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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

A multilayer perceptron solution to the match phase problem in rule-based artificial intelligence systems

In rule-based AI planning, expert, and learning systems, it is often the case that the left-hand-sides of the rules must be repeatedly compared to the contents of some 'working memory'. The traditional approach to solve such a 'match phase problem' for production systems is to use the Rete Match Algorithm. Here, a new technique using a multilayer perceptron, a particular artificial neural network model, is presented to solve the match phase problem for rule-based AI systems. A syntax for premise formulas (i.e., the left-hand-sides of the rules) is defined, and working memory is specified. From this, it is shown how to construct a multilayer perceptron that finds all of the rules which can be executed for the current situation in working memory. The complexity of the constructed multilayer perceptron is derived in terms of the maximum number of nodes and the required number of layers. A method for reducing the number of layers to at most three is also presented.

Sartori, Michael A.↗
DOE OSTI2021

The Patterson function as auto-hologram and graph enables the direct solution to the phase problem for coherently illuminated atomistic structures

Abstract The coherent Patterson function, derived from the coherent scattering intensities from N atoms, can be described as an auto-holographic image, i.e., the superposition of N -holographic images in which each atom serves as the source of a different reference wave, and as a mathematical graph of the unknown structure. These insights indicate that the unknown structure is significantly over-determined by the inherent information content in a Patterson function by a factor of ( N − 1)/2 (for non-degenerate structures), independent of dimensionality. However, we also show that the ability to resolve the distinct features in the Patterson function depends strongly on details of the experimental design (data range, sampling frequency, and dimensionality). This re-interpretation suggests that the coherent Patterson function provides a natural context for describing the information content in coherent scattering, reveals that there is no inherent phase problem for coherently illuminated pointwise structures, and enables the design of an algorithm which retrieves the structure directly from the Patterson function, without using error metric minimization.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1993

Self-Organized Criticality and Phase Problem in Magnetoaocustic Emission Burst in Ferromagnets

Two types of ferromagnets, pure iron and steel with varying geometry and microstructural properties, were prepared for the present study of magnetoacoustic emission (MAE). The purpose was to separate the effects of structural property variations from changes caused by differences in the sample geometry. The position and shape of the leading MAE sub-burst and its variation among the samples are explained by magnetic anisotropy and the results of numerical simulations which utilized the concept of self-organized criticality (SOC). The amplitude and duration of the second sub-burst, which previously was thought to occur as a result of a complicated interaction between non-180 deg domain walls and lattice defects, can easily be explained by the results of our simulation.

Namkung, M.↗
NASA NTRS1990

A numerical method for phase-change problems

A highly accurate and efficient finite-difference method for phase-change problems with multiple moving boundaries of irregular shape is developed by employing a coordinate transformation that immobilizes moving boundaries and preserves the conservative forms of the original governing equations. The numerical method is first presented for one-dimensional phase-change problems (involving large density variation between phases, heat generation, and multiple moving boundaries) and then extended to solve two-dimensional problems (without change of densities between phases). Numerical solutions are obtained non-iteratively using an explicit treatment of the interfacial mass and energy balances and an implicit treatment of the temperature field equations. The accuracy and flexibility of the present numerical method are verified by solving some phase-change problems and comparing the results with existing analytical, semi-analytical and numerical solutions. Results indicate that one- and two-dimensional phase-change problems can be handled easily with excellent accuracies.

Kim, Charn-Jung↗
NASA NTRS1992

Finite element developments for two dimensional multiple-interface phase change problems

Finite element developments for multiple phase change problems in two-dimensional models are presented for the first time. The enthalpy method is used to simulate latent heat release in conjunction with fixed grid techniques. An unconditionally stable implicit method is used for the time integration. The effects of boundary conditions and the different phase regions on the multiple phase front developments are examined for numerous examples. Discussions and conclusions are appropriately addressed.

Ouyang, Tianhong↗
DOE OSTI2026

The ABCs of phase retrieval: Connecting the acronyms of scanning transmission electron microscopy

High-resolution scanning transmission electron microscopy (S/TEM) is an indispensable tool for characterizing the structure and properties of materials down to the atomic scale. Conventional S/TEM imaging, however, is limited by the phase problem, whereby the phase of the electron exit wave is lost upon detection. Recent advances in diffractive imaging and 4D-STEM have enabled a range of phase-retrieval techniques that computationally reconstruct the missing information encoded in the phase of the transmission function. These approaches offer improved dose efficiency and enhanced sensitivity to weakly scattering signals, extending quantitative imaging to beam-sensitive materials composed of light elements. In this work, we introduce the phase problem in electron microscopy and survey the diverse landscape of phase-retrieval techniques used in the field. Despite their many acronyms and algorithmic variations, these techniques share a common physical and mathematical foundation. We present a unified framework that connects these seemingly distinct methods, from parallax imaging and tilt-corrected bright-field (tcBF-STEM), to aberration-corrected bright-field (acBF-STEM), optimum bright-field (OBF-STEM) and single-sideband (SSB) ptychography, as well as first-moment integrated center of mass techniques (iCOM) and iterative ptychographic algorithms. Based on these insights, we discuss the opportunities and practical limitations of applying these methods across different materials systems, detector designs, and microscope configurations.Graphical abstractRepresentative electron microscopy configurations used for phase retrieval and diffractive imaging in S/TEM: (a) Zernike phase-contrast transmission electron microscopy (TEM), (b) small-convergence-angle four-dimensional scanning transmission electron microscopy (4D-STEM) for nanobeam-based phase reconstruction methods, and (c) large-convergence-angle 4D-STEM for ptychographic and related diffractive imaging techniques reviewed in this work.

36 MATERIALS SCIENCE↗
NASA NTRS1992

Finite element simulations involving simultaneous multiple interface fronts in phase change problems

The present paper describes the simulation of phase change problems involving simultaneous multiple interface fronts employing the finite element method. Much of the past investigations employing finite elements have been restricted to primarily a single phase change situation. The existence of more than one phase, that is, the presence of multiple phase fronts poses certain challenges and further complications. However, the results provide a very interesting thermal behavior for this class of problems. In this paper, attention is focused on fixed grid methods and the trapezoidal family of one-step methods using the enthalpy formulations. Illustrative examples which handle simultaneous multiple fronts in phase change problems are presented.

Ouyang, Tianhong↗
DOE OSTI2024

Benchmarking machine learning strategies for phase-field problems

Abstract We present a comprehensive benchmarking framework for evaluating machine-learning approaches applied to phase-field problems. This framework focuses on four key analysis areas crucial for assessing the performance of such approaches in a systematic and structured way. Firstly, interpolation tasks are examined to identify trends in prediction accuracy and accumulation of error over simulation time. Secondly, extrapolation tasks are also evaluated according to the same metrics. Thirdly, the relationship between model performance and data requirements is investigated to understand the impact on predictions and robustness of these approaches. Finally, systematic errors are analyzed to identify specific events or inadvertent rare events triggering high errors. Quantitative metrics evaluating the local and global description of the microstructure evolution, along with other scalar metrics representative of phase-field problems, are used across these four analysis areas. This benchmarking framework provides a path to evaluate the effectiveness and limitations of machine-learning strategies applied to phase-field problems, ultimately facilitating their practical application.

36 MATERIALS SCIENCE↗
NASA NTRS1978

Numerical analyses for treating diffusion in single-, two- and three-phase binary alloy systems

Numerical solutions were applicable for planar, cylindrical, or spherical geometries with any diffusion-zone size and any continuous variation of the diffusion coefficient with concentration. Special techniques were included in the analyses to account for differences in molal volumes, initiation and growth of an intermediate phase, disappearance of a phase, and the presence of an initial composition profile in the specimen. A major improvement in solution accuracy was achieved in the two phase analysis by employing a mass conservation criterion to establish the location of the interface rather than the conventional interface-flux-balance criterion. In the three phase analysis, computation time was minimized without sacrificing solution accuracy by treating the three phase problem as a two phase problem when the thickness of the intermediate phase was less than a preset small value. Three computer codes were developed to perform these analyses.

Tenney, D. R.↗
NASA NTRS1988

Hybrid transfinite element modeling/analysis of nonlinear heat conduction problems involving phase change

The present paper describes the applicability of hybrid transfinite element modeling/analysis formulations for nonlinear heat conduction problems involving phase change. The methodology is based on application of transform approaches and classical Galerkin schemes with finite element formulations to maintain the modeling versatility and numerical features for computational analysis. In addition, in conjunction with the above, the effects due to latent heat are modeled using enthalpy formulations to enable a physically realistic approximation to be dealt computationally for materials exhibiting phase change within a narrow band of temperatures. Pertinent details of the approach and computational scheme adapted are described in technical detail. Numerical test cases of comparative nature are presented to demonstrate the applicability of the proposed formulations for numerical modeling/analysis of nonlinear heat conduction problems involving phase change.

Tamma, Kumar K.↗
DOE OSTI2022

AutoPhaseNN: unsupervised physics-aware deep learning of 3D nanoscale Bragg coherent diffraction imaging

Abstract The problem of phase retrieval underlies various imaging methods from astronomy to nanoscale imaging. Traditional phase retrieval methods are iterative and are therefore computationally expensive. Deep learning (DL) models have been developed to either provide learned priors or completely replace phase retrieval. However, such models require vast amounts of labeled data, which can only be obtained through simulation or performing computationally prohibitive phase retrieval on experimental datasets. Using 3D X-ray Bragg coherent diffraction imaging (BCDI) as a representative technique, we demonstrate AutoPhaseNN, a DL-based approach which learns to solve the phase problem without labeled data. By incorporating the imaging physics into the DL model during training, AutoPhaseNN learns to invert 3D BCDI data in a single shot without ever being shown real space images. Once trained, AutoPhaseNN can be effectively used in the 3D BCDI data inversion about 100× faster than iterative phase retrieval methods while providing comparable image quality.

36 MATERIALS SCIENCE↗
NASA NTRS1987

A fixed grid numerical methodology for phase change problems involving a moving heat source

A numerical method for solving phase change problems involving a moving heat source is presented and illustrated by a two-dimensional example. The method uses a fixed grid and does not require the implementation of the Stefan condition at the solid-liquid interface; the procedure can thus be easily implemented using existing fixed grid codes. The problem considered as an example involves natural convection flow in the molten metal during tungsten inert gas welding.

Prakash, C.↗
DOE OSTI2021

PhaseGAN: a deep-learning phase-retrieval approach for unpaired datasets

Phase retrieval approaches based on deep learning (DL) provide a framework to obtain phase information from an intensity hologram or diffraction pattern in a robust manner and in real-time. However, current DL architectures applied to the phase problem rely on i) paired datasets, i. e., they arc only applicable when a satisfactory solution of the phase problem has been found, and ii) the fact that most of them ignore the physics of the imaging process. Here, we present PhaseGAN, a new DL approach based on Generative Adversarial Networks, which allows the use of unpaired datasets and includes the physics of image formation. The performance of our approach is enhanced by including the image formation physics and a novel Fourier loss function, providing phase reconstructions when conventional phase retrieval algorithms fail, such as ultra-fast experiments. Thus, PhaseGAN offers the opportunity to address the phase problem in real-time when no phase reconstructions but good simulations or data from other experiments are available.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Development of Modified Perturbation Solutions to the One-Phase Stefan Problems With a Convective Boundary

The classical Stefan problem is used to track the moving solid-liquid interface during the freezing process. Perturbation theory has often been applied to find an approximate analytical solution due to the nonlinearity of the moving interface. However, the Stefan number (i.e., the sensible over latent heat) must be small and usually less than 0.01 to assume the perturbation expansion, which in turn limits the thermal engineering applications. In this study, a modified perturbation solution is developed by adding a correction term after the leading-order solution to be valid for a much wider range of Stefan numbers (i.e., 0.01 less than or equal to Ste less than or equal to 1). Specifically, a one-phase Stefan problem is first formulated subjected to a convective boundary in the Cartesian, cylindrical, and spherical coordinate systems for inward solidification. The leading-order solution is calculated based on the regular perturbation theory, while the correction term is obtained using the Monte-Carlo method and a multi-variant regression. Results show that the correction term has a linear relationship with the Stefan number and is not significantly influenced by the Biot number. The proposed modified perturbation solution can accurately and rapidly predict the nonlinear moving interface motion for the freezing process.

DIRECT ENERGY CONVERSION,MATHEMATICS AND COMPUTING↗
NASA NTRS1989

Similarity solutions for phase-change problems

A modification of Ivantsov's (1947) similarity solutions is proposed which can describe phase-change processes which are limited by diffusion. The method has application to systems that have n-components and possess cross-diffusion and Soret and Dufour effects, along with convection driven by density discontinuities at the two-phase interface. Local thermal equilibrium is assumed at the interface. It is shown that analytic solutions are possible when the material properties are constant.

Canright, D.↗