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Modeling effective transport properties of 3D porous media, such as permeability, at multiple scales is challenging as a result of the combined complexity of the pore structures and fluid physics—in particular, confinement effects which vary across the nanoscale to the microscale. While numerical simulation is possible, the computational cost is prohibitive for realistic domains, which are large and complex. Although machine learning (ML) models have been proposed to circumvent simulation, none so far has simultaneously accounted for heterogeneous 3D structures, fluid confinement effects, and multiple simulation resolutions. By utilizing numerous computer science techniques to improve the scalability of training, we have for the first time developed a general flow model that accounts for the pore-structure and corresponding physical phenomena at scales from Angstrom to the micrometer. Using synthetic computational domains for training, our ML model exhibits strong performance ( R ^2 = 0.9) when tested on extremely diverse real domains at multiple scales.

Multiphase flow properties of fractures are important in engineering applications such as hydraulic fracturing, evaluating the sealing capacity of caprocks, and the productivity of hydrocarbon-bearing tight rocks. Due to the computational requirements of high fidelity simulations, investigations of flow and transport through fractures typically rely on simplified assumptions applied to large fracture networks. These simplifications ignore the effect of pore-scale capillary phenomena and 3D realistic fracture morphology (for instance, tortuosity, contact points, and crevasses) that lead to macro-scale effective transport properties. The effect of these properties can be studied through lattice Boltzmann simulations, but they require high performance computing clusters and are generally limited in their domain size. In this work, we develop a technique to represent 3D fracture geometries and fluid distributions in 2D without losing any information. Using this innovative approach, we present a specialized machine learning model which only requires a few simulations for training but still accurately predicts fluid flow through 3D fractures. We demonstrate our technique using simulations of a water filled fracture being displaced by supercritical CO 2 . By generating highly efficient simulations of micro-scale multiphase flow in fractures, we hope to investigate a wide range of fracture types and generalize our method to be incorporated into larger discrete fracture network simulations. [ABSTRACT FROM AUTHOR]

[Display omitted] • A microfluidic DSSC with a gapless configuration minimizes mass transport resistance. • Reducing series resistance in µDSSC increases efficiency near the theoretical limit. • μDSSC is less sensitive to light color temperature variations than Si cells. • The electrolyte flow does not decrease the efficiency of μDSSC. • The thermal efficiency of μDSSC is not limited by heat conduction within the cell. A dye-sensitized solar cell (DSSC) is a type of photoelectrochemical cell that converts sunlight directly into electricity using a photoanode with a dye-sensitized, nonporous semiconductor layer. This study investigates the impact of integrating microfluidic capabilities into DSSCs, resulting in a flow-cell configuration that introduces new electrical characteristics without compromising its performance. The primary goal of the work was to define and determine the values of heat, mass, and charge transport resistances, and to explore their relationships with the cell's current – voltage characteristics, temperature, light intensity, and spectra. We employed both experimental methods and computational fluid dynamics using the Lattice-Boltzmann solver to analyze the cell's dynamics. A novel multilayered microfluidic DSSC (µDSSC) was designed, featuring an innovative "gapless" configuration with a photoactive surface area exceeding 7 cm2, integrated directly with a microfluidic heat exchanger. This configuration allowed the µDSSC to achieve a power conversion efficiency (PCE) of at least 6 % under standard test conditions, with a fill factor reaching up to 68 %. By gradually covering the cell surface, the impact of series resistance (Rs) on PCE was minimized, enabling a maximum PCE of 19–22 %. A new integral definition of the fill factor (IFF) was proposed, which accurately describes the performance of cells constrained by ion mass transport resistance. For the gapless µDSSC, the IFF ranged from 58 % to 88 %. Additionally, we introduced a maximum cell efficiency (MCE) parameter to represent the cell's efficiency at the theoretical limit of Rs = 0, determined to be 20.7 % for the gapless µDSSC. This MCE value is specific to the cell and is independent of the illuminated surface area and incident light intensity. The thermal efficiency of µDSSC cells is generally limited by heat conduction through the multilayer structure, but at practical cell surface temperatures of 50–80 °C, this limitation is 3 to 6 times less significant than the limitation imposed by the maximum solar energy flux reaching the cell surface. The integration of microchannels into the cell led to a 58 % reduction in hydraulic resistance along the main flow direction. While electrolyte flow typically reduces efficiency in wide-gap DSSCs, the gapless configuration minimizes mass transport resistance, ensuring that fluid flow does not adversely affect the performance of gapless µDSSCs. [ABSTRACT FROM AUTHOR]

• Identified the contact angle on ZrO 2 using Molecular Dynamics for both main crystallographic planes at Boiling Water Reactor in-situ operating conditions. • Connected the nanoscale Molecular Dynamics simulations to mesoscale Lattice Boltzmann simulations through the contact angle. • Modelled the nucleation of bubbles on a ZrO 2 surface at Boiling Water Reactor in-situ operating conditions taking into account the micro-roughness. • Obtained a correlation between the roughness and the shape of the surface and the nucleation site density. The mechanism of bubble nucleation in boiling water at solid surface remains poorly understood. In this study, the water boiling and bubble nucleation density under nuclear reactor operation conditions were investigated by multiphase Lattice Boltzmann and Molecular Dynamics simulations. The developed multiscale model takes into account the surface energy of ZrO 2 cladding in different crystallographic planes obtained by molecular dynamics simulations and uses it to inform the corresponding contact angle of two-phase fluid in the thermal multiphase Lattice Boltzmann model. The model describes the bubble formation on a rough surface due to boiling and predicts the number of active nucleation sites on surfaces of different roughness. Further, the effect of the different contact angles on bubble dynamics while in close contact with the surface is investigated. The obtained results are in good agreement with experimental observations and provide functional relationships between interface properties (roughness, surface energy) and the nucleation site density, necessary for macroscopic simulations of the boiling phenomena. [ABSTRACT FROM AUTHOR]

MPLBM-UT is a specialized lattice-Boltzmann library that makes running single- and two-phase flow simulations in porous media accessible to everyone. We provide a suite of tools to pre-process computational domains for simulation, to set up custom boundary conditions, to run simulations, to post-process simulation outputs, and to visualize simulation results and data. All of these tools are easily accessible to users through the mplbm_utils Python package included in and automatically installed with MPLBM-UT. The high-performance, highly parallel library Palabos is used as the solver backend. MPLBM-UT is easily deployed in a variety of systems, from laptops to supercomputer clusters. MPLBM-UT also features multiple examples and benchmark templates that allow for fast prototyping of different porous media problems. We also provide an interface for reading in different file types and downloading domains from the Digital Rocks Portal to perform simulations.

Featured Application: A microfluidic solar cell with energy storage capability–the solar redox flow batteries (SRFB). The dye-sensitized solar cells microfluidically integrated with a redox flow battery (µDSSC-RFB) belong to a new emerging class of green energy sources with an inherent opportunity for energy storage. The successful engineering of microfluidically linked systems is, however, a challenging subject, as the hydrodynamics of electrolyte flow influences the electron and species transport in the system in several ways. In the article, we have analyzed the microflows hydrodynamics by means of the lattice-Boltzmann method, using the algebraic solution of the Navier-Stokes equation for a duct flow and experimentally by the micro particle image velocimetry method. Several prototypes of µDSSC were prepared and tested under different flow conditions. The efficiency of serpentine µDSSC raised from 2.8% for stationary conditions to 3.1% for electrolyte flow above 20 mL/h, while the fill factor increased about 13% and open-circuit voltage from an initial 0.715 V to 0.745 V. Although the hexagonal or circular configurations are the straightforward extensions of standard photo chambers of solar cells, those configurations are hydrodynamically less predictable and unfavorable due to large velocity gradients. The serpentine channel configuration with silver fingers would allow for the scaling of the µDSSC-RFB systems to the industrial scale without loss of performance. Furthermore, the deterioration of cell performance over time can be inhibited by the periodic sensitizer regeneration, which is the inherent advantage of µDSSC. [ABSTRACT FROM AUTHOR]

Direct numerical simulation and pore-network modeling are common approaches to study the physics of two-phase flow through natural rocks. For assessment of the long-term performance of geological sequestration of CO2, it is important to model the full drainage-imbibition cycle to provide an accurate estimate of the trapped CO2. While direct numerical simulation using pore geometry from micro-CT rock images accurately models two-phase flow physics, it is computationally prohibitive for large rock volumes. On the other hand, pore-network modeling on networks extracted from micro-CT rock images is computationally efficient but utilizes simplified physics in idealized geometric pore elements. This study uses the lattice-Boltzmann method for direct numerical simulation of CO2-brine flow in idealized pore elements to develop a new set of pore-level flow models for the pore-body filling and snap-off events in pore-network modeling of imbibition. Lattice-Boltzmann simulations are conducted on typical idealized pore-network configurations, and the interface evolution and local capillary pressure are evaluated to develop modified equations of local threshold capillary pressure of pore elements as a function of shape factor and other geometrical parameters. The modified equations are then incorporated into a quasi-static pore-network flow solver. The modified model is applied on extracted pore-network of sandstone samples, and saturation of residual trapped CO2 is computed for a drainage-imbibition cycle. The modified model yields different statistics of pore-level events compared with the original model; in particular, the occurrence of snap-off in pore-throats is reduced resulting in a more frontal displacement pattern along the main injection direction. Compared to the original model, the modified model is in closer agreement with the residual trapped CO2 obtained from core flow experiments and direct numerical simulation.

Multiphase flow properties of fractures are important in engineering applications such as hydraulic fracturing, evaluating the sealing capacity of caprocks, and the productivity of hydrocarbon-bearing tight rocks. Due to the computational requirements of high fidelity simulations, investigations of flow and transport through fractures typically rely on simplified assumptions applied to large fracture networks. These simplifications ignore the effect of pore-scale capillary phenomena and 3D realistic fracture morphology (for instance, tortuosity, contact points, and crevasses) that lead to macro-scale effective transport properties. The effect of these properties can be studied through lattice Boltzmann simulations, but they require high performance computing clusters and are generally limited in their domain size. In this work, we develop a technique to represent 3D fracture geometries and fluid distributions in 2D without losing any information. Using this innovative approach, we present a specialized machine learning model which only requires a few simulations for training but still accurately predicts fluid flow through 3D fractures. We demonstrate our technique using simulations of a water filled fracture being displaced by supercritical CO2. By generating highly efficient simulations of micro-scale multiphase flow in fractures, we hope to investigate a wide range of fracture types and generalize our method to be incorporated into larger discrete fracture network simulations.

Lattice Boltzmann simulations have been carried out in order to study the flow of blood in normal and constricted blood channels using Newtonian and non-Newtonian rheological models. Instead of using parameters from previous works as is usually done, we propose a new optimization methodology that provides in a consistent manner the complete set of parameters for the studied models, namely Newtonian, Carreau-Yassuda and Kuang-Luo. The optimization was performed simultaneously using experimental data from several sources. Physical observables such as velocity profiles, shear rate profiles and pressure fields were evaluated. For the normal channel case, it was found that the Newtonian model predicts both the highest velocity and shear rates profiles followed by the Carreau-Yassuda and the Kuang-Luo models. For a constricted channel, important differences were found in the velocity profiles among the studied models. First, the Newtonian model was observed to predict the velocity profile maximum at different channel width positions compared to the non-Newtonian ones. Second, the obtained recirculation region was found to be longer for the Newtonian models. Finally, concerning the constriction shape, the global velocity was found to be lower for a rectangular geometry than for a semi-circular one.

We introduce a structured approach to the construction of linear BGK-type collision operators ensuring that the resulting Lattice-Boltzmann methods are stable with respect to a weighted L 2 -norm. The results hold for particular boundary conditions including periodic, bounce-back, and bounce-back with flipping of sign boundary conditions. This construction uses the equivalent moment-space definition of BGK-type collision operators and the notion of stability structures as guiding principle for the choice of the equilibrium moments for those moments influencing the error term only but not the order of consistency. The presented structured approach is then applied to the 3D isothermal linearized Euler equations with non-vanishing background velocity. Finally, convergence results in the strong discrete L ∞ -norm highlight the suitability of the structured approach introduced in this manuscript. [ABSTRACT FROM AUTHOR]

We present an auto-tuning approach to optimize application performance on emerging multicore architectures. The methodology extends the idea of search-based performance optimizations, popular in linear algebra and FFT libraries, to application-specific computational kernels. Our work applies this strategy to a lattice Boltzmann application (LBMHD) that historically has made poor use of scalar microprocessors due to its complex data structures and memory access patterns. We explore one of the broadest sets of multicore architectures in the HPC literature, including the Intel Xeon E5345 (Clovertown), AMD Opteron 2214 (Santa Rosa), AMD Opteron 2356 (Barcelona), Sun T5140 T2+ (Victoria Falls), as well as a QS20 IBM Cell Blade. Rather than hand-tuning LBMHD for each system, we develop a code generator that allows us to identify a highly optimized version for each platform, while amortizing the human programming effort. Results show that our auto-tuned LBMHD application achieves up to a 15x improvement compared with the original code at a given concurrency. Additionally, we present detailed analysis of each optimization, which reveal surprising hardware bottlenecks and software challenges for future multicore systems and applications.

The goal of this paper is to investigate the effects of flow confinement on the noise generated by a small unmanned aerial system rotor measured and simulated in a partially closed test room. More specifically, the influence of the flow recirculation in the test room and the consequent blade turbulence interaction on both the tonal unsteady loading noise and the broadband laminar separation noise components are scrutinized. The study also aims at improving our prediction capabilities of drone rotor noise, and deepening our fundamental knowledge of rotor aeroacoustics in transitional boundary layer regimes. Numerical simulations are conducted by means of a scale-resolving wall-modelled lattice Boltzmann solver to calculate the unsteady flow and the noise generated by the same reference configuration used in our previous works, which consists in a rotor operated at a chord-based Reynolds number of about 70000 at 75% of the tip radius, both in hover and axial flow conditions. Results for a rotor in pristine flow conditions are compared to results obtained by simulating the rotor in a confined environment that reproduces the A-Tunnel test chamber of Delft University of Technology. On one hand, our study reveals that previously observed discrepancies between measured and predicted noise spectra in hover conditions are not due to the influence of the flow confinement on the laminar separation mechanisms, as hypothesized in our previous study, rather to a lack of numerical resolution. On the other hand, the new results reveal that, in hover conditions, the dominant effect of the flow recirculation is to increase the unsteady loading tonal noise components, whereas, in axial flow conditions, no significant effect due to the test environment is observed. Some of our conclusive observations are supported by results obtained using a source identification technique herein presented for the first time. [ABSTRACT FROM AUTHOR]

Lattice Boltzmann simulations have been carried out in order to study the flow of blood in normal and constricted blood channels using Newtonian and non-Newtonian rheological models. Instead of using parameters from previous works as is usually done, we propose a new optimization methodology that provides in a consistent manner the complete set of parameters for the studied models, namely Newtonian, Carreau- Yassuda and Kuang-Luo. The optimization was performed simultaneously using experimental data from several sources. Physical observables such as velocity profiles, shear rate profiles and pressure fields were evaluated. For the normal channel case, it was found that the Newtonian model predicts both the highest velocity and shear rates profiles followed by the Carreau-Yassuda and the Kuang-Luo models. For a constricted channel, important differences were found in the velocity profiles among the studied models. First, the Newtonian model was observed to predict the velocity profile maximum at different channel width positions compared to the non- Newtonian ones. Second, the obtained recirculation region was found to be longer for the Newtonian models. Finally, concerning the constriction shape, the global velocity was found to be lower for a rectangular geometry than for a semi-circular one. [ABSTRACT FROM AUTHOR]

We present a validation study comparing results from a patient-specific lattice-Boltzmann simulation to transcranial Doppler (TCD) velocity measurements in four different planes of the middle cerebral artery (MCA). As part of the study, we compared simulations using a Newtonian and a Carreau-Yasuda rheology model. We also investigated the viability of using downscaled velocities to reduce the required resolution. Simulations with unscaled velocities predict the maximum flow velocity with an error of less than 9%, independent of the rheology model chosen. The accuracy of the simulation predictions worsens considerably when simulations are run at reduced velocity, as is for example the case when inflow velocities from healthy individuals are used on a vascular model of a stroke patient. Our results demonstrate the importance of using directly measured and patient-specific inflow velocities when simulating blood flow in MCAs. We conclude that localized TCD measurements together with predictive simulations can be used to obtain flow estimates with high fidelity over a larger region, and reduce the need for more invasive flow measurement procedures.

We present a validation study comparing results from a patient-specific lattice-Boltzmann simulation to transcranial Doppler (TCD) velocity measurements in four different planes of the middle cerebral artery (MCA). As part of the study, we compared simulations using a Newtonian and a Carreau-Yasuda rheology model. We also investigated the viability of using downscaled velocities to reduce the required resolution. Simulations with unscaled velocities predict the maximum flow velocity with an error of less than 9%, independent of the rheology model chosen. The accuracy of the simulation predictions worsens considerably when simulations are run at reduced velocity, as is for example the case when inflow velocities from healthy individuals are used on a vascular model of a stroke patient. Our results demonstrate the importance of using directly measured and patient-specific inflow velocities when simulating blood flow in MCAs. We conclude that localized TCD measurements together with predictive simulations can be used to obtain flow estimates with high fidelity over a larger region, and reduce the need for more invasive flow measurement procedures. [ABSTRACT FROM AUTHOR]

The MPI intercommunication framework was used for coupling of two lattice-Boltzmann solvers with suspended particles, which model advection and diffusion respectively of these particles in a carrier fluid. Simulation domain was divided into two parts, one with advection and diffusion, and the other with diffusion only (no macroscopic flow). Particles were exchanged between these domains at their common boundary by a direct process to process communication. By analysing weak and strong scaling, it was shown that the linear scaling characteristics of the lattice-Boltzmann solvers were not compromised by their coupling. [ABSTRACT FROM AUTHOR]

A large number of currently available Computational Fluid Dynamics numerical models of Polymer Electrolyte Membrane Fuel Cells (PEMFC) are based on the assumption that porous structures are mainly considered as thin and homogenous layers, hence the mass transport equations in structures such as Gas Diffusion Layers (GDL) are usually modelled according to the Darcy assumptions. Application of homogenous models implies that the effects of porous structures are taken into consideration via the effective transport properties of porosity, tortuosity, permeability (or flow resistance), diffusivity, electric and thermal conductivity. Therefore, reliable values of those effective properties of GDL play a significant role for PEMFC modelling when employing Computational Fluid Dynamics, since these parameters are required as input values for performing the numerical calculations. The objective of the current study is to calculate the effective transport properties of GDL, namely gas permeability, diffusivity and thermal conductivity, as a function of liquid water saturation by using the Lattice-Boltzmann approach. The study proposes a method of uniform water impregnation of the GDL based on the “Fine-Mist” assumption by taking into account the surface tension of water droplets and the actual shape of GDL pores. [ABSTRACT FROM AUTHOR]

This study investigated heat transfer characteristics of natural convective flow in the packed bed geometry experimentally and numerically. The natural convection experiments for self-heating condition were performed using the copper sulfate electroplating system based on the analogy between heat and mass transfers. Also, the same conditions were simulated with Lattice-Boltzmann Method (LBM) and the results were compared. The spheres diameters were d = 4, 6 and 10 mm and the corresponding Rayleigh numbers were 5.43 × 106, 1.83 × 107 and 8.48 × 107 respectively. The packed bed height to sphere diameter ratios, H / d were 5, 10 and 20. The Nusselt numbers (Nu d), velocity and shear stress distributions of both analyses were in good agreement. Both results showed the same order (10−2 m/s) of irregular velocity distributions resulting from the random arrangement of the spheres. In spite of the laminar flow condition, wake and vortex generated by the packed bed geometry increased the turbulent kinetic energies to one- or two-order higher values than those at the entrance. The temperature profiles of flow inside packed bed were approximately uniform for d = 4 mm cases but there were temperature gradients in case of d = 10 mm. This revealed that the use of smaller fuel sphere can prevent from unwanted hot spots inside the packed bed. The Nu d values from LBM results and newly developed empirical correlation for natural convective flow in packed bed were consistent. • Self-heating sphere condition was tested with high Prandtl number considering a Molten Salt. • Mass transfer experiments realized the uniform self-heating condition of spheres. • Nusselt numbers, velocity and turbulent intensity distributions of both studies agreed well. • Lattice Boltzmann calculation revealed crooked • LBM results revealed winding and crooked passages, wake and vortex in the packed bed. [ABSTRACT FROM AUTHOR]

• Lattice Boltzmann methodology to predict behavior in fluid mechanical systems. • CFD used to model two-fluid blending of non-Newtonian fluids. • CFD used to accurately model mixing of yield stress fluids. • Mixing of radioactive slurry waste and glass frit was modeled using CFD. A numerical approach for predicting the time-accurate fluid flow and mixing properties of non-Newtonian fluids is presented. This approach, which is based on the lattice Boltzmann method, is used to characterize the blending in shear-thinning fluids, as well as cavern formation in yield-stress fluids. Predictions compare favorably to measured data and expectations from first-principles theory. Importantly, across the range of fluids and systems here, the simulations require no reparameterization or retuning between scenarios. This generality is exploited to model a nuclear waste processing unit operation. [ABSTRACT FROM AUTHOR]

The goal of this paper is to revise the Rossiter-Heller formula of cavity resonance frequencies for rectangular cavities in subsonic and supersonic flow conditions. Two modifications are proposed; the first one consists in using a second-order polynomial fit of literature experimental data for the non-dimensional time lag coefficient as a function of the cavity aspect ratio. The second modification consists in taking into account the reversed flow convective effects in the calculation of the backward acoustic propagation time, by including the reversed flow Mach number in the formula, expressed as a function of the free-stream Mach number and cavity aspect ratio. A second-order polynomial fit of scale-resolving flow simulation results of the reversed flow Mach number is used to derive the final resonance frequency formula. The effects of the two modifications are investigated for three values of the aspect ratio in the range 5 to 10, and four values of the free-stream Mach number in the range 0.6 to 1.35. It is concluded that taking into account both modifications yields globally more accurate predictions of the resonance frequencies. Finally, an attempt is made to identify the nature of additional tones observed for the deep supersonic case around the fourth and fifth Rossiter-Heller resonance modes. [ABSTRACT FROM AUTHOR]

In this study, three-dimensional flow measurements by means of 4D-Particle Tracking Velocimetry (4D-PTV) are carried out in a laboratory-scale 3 L stirred tank reactor in order to investigate the flow-following behavior of two different inertial particle types, Polyethylene (PE) particles and alginate beads, at different impeller frequencies. Applied particles mimic Lagrangian sensor particles, which are intended to determine process parameters such as oxygen concentration at their corresponding position inside a bioreactor. Accompanying Lattice-Boltzmann Large Eddy Simulations (LB LES) provide additional information about the fluid flow and the difference in the trajectories between inertial and non-inertial particles. The data acquired from LB LES is validated with the experimental data by means of a Lagrangian and a Eulerian approach. In their tail, the probability distributions show higher Lagrangian velocities and accelerations for 4D-PTV data compared to LB LES data. Time-averaged Eulerian data is utilized to determine particle Reynolds numbers lower than 200. The Stokes number distributions show 10-fold higher values for the alginate beads than for PE particles, however, both particle types do not sufficiently meet the criterion of a flow-following Stokes number of S t ≤ 0. 01. Generally, time-averaged results from LB LES are in good accordance to the 4D-PTV data. From the LB LES, a theoretical, maximum particle diameter of approx. 20 μ m is determined, which meets the criterion of S t ≤ 0. 01 throughout the reactor. This result implies that with current sensor particle technology it is not possible to meet the flow-following behavior and depict the lifelines of cells during a cultivation process. Therefore, further research is necessary to understand particle trajectories and to translate them into lifelines of cells. • Inertial particles are analyzed regarding their flow-following behavior in a 3 L STR. • They act as downsized Lagrangian sensor particles that are applied at industrial scale. • 4D-PTV measurement results are used to validate Lattice-Boltzmann simulations. • Particle Reynolds- and Stokes numbers are spatially evaluated throughout the reactor. • Used particles do not follow the flow, and thus sensors do not depict cell lifelines. [ABSTRACT FROM AUTHOR]

The goal of this paper is to demonstrate the predictive capabilities of the Lattice-Boltzmann/Very-Large-Eddy-Simulation CFD solver SIMULIA PowerFLOW® when a transitional flow past a small drone rotor blade is simulated, without using any numerical or physical turbulence triggering system. A recently developed variant of PowerFLOW VLES model is validated against measurements performed at Delft University of Technology. A 2-bladed propeller of 0.3 m diameter is considered, which is operated at 4000 and 5000 RPM and two different advance ratios, 0.0 and 0.6, for each angular velocity. In such conditions, corresponding to a Reynolds number based on the chord at 75% of the tip radius ranging between 7 ⋅ 10 4 and 9 ⋅ 10 4 , the presence of a laminar separation bubble was experimentally observed and related to the occurrence of a high-frequency broadband noise hump in the far-field noise spectra. The numerical results are in a good agreement with the loading, noise and PIV experimental measurements, demonstrating the capability of the new PowerFLOW VLES model to predict boundary layer flow transitional phenomena such as laminar separation, reattachment and transition to turbulence, as well as the corresponding broadband trailing-edge noise radiation. [ABSTRACT FROM AUTHOR]

This work presents a contribution on the numerical modelling capabilities for the simulation of fluid flow and heat transfer in cellular solids – in particular we focus on open cell aluminium foams. Rather than applying one of the classical academical or commercial numerical finite volume (FV), finite difference (FD) or finite element (FE) interface tracking methods, we base our models on an interface capturing phase field method (Nestler, 2005). A coupled diffuse interface lattice Boltzmann fluid flow solver (Ettrich, 2014) and a diffuse interface heat transfer approach (Ettrich et al., 2014) are combined in view of dealing with even more convoluted geometries, incorporating the dynamics of interfaces and complex multiphysics applications. Numerical results for the combined fluid flow and heat transfer simulations in open cell metal foams are in very good agreement with experimental data (Ettrich and Martens, 2012; Ettrich et al., 2012). [ABSTRACT FROM AUTHOR]

Simulation of fluid flow and friction in a circular shaped ribbed microchannel using the Lattice Boltzmann Method (LBM) has been studied in the present paper. In micro-flows, the local density variation is still relatively small, but the total density changes, therefore, in order to account this density variation and its effect on the kinematic viscosity ν , a new relaxation time is used. The roughness geometry is modeled as a series of circular riblets with a relative roughness (ɛ) height up to a maximum 10% of the channel height. To analyze the roughness effects, the friction coefficients in terms of Poiseuille number, Pn, has been discussed. Actually, the friction factor properties of riblets, depending on the particular geometry, are analyzed in the slip flow regime at Knudsen number, Kn, ranging from 0.01 to 0.10 with other controlling parameters. The velocity profiles in terms streamlines near the riblets are demonstrated to be responsible for the roughness effect. Finally the results have been compared with previous published works and it is found to be in good agreement. [ABSTRACT FROM AUTHOR]