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Numerical simulation of turbulent flows is discussed. Computational requirements for the direct simulaton of turbulence, simulation of arbitrary homogeneous flows, an expansion technique for wall bounded flows with application to pipe flow, and possibilities of flow representations or modeling techniques that allow the simulation of high Reynolds number flows with a relatively small number of dependent variables are included.
Examples of convection in rotating layers are presented to illustrate how convection can drive global circulations on the Jovian planets. For rapid rotation the convective motions become largely two-dimensional and produce Reynold stresses which drive large scale flows. The initial tendency is to produce a prograde equatorial jet and a meridional circulation which is directed toward the poles in the surface layers. Fully nonlinear numerical simulations for the slowly rotating solar convection zone show that the meridional circulation does not reach the poles. Instead a multicellular meridional circulation is produced which has a downward flowing branch in the mid-latitudes. For more rapidly rotating objects such as Jupiter and Saturn this meridional circulation may consist of a larger number of cells. Axisymmetric convective models then show that prograde jets form at the downflow latitudes. A nonlinear numerical simulation of convection in a prograde jet is presented to illustrate the interactions which occur between convection and these jets. Without rotation the convection removes energy and momentum from the jet. With rotation the convection feeds energy and momentum into the jet.
The current sheet created in the wake of an erupting filament during a two-ribbon flare is studied. A comparison with the geomagnetic tail shows that the physics of these systems is very similar, and therefore the existence of super Dreicer fields and the generation of netural beams traveling down the postflare loops with small pitch angles may be expected. The observational evidence for neutral beams in flares is reviewed and found to be generally supportive, while contracting the widely held hypothesis of electron beams. A dimensional analysis further demonstrates that the results for self-consistent numerical simulations of the current sheet in the geomagnetic tail can directly be scaled to the coronal current sheet, and the scaling parameters are derived.
Successful return of interstellar dust and cometary material by the Stardust Sample Return Capsule requires an accurate description of the Earth entry vehicle's aerodynamics. This description must span the hypersonic-rarefied, hypersonic-continuum, supersonic, transonic, and subsonic flow regimes. Data from numerous sources are compiled to accomplish this objective. These include Direct Simulation Monte Carlo analyses, thermochemical nonequilibrium computational fluid dynamics, transonic computational fluid dynamics, existing wind tunnel data, and new wind tunnel data. Four observations are highlighted: 1) a static instability is revealed in the free-molecular and early transitional-flow regime due to aft location of the vehicle s center-of-gravity, 2) the aerodynamics across the hypersonic regime are compared with the Newtonian flow approximation and a correlation between the accuracy of the Newtonian flow assumption and the sonic line position is noted, 3) the primary effect of shape change due to ablation is shown to be a reduction in drag, and 4) a subsonic dynamic instability is revealed which will necessitate either a change in the vehicle s center-of-gravity location or the use of a stabilizing drogue parachute.
Opposed Jet Burner tools have been used extensively by the authors to measure Flame Strength (FS) of laminar non-premixed H2 air and simple hydrocarbon (HC) air counterflow diffusion flames at 1-atm. FS represents a strain-induced extinction limit based on air jet velocity. This paper follows AIAA-2006-5223, and provides new HC air FSs for global testing of chemical kinetics, and for characterizing idealized flameholding potentials during early scramjet-like combustion. Previous FS data included six HCs, pure and N2-diluted; and three HC-diluted H2 fuels, where FS decayed very nonlinearly as HC was added to H2, due to H-atom scavenging. This study presents FSs on mixtures of (candidate surrogate) HCs, some with very high FS ethylene. Included are four binary gaseous systems at 300 K, and a hot ternary system at approx. 600 K. The binaries are methane + ethylene, ethane + ethylene, methane + ethane, and methane + propylene. The first three also form two ternary systems. The hot ternary includes both 10.8 and 21.3 mole % vaporized n-heptane and full ranges of methane + ethylene. Normalized FS data provide accurate means of (1) validating, globally, chemical kinetics for extinction of non-premixed flames, and (2) estimating (scaling by HC) the loss of incipient flameholding in scramjet combustors. The n-heptane is part of a proposed baseline simulant (10 mole % with 30% methane + 60% ethylene) that mimics the ignition of endothermically cracked JP-7 like kerosene fuel, as suggested by Colket and Spadaccini in 2001 in their shock tube Scramjet Fuels Autoignition Study. Presently, we use FS to gauge idealized flameholding, and define HC surrogates. First, FS was characterized for hot nheptane + methane + ethylene; then a hot 36 mole % methane + 64% ethylene surrogate was defined that mimics FS of the baseline simulant system. A similar hot ethane + ethylene surrogate can also be defined, but it has lower vapor pressure at 300 K, and thus exhibits reduced gaseous capacity. The new FS results refine our earlier idealized reactivity scale that shows wide ranging (50 x) diameter-normalized FSs for various HCs. These range from JP-10 and methane to H2 air, which produces an exceptionally strong flame that agrees within approx. 1% of recent 2-D numerically simulations. Finally, we continue advocating the FS approach as more direct and fundamental, for assessing idealized scramjet flameholding potentials, than measurements of unstrained laminar burning velocity or blowout in a Perfectly Stirred Reactor.
Empirical evidence from multiple sources show the Earth has been warming since the late 19th century. More recently, evidence for this warming trend is strongly supported by satellite data since the late 1970s from the cryosphere, atmosphere, oceans, and land that confirms increasing temperature trends and their consequences (e.g., reduced Arctic sea ice, rising sea level, ice sheet mass loss, etc.). At the same time, satellite observations of the Sun show remarkably stable solar cycles since the late 1970s, when direct observations of the Sun's total solar irradiance began. Numerical simulation models, driven in part by assimilated satellite data, suggest that future-warming trends will lead to not only a warmer planet, but also a wetter and drier climate depending upon location in a fashion consistent with large-scale atmospheric processes. Continued global warming poses new opportunities for the emergence and spread of fungal disease, as climate systems change at regional and global scales, and as animal and plant species move into new niches. Our contribution to this proceedings is organized thus: First, we review empirical evidence for a warming Earth. Second, we show the Sun is not responsible for the observed warming. Third, we review numerical simulation modeling results that project these trends into the future, describing the projected abiotic environment of our planet in the next 40 to 50 years. Fourth, we illustrate how Rift Valley fever outbreaks have been linked to climate, enabling a better understanding of the dynamics of these diseases, and how this has led to the development of an operational predictive outbreak model for this disease in Africa. Fifth, We project how this experience may be applicable to predicting outbreaks of fungal pathogens in a warming world. Lastly, we describe an example of changing species ranges due to climate change, resulting from recent warming in the Andes and associated glacier melt that has enabled amphibians to colonize higher elevation lakes, only to be followed shortly by the emergence of fungal disease in the new habitats.
Many geological materials, such as shale, mudstone, carbonate rock, limestone and rock salt are multi-porosity porous media in which pores of different scales may co-exist in the host matrix. When fractures propagate in these multi-porosity materials, these pores may enlarge and coalesce and therefore change the magnitude and the principal directions of the effective permeability tensors. The pore-fluid inside the cracks and the pores of host matrix may interact and exchange fluid mass, but the difference in hydraulic properties of these pores often means that a single homogenized effective permeability tensor field is insufficient to characterize the evolving hydraulic properties of these materials at smaller time scale. Furthermore, the complexity of the hydro-mechanical coupling process and the induced mechanical and hydraulic anisotropy originated from the micro-fracture and plasticity at grain scale also makes it difficult to propose, implement and validate separated macroscopic constitutive laws for numerical simulations. Here this article presents a hybrid data-driven method designed to capture the multiscale hydro-mechanical coupling effect of porous media with pores of various different sizes. At each scale, data-driven models generated from supervised machine learning are hybridized with classical constitutive laws in a directed graph that represents the numerical models. By using sub-scale simulations to generate database to train material models, an offline homogenization procedure is used to replace the up-scaling procedure to generate cohesive laws for localized physical discontinuities at both grain and specimen scales. Through a proper homogenization procedure that preserves spatial length scales, the proposed method enables field-scale simulations to gather insights from meso-scale and grain-scale micro-structural attributes. This method is proven to be much more computationally efficient than the classical DEM–FEM or FEM2 approach while at the same time more robust and flexible than the classical surrogate modeling approach. Due to the usage of bridging-scale technique, the proposed model may provide multiple opportunities to incorporate different types of simulations and experimental data across different length scales for machine learning. Numerical issues will also be discussed.
Atmospheric 3D winds in the horizontal and vertical directions are critical for improving short-range and long-range forecasting. Such advancement in forecasting directly applies to research in a number of areas including convective processes, wildfire plumes and tornado prediction. Atmospheric Motion Vectors (AMVs) provide a passively sensed approach to quantifying horizontal motion and cloud heights, which are typically sourced from geostationary sensors due to the availability of high frequency observations. Recent work has shown that estimating AMVs by tracking individual pixels with dense optical flow is a promising new direction. In this work, we use a state-of-the-art convolutional neural network for optical flow (FlowNetS) in a physics-guided deep learning framework for predicting AMVs in the horizontal direction. The approach is semi-supervised and uses physically informed wind vectors from high-resolution numerical simulations (DYAMOND) for supervised learning followed by fine-tuning though warping and reconstruction of full-disk geostationary images (GOES-16). In the vertical direction, we use labels from the CALIPSO low-earth orbit satellite to predict cloud height from 16-band geostationary images with a neural network. We present results for both tasks on held-out time periods and secondary datasets.
Very large eddy simulation (VLES) of the nonreacting turbulent flow in a single-element lean direct injection (LDI) combustor has been successfully performed via the approach known as the partially resolved numerical simulation (PRNS/VLES) using a nonlinear subscale model. The grid is the same as the one used in a previous RANS simulation, which was considered as too coarse for a traditional LES simulation. In this study, we first carry out a steady RANS simulation to provide the initial flow field for the subsequent PRNS/VLES simulation. We have also carried out an unsteady RANS (URANS) simulation for the purpose of comparing its results with that of the PRNS/VLES simulation. In addition, these calculated results are compared with the experimental data. The present effort has demonstrated that the PRNS/VLES approach, while using a RANS type of grid, is able to reveal the dynamically important, unsteady large-scale turbulent structures occurring in the flow field of a single-element LDI combustor. The interactions of these coherent structures play a critical role in the dispersion of the fuel, hence, the mixing between the fuel and the oxidizer in a combustor.
A crucial process in Galactic cosmic-ray (CR) transport is the spatial diffusion due to the interaction with the interstellar turbulent magnetic field. Usually, CR diffusion is assumed to be uniform and isotropic all across the Galaxy. However, this picture is clearly inaccurate: several data-driven and theoretical arguments, as well as dedicated numerical simulations, show that diffusion exhibits highly anisotropic properties with respect to the direction of a background (ordered) magnetic field (i.e., parallel or perpendicular to it). In this paper we focus on a recently discovered anomaly in the hadronic CR spectrum inferred by the Fermi-LAT gamma-ray data at different positions in the Galaxy, i.e. the progressive hardening of the proton slope at low Galactocentric radii. We propose the idea that this feature can be interpreted as a signature of anisotropic diffusion in the complex Galactic magnetic field: in particular, the harder slope in the inner Galaxy is due, in our scenario, to the parallel diffusive escape along the poloidal component of the large-scale, regular, magnetic field. We implement this idea in a numerical framework, based on the DRAGON code, and perform detailed numerical tests on the accuracy of our setup. We discuss how the effect proposed depends on the relevant free parameters involved. Based on low-energy extrapolation of the few focused numerical simulations aimed at determining the scalings of the anisotropic diffusion coefficients, we finally present a set of plausible models that reproduce the behavior of the CR proton slopes inferred by gamma-ray data.
Caprock leakage is of crucial concern for environmentally and economically sustainable development of carbon dioxide sequestration and utilization operations. One potential leakage pathway is through fractures or faults that penetrate the caprock. In this study, we investigate the permeability induced by fracturing initially intact Marcellus shale outcrop specimens at stressed conditions using a triaxial direct-shear method. Measurements of induced permeability, fracture geometry, displacement, and applied stresses were all obtained at stressed conditions to investigate the coupled processes of fracturing and fluid flow as may occur in the subsurface. Fracture geometry was directly observed at stressed conditions using X-ray radiography video. Numerical simulation was performed to evaluate the stress distribution developed in the experiments. Our experiments show that permeability induced by fracturing is strongly dependent on the stresses at which the fractures are created, the magnitude of shearing displacement, and the duration of flow. The strongest permeability contrast was observed when comparing specimens fractured at low stress to others fractured at higher stress. Measureable fracture permeability decreased by up to 7 orders of magnitude over a corresponding triaxial confining stress range of 3.5 MPa to 30 MPa. These results show that increasing stress, depth, and time are all significant permeability inhibitors that may limit potential leakage through fractured caprock.
The mechanical properties of Fused Filament Fabrication (FFF) parts are limited in the build direction, albeit advantages such as design flexibility and in-house customization. Here, in this paper, a novel z-pinning approach that enhances mechanical properties in the build direction by depositing material across multiple layers within the part was investigated through numerical simulations and validated experimentally. A finite element model for z-pinned composite structures was developed by assigning fiber-orientation dependent material properties obtained using a micromechanics approach to beads and pins. The bead-to-bead and pin-to-pin adhesions within the z-pinned structures were modeled using a cohesive traction separation law. The properties of cohesive elements for carbon fiber-reinforced polylactic acid (CF-PLA) z-pinned composites were calibrated using tensile experiments. The elastic modulus and tensile strength of CF-PLA z-pinned composites in the build direction were predicted with the developed numerical model. The numerical investigation on various geometrical parameters revealed that the largest pin volume increases the stiffness and tensile strength by 40% and thus, has the greatest influence on the mechanical properties of the z-pinned composites. The effect of z-pin geometrical parameters on the mechanical properties was summarized to aid in the design of z-pinned additively manufactured composite structures.
Second-year efforts within a three-year study to develop and extend finite element (FE) methodology to efficiently handle the transient/steady state response of rotor-bearing-stator structure associated with gas turbine engines are outlined. The two main areas aim at (1) implanting the squeeze film damper element into a general purpose FE code for testing and evaluation; and (2) determining the numerical characteristics of the FE-generated rotor-bearing-stator simulation scheme. The governing FE field equations are set out and the solution methodology is presented. The choice of ADINA as the general-purpose FE code is explained, and the numerical operational characteristics of the direct integration approach of FE-generated rotor-bearing-stator simulations is determined, including benchmarking, comparison of explicit vs. implicit methodologies of direct integration, and demonstration problems.
Neutrino quantum kinetics is a rapidly evolving field in computational astrophysics, with a primary focus on collective neutrino oscillations in core-collapse supernovae and postmerger phases of binary neutron star mergers. In recent years, there has been considerable debate concerning resolution dependence in numerical simulations. In this paper, we conduct a comprehensive resolution study in both angular- and spatial directions by using two independent schemes of quantum kinetic neutrino transport: finite volume and pseudospectral methods. We complement our discussion by linear stability analysis including inhomogeneous modes. Our result suggests that decreasing spatial resolutions underestimates the growth of flavor instability, and then leads to wrong asymptotic states of flavor conversions, which potentially has a critical impact on astrophysical consequences. We further delve into numerical results of low resolution simulations, that reveals the underlying mechanism responsible for numerical artifacts caused by insufficient resolutions. Finally, this study settles the debate on requirements of resolutions and serves as a guideline for numerical modeling of quantum kinetic neutrino transport.
Current commercial long-range guided wave inspection and monitoring technologies for pipes usually require establishment of certain specific acoustic modes for wave propagation and use a large number of sensors in a certain geometric arrangement (for example, uniformly-spaced arrays of sensors on a collar, placed around a pipe). This paper, in contrast, presents a long-range corrosion detection method in pipes based on multi-mode guided acoustic waves, generated and received using simple, single-element sensors. In this technique, available guided wave modes in any interrogated zone of the structure are automatically down-selected by the medium, and changes in energy distribution over the selected modes are analyzed through signal processing to monitor material loss or addition. Here, to investigate the feasibility of the proposed method, we have performed both experimental and numerical simulation studies on 50.8-mm (2-in)-diameter schedule-40 carbon steel pipes. In these studies, a linear chirp signal is injected in compression mode, perpendicular to the surface of the pipe, generating multi-mode, multi-directional guided waves that travel within the pipe wall. Corrosion effects in the pipes are simulated numerically and experimentally. To reduce errors in the measurement technique due to changes in the local or global temperature of the measured media, a universal temperature compensation algorithm is introduced. The experimental results show good agreement with simulation results, indicating that the proposed multi-mode wave generation and detection in a pipe could be used for long-range detection and monitoring of corrosion effects, such as pipe wall losses or solid material deposits.
Report discusses use of upwind-biased finite-difference numerical-integration scheme to simulate evolution of small disturbances and fully developed turbulence in three-dimensional flow of viscous, incompressible fluid in channel. Involves use of computational grid sufficiently fine to resolve motion of fluid at all relevant length scales.
This study evaluates some available schemes designed to solve the stochastic collection equation (SCE) for collision–coalescence of hydrometeors using a size-resolved (bin) microphysics approach and documents their numerical properties within the framework of a box model. Comparing three widely used SCE schemes, we find that all converge to almost identical solutions at sufficiently fine mass grids. However, one scheme converges far slower than the other two and shows pronounced numerical diffusion at the large-drop tail of the size distribution. One of the remaining two schemes is recommended on the basis that it is well converged on a relatively coarse mass grid, stable for large time steps, strictly mass conservative, and computationally efficient. To examine the effects of SCE scheme choice on simulating clouds and precipitation, two of the three schemes are compared in large-eddy simulations of a drizzling stratocumulus field. A forward simulator that produces Doppler spectra from the large-eddy simulation results is used to compare the model output directly with radar observations. The scheme with pronounced numerical diffusion predicts excessively large mean Doppler velocities and overly broad and negatively skewed spectra compared with observations, consistent with numerical diffusion demonstrated in the box model. Statistics obtained using the recommended scheme are closer to observations, but notable differences remain, indicating that factors other than SCE scheme accuracy are limiting simulation fidelity.
In additive manufacturing, modification of the viscosity of softened or molten metal plays a significant role in the development of mechanical properties distribution. Similar to soft polymers, molten or softened metal usually exhibits vastly different viscoelastic properties. During scratching tests, viscoelastic polymers undergo spatiotemporal stress development and relaxation, causing stress ripples to form on their surfaces. Here, it is observed that friction stir-based solid-state manufacturing can yield similar stress ripples on softened aluminum alloys due to the linear motion of the deposition tool. Softened aluminum alloys exhibit viscoelastic and viscoplastic responses similar to polymeric material during the solid-state deposition process. In the final product, residual stress ripples appear on the surface of the metal alloy due to periodic residual stress relaxation, leading to oscillatory behavior from the bulk mechanical properties of the material. The orientation of the in-built stress pattern formed in the bulk of the additively manufactured metal alloy underneath the visually evident onion ring-like surface pattern formation is diametrically in the opposite direction. The experimentally observed results are consistent with analytical calculation and numerical simulations in terms of behaviors.