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Results for “algorithmic differentiation”

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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

A second-order 3D electromagnetics algorithm for curved interfaces between anisotropic dielectrics on a Yee mesh

A new frequency-domain electromagnetics algorithm is developed for simulating curved interfaces between anisotropic dielectrics embedded in a Yee mesh with second-order error in resonant frequencies. The algorithm is systematically derived using the finite integration formulation of Maxwell's equations on the Yee mesh. Second-order convergence of the error in resonant frequencies is achieved by guaranteeing first-order error on dielectric boundaries and second-order error in bulk (possibly anisotropic) regions. Convergence studies, conducted for an analytically solvable problem and for a photonic crystal of ellipsoids with anisotropic dielectric constant, both show second-order convergence of frequency error; the convergence is sufficiently smooth that Richardson extrapolation yields roughly third-order convergence. The convergence of electric fields near the dielectric interface for the analytic problem is also presented.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Multi-fidelity modeling to predict the rheological properties of a suspension of fibers using neural networks and Gaussian processes

Unveiling the rheological properties of fiber suspensions is of paramount interest to many industrial applications. There are multiple factors, such as fiber aspect ratio and volume fraction, that play a significant role in altering the rheological behavior of suspensions. Three-dimensional (3D) numerical simulations of coupled differential equations of the suspension of fibers are computationally expensive and time-consuming. Machine learning algorithms can be trained on the available data and make predictions for the cases where no numerical data are available. However, some widely used machine learning surrogates, such as neural networks, require a relatively large training dataset to produce accurate predictions. Multi-fidelity models, which combine high-fidelity data from numerical simulations and less expensive lower fidelity data from resources such as simplified constitutive equations, can pave the way for more accurate predictions. Here, we focus on neural networks and the Gaussian processes with two levels of fidelity, i.e., high and low fidelity networks, to predict the steady-state rheological properties, and compare them to the single-fidelity network. High-fidelity data are obtained from direct numerical simulations based on an immersed boundary method to couple the fluid and solid motion. The low-fidelity data are produced by using constitutive equations. Multiple neural networks and the Gaussian process structures are used for the hyperparameter tuning purpose. Results indicate that with the best choice of hyperparameters, both the multi-fidelity Gaussian processes and neural networks are capable of making predictions with a high level of accuracy with neural networks demonstrating marginally better performance.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Lagrangian particle simulation of hydrogen pellets and SPI into runaway electron beam in ITER

Numerical studies of the ablation of pellets and shattered pellet injection (SPI) fragments into a runaway electron beam in ITER have been performed using a time-dependent pellet ablation code [Samulyak et al., Nucl. Fusion, 61(4), 046007 (2021)]. The code resolves detailed ablation physics near pellet fragments and large-scale expansion of ablated clouds. The study of a single-fragment ablation quantifies the influence of various factors, in particular, the impact ionization by runaway electrons and cross-field transport models, on the dynamics of ablated plasma and its penetration into the runaway beam. Simulations of SPI performed using different numbers of pellet fragments study the formation and evolution of the ablation clouds and their large-scale dynamics in ITER. In conclusion, the penetration depth of the ablation clouds is found to be of the order of 50 cm.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Generative deep-learning reveals collective variables of Fermionic systems

Complex processes of fermionic systems ranging from protein folding to nuclear fission often follow a low-dimensional reaction path parametrized in terms of a few collective variables. In nuclear theory, variables related to the shape of the nuclear density in a mean-field picture are key to describing the large amplitude collective motion of the neutrons and protons. Exploring the adiabatic energy landscape spanned by these degrees of freedom reveals the possible reaction channels while simulating the dynamics in this reduced space yields their respective probabilities. Unfortunately, this theoretical framework breaks down whenever the systems encounters a quantum phase transition with respect to the collective variables. Here, in this study, we introduce a novel generative deep-learning algorithm designed to build reaction paths that ensure that the many-fermion wave function stays differentiable with respect to the collective variables. This approach is applicable to any fermionic system described by a coherent state. We use the case of potential energy curves in the 16 O nucleus within the Hartree-Fock theory to illustrate its main features.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Generalized master equation for particle transport in binary random media with renewal statistics

Particle transport in binary stochastic mixtures is classically modeled assuming Markovian or exponential mixing statistics but in many applications material memory invalidates the Markov assumption. For non-Markovian mixing characterized by alternating renewal processes, a transport-theoretic framework is presented that provides an exact description of transport in nonscattering random binary media with general non-exponential statistics. Our approach is to Markovianize the problem by augmenting the {material type, particle flux} state space with the age or distance from the last interface. A Chapman-Kolmogorov equation is formulated for the joint probability density of the material type, particle flux, and age, and subsequently reduced to a generalized Master equation (GME) in differential form. This constitutes the primary result of this work. A state-updating Monte Carlo algorithm consistent with the GME is developed and benchmarked against analytical solutions for multiple chord-length laws. For purely absorbing renewal statistical media, the GME reproduces analytical benchmarks for the equilibrium age distribution, interior mean/variance of material-conditioned fluxes, and boundary transmittance. Simulations further demonstrate that a Markov (exponential) approximation of non-exponential statistics can introduce large errors in transmittance and interior flux profiles. Lastly, the reintroduction of memory due to scattering is briefly addressed through heuristic considerations.

Fluctuations & noise↗
DOE OSTI2011

Three-dimensional anisotropic adaptive filtering of projection data for noise reduction in cone beam CT

Purpose: The combination of quickly rotating C-arm gantry with digital flat panel has enabled the acquisition of three-dimensional data (3D) in the interventional suite. However, image quality is still somewhat limited since the hardware has not been optimized for CT imaging. Adaptive anisotropic filtering has the ability to improve image quality by reducing the noise level and therewith the radiation dose without introducing noticeable blurring. By applying the filtering prior to 3D reconstruction, noise-induced streak artifacts are reduced as compared to processing in the image domain. Methods: 3D anisotropic adaptive filtering was used to process an ensemble of 2D x-ray views acquired along a circular trajectory around an object. After arranging the input data into a 3D space (2D projections + angle), the orientation of structures was estimated using a set of differently oriented filters. The resulting tensor representation of local orientation was utilized to control the anisotropic filtering. Low-pass filtering is applied only along structures to maintain high spatial frequency components perpendicular to these. The evaluation of the proposed algorithm includes numerical simulations, phantom experiments, and in-vivo data which were acquired using an AXIOM Artis dTA C-arm system (Siemens AG, Healthcare Sector, Forchheim, Germany). Spatial resolution and noise levels were compared with and without adaptive filtering. A human observer study was carried out to evaluate low-contrast detectability. Results: The adaptive anisotropic filtering algorithm was found to significantly improve low-contrast detectability by reducing the noise level by half (reduction of the standard deviation in certain areas from 74 to 30 HU). Virtually no degradation of high contrast spatial resolution was observed in the modulation transfer function (MTF) analysis. Although the algorithm is computationally intensive, hardware acceleration using Nvidia's CUDA Interface provided an 8.9-fold speed-up of the processing (from 1336 to 150 s). Conclusions: Adaptive anisotropic filtering has the potential to substantially improve image quality and/or reduce the radiation dose required for obtaining 3D image data using cone beam CT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

P Finder

P Finder is written in C# and has been tested in multiple 64-bit Windows environments (Windows 7/8/Vista). It has a user-friendly graphical user interface (GUI) that allows for intuitive RNase P RNA identification and/or annotation. The user can select from four search criteria including the use multiple threads. In addition, the user can determine what display data they wish to incorporate in the output such as: bitscore, E-value, percent ID, start location, end location, the strand in which the sequence is located, and of course the sequence itself. P Finder is the only available algorithm that is capable of not only identifying the RNase P RNA for annotation but also differentiating among the five different RNase P RNA structural types (A, B, C, M, and T) with the option to select these data types for display in the final output.

Ellis, JosephC↗
DOE OSTI2026

PDEHats

This is code used to train and evaluate neural partial differential equation solvers on an open source fluid flow data. We evaluate two standard deep learning algorithms for their ability to generalize, a desirable capability for trusthworthy and performant models.

Amarel, James↗
DOE OSTI2025

Estimating Ice Water Content for Winter Storms from Millimeter-Wavelength Radar Measurements Using a Synthesis of Polarimetric and Dual-Frequency Radar Observations

The potential of millimeter-wavelength radar-based ice water content (IWC) estimation is demonstrated using a Ka-band Scanning Polarimetric Radar (KASPR) for the U.S. northeast coast winter storms. Two IWC relations for Ka-band polarimetric radar measurements are proposed: one that uses a combination of the radar reflectivity Z and the estimated total number concentration of snow particles N t and the other based on the joint use of Z, specific differential phase K DP , and the degree of riming f rim . A key element of the algorithms is to obtain the “Rayleigh-equivalent” value of Z measured at the Ka band, i.e., the corresponding Z at a longer radar wavelength for which Rayleigh scattering takes place. This is achieved via polarimetric retrieval of the mean volume diameter D m and incorporating the relationship between the dual-wavelength ratio DWR S/Ka and D m . Those techniques allow for retrievals from single millimeter-wavelength radar measurements and do not necessarily require the dual-wavelength ratio (DWR) measurements, if the DWR–D m relation and Rayleigh assumption for Ka-band K DP are valid. Comparison between the quasivertical profile product obtained from KASPR and the columnar vertical profile product generated from the nearby WSR-88D S-band radar measurements demonstrates that the DWR S/Ka can be estimated from the two close radars without the need for collocated radar beams and synchronized antenna scanning and can be used for determining the Rayleigh-equivalent value of Z. As a result, the performance of the suggested techniques is evaluated for seven winter storms using surface disdrometer and snow accumulation measurements.

Cloud retrieval↗
DOE OSTI2020

Effect of GPS Manipulation to Traditional and Next Generation Relay Protection

This project’s objective is to test the effect of GPS timing variations on relay protection algorithms to determine vulnerabilities and the associated hazards to the electric grid. This will focus on differential protection which utilizes peer to peer communication between substations to determine if the current is not equivalent. This requires the use of GPS to sync the two substations and can be vulnerable to GPS manipulation. However, the effects of GPS manipulation are not a commonly known risk. Therefore, this LDRD will address the risks of GPS manipulation for such a widely implemented technology. For differential protection a GPS resilient architecture was implemented and tested for differential protective relays through a direct serial fiber connection between the two relays. This allows for one relay to be the master and provide synchronization outside of timestamp for differential protection.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1983

Robot arm dynamic model reduction for control

General methods are described by which the mathematical complexities of explicit and exact state equations of robot arms can be reduced to a simplified and compact state equation representation without introducing significant errors into the robot arm dynamic model. The model reduction methods are based on homogeneous coordinates and on the Langrangian algorithm for robot arm dynamics, and utilize matrix, vector and numeric analysis techniques. The derivation of differential vector representation of centripetal and Coriolis forces which has not yet been established in the literature is presented.

Bejczy, A. K.↗
NASA NTRS1989

Personal computer study of finite-difference methods for the transonic small disturbance equation

Calculation of unsteady flow phenomena requires careful attention to the numerical treatment of the governing partial differential equations. The personal computer provides a convenient and useful tool for the development of meshes, algorithms, and boundary conditions needed to provide time accurate solution of these equations. The one-dimensional equation considered provides a suitable model for the study of wave propagation in the equations of transonic small disturbance potential flow. Numerical results for effects of mesh size, extent, and stretching, time step size, and choice of far-field boundary conditions are presented. Analysis of the discretized model problem supports these numerical results. Guidelines for suitable mesh and time step choices are given.

Bland, Samuel R.↗
NASA NTRS1990

Personal computer study of finite-difference methods for the transonic small disturbance equation

Calculation of unsteady flow phenomena requires careful attention to the numerical treatment to the governing partial differential equations. The personal computer provides a convenient and useful tool for the development of meshes, algorithms, and boundary conditions needed to provide time accurate solution of these equations. The one-dimensional equation considered provides a suitable model for the study of wave propagation in the equations of transonic small disturbance potential flow. Numerical results for effects of mesh size, extent, and stretching, time step size, and choice of far-field boundary conditions are presented. Analysis of the discretized model problem supports these numerical results. Guidelines for suitable mesh and time step choices are given.

Bland, Samuel R.↗
NASA NTRS1990

A fully Sinc-Galerkin method for Euler-Bernoulli beam models

A fully Sinc-Galerkin method in both space and time is presented for fourth-order time-dependent partial differential equations with fixed and cantilever boundary conditions. The Sinc discretizations for the second-order temporal problem and the fourth-order spatial problems are presented. Alternate formulations for variable parameter fourth-order problems are given which prove to be especially useful when applying the forward techniques to parameter recovery problems. The discrete system which corresponds to the time-dependent partial differential equations of interest are then formulated. Computational issues are discussed and a robust and efficient algorithm for solving the resulting matrix system is outlined. Numerical results which highlight the method are given for problems with both analytic and singular solutions as well as fixed and cantilever boundary conditions.

Smith, R. C.↗
NASA NTRS1994

A sensitivity equation approach to shape optimization in fluid flows

A sensitivity equation method to shape optimization problems is applied. An algorithm is developed and tested on a problem of designing optimal forebody simulators for a 2D, inviscid supersonic flow. The algorithm uses a BFGS/Trust Region optimization scheme with sensitivities computed by numerically approximating the linear partial differential equations that determine the flow sensitivities. Numerical examples are presented to illustrate the method.

Borggaard, Jeff↗
NASA NTRS2007

Two-Stage Path Planning Approach for Designing Multiple Spacecraft Reconfiguration Maneuvers

The paper presents a two-stage approach for designing optimal reconfiguration maneuvers for multiple spacecraft. These maneuvers involve well-coordinated and highly-coupled motions of the entire fleet of spacecraft while satisfying an arbitrary number of constraints. This problem is particularly difficult because of the nonlinearity of the attitude dynamics, the non-convexity of some of the constraints, and the coupling between the positions and attitudes of all spacecraft. As a result, the trajectory design must be solved as a single 6N DOF problem instead of N separate 6 DOF problems. The first stage of the solution approach quickly provides a feasible initial solution by solving a simplified version without differential constraints using a bi-directional Rapidly-exploring Random Tree (RRT) planner. A transition algorithm then augments this guess with feasible dynamics that are propagated from the beginning to the end of the trajectory. The resulting output is a feasible initial guess to the complete optimal control problem that is discretized in the second stage using a Gauss pseudospectral method (GPM) and solved using an off-the-shelf nonlinear solver. This paper also places emphasis on the importance of the initialization step in pseudospectral methods in order to decrease their computation times and enable the solution of a more complex class of problems. Several examples are presented and discussed.

Aoude, Georges S.↗
NASA NTRS2004

Rapid Switching and Modulation by use of Coupled VCSELs

Devices incorporating coupled vertical-cavity surface-emitting lasers (VCSELs) have been proposed as means to effect unprecedentedly rapid modulation and/or switching of light beams in advanced optical communication and information-processing systems. A basic device according to the proposal would comprise two or more VCSELs (1) positioned so close to each other that they are coupled and (2) connected to a current source that biases them at a steady current above the threshold current for lasing. The operation of VCSELs under the conditions stated above has been simulated computationally with an algorithm that solves an approximation of the Maxwell-Bloch equations. (These are nonlinear coupled partial differential equations that model the relevant aspects of the physics of semiconductor lasers.) The results of the simulations show that the intensities of the beams oscillate, out of phase relative to each other, at a frequency that is typically of the order of tens of gigahertz. In particular, one simulation was performed for two coupled VCSELs, each having a circular aperture 5.6 microns in diameter, operating at a wavelength of 980 nm. The results of the simulation showed that the intensities of the two beams oscillated in opposite phase (see Figure 1) at a frequency of 42 GHz. In the far field, the beams were found to be separated by an angle of approx.=8deg. The intensities of the beams were also found to oscillate in the near field, 90deg out of phase with the oscillation in the far field. Figure 2 depicts a simple near-field switching device in which an assembly of microlenses would couple the two oscillating beams to two receivers.

Goorjian, Peter M.↗
DOE OSTI2017

Achieving algorithmic resilience for temporal integration through spectral deferred corrections

Spectral deferred corrections (SDC) is an iterative approach for constructing higher-order-accurate numerical approximations of ordinary differential equations. SDC starts with an initial approximation of the solution defined at a set of Gaussian or spectral collocation nodes over a time interval and uses an iterative application of lower-order time discretizations applied to a correction equation to improve the solution at these nodes. Each deferred correction sweep increases the formal order of accuracy of the method up to the limit inherent in the accuracy defined by the collocation points. In this paper, we demonstrate that SDC is well suited to recovering from soft (transient) hardware faults in the data. A strategy where extra correction iterations are used to recover from soft errors and provide algorithmic resilience is proposed. Specifically, in this approach the iteration is continued until the residual (a measure of the error in the approximation) is small relative to the residual of the first correction iteration and changes slowly between successive iterations. Here, we demonstrate the effectiveness of this strategy for both canonical test problems and a comprehensive situation involving a mature scientific application code that solves the reacting Navier-Stokes equations for combustion research.

97 MATHEMATICS AND COMPUTING↗