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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Machine Learning for Conservative-to-Primitive in Relativistic Hydrodynamics

The numerical solution of relativistic hydrodynamics equations in conservative form requires root-finding algorithms that invert the conservative-to-primitive variables map. These algorithms employ the equation of state of the fluid and can be computationally demanding for applications involving sophisticated microphysics models, such as those required to calculate accurate gravitational wave signals in numerical relativity simulations of binary neutron stars. This work explores the use of machine learning methods to speed up the recovery of primitives in relativistic hydrodynamics. Artificial neural networks are trained to replace either the interpolations of a tabulated equation of state or directly the conservative-to-primitive map. The application of these neural networks to simple benchmark problems shows that both approaches improve over traditional root finders with tabular equation-of-state and multi-dimensional interpolations. In particular, the neural networks for the conservative-to-primitive map accelerate the variable recovery by more than an order of magnitude over standard methods while maintaining accuracy. Neural networks are thus an interesting option to improve the speed and robustness of relativistic hydrodynamics algorithms.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1976

On the structure of contact binaries. I - The contact discontinuity

The problem of the interior structure of contact binaries is reviewed, and a simple resolution of the difficulties which plague the theory is suggested. It is proposed that contact binaries contain a contact discontinuity between the lower surface of the common envelope and the Roche lobe of the cooler star. This discontinuity is maintained against thermal diffusion by fluid flow, and the transition layer is thin to the extent that the dynamical time scale is short in comparison with the thermal time scale. The idealization that the transition layer has infinitesimal thickness allows a simple formulation of the structure equations which are closed by appropriate jump conditions across the discontinuity. The further imposition of the standard boundary conditions suffices to define a unique model for the system once the chemical composition, the masses of the two stars, and the orbital separation are specified.

Shu, F. H.↗
DOE OSTI2024

The Evolution of Inclined Binary Black Holes in the Disks of Active Galactic Nuclei

The accretion disks that fuel active galactic nuclei (AGNs) may house numerous stars and compact objects, formed in situ or captured from nearby star clusters. Embedded neutron stars and black holes may form binaries and eventually merge, emitting gravitational waves detectable by LIGO/VIRGO. AGN disks are a particularly promising environment for the production of high-mass gravitational-wave events involving black holes in the pair-instability mass gap, and may facilitate electromagnetic counterparts to black hole binary mergers. However, many orders of magnitude separate the typical length scales of binary formation and those on which gravitational waves can drive binary inspirals, making binary mergers inside the disk uncertain. Previous hydrodynamical simulations of binaries have either been restricted to two dimensions entirely, or focused on binaries aligned with the midplane of the disk. Herein we present the first three-dimensional, high-resolution, local-shearing-box, inviscid hydrodynamical simulations of disk-embedded binaries over a range of orbital inclinations. We find that retrograde binaries can shrink up to 4 times as quickly as prograde binaries, and that all binaries not perfectly aligned (or anti-aligned) with the AGN disk are driven into alignment. An important consequence of this is that initially retrograde binaries will traverse the inclinations where von Zeipel–Lidov–Kozai oscillations can drive binary eccentricities to large values, potentially facilitating mergers. We also find that interactions with the AGN disk may excite eccentricities in retrograde binaries and cause the orbits of embedded binaries to precess.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2007

Binary Colloidal Alloy Test-3 and 4: Critical Point

Binary Colloidal Alloy Test - 3 and 4: Critical Point (BCAT-3-4-CP) will determine phase separation rates and add needed points to the phase diagram of a model critical fluid system. Crewmembers photograph samples of polymer and colloidal particles (tiny nanoscale spheres suspended in liquid) that model liquid/gas phase changes. Results will help scientists develop fundamental physics concepts previously cloaked by the effects of gravity.

Weitz, David A.↗
DOE OSTI2022

At-Line Sampling and Characterization of Pyrolytic Vapors from Biomass Feedstock Blends Using SPME-GC/MS-PCA: Influence of Char on Fast Pyrolysis

Solid-phase microextraction (SPME) coupled with GC-MS analysis was used for at-line sampling of pyrolytic vapors produced during fast pyrolysis of biomass. The pure and binary blends of switchgrass (SWG) and pine harvest residues (PT6) were used as feedstock. Sequential SPME sampling allowed for monitoring of changes in the pyrolysis vapors as char accumulated in the fluid bed. The concentration and composition of the vapors desorbed from the SPME fibers were investigated using GC-MS, and the data sets were then analyzed using principal component analysis (PCA) to compare the composition of the pyrolysis vapors over the course of the pyrolysis run. The chemical composition of both carbohydrate and lignin fragments varied as the char builds up in the reactor bed. Fragments derived from cellulose and xylan included anhydrosugars, furans and light oxygenated compounds. Lignin fragments included methoxyphenols, phenolic ketones and aldehydes, low molecular weight aromatics. The composition of the carbohydrate fragments changed more than the lignin fragments as the char build-up in the fluid bed. This combination of SPME-GC/MS-PCA were a novel, easy and effective method for measuring the composition and changes in the composition of pyrolysis vapors during the fast pyrolysis process. Here, this work also highlighted the effect of char build-up on the composition of the overall pyrolysis vapors.

09 BIOMASS FUELS↗
NASA NTRS1985

Research Reports: 1984 NASA/ASEE Summer Faculty Fellowship Program

A NASA/ASEE Summer Faulty Fellowship Program was conducted at the Marshall Space Flight Center (MSFC). The basic objectives of the programs are: (1) to further the professional knowledge of qualified engineering and science faculty members; (2) to stimulate an exchange of ideas between participants and NASA; (3) to enrich and refresh the research and teaching activities of the participants' institutions; and (4) to contribute to the research objectives of the NASA Centers. The Faculty Fellows spent ten weeks at MSFC engaged in a research project compatible with their interests and background and worked in collaboration with a NASA/MSFC colleague. This document is a compilation of Fellows' reports on their research during the summer of 1984. Topics covered include: (1) data base management; (2) computational fluid dynamics; (3) space debris; (4) X-ray gratings; (5) atomic oxygen exposure; (6) protective coatings for SSME; (7) cryogenics; (8) thermal analysis measurements; (9) solar wind modelling; and (10) binary systems.

Freeman, L. M.↗
DOE OSTI2020

Giant Planet Scatterings and Collisions: Hydrodynamics, Merger-Ejection Branching Ratio, and Properties of the Remnants

Planetary systems with sufficiently small orbital spacings can experience planetary mergers and ejections. The branching ratio of mergers vs ejections depends sensitively on the treatment of planetary close encounters. Previous works have adopted a simple “sticky-sphere” prescription, whose validity is questionable. We apply both smoothed particle hydrodynamics and N-body integrations to investigate the fluid effects in close encounters between gas giants and the long-term evolution of closely-packed planetary systems. Focusing on parabolic encounters between Jupiter-like planets with MJ and 2MJ, we find that quick mergers occur when the impact parameter rp (the pericenter separation between the planets) is less than 2RJ, and the merger conserved at least 97% of the initial mass. Strong tidal effects can affect the “binary-planet” orbit when rp is between 2RJ and 4RJ. We quantify these effects using a set of fitting formulae that can be implemented in N-body codes. We run a suite of N-body simulations with and without the formulae for systems of two giant planets initially in unstable, nearly circular and nearly coplanar orbits. The fluid (tidal) effects significantly increase the branching ratio of planetary mergers relative to ejections by doubling the effective collision radius. While the fluid effects do not change the distributions of semi-major axis and eccentricity of each type of remnant planets (mergers vs surviving planets in ejections), the overall orbital properties of planet scattering remnants are strongly affected due to the branching ratio change. We also find that the merger products have broad distributions of spin magnitudes and obliquities.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1982

Hydrodynamic stability of jets produced by mass accreting systems

The existing model for pulsed X-ray emission from the source Hercules X-1 is reviewed. A necessary part of this model is a processing accretion disk which turns the source on and off with 35 day cycle. It is usually assumed that precession of the primary star in this binary system, Hz Hercules, slaves the disk to its precession rate. This model can account for the system behavior in a qualitative manner. Precession of Hz Hercules with 35 day period requires precession of the binary orbit. Pulse arrival times from Herc X-1 have been analyzed for orbital precession. The inclusion of precession does not significantly improve the results obtained assuming a non-precessing orbit. The fluid dynamical stability of extra-galactic jets and the possible consequences of Kelvin-Helmholtz instability at the jet surface external medium interface are considered.

Hardee, P. E.↗
NASA NTRS1987

Double-diffusive effects during solidification

When a fluid contains two diffusing components with different molecular diffusivities, such as heat and solute concentration, convective motion may be generated when potential energy is released owing to differential diffusion. In the solidification of binary alloys and doped semiconductors, temperature and concentration gradients do exist simultaneously. If these gradients are aligned in a suitable manner, convection may ensue. In the case of the binary alloy, such convection may extend through the mushy zone and may be the cause of macrosegregations. In the case of doped semiconductors, the convective motion may cause the nonuniform distribution of dopant in the product. In this paper, the fundamentals of double-diffusive convection will be reviewed, and its effect on solidification will be discussed.

Chen, C. F.↗
DOE OSTI2024

Efficient data-driven models for prediction and optimization of geothermal power plant operations

Increasing the capacity of geothermal energy as a renewable resource calls for development and deployment of efficient control and optimization technologies for geothermal power plants. A data-driven prediction and optimization model is presented as a cost-effective and efficient alternative to physics-based approach. The model predicts power output and operational cost by propagating the influence of control and disturbance variables within an artificial neural network (ANN). Numerical experiments with simulated and field data from a real geothermal power plant are first used to demonstrate the prediction performance of the ANN model. The model is then adopted to maximize the net predicted power production by automatically adjusting the working fluid circulation rate. The optimization performance of the model in evaluated using a thermodynamic flowsheet simulation model. The workflow is applied to model and control the effect of ambient temperature on an air-cooled binary cycle power plant, which is complex and costly to perform using a physics-based predictive model. As a result, the performance of the method is demonstrated by applying it to both simulated and field datasets from a binary cycle geothermal power plant.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Closures for multicomponent reacting flows based on dispersion analysis

This work presents algebraic closure models associated with advective transport and nonlinear reactions in a Reynolds-averaged Navier-Stokes context for a system of species subject to binary reactions and transport by advection and diffusion. Expanding upon analysis originally developed for non-reactive transport in the context of Taylor dispersion of scalars, this work extends the modified gradient diffusion model explicated by Peters [N. Peters, Turbulent Combustion, Cambridge Monographs on Mechanics (Cambridge University Press, Cambridge, 2000)] and based on work by Corrsin [S. Corrsin, The reactant concentration spectrum in turbulent mixing with a first-order reaction, J. Fluid Mech. 11, 407 (1961)] beyond single-component transport phenomena and involving nonlinear reactions. The presented model forms, from this weakly nonlinear extension of the original dispersion theory, lead to an analytic expression for the eddy diffusivity matrix that explicitly captures the influence of the reaction kinetics on the closure operators. Furthermore, we demonstrate that the derived model form directly translates between flow topologies through a priori and a posteriori testing of a binary species system subject to homogeneous isotropic turbulence. Using two- and three-dimensional direct numerical simulations involving laminar and turbulent flows, it is shown that this framework improves prediction of mean quantities compared to previous results. Lastly, the presented model form, collapses to the earlier gradient diffusion and its modified version derived by Corrsin in the limits of nonreactive species and linear reactions, respectively.

42 ENGINEERING↗
DOE OSTI2021

Integrated modeling methodology for ash agglomeration in poly-disperse fluidized beds using particle population framework

This article discusses a unique agglomeration modeling methodology developed based on binary collisions to combine the effects of heterogeneity in ash chemistry and granular physics. A simple population balance is defined to find changes in the particle size distribution (PSD) of a fluidized bed. Thermodynamic equilibrium calculations and a computational fluid dynamics (CFD) code, are used to obtain hydrodynamic parameters. A method to calculate and use a distribution of collision frequencies in fluidized beds, corresponding to a poly-disperse particle size distribution, was developed in order to incorporate the particle level heterogeneities. A distribution of collision frequencies obtained for poly-dispersed particles showed a three orders of magnitude higher collision frequency amongst the smaller particles than the coarser ones, at the initiation of agglomeration. Ash agglomeration occurred when the slag amount (binder) was less than 10 wt% at temperatures <850 °C for Pittsburgh No. 8 coal.

42 ENGINEERING↗
NASA NTRS1992

Natural convection in binary gases driven by combined horizontal thermal and vertical solutal gradients

An investigation of natural convection is presented to examine the influence of a horizontal temperature gradient and a concentration gradient occurring from the bottom to the cold wall in a cavity. As the solutal buoyancy force changes from augmenting to opposing the thermal buoyancy force, the fluid motion switches from unicellular to multicellular flow (fluid motion is up the cold wall and down the hot wall for the bottom counterrotating flow cell). Qualitatively, the agreement between predicted streamlines and smoke flow patterns is generally good. In contrast, agreement between measured and predicted temperature and concentration distributions ranges from fair to poor. Part of the discrepancy can be attributed to experimental error. However, there remains considerable discrepancy between data and predictions due to the idealizations of the mathematical model, which examines only first-order physical effects. An unsteady flow, variable thermophysical properties, conjugate effects, species interdiffusion, and radiation were not accounted for in the model.

Weaver, J. A.↗
NASA NTRSDate not supplied

Deep Neural Network Based Convergence Classification for Computational Fluid Dynamics

A supervised deep learning approach is coupled with heuristic convergence criteria to construct a classification model for detecting the completion (convergence) of computational fluid dynamics (CFD) simulations. Heuristic convergence criteria alone are not always sufficient and more complex decisions are often left to a human analyst. The proposed approach leverages heuristic convergence criteria as well as two deep neural network (DNN) models, one binary and one multi-class, to improve the efficiency and consistency of convergence classification across a wide range of flight regimes. The DNN models presented are each trained on a subset of ascent aerodynamic CFD simulations for NASA’s Space Launch System and were produced using NASA’s unstructured Navier-Stokes solver FUN3D. Individual solutions are analyzed intermittently and are classified as sufficiently converged, further iterations required, or switch from steady Reynolds Averaged Navier-Stokes (RANS) to unsteady RANS CFD based on the iterative histories of four aerodynamic coefficients. The implemented classification model is shown to produce solutions that closely correlate to solutions produced by a human analyst. This work lays groundwork for expanding the capabilities of DNNs for automating and improving more of the CFD process.

SLS↗
NASA NTRS1997

Data Base for CFD Validation

The flow behind the shock wave formed around objects which fly at hypervelocity behaves differently from that of a perfect gas. Molecules become vibrationally excited, dissociated, and ionized. The hot gas may emit or absorb radiation. When the atoms produced by dissociation reach the wall surface, chemical reactions, including recombination, may occur. The thermochemical phenomena of vibration, dissociation, ionization, surface chemical reaction, and radiation are referred to commonly as high-temperature real-gas phenomena. The phenomena cause changes in the dynamic behavior of the flow and the surface pressure and heat transfer distribution around the object. The character of a real gas is described by the internal degrees of freedom and state of constituent molecules; nitrogen and oxygen for air. The internal energy states, rotation, vibration and electronic, of the molecules are excited and, in the limit, the molecular bonds are exceeded and the gas dissociated into atomic and, possibly, ionic constituents. The process of energy transfer causing excitation, dissociation and recombination is a rate process controlled by particle collisions. Binary, two-body, collisions are sufficient to cause internal excitation, dissociation and ionization while three-body collisions are required to recombine the particles into molecular constituents. If the rates of energy transfer are fast with respect to the local fluid dynamic time scale the gas is in, or nearly in, equilibrium. If the energy transfer rates are very slow the gas can be described as frozen. In all other instances, wherein any of the energy exchange rates are comparable to the local fluid time scale, the gas will be thermally or chemically reacting and out of equilibrium. Real gas thermochemical nonequilibrium processes are important in the determination of aerodynamic heating; both convective (including wall catalytic effects) and radiative heating. To illustrate this we consider the hypervelocity flow over a bluff body typical of an atmospheric entry vehicle or an aerospace transfer vehicle (ASTV). The qualitative aspects of a hypersonic flow field over a bluff body are discussed in two parts, forebody and afterbody, with attention to which particular physical effects must be included in an analysis. This will indicate what type of numerical modeling will be adequate in each region of the flow. A bluff forebody flow field is dominated by the presence of the strong bow shock wave and the consequent heating, and chemical reaction of the gas. At high altitude hypersonic flight conditions the thermal excitation and chemical reaction of the gas occur slowly enough that a significant portion of the flow field is in a state of thermochemical nonequilibrium. A second important effect is the presence of the thick boundary layer along the forebody surface. In this region there are large thermal and chemical species gradients due to the interaction of the gas with the wall. Also at high altitudes the shock wave and the boundary layer may become so thick that they merge; in this case the entire shock layer is dominated by viscous effects.

Deiwert, George S.↗
DOE OSTI2024

Accurate and Data‐Efficient Micro X‐ray Diffraction Phase Identification Using Multitask Learning: Application to Hydrothermal Fluids

Traditional analysis of highly distorted micro X‐ray diffraction (μ‐XRD) patterns from hydrothermal fluid environments is a time‐consuming process, often requiring substantial data preprocessing and labeled experimental data. Herein, the potential of deep learning with a multitask learning (MTL) architecture to overcome these limitations is demonstrated. MTL models are trained to identify phase information in μ‐XRD patterns, minimizing the need for labeled experimental data and masking preprocessing steps. Notably, MTL models show superior accuracy compared to binary classification convolutional neural networks. Additionally, introducing a tailored cross‐entropy loss function improves MTL model performance. Most significantly, MTL models tuned to analyze raw and unmasked XRD patterns achieve close performance to models analyzing preprocessed data, with minimal accuracy differences. This work indicates that advanced deep learning architectures like MTL can automate arduous data handling tasks, streamline the analysis of distorted XRD patterns, and reduce the reliance on labor‐intensive experimental datasets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Bimodal particle distributions with increased thermal conductivity for solid particles as heat transfer media and storage materials

Solid particles are being considered in several high temperature thermal energy storage systems and as heat transfer media in a variety of advanced power generation systems, particularly in concentrated solar power plants. The downside of such an approach is the low overall heat transfer coefficients caused by the inherently low thermal conductivity values of the low-cost solid media when coupled to heat exchanger for the power cycle working fluid. Choosing the right particle size distribution, emittance, and material of the solid media can all make a substantial difference in packed bed thermal conductivity. Current research though exclusively focuses on continuous unimodal distributions of particles. Here, in this work, we propose the use of a binary particle system with a bimodal size distribution to significantly increase packed bed thermal conductivity by reducing packed bed porosity. This is the first study related to ceramic solid particle heat transfer that has considered the thermal conductivity of non-unimodal size distributions at room and elevated temperatures. The following study found that for the binary particle system using Carbo particles CP 16/30 – CP 70/140 where the large particle volume fraction was 50% there was an 17–47% increase in packed bed thermal conductivity when compared with a nearly unimodal particle size distribution of CP 16/30 between 50 and 300 °C. Two different porosity and effective thermal conductivity models were studied, with one providing better prediction of porosity but both effective thermal conductivity models providing less predictive capacity. Importantly this approach can have a substantial impact of thermal performance, with little to no impact on the particle cost.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Effects of thermophoresis on high-pressure binary-species boundary layers with uniform and non-uniform compositions

Direct numerical simulations of high-pressure binary-species temporal boundary layers are performed to investigate the flow physics for three situations: (1) uniform and equal composition, (2) uniform but unequal compositions and (3) non-uniform composition. Both colder- and hotter-wall situations compared with the free stream are simulated. The working fluid is a nitrogen/methane mixture. The analysis is performed at a case-specific self-similar state. Even when the initial composition is uniform, the methane mean mass fraction decreases near the colder wall, whereas it increases near the hotter wall and the mass fraction fluctuates in the entire boundary layer. Analysis of the species-mass diffusion balance and flow structures reveal that both mass-fraction variation and fluctuations are induced by the Soret effect. When the initial composition is non-uniform and the wall is colder, the methane mean mass fraction monotonically increases from the wall akin to its initial profile. However, when the wall is hotter the mean mass fraction decreases near the wall in contrast to its initial profile, a fact traced through the species-mass diffusion balance to the Soret effect being large and enriching methane near the wall. In contrast, the direction of the Soret flux is opposite for the colder wall, thus keeping the methane concentration small. Although the initial magnitude of the difference between the wall and free-stream temperature is the same in all cases, the situation is not symmetric between colder- and hotter-wall cases; the flow structure exhibits much smaller scales when the wall is hotter than when the wall is colder.

Mechanics↗