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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

AMReX: Block-structured adaptive mesh refinement for multiphysics applications

Block-structured adaptive mesh refinement (AMR) provides the basis for the temporal and spatial discretization strategy for a number of Exascale Computing Project applications in the areas of accelerator design, additive manufacturing, astrophysics, combustion, cosmology, multiphase flow, and wind plant modeling. AMReX is a software framework that provides a unified infrastructure with the functionality needed for these and other AMR applications to be able to effectively and efficiently utilize machines from laptops to exascale architectures. AMR reduces the computational cost and memory footprint compared to a uniform mesh while preserving accurate descriptions of different physical processes in complex multiphysics algorithms. AMReX supports algorithms that solve systems of partial differential equations in simple or complex geometries and those that use particles and/or particle–mesh operations to represent component physical processes. In this article, we will discuss the core elements of the AMReX framework such as data containers and iterators as well as several specialized operations to meet the needs of the application projects. In addition, we will highlight the strategy that the AMReX team is pursuing to achieve highly performant code across a range of accelerator-based architectures for a variety of different applications.

Zhang, Weiqun↗
NASA NTRS1964

On an Approximation Theorem of Kupka and Smale

Simplified and generalized geometrical proof of Kupka and Smale approximation theorem concerning differential equations defined on closed, compact, infinitely differentiable manifold

THEOREM PROVING↗
NASA NTRS1981

Numerical solutions of atmospheric flow over semielliptical simulated hills

Atmospheric motion over obstacles on plane surfaces to compute simulated wind fields over terrain features was studied. Semielliptical, two dimensional geometry and numerical simulation of flow over rectangular geometries is also discussed. The partial differential equations for the vorticity, stream function, turbulence kinetic energy, and turbulence length scale were solved by a finite difference technique. The mechanism of flow separation induced by a semiellipse is the same as flow over a gradually sloping surface for which the flow separation is caused by the interaction between the viscous force, the pressure force, and the turbulence level. For flow over bluff bodies, a downstream recirculation bubble is created which increases the aspect ratio and/or the turbulence level results in flow reattachment close behind the obstacle.

Shieh, C. F.↗
DOE OSTI2020

Comparison between PARFUME and Bison Using the AGR-2 Irradiation Experiment

This report documents comparisons between Fuel Model (PARFUME) model predictions versus Bison for selected compacts from the second irradiation test of the Advanced Gas Reactor (AGR) program that occurred from June 2010 to October 2013 in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). PARFUME is a fuel performance analysis and modeling code, used for evaluating gas-reactor tristructural isotropic (TRISO) coated particle fuel for prismatic, pebble bed, plate, and cylindrical type fuel geometries. PARFUME is an integrated mechanistic computer code that evaluates the thermal, mechanical, and physico-chemical behavior of TRISO coated-fuel particles and the probability for fuel failure given the particle-to-particle statistical variations in physical dimensions and material properties that arise during the fuel fabrication process. Bison is a nuclear fuel performance application built using the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element library (Permann 2020). Bison is capable of modeling multiple fuel forms in a wide variety of dimensions and geometries. It solves coupled nonlinear partial differential equations, including heat conduction, mechanics, fission product species transport etc., in a fully implicit manner. Comparisons between PARFUME and Bison were performed using four compacts from the AGR-2 experiment. Selected outputs were chosen based on their impact on the probability of the SiC layer failing. In general there was good agreement between PARFUME and Bison with the exception of predicting the gap formed between the buffer and IPyC. Further comparisons between PARFUME and Bison are planned to further develop Bison’s capabilities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Design of water-moderated heterogeneous cores in new STACY facility through JAEA/IRSN collaboration - 14363

In the post-Fukushima prospect, Japan Atomic Energy Agency, JAEA, intends to re-open its Static Experiment Critical Facility STACY, in order to contribute to the validation of fuel debris calculations in conditions close to those affected by the Fukushima Daiichi Nuclear Power Station accident. The reactor core of STACY is being modified by JAEA from homogeneous solution fuel core to heterogeneous pin- type fuel core. The first step of critical experiments is to establish reference experiments involving lattices of UO{sub 2} rods without fuel debris. A design of such experiments is in progress for the widest range of moderation ratios in the frame of JAEA/IRSN collaboration. To anticipate the specification values of materials to be manufactured (grids, rods), an evaluation of uncertainties pertaining to the different parameters driving k{sub eff} is paramount. The following uncertainties of experimental cores are evaluated to estimate the reactivity effect of engineering tolerance/or measurements of the modified STACY: (1) Density of fuel pellets, (2) Enrichment of uranium, (3) Diameter of fuel pellets, (4) Thickness of fuel claddings, (5) Impurities of fuel pellets, (6) Impurities of fuel claddings and (7) Positioning of fuel rods in the lattice. For these calculations, three types of moderation conditions were considered within the experimental parameters of STACY: the lowest moderation (lattice pitch = 1.15 cm; V{sub m}/V{sub f}=1.2), optimum moderation (lattice pitch = 1.5 cm, V{sub m}/V{sub f} = 2.9) and an over moderated case (lattice pitch = 2.55 cm; V{sub m}/V{sub f} = 11). The calculations to derive the overall uncertainty of modified STACY were performed propagating the 1σ uncertainties of parameters of existing STACY in terms of k{sub eff}. For that purpose, a perturbation calculation (differential operator) technique and a stochastic geometry modeling technique were used with the MCNP5 continuous energy Monte Carlo code and a point-wise cross section library based on the JENDL-4.0 evaluated nuclear data library. Moreover, the results of calculations were compared with those calculated by two continuous energy Monte Carlo codes using the correlated sampling technique: - An experimental version of the Japanese MVP2 code combined to the JENDL-4.0 nuclear data library, - The MORET 5 code, developed by IRSN, combined to the JEFF-3.1 nuclear data library. The proposed paper discusses all the aforementioned issues, and confirms that the uncertainty pertaining to the critical experiments of the STACY is sufficiently small. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2013

Propellant-Flow-Actuated Rocket Engine Igniter

A rocket engine igniter has been created that uses a pneumatically driven hammer that, by specialized geometry, is induced into an oscillatory state that can be used to either repeatedly impact a piezoelectric crystal with sufficient force to generate a spark capable of initiating combustion, or can be used with any other system capable of generating a spark from direct oscillatory motion. This innovation uses the energy of flowing gaseous propellant, which by means of pressure differentials and kinetic motion, causes a hammer object to oscillate. The concept works by mass flows being induced through orifices on both sides of a cylindrical tube with one or more vent paths. As the mass flow enters the chamber, the pressure differential is caused because the hammer object is supplied with flow on one side and the other side is opened with access to the vent path. The object then crosses the vent opening and begins to slow because the pressure differential across the ball reverses due to the geometry in the tube. Eventually, the object stops because of the increasing pressure differential on the object until all of the kinetic energy has been transferred to the gas via compression. This is the point where the object reverses direction because of the pressure differential. This behavior excites a piezoelectric crystal via direct impact from the hammer object. The hammer strikes a piezoelectric crystal, then reverses direction, and the resultant high voltage created from the crystal is transferred via an electrode to a spark gap in the ignition zone, thereby providing a spark to ignite the engine. Magnets, or other retention methods, might be employed to favorably position the hammer object prior to start, but are not necessary to maintain the oscillatory behavior. Various manifestations of the igniter have been developed and tested to improve device efficiency, and some improved designs are capable of operation at gas flow rates of a fraction of a gram per second (0.001 lb/s) and pressure drops on the order of 30 to 50 kilopascal (a few psi). An analytical model has been created and tested in conjunction with a precisely calibrated reference model. The analytical model accurately captures the overall behavior of this innovation. The model is a simple "volume-orifice" concept, with each chamber considered a single temperature and pressure "node" connected to adjacent nodes, or to vent paths through flow control orifices. Mass and energy balances are applied to each node, with gas flow predicted using simple compressible flow equations.

Wollen, Mark↗
DOE OSTI2015

Integrated high-order surface diffraction gratings for diode lasers

High-order surface diffraction gratings acting as a distributed Bragg reflector (DBR) in mesa stripe semiconductor lasers (λ = 1030 nm) have been studied theoretically and experimentally. Higher order interfering radiation modes (IRMs), which propagate off the plane of the waveguide, have been shown to have a crucial effect on the reflection and transmission spectra of the DBR. The decrease in the reflectivity of the DBR in response to the increase in the diffraction efficiency of these modes may reach 80% and more. According to theoretical analysis results, the intensity of the higher order IRMs is determined by the geometry of the DBR groove profile. Experimental data demonstrate that the noncavity modes are responsible for parasitic light leakage losses in the laser cavity. It has been shown that, in the case of nonoptimal geometry of the grating groove profile, the overall external differential quantum efficiency of the parasitic laser emission may exceed 45%, which is more than half of the laser output power. The optimal geometry of the DBR groove profile is trapezoidal, with the smallest possible lower base. Experimental evidence has been presented that this geometry considerably reduces the power of the higher order IRMs and minimises the parasitic light leakage loss. (lasers)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

A Tailored Convolutional Neural Network for Nonlinear Manifold Learning of Computational Physics Data Using Unstructured Spatial Discretizations

In this work, we propose a nonlinear manifold learning technique based on deep convolutional autoencoders that is appropriate for model order reduction of physical systems in complex geometries. Convolutional neural networks have proven to be highly advantageous for compressing data arising from systems demonstrating a slow-decaying Kolmogorov n-width. However, these networks are restricted to data on structured meshes. Unstructured meshes are often required for performing analyses of real systems with complex geometry. Our custom graph convolution operators based on the available differential operators for a given spatial discretization effectively extend the application space of deep convolutional autoencoders to systems with arbitrarily complex geometry that are typically discretized using unstructured meshes. We propose sets of convolution operators based on the spatial derivative operators for the underlying spatial discretization, making the method particularly well suited to data arising from the solution of partial differential equations. We demonstrate the method using examples from heat transfer and fluid mechanics and show better than an order of magnitude improvement in accuracy over linear methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Application of the GBFP Method to Electron Partial-Wave Expansion Elastic Scattering Differential Cross Sections Within the Geant4 Toolkit - Paper 69

Analog Monte Carlo simulation of electrons in complex material geometries is generally impractical because the long range Coulomb interactions result in highly peaked differential cross sections (DCS) for scattering and energy-loss and extremely small collision mean free paths (mfp). The condensed history (CH) Monte Carlo method attempts to alleviate this limitation by advancing electrons in fixed steps and sampling angular deflections and energy losses from precomputed distributions obtained from approximate solutions to the underlying transport equation that are valid only for thin layers. Though CH is efficient and is widely employed in production codes (ITS, MCNP, EGS, Geant), step size restrictions and inconsistent handling of material and free surface boundaries limit the ultimate accuracy possible with this approach, especially in applications to highly heterogeneous media. Recently proposed alternatives to the CH method, such as the Generalized Boltzmann Fokker-Planck (GBFP) method, restore the correct transport mechanics by simulating single events based on a Boltzmann transport equation but with efficiency and accuracy achieved through the use of reduced-physics interaction models. Motivated by Lewis theory, various moment-preserving strategies are employed in the GBFP approach to construct DCSs that are less singular, and with mfps shorter than analog. Specifically, the approximate cross sections are constructed to rigorously preserve a finite number of angular and energy-loss moments of the analog DCSs while all higher moments are approximated in terms of the exact lower moments. By systematically increasing the number of moments retained, any desired accuracy can be obtained for integrated quantities, such as dose, reflection and transmission yields, as well as distributed quantities such as energy and angular distributions. For relativistic Rutherford cross section models, the GBFP method has been demonstrated in Monte Carlo simulation to yield accuracy comparable to analog but at a fraction of the cost. One advantage of the GBFP approach is that angular deflection and energy-loss interactions depend only on Legendre moments and energy-loss moments and not the detailed form of the analog DCSs. This feature allows moment-preservation to be enforced through DCSs expressed as a superposition of discrete (i.e., using delta-functions) angular deflections and discrete energy losses. This promotes extremely efficient computation when compared to analog and completely continuous or hybrid discrete-continuous moment-based DCS reconstructions, while yielding highly accurate results for integrated and distributed quantities. In this paper, we demonstrate that the moment-preserving algorithms central to our fully discrete GBFP method can be readily extended to apply to tabulated DCS data, specifically to the partial-wave expansion (PWE) elastic scattering DCSs. Since data libraries for the PWE DCSs for energy and material combinations of interest can be prohibitively large, the GBFP method provides a means to reduce data storage requirements. We implemented our algorithm in the Geant4 Monte Carlo code and all numerical results are obtained using this implementation. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2024

Correlation Between Microscopic Current Fluctuations Observed at Ultra-Microelectrodes and Macroscopic Bulk Electrolysis Performance in Redox-Active Microemulsions

Microemulsions (μEs) have been proposed as redox flow battery (RFB) electrolytes that maximize ionic conductivity and charge capacity by synergizing two immiscible phases. However, charge transfer during electrolysis in μEs is poorly understood. Here, we show that ultramicroelectrode electrolysis of ferrocene-loaded μEs –20%, 60%, and 90% water - reveals stochastic current fluctuations. These are differentiated in the scanning electrochemical microscopy (SECM) geometry, where power spectral density analysis showed distinct changes in the frequency contributions. SECM in the substrate generation-tip collection mode showed that fluctuations arise under mass-transfer control. Significant differences in the diffusion coefficient of ferrocene species were deducted from SECM approach curves, suggesting phase transfer behavior. Using bulk electrolysis, we calculated the charge accessibility and cycling behavior in the μEs. A decrease in the stochastic behavior of the μEs seems to correlate to a higher accessibility and cycling performance, with the 90% water μE displaying the best reversibility and the 60% the lowest. Altogether, these results suggest that Marangoni-type convection driven by concentration gradients and/or μE restructuring during charge transfer play a role in the electrochemical performance of μEs. This presents opportunities for screening and diagnosing the performance of these emerging RFB electrolytes.

25 ENERGY STORAGE↗
DOE OSTI2020

Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonlinear Partial Differential Equations

Here we propose a generalized space-time domain decomposition approach for the physics-informed neural networks (PINNs) to solve nonlinear partial differential equations (PDEs) on arbitrary complex-geometry domains. The proposed framework, named eXtended PINNs ( X P I N N s ), further pushes the boundaries of both PINNs as well as conservative PINNs (cPINNs), which is a recently proposed domain decomposition approach in the PINN framework tailored to conservation laws. Compared to PINN, the XPINN method has large representation and parallelization capacity due to the inherent property of deployment of multiple neural networks in the smaller subdomains. Unlike cPINN, XPINN can be extended to any type of PDEs. Moreover, the domain can be decomposed in any arbitrary way (in space and time), which is not possible in cPINN. Thus, XPINN offers both space and time parallelization, thereby reducing the training cost more effectively. In each subdomain, a separate neural network is employed with optimally selected hyperparameters, e.g., depth/width of the network, number and location of residual points, activation function, optimization method, etc. A deep network can be employed in a subdomain with complex solution, whereas a shallow neural network can be used in a subdomain with relatively simple and smooth solutions. We demonstrate the versatility of XPINN by solving both forward and inverse PDE problems, ranging from one-dimensional to three-dimensional problems, from time-dependent to time-independent problems, and from continuous to discontinuous problems, which clearly shows that the XPINN method is promising in many practical problems. The proposed XPINN method is the generalization of PINN and cPINN methods, both in terms of applicability as well as domain decomposition approach, which efficiently lends itself to parallelized computation. The XPINN code is available on h t t p s : / / g i t h u b . c o m / A m e y a J a g t a p / X P I N N s .

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

AMReX

AMReX is a software framework for the development and implementation of massively parallel algorithms using block-structured adaptive mesh refinement (AMR). Block-structured AMR provides the basis for the temporal and spatial discretization strategy for a large variety of applications of interest to the DOE. AMReX provides a unified infrastructure with the functionality needed for applications to be able to effectively and efficiently utilize machines from laptops to exascale accelerator-based architectures. AMR reduces the computational cost and memory footprint compared to a uniform mesh while preserving accurate descriptions of different physical processes in complex multi-physics algorithms. AMReX supports algorithms that solve systems of partial differential equations (PDEs) in simple or complex geometries, and those that use particles and/or particle-mesh operations to represent component physical processes.

Zhang, Weiqun↗
NASA NTRS1981

A Quasi-Parabolic technique for computation of three-dimensional viscous flows

A computational technique is presented for obtaining flowfield solutions to a parabolic form of the Navier-Stokes equations. The point of departure is the General Interpolant Method (GIM) which provides a discretization for partial differential equations on arbitrary three-dimensional geometries. The new scheme, termed Quasi-Parabolic, treats the parabolized equations but with 'time-like' terms appended. Addition of these extra terms, which are relaxed by iteration, avoid many of the singularities inherent in classical parabolic Navier-Stokes methods. Streamwise derivatives are approximated by three-point backward differences and the cross plane operators use an alternating forward-backward sweep. A two-step sequence is used to implement the difference scheme in the spatial dimensions and a time-like relaxation converges the quasi-parabolic procedure at each plane. Solutions are presented for flows in two and three dimensions. Inviscid flows are solved for internal and external applications and viscous flows in boundary layers and free shear layers are also computed with the GIM/Quasi-Parabolic scheme.

Spradley, L. W.↗
NASA NTRS2000

Testing Models of Resonant Compton Scattering in X-Ray Pulsars

Over the performance period covered by the grant, the principal investigator modified a Monte Carlo Compton scattering code to model the propagation of x-rays through the magnetosphere of accreting neutron stars. These modifications were made to enable the author to compare the observations of x-ray pulsars to theoretical models of the system. The original code was designed to study relativistic plasmas with one of two geometries: a plane parallel plasma with a differential relativistic bulk velocity, and a static spherically symmetric plasma.- This code did not treat gravitational bending or bulk motion in the magnetosphere of a neutron star. Under the grant, the author incorporated code to trace light paths in a Schwarzschild metric. The code was modified to keep track of the photon polarization during propagati on. The investigator also modified the code so that bulk motion in an axisymmetric system is treated properly. An approximate treatment for resonant Compton scattering was added to the code. Finally, code was added that creates model observables that can be compared to observations, such as projected x-ray emission maps and energy-dependent light curves. Comparison to observations is now commencing.

Brainerd, Jerome J.↗
DOE OSTI2024

Importance of Higher Fidelity Model Geometries during Optimization of Critical Experiments

PARADIGM, PARallel Approach of Differential and InteGral Measurements, is a cross-collaborative effort at Los Alamos National Laboratory between nuclear data theorists, differential and integral experimenters, as well as machine learning statisticians to tackle uncertainties in the intermediate region of 239 Pu. In essence, the idea behind PARADIGM is to remove the linear conceptualization of the nuclear data pipeline, shown in Figure 1, and replace it with a far more parallelized approach. The novel approach leverages machine learning to guide which differential measurements and integral experiments will result in the largest decrease in uncertain ties for a nuclide reaction pair in a given energy range. The concept builds off earlier work, EUCLID, which focused on the fast region of 239 Pu. The practical benefit of having evaluation, differential measurement, and integral experiment personnel in collaboration with machine learning is to represent the entire nuclear data in one snapshot. This enable large reduction in the time to deliver improved nuclear data, which using the PARADIGM approach could be done in 3 years. A general outline of PARADIGM and specific topics are available in other papers. The discussion here will pertain directly to the integral experiment design. More specifically, the process of taking a rough design and transforming it into a finalized neutronic model will be discussed.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1987

Geometric description and grid generation for space vehicles

The understanding and analysis of three dimensional fluid behavior around reentry vehicles, like the Space Shuttle Orbiter, is of considerable importance for flight applications. Vehicle designers need pressure, heat transfer, and shear distributions to support design activities. Traditionally these have been obtained by experimental data. Significant reduction in design costs can be obtained if the calculated results based on finite difference procedures are used to verify and supplement experimental results. Computing the flow field over Space Shuttle Orbiter, which has complex cross sectional geometries is a major problem. A first step in this direction is development of body definition and grid generation procedure. In this project a digitized body definition and grid generation procedure, developed earlier at JSC, is modified and applied to the Shuttle Orbiter X24C-10D. Two dimensional grid and body definition for various sections of the space vehicle is obtained using the differential equation method. This study demonstrates that this geometry and grid generation procedure can be applied to other aerospace vehicles such as aerospaceplanes.

Krishna, Madakasira G.↗
DOE OSTI2022

Nonperturbative negative geometries: amplitudes at strong coupling and the amplituhedron

The amplituhedron determines scattering amplitudes in planar N = 4 super Yang-Mills by a single “positive geometry” in the space of kinematic and loop variables. We study a closely related definition of the amplituhedron for the simplest case of four-particle scattering, given as a sum over complementary “negative geometries”, which provides a natural geometric understanding of the exponentiation of infrared (IR) divergences, as well as a new geometric definition of an IR finite observable F(g, z) — dually interpreted as the expectation value of the null polygonal Wilson loop with a single Lagrangian insertion — which is directly determined by these negative geometries. This provides a long-sought direct link between canonical forms for positive (negative) geometries, and a completely IR finite post-loop-integration observable depending on a single kinematical variable z, from which the cusp anomalous dimension Γ cusp (g) can also be straightforwardly obtained. We study an especially simple class of negative geometries at all loop orders, associated with a “tree” structure in the negativity conditions, for which the contributions to F(g, z) and Γ cusp can easily be determined by an interesting non-linear differential equation immediately following from the combinatorics of negative geometries. This lets us compute these “tree” contributions to F(g, z) and Γ cusp for all values of the ‘t Hooft coupling. The result for Γ cusp remarkably shares all main qualitative characteristics of the known exact results obtained using integrability.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗