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At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Thermal Modelling of the In-Situ Consolidation of Automated Fiber Placement Of Thermoplastic Composites

NASA is developing carbon fiber reinforced thermoplastic composites processing methods under the Hi-rate Composites Aircraft Manufacturing (HiCAM) project. The in-situ consolidation automated fiber placement (AFP) of thermoplastics (ICAT) process has high potential to increase manufacturing throughput and lower costs as it combines the repeatability and fast lay down rates of AFP with the thermoformability of thermoplastic materials to achieve part consolidation out of the autoclave. Physics-based process models are employed in the ICAT process development to understand, fundamentally, the thermal response of the carbon fiber (CF)/polyaryletherketone (PAEK) material during the rapid heating and cooling associated with laser-assisted AFP. A one-dimensional (1-D) closed-form model was developed capable of predicting the temperature profile through-the-thickness of the tape material. In addition, a two-dimensional (2-D) model was developed to predict the heat transfer through-the-thickness and in the laydown x-direction of the AFP head motion. The solution of the Fourier heat-transfer equations in the 2-D model is approximated using the explicit finite difference numerical method. The temperature profile during placement of PAEK slit-tape materials at various laser target temperatures and placement speeds were measured during ICAT process development trials at Electroimpact®, Inc. †† and the resulting experimental data is compared with the predictions of the 1-D and 2-D models.

Christopher J. Stelter↗
DOE OSTI2023

Exploring numerical blow-up phenomena for the Keller–Segel–Navier–Stokes equations

The Keller–Segel–Navier–Stokes system governs chemotaxis in liquid environments. This system is to be solved for the organism and chemoattractant densities and for the fluid velocity and pressure. It is known that if the total initial organism density mass is below 2π there exist globally defined generalised solutions, but what is less understood is whether there are blow-up solutions beyond such a threshold and its optimality. Motivated by this issue, a numerical blow-up scenario is investigated. Approximate solutions computed via a stabilised finite element method founded on a shock capturing technique are such that they satisfy a priori bounds as well as lower and L 1 (Ω) bounds for the organism and chemoattractant densities. In particular, these latter properties are essential in detecting numerical blow-up configurations, since the non-satisfaction of these two requirements might trigger numerical oscillations leading to non-realistic finite-time collapses into persistent Dirac-type measures. Our findings show that the existence threshold value 2π encountered for the organism density mass may not be optimal and hence it is conjectured that the critical threshold value 4π may be inherited from the fluid-free Keller–Segel equations. Additionally it is observed that the formation of singular points can be neglected if the fluid flow is intensified.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Power Flow Geometry and Approximation

Here, the power flow equations are important in numerous power systems problems of practical interest which consider alternating current power flow (ACPF) physics. Perhaps the most well studied being the alternating current optimal power flow problem (ACOPF), seeking to optimize the operation of an electric power system. Due to their non-linearity, problems which include the power flow equations are typically challenging, particularly in optimization. Interestingly, the set of solutions to the power flow equations forms a smooth manifold. As a result, differential geometry can be used to describe and analyze this set of equations. This approach has proven effective in several engineering applications (e.g., solving ACOPF and analyzing the solution space boundary). Central to the success of this approach is an understanding of the power flow manifold's geometry. In this work, we develop the geometric and topological properties of this manifold using concepts from differential geometry. After demonstrating the convenience of this manifold's representation as a function's graph, computational methods are emphasized: we develop retractions, error bounds for linear approximation, and formulas for evaluating the Riemannian metric (including associated objects such as geodesics and the curvature tensor). Scalar curvature and the second fundamental form play a new role in quantifying the quality of linear approximations, like the popular direct current approximation. All functions are implemented in Julia and available in an online repository. Proofs are included for completeness.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Modifying the Asynchronous Jacobi Method for Data Corruption Resilience

Moving scientific computation from high-performance computing (HPC) and cloud computing (CC) environments to devices on the edge, i.e., physically near instruments of interest, has received tremendous interest in recent years. Such edge computing environments can operate on data in situ, offering enticing benefits over data aggregation to HPC and CC facilities that include avoiding costs of transmission, increased data privacy, and real-time data analysis. Because of the inherent unreliability of edge computing environments, new fault-tolerant approaches must be developed before the benefits of edge computing can be realized. Motivated by algorithm-based fault tolerance, a variant of the asynchronous Jacobi (ASJ) method is developed that achieves resilience to data corruption by rejecting solution approximations from neighbor devices according to a bound derived from convergence theory. Numerical results on a two-dimensional Poisson problem show that the new rejection criterion, along with a novel approximation to the shortest path length on which the criterion depends, restores convergence for the ASJ variant in the presence of certain types data corruption. Numerical results are obtained for when the singular values in the analytic bound are approximated. Additional linear systems are also explored, one with a more dense sparsity pattern and one that includes advection. All results indicate that successful resilience to data corruption depends on whether the bound tightens fast enough to reject corrupted data before the iteration evolution deviates significantly from that predicted by the convergence theory defining the bound. This observation generalizes to future work on algorithm-based fault tolerance for other asynchronous algorithms, including upcoming approaches that leverage Krylov subspaces.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Numerical model for dendritic solidification of binary alloys

A finite element model capable of simulating solidification of binary alloys and the formation of freckles is presented. It uses a single system of equations to deal with the all-liquid region, the dendritic region, and the all-solid region. The dendritic region is treated as an anisotropic porous medium. The algorithm uses the bilinear isoparametric element, with a penalty function approximation and a Petrov-Galerkin formulation. Numerical simulations are shown in which an NH4Cl-H2O mixture and a Pb-Sn alloy melt are cooled. The solidification process is followed in time. Instabilities in the process can be clearly observed and the final compositions obtained.

Felicelli, S. D.↗
NASA NTRS1983

The scaling of oblique plasma double layers

Strong oblique plasma double layers are investigated using three methods, i.e., electrostatic particle-in-cell simulations, numerical solutions to the Poisson-Vlasov equations, and analytical approximations to the Poisson-Vlasov equations. The solutions to the Poisson-Vlasov equations and numerical simulations show that strong oblique double layers scale in terms of Debye lengths. For very large potential jumps, theory and numerical solutions indicate that all effects of the magnetic field vanish and the oblique double layers follow the same scaling relation as the field-aligned double layers.

Borovsky, J. E.↗
DOE OSTI2022

Tensor Network Path Integral Study of Dynamics in B850 LH2 Ring with Atomistically Derived Vibrations

The recently introduced multisite tensor network path integral (MS-TNPI) allows simulation of extended quantum systems coupled to dissipative media. We use MS-TNPI to simulate the exciton transport and the absorption spectrum of a B850 bacteriochlorophyll (BChl) ring. The MS-TNPI network is extended to account for the ring topology of the B850 system. Accurate molecular-dynamics-based description of the molecular vibrations and the protein scaffold is incorporated through the framework of Feynman–Vernon influence functional. To relate the present work with the excitonic picture, an exploration of the absorption spectrum is done by simulating it using approximate and topologically consistent transition dipole moment vectors. Comparison of these numerically exact MS-TNPI absorption spectra are shown with second-order cumulant approximations. Finally, the effect of temperature on both the exact and the approximate spectra is also explored.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRSDate not supplied

A Numerical Method for Computing the State Transition Matrix Using Poincare Integral Invariants

The Poincare integral invariants describe the volumes of sets in Hamiltonian phase space. We use these invariants to derive a new numerical procedure for obtaining the state transition matrix (STM), which can be applied to both conservative and nonconservative systems. The method is analogous to a finite difference approximation of the STM, where perturbed states are numerically propagated along with the reference trajectory. We discuss the mathematical similarities between this new STM and existing methods, show numerical results for orbital motion and uncertainty propagation, and discuss new insights afforded by the Hamiltonian properties of phase flow.

state transition matrix↗
NASA NTRS1986

Efficient inverse solution of Kepler's equation

A bicubic polynomial approximation to Kepler's equation for elliptic orbits is shown to provide accurate starting values for efficient numerical solution of this equation for eccentric anomaly. In the approximate equation, a cubic in mean anomaly is set equal to a cubic in eccentric anomaly. The coefficients in the two cubics are obtained as functions of eccentricity by specifying values of function and slope at the midpoint and the endpoint of the complete interval (0 to pi). The initial estimate of eccentric anomaly to use in an iteration formula is obtained by evaluating the cubic in mean anomaly and finding the single real root of the cubic in eccentric anomaly. Numerical results are presented which indicate that the estimate accuracy of this method is roughly an order of magnitude better than that of other recently-reported formulas.

Boltz, Frederick W.↗
NASA NTRS1992

Computation of non-equilibrium flow downstream of a plasma torch

Numerical solutions of the Navier-Stokes equations for compressible reacting flow in an axisymmetric geometry are presented for a nitrogen plasma torch with both thermal and chemical nonequilibrium. The Navier-Stokes equations are solved using a new axisymmetric finite element/finite volume formulation in which the convective flux is treated by an extension of the approximate Riemann solver due to Osher. The numerical scheme is validated by comparison with a previous solution of the same problem using a different computational scheme. Results obtained using two different models of nonthermal dissociation rates are compared to experimental data.

Harle, Christophe↗
DOE OSTI2026

Taylor approximation variance reduction for approximation errors in PDE-constrained Bayesian inverse problems

In numerous applications, surrogate models are used as a replacement for accurate parameter-to-observable mappings when solving large-scale inverse problems governed by partial differential equations (PDEs). The surrogate model may be a computationally cheaper alternative to the accurate parameter-to-observable mappings and/or may ignore additional unknowns or sources of uncertainty. The Bayesian approximation error (BAE) approach provides a means to account for the induced uncertainties and approximation errors, i.e. the errors between the accurate parameter-to-observable mapping and the surrogate. The statistics of these errors are, however, in general unknown a priori, and are thus calculated using Monte Carlo sampling. Although the sampling is typically carried out offline, i.e. before considering the data, the process can still represent a computational bottleneck. In this work, we develop a scalable computational approach for reducing the costs associated with the sampling stage of the BAE approach. Specifically, we consider the Taylor expansion of the accurate and surrogate forward models with respect to the uncertain parameter fields either as a control variate for variance reduction or as a means to directly and efficiently approximate the mean and covariance of the approximation errors. We propose efficient methods for evaluating the expressions for the mean and covariance of the Taylor approximations based on linear(-ized) PDE solves. Furthermore, the proposed approach is independent of the dimension of the uncertain parameter, depending instead on the intrinsic dimension of the data, ensuring scalability to high-dimensional problems. The potential benefits of the proposed approach are demonstrated for two high-dimensional inverse problems governed by PDE examples, namely for the estimation of a distributed Robin boundary coefficient in a linear diffusion problem, and for a coefficient estimation problem governed by a nonlinear diffusion problem.

Bayesian approximation error↗
NASA NTRS1993

Numerical simulation of upstream disturbance on flows around a slender body

Numerical solutions of the thin-layer approximation of the compressible Navier-Stokes equations have been obtained for flows around an ogive-cylinder body with and without a small fixed disturbance placed upstream of the body tip. Locating the disturbance at positions in the flow field upstream of the tip provokes the same range of behavior of the asymmetric flow that was numerically produced earlier by use of a geometrical disturbance on the body tip. Results remain consistent with the presence of a convective instability mechanism, and demonstrate the potential for a precise mapping of the body's receptivity to fixed disturbances in the flow field. Numerical solutions were also obtained for the flow-field responses to impulsive upstream disturbances to determine whether there is a growing response to an asymmetric impulsive disturbance that is consistent with presence of a convective instability mechanism. Results for surface pressure are interpreted with the aid of a mathematical model. The model suggests that the observed growth of surface pressure gradient with time and distance along a ray in response to an asymmetnc impulsive disturbance is in accord with the solution of a Ginzberg-Landau equation, with distinguishing features of the solution being consistent with the convective instability mode of behavior.

Degani, David↗
DOE OSTI2025

A charged particle transport approximation for thick and thin plasmas

In this work, we will construct a simple method to be utilized in the interpretation of the properties of a thin plasma from a study of the transport of charged particles through it. We do so by first demonstrating how charged particle fluxes encode local plasma information in their spectra for sufficiently thick plasmas and then propose how to extend that analysis to the thin plasma limit where the extensive geometry cannot be neglected through arguments from scale separation. We provide a numerical treatment of the transport problem and demonstrate that it is in good agreement with the approximation we present. Finally, we utilize both the numerical solution and our novel approximation to study the impact of the extensive scale of the plasma on the yield and flux normalized high-energy neutron spectra resulting from the upscattering of charged fuel ions. Using this analysis, we show that (after controlling for fusion yield) for the same uniform densities and temperatures, larger plasmas have higher magnitude but softer reaction-in-flight (RIF) neutron spectra relative to smaller plasmas. This is because larger plasmas retain more knocked-on suprathermal ions within their bulk and can downscatter them to lower average energies, while smaller plasmas allow a larger fraction of high energy particles to “range out” of the system prior to substantial downscattering or inducing an RIF reaction.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1984

Time dependent computation of the Euler equations for designing 2-D cascades, including the case of transonic shock free design

A numerical method to solve the inverse problem for airfoil cascades is described. The case of compressible, inviscid flow is considered. The proposed method is based on the finite difference approximation of the time-dependent Euler equations. Numerical examples show the capability of the method to design subsonic or transonic shockless blades.

Zannetti, L.↗
NASA NTRS1977

Numerical solutions of single-mode convection equations

In the Boussinesq approximation, single-mode equations describing thermal convection are constructed by expanding the fluctuating velocity and temperature fields in a complete set of functions (or planforms) of the horizontal coordinates and retaining just one term. Numerical solutions of the single-mode equations are investigated, chief consideration being given to hexagonal planforms. Extensive surveys of steady solutions are presented for various Rayleigh numbers, Prandtl numbers, and horizontal wavenumbers. The dependences on Rayleigh number and Prandtl number at very large Rayleigh number are in satisfactory agreement with the results of asymptotic expansions.

Toomre, J.↗
NASA NTRS2006

Heat Transfer In High-Temperature Multilayer Insulation

The combined radiation/conduction heat transfer in high-temperature multilayer insulations for typical reentry of reusable launch vehicles from low Earth orbit was investigated experimentally and numerically. The high-temperature multilayer insulation investigated consisted of gold-coated reflective foils separated by alumina fibrous insulation spacers. The steady-state heat transfer through four multilayer insulation configurations was investigated experimentally over the temperature range of 300-1300 K and environmental pressure range of 1.33 10(exp -5)-101.32 kPa. It was shown that including the reflective foils reduced the effective thermal conductivity compared to fibrous insulation sample at 1.5 times the density of the multilayer sample. A finite volume numerical model was developed to solve the governing combined radiation/conduction heat transfer equations. The radiation heat transfer in the fibrous insulation spacers was modeled using the modified two-flux approximation assuming anisotropic scattering and gray medium. The numerical model was validated by comparison with steady-state experimental data. The root mean square deviation between the predicted and measured effective thermal conductivity of the samples was 9.5%.

Daryabeigi, Kamran↗
DOE OSTI2023

Generalized moving least squares vs. radial basis function finite difference methods for approximating surface derivatives

Approximating differential operators defined on two-dimensional surfaces is an important problem that arises in many areas of science and engineering. Over the past ten years, localized meshfree methods based on generalized moving least squares (GMLS) and radial basis function finite differences (RBF-FD) have been shown to be effective for this task as they can give high orders of accuracy at low computational cost, and they can be applied to surfaces defined only by point clouds. However, there have yet to be any studies that perform a direct comparison of these methods for approximating surface differential operators (SDOs). The first purpose of this work is to fill that gap. For this comparison, we focus on an RBF-FD method based on polyharmonic spline kernels and polynomials (PHS+Poly) since they are most closely related to the GMLS method. Additionally, we use a relatively new technique for approximating SDOs with RBF-FD called the tangent plane method since it is simpler than previous techniques and natural to use with PHS+Poly RBF-FD. Further, the second purpose of this work is to relate the tangent plane formulation of SDOs to the local coordinate formulation used in GMLS and to show that they are equivalent when the tangent space to the surface is known exactly. The final purpose is to use ideas from the GMLS SDO formulation to derive a new RBF-FD method for approximating the tangent space for a point cloud surface when it is unknown. For the numerical comparisons of the methods, we examine their convergence rates for approximating the surface gradient, divergence, and Laplacian as the point clouds are refined for various parameter choices. We also compare their efficiency in terms of accuracy per computational cost, both when including and excluding setup costs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Iterative quantum optimization of spin glass problems with rapidly oscillating transverse fields

In this work, we introduce a new iterative quantum algorithm, called Iterative Symphonic Tunneling for Satisfiability problems (IST-SAT), which solves quantum spin glass optimization problems using high-frequency oscillating transverse fields. IST-SAT operates as a sequence of iterations, in which bitstrings returned from one iteration are used to set spin-dependent phases in oscillating transverse fields in the next iteration. Over several iterations, the novel mechanism of the algorithm steers the system toward the problem ground state. We benchmark IST-SAT on sets of hard MAX-3-XORSAT problem instances with exact state vector simulation, and report polynomial speedups over Trotterized adiabatic quantum computation and the best known semi-greedy classical algorithm. When IST-SAT is seeded with a sufficiently good initial approximation, the algorithm converges to exact solution(s) in a polynomial number of iterations. Our numerical results identify a critical Hamming radius, or quality of initial approximation, where the time-to-solution crosses from exponential to polynomial scaling in problem size. This work proposes IST-SAT a new quantum algorithm, which improves upon solutions obtained from initial classical or quantum optimization algorithms. The steering mechanism we introduce through IST-SAT presents a new path toward achieving quantum advantage in optimization.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗