinary and single discipline feasibility schemes are considered. In all these cases a "convergence factor" is estimated in terms of the Jacobians and Hessians of the system, thus it can also be approximated by existing disciplinary analysis and optimization codes. The convergence factor is identified with the measure for the "coupling" between the disciplines in the system. Applications to algorithm development are discussed. Demonstration of the convergence estimates and numerical results are given for a system composed of two non-linear algebraic equations, and for a system composed of two PDEs modeling aeroelasticity.

Arian, Eyal↗
DOE OSTI2024

Wearable Technology and Its Influence on Motor Development and Biomechanical Analysis

The convergence among biomechanics, motor development, and wearable technology redefines our understanding of human movement. These technologies allow for the continuous monitoring of motor development and the state of motor abilities from infancy to old age, enabling early and personalized interventions to promote healthy motor skills. For athletes, they offer valuable insights to optimize technique and prevent injuries, while in old age, they help maintain mobility and prevent falls. Integration with artificial intelligence further extends these capabilities, enabling sophisticated data analysis. Wearable technology is transforming the way we approach motor development and maintenance of motor skills, offering unprecedented possibilities for improving health, performance, and quality of life at every stage of life. The promising future of these technologies paves the way for an era of more personalized and effective healthcare, driven by innovation and interdisciplinary collaboration.

Morouço, Pedro (ORCID:0000000259569790)↗
NASA NTRS1986

Evaluation of several modal methods for transient structural analysis

The convergence properties of three modal methods for solving structural transient response (STR) problems are examined by comparing the accuracy of the total number of modes used to represent the responses. The goal is to identify a method which involves as few degrees of freedom as possible. Two mode superposition methods, the mode displacement method (MDM) and the mode acceleration method (MAM), are fitted with equivalent expressions for damped response. An error norm is employed to compare the accuracies of the methods in calculating displacements, moments, and shear forces for a viscously-damped cantilevered beam experiencing several dynamic loading conditions and levels of damping. The MAM converges quicker and uses fewer dof, mainly because it has a pseudo-static response term which accounts for some of the flexibility of higher modes. A third method, which integrates the convolution integral iteratively over time, generates a higher order approximation to the STR with a reduced number of modes. It converges fastest among the three, but requires definition of an appropriate forcing function. Finally, the MAM and MDM models are applied to study the effects of the forcing frequency and the initial conditions.

Camarda, Charles J.↗
NASA NTRS1989

Jacobi-Bessel Analysis Of Antennas With Elliptical Apertures.

Coordinate transformation improves convergence pattern analysis of elliptical-aperture antennas. Modified version of Jacobi-Bessel expansion for vector diffraction analysis of reflector antennas uses coordinate transformation to improve convergence with elliptical apertures. Expansion converges rapidly for antennas with circular apertures, but less rapidly for elliptical apertures. Difference in convergence behavior between circular and elliptical Jacobi-Bessel algorithms indicated by highest values of indices m, n, and p required to achieve same accuracy in computed radiation pattern of offset paraboloidal antenna with elliptical aperture.

Rahmat-Samii, Y.↗
DOE OSTI2020

Atomic resolution convergent beam electron diffraction analysis using convolutional neural networks

Two types of convolutional neural network (CNN) models, a discrete classification network and a continuous regression network, were trained to determine local sample thickness from convergent beam diffraction (CBED) patterns of SrTiO 3 collected in a scanning transmission electron microscope (STEM) at atomic column resolution. Acquisition of atomic resolution CBED patterns for this purpose requires careful balancing of CBED feature size in pixels, acquisition speed, and detector dynamic range. The training datasets were derived from multislice simulations, which must be convolved with incoherent source broadening. Sample thicknesses were also determined using quantitative high-angle annular dark-field (HAADF) STEM images acquired simultaneously. The regression CNN performed well on sample thinner than 35 nm, with 70% of the CNN results within 1 nm of HAADF thickness, and 1.0 nm overall root mean square error between the two measurements. The classification CNN was trained for a thicknesses up to 100 nm and yielded 66% of CNN results within one classification increment of 2 nm of HAADF thickness. Our approach depends on methods from computer vision including transfer learning and image augmentation.

36 MATERIALS SCIENCE↗