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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Surface Processes of Faceted Growth

Atomic force microscopy and high precision optical interferometry allow to analyze the processes that are in the core of our present understanding of faceted crystal growth. Some of these processes will be reviewed. Recent experiments suggest that the Gibbs-Thomson Law (GTL) may not be applicable to the weakly fluctuating strongly polygonized steps, with low kink density. Propagation rate of a straight short step segment changes with the segment length much steeper than predicted by GTL. If the step fluctuations are still well developed, the typical transition length may be determined just by the radius of rounded comers of the polygonized step. If fluctuations do not have enough time to develop, the kinetic effects may be essential. Indeed, 'communications' between comers of a short straight step segment may occur and, thus, the GTL may be implemented only via kink exchange. E.g., dissolutions of this short segment at macroscopic equilibrium occurs as follows: The kinks are split from one comer as a result of fluctuations, and annihilate with kinks of the opposite sign generated by another comer. Similarly, an exchange via chain of kinks on a rough step is the mechanism to implement the GT Law. If there is a supersaturation with respect to a large crystal, the kinks not only diffuse along the step, but move back the generating comers. This 'wind' prevents communication between the comers and places upper limit supersaturation only below which GTL is applicable. Steps replace kinks in the 3D case, though, of course, another dimensionality brings about another physics. Another specific problem to think about is if fluctuations are always fast enough to provide enough kinks for linear dependence of step rate on supersaturation. Increasing azimuthal polygonization of growth hillocks is a sign of insufficient fluctuation rate. Morphological stability of vicinal faces is usually considered on the basis of mutually parallel steps. Azimuthal anisotropy and interlacing of step bunches inducing the well known bunch splitting is another challenge. Among other challenging problems are: existence of surface diffusion on the crystal/so1ution interface, step interaction in solutions, achievement of step flow modes from liquids, impurity effects. New phenomena essential in biomacromolecular crystallization is another interesting area.

Chernov, A.↗
NASA NTRS1993

Computational Fluid Dynamics (CFD) Analysis for the Reduction of Impeller Discharge Flow Distortion

The use of Computational Fluid Dynamics (CFD) in the design and analysis of high performance rocket engine pumps has increased in recent years. This increase has been aided by the activities of the Marshall Space Flight Center (MSFC) Pump Stage Technology Team (PSTT). The team's goals include assessing the accuracy and efficiency of several methodologies and then applying the appropriate methodology(s) to understand and improve the flow inside a pump. The PSTT's objectives, team membership, and past activities are discussed in Garcia1 and Garcia2. The PSTT is one of three teams that form the NASA/MSFC CFD Consortium for Applications in Propulsion Technology (McConnaughey3). The PSTT first applied CFD in the design of the baseline consortium impeller. This impeller was designed for the Space Transportation Main Engine's (STME) fuel turbopump. The STME fuel pump was designed with three impeller stages because a two-stage design was deemed to pose a high developmental risk. The PSTT used CFD to design an impeller whose performance allowed for a two-stage STME fuel pump design. The availability of this design would have lead to a reduction in parts, weight, and cost had the STME reached production. One sample of the baseline consortium impeller was manufactured and tested in a water rig. The test data showed that the impeller performance was as predicted and that a two-stage design for the STME fuel pump was possible with minimal risk. The test data also verified another CFD predicted characteristic of the design that was not desirable. The classical 'jet-wake' pattern at the impeller discharge was strengthened by two aspects of the design: by the high head coefficient necessary for the required pressure rise and by the relatively few impeller exit blades, 12, necessary to reduce manufacturing cost. This 'jet-wake pattern produces an unsteady loading on the diffuser vanes and has, in past rocket engine programs, lead to diffuser structural failure. In industrial applications, this problem is typically avoided by increasing the space between the impeller and the diffuser to allow the dissipation of this pattern and, hence, the reduction of diffuser vane unsteady loading. This approach leads to small performance losses and, more importantly in rocket engine applications, to significant increases in the pump's size and weight. This latter consideration typically makes this approach unacceptable in high performance rocket engines.

Garcia, R.↗
DOE OSTI2022

Learning functional priors and posteriors from data and physics

In this work, we develop a new Bayesian framework based on deep neural networks to be able to extrapolate in space-time using historical data and to quantify uncertainties arising from both noisy and gappy data in physical problems. Specifically, the proposed approach has two stages: (1) prior learning and (2) posterior estimation. At the first stage, we employ the physics-informed Generative Adversarial Networks (PI-GAN) to learn a functional prior either from a prescribed function distribution, e.g., Gaussian process, or from historical data and physics. At the second stage, we employ the Hamiltonian Monte Carlo (HMC) method to estimate the posterior in the latent space of PI-GANs. In addition, we use two different approaches to encode the physics: (1) automatic differentiation, used in the physicsinformed neural networks (PINNs) for scenarios with explicitly known partial differential equations (PDEs), and (2) operator regression using the deep operator network (DeepONet) for PDE-agnostic scenarios. We then test the proposed method for (1) meta-learning for one-dimensional regression, and forward/inverse PDE problems (combined with PINNs); (2) PDE-agnostic physical problems (combined with DeepONet), e.g., fractional diffusion as well as saturated stochastic (100-dimensional) flows in heterogeneous porous media; and (3) spatial-temporal regression problems, i.e., inference of a marine riser displacement field using experimental data from the Norwegian Deepwater Programme (NDP). The results demonstrate that the proposed approach can provide accurate predictions as well as uncertainty quantification given very limited scattered and noisy data, since historical data could be available to provide informative priors. In summary, the proposed method is capable of learning flexible functional priors, e.g., both Gaussian and non-Gaussian process, and can be readily extended to big data problems by enabling mini-batch training using stochastic HMC or normalizing flows since the latent space is generally characterized as low dimensional.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

A Variable Eddington Factor Model for Thermal Radiative Transfer with Closure Based on Data-Driven Shape Function

Here, a new variable Eddington factor (VEF) model is presented for nonlinear problems of thermal radiative transfer (TRT). The VEF model is data-driven and acts on known (a-priori) radiation-diffusion solutions for material temperatures in the TRT problem. A linear auxiliary problem is constructed for the radiative transfer equation (RTE) whose emission source and opacities are evaluated at these known material temperatures. The solution to this RTE approximates the specific intensity distribution in phase-space and time. It is applied as a shape function to define the Eddington tensor for the presented VEF model. The shape function computed via the auxiliary RTE problem will capture some degree of transport effects within the TRT problem. The VEF moment equations closed with this approximate Eddington tensor will thus carry with them these captured transport effects. In this study, the temperature data comes from multigroup P 1 , P 1/3 , and flux-limited diffusion radiative transfer models. The proposed VEF model can be interpreted as a transport-corrected diffusion reduced-order model. Numerical results are presented on the Fleck-Cummings test problem which models a supersonic wavefront of radiation. The VEF model is shown to improve accuracy by 1–2 orders of magnitude compared to the considered radiation-diffusion model solutions to the TRT problem.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

On the Diffusivity of Moist Static Energy and Implications for the Polar Amplification Response to Climate Warming

Energy balance models (EBMs) have been widely used in a range of climate problems, but the assumption of constant diffusivity in the parameterization of the moist static energy (MSE) flux can be hardly justified. We demonstrate in this study that the diffusive MSE flux can be derived from the basic energy balance equation with a few tolerable assumptions. The estimated diffusivity is both spatially and seasonally dependent, and its midlatitude average is then tested against several scaling theories for the midlatitude eddy diffusivity. The result supports the diffusivity theory of Held and Larichev (1996) modified for the moist atmosphere, affording a dynamics-based parameterization of MSE diffusivity. The implementation of the parameterization in an EBM leads to an interactive MSE diffusivity that accounts for the midlatitude eddy response to climate forcing perturbations. Under a uniform radiative forcing, the EBM with a diffusivity so parameterized produces a weakening of the midlatitude diffusivity and a modestly polar-amplified surface temperature response as an inevitable outcome under the dual constraints of the nonlinear Clausius-Clapeyron relation and the temperature gradient-dependent diffusivity, even in the absence of any poleward amplifying radiative feedbacks. As the consequence of more isothermal temperature and reduced diffusivity, the variance of the midlatitude surface temperature also decreases with warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Heat and Mass Transfer in the Drying of a Cylindrical Body in an Oscillating Magnetic Field

A problem on the heating of a cylindrical body of infinite length in an oscillating electromagnetic field in the process of its drying has been formulated and solved analytically with account of the intermittence of irradiation of the body defined by the Heaviside unit function, the exponential-law absorption of electromagnetic energy by it, and the convective heat and mass exchange between the surface of the body and the environment having constant parameters. The intensity of evaporation of moisture from the surface of the body was determined on the basis of analytical solution of the problem on the mass transfer (moisture diffusion) in it on the assumption that the phase transformations of the body proceed near its surface. Solutions of the problem on the heating of the cylindrical body have been obtained for the cases of nonuniform and uniform distributions of its local temperature, the temperature of the body averaged over its volume, and the temperature gradient near the surface of the body. The 'serviceability' of these solutions was verified on the basis of numerical simulation, with them, of the drying of a seed shaped as a cylinder under the action of an oscillating infrared radiation. As a result of the numerical simulation performed, a technological regime of drying of seeds at minimum and maximum temperatures of their heating by on oscillating infrared radiation for a definite period of time in a cycle, providing not only the drying of the seeds but also substantial improvement of their sowing properties (the sprouting energy and the germination power), has been found. It is shown that the oscillating infrared heating of seeds can be used for their drying in pseudofluidized and vibrofluidized beds.

42 ENGINEERING↗
DOE OSTI2016

Fourier Analysis of the Multilevel QD Method with {alpha}-Approximation For Time-Dependent Radiative Transfer Problems

Thermal radiation transfer (TRT) problems describe interaction of photon radiation with matter. They are defined by the time-dependent radiative transfer (RT) equation for the specific intensity I coupled with the energy balance (EB) equation. This class of problems is characterised by high dimensionality, multiple scales and strong nonlinearity. In this paper we analyze the multilevel quasi-diffusion (QD) method for solving TRT problems. This is a nonlinear method of moments with exact closures. The QD method enables one to reduce dimensionality of the original radiative transfer problem. It is formulated by a nonlinear system of equations consisting of (i) the high-order RT (HORT) equation for the intensity of photon radiation and (ii) low-order equations for the angular and energy moments of the intensity. The nonlinear closures are formulated by means of stable factors. The low-order problem brings the radiative transfer model to the level of multi-physics equations. The multilevel QD (MLQD) method possesses attractive features for efficient multi-physics coupling. To calculate the high-order RT solution we apply the {alpha}-approximation which assumes that the intensity changes exponentially in time over a time step. The {alpha}-approximation leads to the steady-state RT equation with a modified opacity and enables one to avoid storing the high-dimensional solution from the previous time step. The rate of change is evaluated by the solution of the time-dependent low-order QD (LOQD) equations for moments. We note that the HORT equation in the {alpha}-approximation contains an extra nonlinear term. It affects the iterative behaviour of the MLQD method. The obtained computational results indicated that the rate of convergence is slower compared to the rate when the time-dependent HORT is used to calculate the intensity. In this paper we perform an iterative stability analysis of the MLQD method in a discretized form and analyze convergence of outer (transport) iterations on a time step. We consider multigroup TRT problems in 1D slab geometry. The fully implicit scheme is used to discretize equations in time. The HORT equation is approximated with the method of step characteristics. A finite volume method is applied for spatial discretization of multigroup LOQD equations. The grey (one-group) LOQD equations are algebraically consistent with the multigroup LOQD equations. To perform Fourier analysis a model TRT problem in an infinite homogeneous medium is considered. The system of nonlinear equations of the MLQD method is linearized near an equilibrium solution at some given temperature. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1974

The design and performance of axially symmetrical contoured wall diffusers employing suction boundary layer control

This paper presents a procedure for the design and the performance prediction of axially symmetrical contoured wall diffusers employing suction boundary layer control. An inverse problem approach was used in the potential flow design of the diffuser wall contours. The experimentally observed flow characteristics and the stability of flows within the diffuser are also described. Guidelines for the design of low suction (less than 10 percent of the inlet flow) and thus high effectiveness contoured wall diffusers are also provided based on the results of the experimental program.

Nelson, C. D., Jr.↗
DOE OSTI2021

On a nonlocal Cahn–Hilliard model permitting sharp interfaces

A nonlocal Cahn–Hilliard model with a non-smooth potential of double-well obstacle type that promotes sharp interfaces in the solution is presented. To capture long-range interactions between particles, a nonlocal Ginzburg–Landau energy functional is defined which recovers the classical (local) model as the extent of nonlocal interactions vanish. In contrast to the local Cahn–Hilliard problem that always leads to diffuse interfaces, the proposed nonlocal model can lead to a strict separation into pure phases of the substance. In this work, the lack of smoothness of the potential is essential to guarantee the aforementioned sharp-interface property. Mathematically, this introduces additional inequality constraints that, in a weak formulation, lead to a coupled system of variational inequalities which at each time instance can be restated as a constrained optimization problem. We prove the well-posedness and regularity of the semi-discrete and continuous in time weak solutions, and derive the conditions under which pure phases are admitted. Moreover, we develop discretizations of the problem based on finite element methods and implicit–explicit time-stepping methods that can be realized efficiently. Finally, we illustrate our theoretical findings through several numerical experiments in one and two spatial dimensions that highlight the differences in features of local and nonlocal solutions and also the sharp interface properties of the nonlocal model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Learning and meta-learning of stochastic advection–diffusion–reaction systems from sparse measurements

Physics-informed neural networks (PINNs) were recently proposed in [18] as an alternative way to solve partial differential equations (PDEs). A neural network (NN) represents the solution, while a PDE-induced NN is coupled to the solution NN, and all differential operators are treated using automatic differentiation. Here, we first employ the standard PINN and a stochastic version, sPINN, to solve forward and inverse problems governed by a non-linear advection–diffusion–reaction (ADR) equation, assuming we have some sparse measurements of the concentration field at random or pre-selected locations. Subsequently, we attempt to optimise the hyper-parameters of sPINN by using the Bayesian optimisation method (meta-learning) and compare the results with the empirically selected hyper-parameters of sPINN. In particular, for the first part in solving the inverse deterministic ADR, we assume that we only have a few high-fidelity measurements, whereas the rest of the data is of lower fidelity. Hence, the PINN is trained using a composite multi-fidelity network, first introduced in [12], that learns the correlations between the multi-fidelity data and predicts the unknown values of diffusivity, transport velocity and two reaction constants as well as the concentration field. For the stochastic ADR, we employ a Karhunen–Loève (KL) expansion to represent the stochastic diffusivity, and arbitrary polynomial chaos (aPC) to represent the stochastic solution. Correspondingly, we design multiple NNs to represent the mean of the solution and learn each aPC mode separately, whereas we employ a separate NN to represent the mean of diffusivity and another NN to learn all modes of the KL expansion. For the inverse problem, in addition to stochastic diffusivity and concentration fields, we also aim to obtain the (unknown) deterministic values of transport velocity and reaction constants. The available data correspond to 7spatial points for the diffusivity and 20 space–time points for the solution, both sampled 2000 times. We obtain good accuracy for the deterministic parameters of the order of 1–2% and excellent accuracy for the mean and variance of the stochastic fields, better than three digits of accuracy. In the second part, we consider the previous stochastic inverse problem, and we use Bayesian optimisation to find five hyper-parameters of sPINN, namely the width, depth and learning rate of two NNs for learning the modes. Here, we obtain much deeper and wider optimal NNs compared to the manual tuning, leading to even better accuracy, i.e., errors less than 1% for the deterministic values, and about an order of magnitude less for the stochastic fields.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Aqueous vs. nonaqueous Zn-ion batteries: consequences of the desolvation penalty at the interface

Zinc ion batteries using metallic zinc as the negative electrode have gained considerable interest for electrochemical energy storage, whose development is crucial for the adoption of renewable energy technologies, as zinc has a very high volumetric capacity (5845 mA h cm -3 ), is inexpensive and compatible with aqueous electrolytes. However, the divalent charge of zinc ions, which restricts the choice of host material due to hindered solid-state diffusion, can also pose a problem for interfacial charge transfer. We report our findings on reversible intercalation of up to two Zn 2+ ions in layered V 3 O 7 ·H 2 O. This material exhibits very high capacity and power (375 mA h g -1 at a 1C rate, and 275 mA h g -1 at an 8C rate) in an aqueous electrolyte compared to a very low capacity and slow rate capabilities in a nonaqueous medium. Operando XRD studies, together with impedance analysis, reveal solid solution behavior associated with Zn 2+ -ion diffusion within a water monolayer in the interlayer gap in both systems, but very sluggish interfacial charge transfer in the nonaqueous electrolyte. This points to desolvation at the interface as a major factor in dictating the kinetics. Temperature dependent impedance studies show high activation energies associated with the nonaqueous charge transfer process, identifying the origin of poor electrochemical performance.

25 ENERGY STORAGE↗
NASA NTRS1995

Effect of CF3H and CF3Br on laminar diffusion flames in normal and microgravity

Chemical inhibition of diffusion flames through addition of halogenated inhibitors is a problem of significant practical and scientific interest. Extensive studies on diffusion flames in microgravity have shown that these flames have significantly different characteristics than those under normal gravity. However, the mechanisms through which inhibitors reach the reaction zone to suppress combustion in diffusion flames and the effectiveness of these compounds under reduced gravity have yet to be investigated. This study reports preliminary results of investigations on the behavior of laminar jet diffusion flames upon the addition of bromotrifluoromethane (CF3Br) and trifluoromethane (CF3H) to the surroundings under normal and microgravity conditions. The results show that the flame structure in microgravity is significantly different from that under normal gravity conditions, and more importantly, that conditions for flame stability are less stringent under microgravity. Experiments show that flames that cannot be stabilized under normal gravity are quite stable under microgravity conditions. In addition, normal gravity experiments at reduced pressure (low buoyancy) did not reproduce the structure or stability limits of inhibited flames in microgravity.

Vanderwege, B. A.↗
DOE OSTI2015

Density-Aware Clustering Based on Aggregated Heat Kernel and Its Transformation

Current spectral clustering algorithms suffer from the sensitivity to existing noise, and parameter scaling, and may not be aware of different density distributions across clusters. If these problems are left untreated, the consequent clustering results cannot accurately represent true data patterns, in particular, for complex real world datasets with heterogeneous densities. This paper aims to solve these problems by proposing a diffusion-based Aggregated Heat Kernel (AHK) to improve the clustering stability, and a Local Density Affinity Transformation (LDAT) to correct the bias originating from different cluster densities. AHK statistically\ models the heat diffusion traces along the entire time scale, so it ensures robustness during clustering process, while LDAT probabilistically reveals local density of each instance and suppresses the local density bias in the affinity matrix. Our proposed framework integrates these two techniques systematically. As a result, not only does it provide an advanced noise-resisting and density-aware spectral mapping to the original dataset, but also demonstrates the stability during the processing of tuning the scaling parameter (which usually controls the range of neighborhood). Furthermore, our framework works well with the majority of similarity kernels, which ensures its applicability to many types of data and problem domains. The systematic experiments on different applications show that our proposed algorithms outperform state-of-the-art clustering algorithms for the data with heterogeneous density distributions, and achieve robust clustering performance with respect to tuning the scaling parameter and handling various levels and types of noise.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Negative magnetic eddy diffusivities from the test-field method and multiscale stability theory

The generation of a large-scale magnetic field in the kinematic regime in the absence of an α-effect is investigated by following two different approaches: the test-field method and the multiscale stability theory relying on the homogenization technique. Our computations of the magnetic eddy diffusivity tensor of the parity-invariant flow IV of G. O. Roberts and the modified Taylor–Green flow confirm the findings of previous studies and also explain some of their apparent contradictions. The two flows have large symmetry groups; this is used to considerably simplify the eddy diffusivity tensor. Finally, a new analytic result is presented: upon expressing the eddy diffusivity tensor in terms of solutions to auxiliary problems for the adjoint operator, we derive relations between the magnetic eddy diffusivity tensors that arise for mutually reverse small-scale flows v(x) and −v(x).

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2011

AGN Obscuration Through Dusty Infrared Dominated Flows: Radiation-Hydrodynamics Solution for the Wind - 1

We construct a radiation-hydrodynamics model for the obscuring toroidal structure in active galactic nuclei. In this model the obscuration is produced at parsec scale by a dense, dusty wind which is supported by infrared radiation pressure on dust grains. To find the distribution of radiation pressure, we numerically solve the 2D radiation transfer problem in a flux limited diffusion approximation. We iteratively couple the solution with calculations of stationary 1D models for the wind, and obtain the z-component of the velocity. Our results demonstrate that for AGN luminosities greater than 0.1 L(sub edd) external illumination can support a geometrically thick obscuration via outflows driven by infrared radiation pressure. The terminal velocity of marginally Compton-thin models (0.2 < tau(sub T) < 0.6), is comparable to or greater than the escape velocity. In Compton thick models the maximum value of the vertical component of the velocity is lower than the escape velocity, suggesting that a significant part of our torus is in the form of failed wind. The results demonstrate that obscuration via normal or failed infrared-driven winds is a viable option for the AGN torus problem and AGN unification models. Such winds can also provide an important channel for AGN feedback.

Dorodnitsyn, A.↗
DOE OSTI2016

Lagrangian Material Tracers (LMT) for Simulating Material Damage in ALEGRA

A method for providing non-diffuse transport of material quantities in arbitrary Lagrangian-Eulerian (ALE) dynamic solid mechanics computations is presented. ALE computations are highly desirable for simulating dynamic problems that incorporate multiple materials and large deformations. Despite the advantages of using ALE for such problems, the method is associated with diffusion of material quantities due to the advection transport step of the computational cycle. This drawback poses great difficulty for applications of material failure for which discrete features are important, but are smeared out as a result of the diffusive advection operation. The focus of this work is an ALE method that incorporates transport of variables on discrete, massless points that move with the velocity field, referred to as Lagrangian material tracers (LMT), and consequently prevents diffusion of certain material quantities of interest. A detailed description of the algorithm is provided along with discussion of its computational aspects. Simulation results include a simple proof of concept, verification using a manufactured solution, and fragmentation of a uniformly loaded thin ring that clearly demonstrates the improvement offered by the ALE LMT method.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Mathematical model of testing of pipeline integrity by thermal fields

Thermal fields testing at the ground surface above a pipeline are considered. One method to obtain and investigate an ideal thermal field in different environments is a direct numerical simulation of heat transfer processes taking into account the most important physical factors. In the paper a mathematical model of heat propagation from an underground source is described with accounting of physical factors such as filtration of water in soil and solar radiation. Thermal processes are considered in 3D origin where the heat source is a pipeline with constant temperature and non-uniform isolated shell (with 'damages'). This problem leads to solution of heat diffusivity equation with nonlinear boundary conditions. Approaches to analysis of thermal fields are considered to detect damages.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Perpendicular diffusion of energetic particles in collisionless plasmas

A fundamental problem in plasma and astrophysics is the interaction between energetic particles and magnetized plasmas. In the current paper, we focus on particle diffusion across the guide magnetic field. It is shown that the perpendicular diffusion coefficient depends only on the parallel diffusion coefficient and the Kubo number. Therefore, one can find four asymptotic limits depending on the values of these two parameters. These regimes are the quasilinear limit, the Kadomtsev and Pogutse limit, the scaling of Rechester and Rosenbluth, and the scaling found by Zybin and Istomin. In the current article, we focus on the Rechester and Rosenbluth scenario because this was not discovered before in the context of collisionless plasmas. Examples and applications are discussed as well. We show that an energy independent ratio of perpendicular and parallel diffusion coefficients can be found and that this ratio can be very small but also close to unity. This is exactly what one observes in the solar wind.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗