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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Graph convolutional networks applied to unstructured flow field data

Abstract Many scientific and engineering processes produce spatially unstructured data. However, most data-driven models require a feature matrix that enforces both a set number and order of features for each sample. They thus cannot be easily constructed for an unstructured dataset. Therefore, a graph based data-driven model to perform inference on fields defined on an unstructured mesh, using a graph convolutional neural network (GCNN) is presented. The ability of the method to predict global properties from spatially irregular measurements with high accuracy is demonstrated by predicting the drag force associated with laminar flow around airfoils from scattered velocity measurements. The network can infer from field samples at different resolutions, and is invariant to the order in which the measurements within each sample are presented. The GCNN method, using inductive convolutional layers and adaptive pooling, is able to predict this quantity with a validation R 2 above 0.98, and a Normalized Mean Squared Error below 0.01, without relying on spatial structure.

Ogoke, Francis (ORCID:0000000224327783)↗
DOE OSTI2025

Infrasonic directivity of monopole, dipole and bipole ground-surface reflected sources

Infrasound (acoustic waves below 20 Hz) can be used to detect, locate and quantify activity in the atmosphere such as volcanic eruptions and anthropogenic explosions. Attempts to quantify volcanic eruption parameters such as exit velocity, plume height and mass flow rate using infrasound data depend strongly on assumptions of the acoustic source type. Infrasonic sources may produce omnidirectional or directional wavefields, while propagation effects, such as interaction with topography, can induce further wavefield directivity that is measured by field instrumentation. Limited sampling of these wavefields can hinder our ability to infer the underlying source, and thus our understanding of the eruption characteristics. Equivalent sources are often used to represent acoustic source mechanisms and resultant wavefields. In this study, we review equivalent acoustic sources as they pertain to infrasonic scale and wavelengths commonly encountered in very local (⁠<5 km range) geophysical field deployments. We highlight the equivalent infrasonic bipole source that can be induced by ground-reflection of an elevated monopole; we are not aware of any prior infrasound studies that use the bipole source concept. We use analytical and numerical methods to explore source directivity of monopole, dipole and bipole ground-reflected sources at infrasonic frequencies as well as the additional directivity complications introduced by interactions with topography. We illustrate that for typical volcano-infrasound wavelengths, increasing height above the ground as well as increasing source frequency leads to increased wavefield directivity. Numerical modelling using a simple omnidirectional monopole source embedded in topography further illustrates that both horizontal and vertical infrasound directionality can be induced by topography at the distance scales appropriate for local volcano infrasound monitoring. Information summarized in this analytical and numerical exploration of infrasound directivity may be used to help guide future volcano-infrasound field deployments intended to estimate source parameters or quantify wavefield directivity. Analytic solutions for simple whole-space or half-space atmospheres provide useful formulations for planning or initially analysing geophysical field-scale experimental data; however, especially at very local distances from the source (⁠<5 km), 3-D simulations are necessary to account for complex topography commonly encountered in volcano-infrasound applications.

Infrasound↗
DOE OSTI2021

A multishock model for the density variance of anisotropic, highly magnetized, supersonic turbulence

ABSTRACT Shocks form the basis of our understanding for the density and velocity statistics of supersonic turbulent flows, such as those found in the cool interstellar medium (ISM). The variance of the density field, $\sigma ^2_{\rho /\rho _0}$, is of particular interest for molecular clouds (MCs), the birthplaces of stars in the Universe. The density variance may be used to infer underlying physical processes in an MC, and parametrizes the star formation (SF) rate of a cloud. However, models for $\sigma ^2_{\rho /\rho _0}$ all share a common feature – the variance is assumed to be isotropic. This assumption does not hold when a trans-/sub-Alfvénic mean magnetic field, ${B}_0$, is present in the cloud, which observations suggest is relevant for some MCs. We develop an anisotropic model for $\sigma _{\rho /\rho _0}^2$, using contributions from hydrodynamical and fast magnetosonic shocks that propagate orthogonal to each other. Our model predicts an upper bound for $\sigma _{\rho /\rho _0}^2$ in the high Mach number $(\mathcal {M})$ limit as small-scale density fluctuations become suppressed by the strong ${B}_0$. The model reduces to the isotropic $\sigma _{\rho /\rho _0}^2\!-\!\mathcal {M}$ relation in the hydrodynamical limit. To validate our model, we calculate $\sigma _{\rho /\rho _0}^2$ from 12 high-resolution, three-dimensional, supersonic, sub-Alfvénic magnetohydrodynamical (MHD) turbulence simulations and find good agreement with our theory. We discuss how the two MHD shocks may be the bimodally oriented overdensities observed in some MCs and the implications for SF theory in the presence of a sub-Alfvénic ${B}_0$. By creating an anisotropic, supersonic density fluctuation model, this study paves the way for SF theory in the highly anisotropic regime of interstellar turbulence.

Beattie, James R.↗
DOE OSTI2024

Numerical study on aerosol sampling in a nuclear facility duct with a 90-degree elbow

Due to the challenging design requirements, elbows are often unavoidable in duct configuration, and these 90-degree bends introduce swirl, velocity variations, recirculation, and secondary flow. These disturbances make it difficult for nuclear facilities to meet particle sampling standards. A series of numerical analyses are conducted to track aerosols in a nuclear facility duct having a 90-degree elbow with the assistance of computational fluid dynamics (CFD). A turbulence model, a continuity, and a momentum, a discrete phase model, and species transport equations are solved simultaneously to track aerosols in the duct. The effect of turbulence models, turbulent dispersion models, droplet drag model, aerosol amount, aerosol spray configuration, guide vanes, and mixers are investigated. Simulation results are analyzed per relevant testing codes such as DOE-HDBK-1169, ASME AG1, ISO 14644-3, ACGIH, and ANSI/HPS N13.1.

Han, Kai [Savannah River Nuclear Solutions (SRNS),↗
DOE OSTI2021

Synthetic Absorption Lines from Simulations of Multiphase Gas in Galactic Winds

Supernova-driven galactic winds are multiphase streams of gas that are often observed flowing at a range of velocities out of star-forming regions in galaxies. In this study, we use high-resolution 3D simulations of multiphase galactic winds modeled with the hydrodynamics code Cholla to investigate the connection between numerical studies and observations. Using a simulated interaction between a hot $T$ ~ 10 4 K supernova-driven wind and a cool $T$ ~ 10 7 K cloud of interstellar material, we create mock observables, including the optical depth ($\tau$) and covering fraction ($C$ $f$ ) of six commonly observed ions (Si II , C II , Si IV , C IV , N V , and O VI ) as a function of gas velocity. We compare our mock observables to surveys of galactic winds in the literature, finding good agreement with velocities and profiles of the low ions. We then compute "empirical" values for the optical depth and covering fraction following observational techniques and compare them to the values calculated directly from the simulation data. We find that the empirically computed values tend to underestimate the "true" value of $\tau$ for ions with high optical depth and overestimate the "true" value of $\tau$ for ions with low optical depth relative to the simulated data. In conclusion, the empirically estimated covering fractions match our direct calculations very well for the low-ionization ions; for the high-ionization ions, the empirical covering fractions underestimate the directly computed values by up to ~40%.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Adaptive Mesh Refinement Large Eddy Simulation of the Supercritical Carbon Dioxide Round Turbulent Jet

Supercritical carbon dioxide (sCO2) is of interest to a range of engineering problems, including carbon capture, utilization, and storage (CCUS) as well as advanced cycles for power generation. Non-ideal variations in physical properties of sCO2 impact the physics of these systems. In this study, we simulate turbulent sCO2 jets to gain a better understanding of these physics.We use a second order finite volume method with adaptive mesh refinement as implemented in the first-principles simulation code PeleC to perform a Large Eddy Simulation (LES) of three turbulent jets of sCO2. Additionally, we use the Soave-Redlich-Kwong equation of state to close the system and examine the impact of a cubic equation of state on the turbulent flow physics. We look at velocity and Reynolds stress profiles at different downstream locations for three cases in which the temperature of the jet andthat of the ambient fluid differ in order to capture the effects of widely varying thermal properties in the pseudocritical region. These results are then contrasted with established theory for ideal gas jets.

adaptive mesh refinement↗
DOE OSTI2023

Deep learning closure models for large-eddy simulation of flows around bluff bodies

Near-wall flow simulation remains a central challenge in aerodynamics modelling: Reynolds-averaged Navier–Stokes predictions of separated flows are often inaccurate, and large-eddy simulation (LES) can require prohibitively small near-wall mesh sizes. A deep learning (DL) closure model for LES is developed by introducing untrained neural networks into the governing equations and training in situ for incompressible flows around rectangular prisms at moderate Reynolds numbers. The DL-LES models are trained using adjoint partial differential equation (PDE) optimization methods to match, as closely as possible, direct numerical simulation (DNS) data. They are then evaluated out-of-sample – for aspect ratios, Reynolds numbers and bluff-body geometries not included in the training data – and compared with standard LES models. The DL-LES models outperform these models and are able to achieve accurate LES predictions on a relatively coarse mesh (downsampled from the DNS mesh by factors of four or eight in each Cartesian direction). We study the accuracy of the DL-LES model for predicting the drag coefficient, near-wall and far-field mean flow, and resolved Reynolds stress. A crucial challenge is that the LES quantities of interest are the steady-state flow statistics; for example, a time-averaged velocity component $\langle {u}_i\rangle (x) = \lim _{t \rightarrow \infty } ({1}/{t}) \int _0^t u_i(s,x)\, {\rm d}s$ . Calculating the steady-state flow statistics therefore requires simulating the DL-LES equations over a large number of flow times through the domain. It is a non-trivial question whether an unsteady PDE model with a functional form defined by a deep neural network can remain stable and accurate on $t \in [0, \infty )$ , especially when trained over comparatively short time intervals. Our results demonstrate that the DL-LES models are accurate and stable over long time horizons, which enables the estimation of the steady-state mean velocity, fluctuations and drag coefficient of turbulent flows around bluff bodies relevant to aerodynamics applications.

Mechanics↗
DOE OSTI2020

Dynamics of Subsiding Shells in Actively Growing Clouds with Vertical Updrafts

The dynamics of a subsiding shell at the edges of actively growing shallow cumulus clouds with updrafts is analyzed using direct numerical simulation. The actively growing clouds have a fixed in-cloud buoyancy and velocity. Turbulent mixing and evaporative cooling at the cloud edges generate a subsiding shell that grows with time. A self-similar regime is observed for first- and second-order moments when normalized with respective maximum values. Internal scales derived from integral properties of the flow problem are identified. A self-similarity analysis using these scales reveals that contrary to classical self-similar flows, the turbulent kinetic energy budget terms and velocity moments scale according to the buoyancy and not with the mean velocity. The shell thickness is observed to increase linearly with time. The buoyancy scale remains time invariant and is set by the initial cloud–environment thermodynamics. The shell accelerates ballistically with a magnitude set by the saturation value of the buoyancy of the cloud–environment mixture. In this regime, the shell is buoyancy driven and independent of the in-cloud velocity. Relations are obtained for predicting the shell thickness and minimum velocities by linking the internal scales with external flow parameters. The values thus calculated are consistent with the thickness and velocities observed in typical shallow cumulus clouds. The entrainment coefficient is a function of the initial state of the cloud and the environment, and is shown to be on the same order of magnitude as fractional entrainment rates calculated for large-scale models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Multi-line FLEET by imaging periodic masks

A simple linear configuration for multi-line FLEET velocimetry is used for the first time to image an overexpanded unsteady supersonic jet. The FLEET lines are spaced 0.5-1.0 mm apart and up to six lines can simultaneously be used to visualize the flowfield. These lines are created using periodic masks, despite the mask blocking 25 — 30% of the 10 mJ incident beam. Maps of mean single-component velocity in the direction along the principal flow axis, and turbulence intensity in that same direction, are created using multi-line FLEET, and computed velocities agree well with that obtained from single-line (traditional) FLEET. Compared to traditional FLEET, multi-line FLEET offers increased simultaneous spatial coverage and the ability to produce spatial correlations in the streamwise direction. This FLEET permutation is especially well-suited for short-duration test facilities

42 ENGINEERING↗
DOE OSTI2021

Resolving Anodic Current and Temperature Distributions in a Polymer Electrolyte Membrane Water Electrolysis Cell Using a Pseudo-Two-Phase Computational Fluid Dynamics Model

Expanding upon our prior experimental work, we constructed a three-dimensional model of a polymer electrolyte membrane water electrolyzer using computational fluid dynamics. We applied the assumption of pseudo-two-phase flow, the flow of two phases with equal velocity. Experimental data were used to obtain parameters and to determine the conditions under which this model was valid. Anodic distributions of current density, temperature, liquid saturation, and relative humidity were obtained at various flow rates. The overall current density and temperature difference from inlet to outlet at the anode agreed strongly with experimental measurements under most circumstances. This verification allowed us to further examine the apparent gas coverage calculated from experimental and model temperature data. Results suggested a low liquid saturation and low relative humidity at the anode due to the consumption of liquid water and water vapor. However, we questioned the accuracy of the pseudo-two-phase assumption at low water feed rates. We concluded that the model was applicable to systems with liquid water feed rates greater than 0.6 ml min -1 cm -2 . Therefore, it is a fair screening method that can advise which operating conditions lead to excessive temperatures or drying at the anode, thereby promoting the longevity of the membrane and catalyst.

25 ENERGY STORAGE↗
DOE OSTI2021

Machine Learning Analysis of Hydrologic Exchange Flows and Transit Time Distributions in a Large Regulated River

Hydrologic exchange between river channels and adjacent subsurface environments is a key process that influences water quality and ecosystem function in river corridors. High-resolution numerical models were often used to resolve the spatial and temporal variations of exchange flows, which are computationally expensive. In this study, we adopt Random Forest (RF) and Extreme Gradient Boosting (XGB) approaches for deriving reduced order models of hydrologic exchange flows and associated transit time distributions, with integrated field observations (e.g., bathymetry) and hydrodynamic simulation data (e.g., river velocity, depth). The setup allows an improved understanding of the influences of various physical, spatial, and temporal factors on the hydrologic exchange flows and transit times. The predictors also contain those derived using hybrid clustering, leveraging our previous work on river corridor system hydromorphic classification. The machine learning-based predictive models are developed and validated along the Columbia River Corridor, and the results show that the top parameters are the thickness of the top geological formation layer, the flow regime, river velocity, and river depth; the RF and XGB models can achieve 70% to 80% accuracy and therefore are effective alternatives to the computational demanding numerical models of exchange flows and transit time distributions. Each machine learning model with its favorable configuration and setup have been evaluated. The transferability of the models to other river reaches and larger scales, which mostly depends on data availability, is also discussed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Understanding the relative importance of vertical and horizontal flow in ice-wedge polygons

Abstract. Ice-wedge polygons are common Arctic landforms. The future of these landforms in a warming climate depends on the bidirectional feedback between the rate of ice-wedge degradation and changes in hydrological characteristics. This work aims to better understand the relative roles of vertical and horizontal water fluxes in the subsurface of polygonal landscapes, providing new insights and data to test and calibrate hydrological models. Field-scale investigations were conducted at an intensively instrumented location on the Barrow Environmental Observatory (BEO) near Utqiaġvik, AK, USA. Using a conservative tracer, we examined controls of microtopography and the frost table on subsurface flow and transport within a low-centered and a high-centered polygon. Bromide tracer was applied at both polygons in July 2015 and transport was monitored through two thaw seasons. Sampler arrays placed in polygon centers, rims, and troughs were used to monitor tracer concentrations. In both polygons, the tracer first infiltrated vertically until encountering the frost table and was then transported horizontally. Horizontal flow occurred in more locations and at higher velocities in the low-centered polygon than in the high-centered polygon. Preferential flow, influenced by frost table topography, was significant between polygon centers and troughs. Estimates of horizontal hydraulic conductivity were within the range of previous estimates of vertical conductivity, highlighting the importance of horizontal flow in these systems. This work forms a basis for understanding complexity of flow in polygonal landscapes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Flow pattern and void fraction characterization in nitrogen/water flows through a diamond-type triply periodic minimal surface lattice

Here, this study presents, to the authors knowledge, the first experimental investigation on the void fraction and flow patterns in two-phase flows through a diamond-type Triply Periodic Minimal Surface (TPMS) lattice. An additively manufactured TPMS structure was tested under upward co-current flow of a water/nitrogen mixture. Superficial velocities varied for a total of 42 test conditions (gas: 0.01–2.4 m/s; liquid: 0.01–2.4 m/s; mass flux: 20–2370 kg/m 2 ·s). High-speed video and X-ray imaging enabled time-averaged void fraction measurements and identified six distinct flow regimes which were used to develop a flow pattern map. Comparison of the void fraction data with correlations from literature demonstrated the Rouhani and Axelsson (1970) [49] correlation modified by Steiner (1993) [52] provided the best agreement, which was improved with empirically fit coefficients. This approach predicted the void fraction with errors < ±20% for 64% of the data, with a mean absolute percent deviation (MAPD) of 23%. The measured frictional pressure drop was compared to correlations from literature which captured the observed trends but did not provide good accuracy. The best agreement was found after optimizing the empirical coefficients of the Muller-Steinhagen & Heck (1986) [56] correlation; this approach captured 33% of the data within ±20% with a MAPD of 46% over the full range and captured 71% of the data within ±20% a MAPD of 13.3% at mass fluxes >1100 kg/m 2 -s. These results provide foundational insight into TPMS two-phase flow behavior and inform modeling and design of advanced heat exchange components incorporating TPMS geometries.

42 - ENGINEERING↗
DOE OSTI2025

Unsteady Land-Sea Breeze Circulations in the Presence of a Synoptic Pressure Forcing

Unsteady land-sea breezes (LSBs) that result from time-varying surface temperature contrasts Δθ(t) are explored in the presence of a constant synoptic pressure forcing, M g , oriented from sea to land (α = 0°) or land to sea (α = 180°). Large eddy simulations reveal the development of four distinctive regimes, depending on the joint interaction between M g , α, and Δθ(t) in modulating the fine-scale dynamics. Time lags, computed as the shifts that maximize correlation coefficients of the velocity between the unsteady and the corresponding steady scenarios at Δθ = Δθ max , are found to be significant and to extend 2 hr longer for α = 0° compared to α = 180°. These diurnal dynamics result in nonequilibrium conditions that are significantly affected by the flow history, and that behave differently over the two patches for the different α’s. Turbulence is found to be out of equilibrium with the mean flow, and the mean itself is found to be out of equilibrium with the thermal forcing. The sea surface heat flux is consistently more sensitive than its land counterpart to the time-varying external forcing Δθ(t), and more so for synoptic forcing from land to sea (α = 180°). Hence, although the land reaches equilibrium faster, the sea patch is found to exert a stronger control on the turbulence-mean flow equilibrium response. Finally, the vertical velocity profile at the shore and shore-normal velocity transects at the first grid level are shown to encode the multiscale regimes of the LSBs evolution and can thus be used to identify these regimes using k-means clustering.

58 GEOSCIENCES↗
DOE OSTI2021

Physics-informed neural networks for solving forward and inverse flow problems via the Boltzmann-BGK formulation

We report the Boltzmann equation with the Bhatnagar-Gross-Krook collision model (Boltzmann-BGK equation) has been employed to describe multiscale flows, i.e., from the hydrodynamic limit to free molecular flow. In this study we employ physics-informed neural networks (PINNs) to solve forward and inverse problems via the Boltzmann-BGK formulation (PINN-BGK), enabling PINNs to model flows in both the continuum and rarefied regimes. In particular, the PINN-BGK is composed of three sub-networks, i.e., the first for approximating the equilibrium distribution function, the second for approximating the non-equilibrium distribution function, and the third one for encoding the Boltzmann-BGK equation as well as the corresponding boundary/initial conditions. By minimizing the residuals of the governing equations and the mismatch between the predicted and provided boundary/initial conditions, we can approximate the Boltzmann-BGK equation for both continuous and rarefied flows. For forward problems, the PINN-BGK is utilized to solve various benchmark flows given boundary/initial conditions, e.g. Kovasznay flow, Taylor-Green flow, cavity flow, and micro Couette flow for Knudsen number up to 5. For inverse problems, we focus on rarefied flows in which accurate boundary conditions are difficult to obtain. We employ the PINN-BGK to infer the flow field in the entire computational domain given a limited number of interior scattered measurements on the velocity without using the (unknown) boundary conditions. Results for the two-dimensional micro Couette and micro cavity flows with Knudsen numbers ranging from 0.1 to 10 indicate that the PINN-BGK can infer the velocity field in the entire domain with good accuracy. Finally, we also present some results on using transfer learning to accelerate the training process. Specifically, we can obtain a three-fold speedup comparted to the standard training process (e.g., Adam plus L-BFG-B) for the two-dimensional flow problems considered in our work.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Birefringence tomography for axion cloud

An axion cloud surrounding a supermassive black hole can be naturally produced through the superradiance process. Its existence can be examined by the axion induced birefringence effect. It predicts an oscillation of the electric vector position angle of linearly polarized radiations. Stringent constraints of the existence of the axion in a particular mass window has been obtained based on the recent Event Horizon Telescope measurement on M87$^\star$. The future Very-Long-Baseline Interferometry (VLBI) observations will be able to measure the vicinity of many supermassive black holes, thus it opens the possibility to search for the existence of axions in a wide mass regime. In this paper, we study how different black hole properties and accretion flows influence the signatures of the axion induced birefringence. We include the impacts of black hole inclination angles, spins, magnetic fields, plasma velocity distributions, the thickness of the accretion flows. We pay special attention to characterize the washout effects induced by the finite thickness of the accretion flows and the lensed photons. Finally, based on this study, we give prospects on how to optimize the axion search using future VLBI observations, such as the next-generation Event Horizon Telescope, to further increase the sensitivity.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Particle Vertical Mixing and Horizontal Conveyance Within an Ambient Temperature Fluidized Bed

Previous studies have shown the advantages of particle-to-sCO2 fluidized bed (FB) heat exchangers, which include high heat transfer coefficients, low material cost, and the ability to horizontally convey solid particles. This paper outlines the design and testing of a compact cold flow FB test apparatus to characterize horizontal conveyance through convolutions within a 100 kWth FB heat exchanger design. Horizontal conveyance is an advantage in FBs because it enables more compact designs for heat exchangers. Two mass flow rates, 0.5 & 1 kg/s, at the inlet & outlet of the FB. To determine consistency of the flow rates, Student’s t-tests were used to assess whether the inlet & outlet values were statistically similar. The mass flow rate exiting the bed was statistically similar to the flow rate entering the bed for both cases, but each case featured a wider range and standard deviation. The range and standard deviation of the 1 kg/s flow rate was 0.69-1.23 kg/s and 0.12 kg/s respectively, and the 0.5 kg/s test featured a range and standard deviation of 0.37-0.73 kg/s and 0.09 kg/s, respectively. These measurements provide confidence that large-scale designs can successfully horizontally convey particles at ````~1.5x minimum fluidization velocity (U­mf) without significant variation in flow rate. A method to characterize the degree of particle vertical mixing and bubble frequency within the FB is also introduced. By using a high-resolution camera together with particle velocimetry, particle motion in the X and Y directions can be estimated to assess bed mixing and bubble frequency.

Khalaf, Jawad↗