Application of Lattice Boltzmann Method for Simulating Stably Stratified Flows past Cylinders

This research looks into the intriguing subject of ambient density-stratified flows, which have long captivated researchers due to their representation of real-world physical phenomena such as diapycnal mixing in oceans driven by environmental influences. The study specifically focuses on the flow past a cylindrical object within such stratified flows, which introduces complexities involving buoyancy and viscous effects. A major focus of this research is the examination of the lattice Boltzmann method as a novel approach to model stratified flows around circular cylinders by solving coupled Navier-Stokes and advection-diffusion equations. The study investigates the impact of stratification on wake characteristics and various flow parameters for a single cylinder at six Reynolds numbers ranging from 10 to 600 and Froude numbers from 2.19 to 7.51. Additionally, the investigation includes the case of two cylinders arranged in tandem at a Reynolds number of 100, with similar Froude numbers. This research demonstrates the suitability and robustness of the lattice Boltzmann method in modeling stratified flows past cylinders. The findings reveal that even moderate levels of stratification can significantly influence the wake pattern, potentially leading to changes in the flow regime. Moreover, the study demonstrates that the introduction of stratification is associated with a reduction in the drag coefficient and shedding frequency, leading to altered flow behaviors. Furthermore, in the case of flow past two cylinders, the presence of stratification increases the critical spacing between the cylinders

Development of lattice Boltzmann CO2 dissolution model

In this study, a novel lattice Boltzmann model (LBM) of CO2 dissolution at porous scale is proposed and developed to predict the CO2 dispersion and dissolution in geo-formations. The developed LBM dissolution model consists of an interfacial momentum interaction model, a mass transfer model and a convection (advection) model. Shen-Chen’s pseudopotential model using Equation of State (EOS) of real fluids is tested for momentum interaction model. It is found that a sharp interface can be maintained by optimizing the interaction strengths of two fluids with minimum numerical diffusion in the interfacial momentum interaction model. This makes it possible to model physical diffusion and interfacial tension individually. A new diffusion force, describing the particle diffusion driving by chemical potential at given solubility, is proposed for mass transfer model by applying the interparticle interaction pseudopotential concept. The dissolution is governed by coupling mechanism of diffusion and convection. The interface between the solute of CO2 and solvent water is monitored by the solubility, which changes and indicates the moving of interface as CO2 dissolving. The solution is considered as the mixture of dissolved CO2 and water. Instead of using an additional Lattice that is requested by the existed LBM, the further dispersion of dissolved solutes is attached to the Lattice of water, by which the cost of computing memory size and time is significantly reduced. The developed LBM dissolution model is calibrated by the data from Lab experiment of dissolution of CO2 droplet in water at a state of CO2 geological storage about 1000m depth. The calibration is made by comparison of simulation results with the data, in terms of the shrinking rate of CO2 droplet and the concentration distribution of dissolved CO2 in the solution layer. As the whole, the numerical predictions are well agreement with those of lab experiment. The developed model is then applied to investigate the mechanism of dispersion and dissolution of CO2 droplet in channels at pore scale, in terms of the effects of the Eo number, channel width and channel tilt angle. It is found under the state at 1000m depth that it is difficult for a dissolving CO2 droplet, unlike that of an immiscible droplet, to reach to a ’terminal velocity’. Because of the shrinking, dissolving CO2 droplets accelerate from a quiescent state to a maximum velocity and then decelerate in the channels. The ratio of droplet diameter (Do) to channel width (Lx), M=Do/Lx, and the inclination are the parameters that significantly affect the dynamics of dissolving CO2 droplets. The smaller the channel width or the tilt angle of the pores of the geoformation, the slower of stored CO2 can penetrate vertically and dissolve out. While, as the channel width increases to provide enough space, M<1, the shrinking rate is independent of the channel width and wobbling of droplets is observed at the region with the Re number of 300-600 and the Eo number of 20-43. The interactions of droplets in the channels (M=1 and M=0.3) are investigated by simulating of a pair of droplets dispersion and dissolution, with an initial distance of 4.5 times of droplet diameter. Comparison is made to that of single droplet in terms of the rising velocity and shrinking rate. It is found that the shrinking rate of the upper droplet is larger than that of the following droplet when the following droplet moves into the solution field of the upper droplet. The following droplet rises, when M=1 and M=0.3, faster than that of the upper droplet and also than that of the single droplet under the same conditions. The coalescence of two droplets is observed in the channel at M=0.3, which is due to the action of tail vortex of the upper droplet on the following droplet. The following droplet accelerates at a different wobbling frequency with that of the upper droplet. As the implication in model development, in term of numerical stability, the so called ’non-linear implicit trapezoidal lattice Boltzmann scheme’, proposed by Nourgaliev et al. [1], is re-examined in order to simulate the large density ratio of two-fluid flows. It is found from the re-derivation that the scheme is a linear scheme in nature. Therefore, the re-derived scheme is more efficient and the CPU time can be reduced. The test cases of the simulation of a steady state droplet using SC EOS show that re-derived scheme improves the numerical stability by reducing the spurious velocity about 21.7% and extending the density ratio 53.4% as relaxation time of the improved scheme is 0.25, in comparison to those from the traditional explicit scheme. Meanwhile, in the multicomponent simulation, with the same density distribution at steady state, the improved scheme reduces both the magnitude and spreading region of the spurious velocity. The spurious velocity of the improved method reduces approximate 4 times than that of the explicit scheme

Towards a solution of the closure problem for convective atmospheric boundary-layer turbulence

We consider the closure problem for turbulence in the dry convective atmospheric boundary layer (CBL). Transport in the CBL is carried by small scale eddies near the surface and large plumes in the well mixed middle part up to the inversion that separates the CBL from the stably stratified air above. An analytically tractable model based on a multivariate Delta-PDF approach is developed. It is an extension of the model of Gryanik and Hartmann [1] (GH02) that additionally includes a term for background turbulence. Thus an exact solution is derived and all higher order moments (HOMs) are explained by second order moments, correlation coefficients and the skewness. The solution provides a proof of the extended universality hypothesis of GH02 which is the refinement of the Millionshchikov hypothesis (quasi- normality of FOM). This refined hypothesis states that CBL turbulence can be considered as result of a linear interpolation between the Gaussian and the very skewed turbulence regimes. Although the extended universality hypothesis was confirmed by results of field measurements, LES and DNS simulations (see e.g. [2-4]), several questions remained unexplained. These are now answered by the new model including the reasons of the universality of the functional form of the HOMs, the significant scatter of the values of the coefficients and the source of the magic of the linear interpolation. Finally, the closures 61 predicted by the model are tested against measurements and LES data. Some of the other issues of CBL turbulence, e.g. familiar kurtosis-skewness relationships and relation of area coverage parameters of plumes (so called filling factors) with HOM will be discussed also

GPU parallelization of a hybrid pseudospectral geophysical turbulence framework using CUDA

An existing hybrid MPI-OpenMP scheme is augmented with a CUDA-based fine grain parallelization approach for multidimensional distributed Fourier transforms, in a well-characterized pseudospectral fluid turbulence code. Basics of the hybrid scheme are reviewed, and heuristics provided to show a potential benefit of the CUDA implementation. The method draws heavily on the CUDA runtime library to handle memory management and on the cuFFT library for computing local FFTs. The manner in which the interfaces to these libraries are constructed, and ISO bindings utilized to facilitate platform portability, are discussed. CUDA streams are implemented to overlap data transfer with cuFFT computation. Testing with a baseline solver demonstrated significant aggregate speed-up over the hybrid MPI-OpenMP solver by offloading to GPUs on an NVLink-based test system. While the batch streamed approach provided little benefit with NVLink, we saw a performance gain of 30% when tuned for the optimal number of streams on a PCIe-based system. It was found that strong GPU scaling is nearly ideal, in all cases. Profiling of the CUDA kernels shows that the transform computation achieves 15% of the attainable peak FlOp-rate based on a roofline model for the system. In addition to speed-up measurements for the fiducial solver, we also considered several other solvers with different numbers of transform operations and found that aggregate speed-ups are nearly constant for all solvers.Fil: Rosenberg, Duane. State University of Colorado - Fort Collins; Estados UnidosFil: Mininni, Pablo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Reddy, Raghu. Environmental Modeling Center; Estados UnidosFil: Pouquet, Annick. State University of Colorado at Boulder; Estados Unidos. National Center for Atmospheric Research; Estados Unido

Validierung eines Lattice Boltzmann Modells für Schneetransport und -ablagerung durch Wind

Risk management became an important issue for many disciplines such as finance, insurance industry or mechanical and civil engineering. In the general framework of risk management, risk analysis and hazard prediction are fundamental preliminary steps. This contribution addresses the prediction of snow-wind hazard resulting from coupled dynamics of snow transport and deposition by wind, which is the key to the prediction of snow load profiles on buildings. The target of this work is the development of a detailed Computational Fluid Dynamics (CFD) model and its validation by means of wind tunnel data available for representative model geometries. This approach for load analysis allows to investigate problems, which are not sufficiently standardized in terms of design codes. For this purpose, a two dimensional numerical large eddy simulation (LES) model for transient snow transport by wind is suggested. The model based on the lattice Boltzmann method (LBM) has been developed and validated. The lattice Boltzmann method presented utilizes the Multiple Relaxation Time (MRT) model and fluid/wall boundary conditions of second order accuracy. In the current approach, dry snow is modeled as a continuous component, which is being advected by the turbulent transient flow field. Snow deposition and erosion are controlled by imposing rules for the influence of wall shear stress and equilibrium approaches for the terminal velocity of snowflakes. The numerical method is compared to the experimental studies which have been carried out by L. Sanpaolesi et al, in the Jules Verne Climatic Wind Tunnel of Nantes, France. These validation studies will be presented including sensitivity studies for various model parameters. Finally, potential extensions and shortcomings of this approach are discussed.In Disziplinen wie beispielsweise dem Finanz- und Versicherungswesen, dem Maschinenbau oder dem Bauingenieurwesen spielt das Risikomanagement eine grosse Rolle. Im Gesamtkonzept des Risikomanagements sind die Risikoanalyse und die Prognose der Gefährdung fundamentale Ausgangsbausteine. Dieser Beitrag behandelt die Vorhersage der Schnee-Wind-Gefährdung resultierend aus gekoppelten dynamischen Prozessen von Schneetransport und -ablagerung zur Vorhersage von Schneelastprofilen auf Bauwerken. Ziel dieser Arbeit ist die Entwicklung eines CFD-Modells und dessen Validierung an Ergebnissen experimenteller Windtunnelversuche, die für repräsentative Modellgeometrien verfügbar sind. Dieses Analyseverfahren erlaubt außerdem die Untersuchung von Problemen, die in den Bemessungsnormen nicht ausreichend standardisiert sind. Zu diesem Zweck wird ein zweidimensionales numerisches Large-Eddy-Simulationsmodell (LES) für den transienten Schneetransport infolge Wind vorgeschlagen. Das Modell, das auf der Lattice-Boltzmann Methode basiert, nutzt das Multiple Relaxation Time (MRT) Modell und Fluid-Wand-Randbedingungen zweiter Ordnung Genauigkeit. Im vorliegenden Verfahren wird trockener Schnee als kontinuierliche Komponente modelliert, der von einem turbulenten transienten Strömungsfeld bewegt wird. Schneeablagerung und Erosion werden durch den Einfluss der Wandschubspannungen und Gleichgewichtsansätzen für die Schneefallgeschwindigkeit modelliert. Das numerische Modell wird mit experimentellen Studien verglichen, welche von L. Sanpaolesi im Jules Verne-Klima-Windtunnel von Nantes in Frankreich durchgeführt wurden. Diese Validierungsuntersuchungen sowie enthaltene Sensitivitätsstudien für verschiedene Modellparameter werden vorgestellt. Schließlich werden Möglichkeiten der Erweiterung dieses Verfahrens sowie Mängel diskutiert

Identifying Structure Transitions Using Machine Learning Methods

Methodologies from data science and machine learning, both new and old, provide an exciting opportunity to investigate physical systems using extremely expressive statistical modeling techniques. Physical transitions are of particular interest, as they are accompanied by pattern changes in the configurations of the systems. Detecting and characterizing pattern changes in data happens to be a particular strength of statistical modeling in data science, especially with the highly expressive and flexible neural network models that have become increasingly computationally accessible in recent years through performance improvements in both hardware and algorithmic implementations. Conceptually, the machine learning approach can be regarded as one that employing algorithms that eschew explicit instructions in favor of strategies based around pattern extraction and inference driven by statistical analysis and large complex data sets. This allows for the investigation of physical systems using only raw configurational information to make inferences instead of relying on physical information obtained from a priori knowledge of the system. This work focuses on the extraction of useful compressed representations of physical configurations from systems of interest to automate phase classification tasks in addition to the identification of critical points and crossover regions