Search Results (540)

A numerical design study is carried out to support the setup of a wind tunnel experiment for the flap cover seal, which will serve as a benchmarking reference database for Fluid–Structure Interaction (FSI) in aeronautics. To this end, 3-D scale-resolving unsteady Large Eddy Simulation (LES) with the Lattice Boltzmann Method (LBM) is carried out using the simulation software ProLB. A new aerodynamic layout for the chosen F15LS (Large-Scale) high-lift wing model is established to fit the high-lift wing in the DLR-AWB tunnel. The design process involves variations in the leading-edge nose contour’s streamwise length and camber lines (inducing a negative S-shape) to reduce the leading-edge suction peak, thereby lowering the absolute lift while preserving the flap operating conditions. Initial simulations utilize a simplified periodic LES slice and a theory of the method of images to model wind tunnel jet flow deflection, culminating in a full-span 3-D WM-LES-LBM simulation of the entire wind tunnel installation, including free shear layers, to confirm the designed performance of the modified F15LS. This simulation serves to make informed decisions on model settings such as the boundary layer fence and model-nozzle distance. The successful experimental validation of critical performance characteristics, including angle-of-attack requirements and flow deflection, confirms the fidelity of the pre-test WM-LES-LBM evaluation. Full article

Particles moving in a fluid interact through the flow field they generate, which can lead to complex nonlinear dynamics. One important example is the synchronization of oscillatory motion in biological systems, such as the coordinated beating of cilia or flagella. In this work, we investigate the synchronization of two oscillators interacting through a Newtonian fluid using numerical simulations based on the lattice Boltzmann method. The oscillators are modeled as solid particles undergoing periodic motion, while hydrodynamic interactions are resolved explicitly through the surrounding flow. We analyze how synchronization depends on key physical parameters, including the fluid viscosity, the distance between the oscillators, the natural oscillation frequency, and the initial phase difference. The results are compared with predictions from the Kuramoto model in order to relate the hydrodynamic interaction to an effective phase coupling. We find that the coupling strength required for synchronization increases with both the oscillation frequency and the fluid viscosity, while it decreases with the distance between the oscillators. These results provide insight into the mechanisms underlying fluid-mediated synchronization and help bridge microscopic hydrodynamic models with reduced phase-oscillator descriptions. Full article

In this work, a partitioned coupling algorithm is developed by integrating the improved discrete velocity method (IDVM) with the lattice Boltzmann flux solver (LBFS) to address conjugate heat transfer (CHT) in microscale systems across all flow regimes. Specifically, the flow field is solved by the IDVM, generating a heat flux that acts as a Neumann boundary condition at the interface for the solid domain. Subsequently, the LBFS calculates the thermal distribution inside the solid, and the updated temperature at the interface is then applied to the fluid computations as a Dirichlet condition. The proposed framework effectively combines the strengths of the IDVM in modeling rarefied gas flows with the advantages of the LBFS in handling heat conduction in complex geometries. Crucially, the current approach implicitly captures temperature jump discontinuities at the conjugate boundary, bypassing the requirement for supplementary jump conditions. To evaluate its performance, several CHT test cases involving rarefied gas in microchannels were conducted. Computational evidence suggests that the scheme is robust across diverse flow regimes. Full article

Quantitative characterization of permeability in porous media represents a central problem in filtration theory, geosciences, and materials engineering. Standard numerical approaches, including finite element methods and Lattice Boltzmann simulations, typically require extensive domain-specific expertise together with specialized computational software. This motivates the development of computationally simpler and more accessible geometric approaches applicable directly to binary volumetric data. We introduce a novel algorithmic framework for the analysis of porous structures that reformulates permeability-related characterization in terms of discrete geometry and graph-based computation. The method combines parallel raster-grid and graph representations of a binarized three-dimensional CT image. The principal transport-limiting feature of the pore network, interpreted as the minimal constriction governing connectivity, is identified through iterative morphological dilation coupled with a three-dimensional scanline seed-fill procedure. In addition, a dichotomous bisection strategy is proposed to accelerate the determination of the critical bottleneck scale. The proposed methodology was evaluated on five volumetric datasets of size 100 × 100 × 100 voxels obtained from CT-derived porous structures. Experimental results demonstrate that dilation- and erosion-based formulations yield equivalent estimates of the bottleneck parameter in four of the five investigated samples. Furthermore, incorporation of the bisection optimization reduces computational time in three-dimensional experiments by approximately 50% relative to sequential iteration. The presented approach provides a computationally efficient and fully open-source alternative to conventional physics-based permeability solvers for binary porous media. The resulting bottleneck parameter b should be interpreted as a discrete geometric invariant characterizing the pore-network connectivity and minimal transport cross-section. It is not intended to replace the absolute permeability coefficient K appearing in Darcy’s law, but rather to serve as an independent structural descriptor suitable for comparative and topological analysis of porous systems. Full article

Accurate prediction of steady-state relative permeability via pore-scale modeling is fundamental to understanding multiphase flow processes in diverse engineering applications. However, the stochastic nature of the initial fluid distribution (IFD) in simulations is frequently overlooked, creating uncertainties that may obscure the physical influence of critical parameters on transport behavior. In this study, a color-gradient lattice Boltzmann method was employed to conduct extensive steady-state simulations across two porous media of varying geometric complexity. The investigation focused on evaluating three representative IFD patterns across different capillary numbers (Ca) and viscosity ratios (M). By introducing the coefficient of variation (CV) and distribution interval overlap analysis, the IFD-induced uncertainty was systematically quantified. The results demonstrate that the IFD is a primary source of statistical variance in relative permeability, exhibiting a strong nonlinear coupling with Ca, M, and structural complexity. CV analysis reveals that uncertainty peaks within specific saturation windows, which shift according to the pore geometry. Specifically, the peak uncertainty window for total relative permeability shifts from S_w$\in$ [0.5, 0.7] in the simple model to S_w$\in$ [0.3, 0.5] in the heterogeneous model. Notably, the wetting phase exhibits pronounced instability in the low-saturation regime, with the wetting-phase CV reaching its maximum at S_w = 0.3 in the simple model. At low Ca conditions, IFD-induced errors can entirely mask the physical sensitivity of relative permeability to Ca and M within certain saturation intervals. Furthermore, variations in initial configurations lead to divergent evolutions of the fluid-fluid interfacial area relative to wetting saturation, highlighting the role of microscopic topological memory in governing flow behavior. This research provides a quantitative foundation for IFD sensitivity in pore-scale modeling and proposes the integration of a CV-based uncertainty framework into macro-scale models to enhance the robustness and reliability of multiphase flow predictions. Full article

Ni coarsening is a primary degradation mechanism in Ni-based anodes, significantly contributing to performance decline and diminished lifespan of methane steam reforming solid oxide fuel cells (SOFCs) during long-term operation. In this study, a novel algorithm is introduced to reconstruct two-dimensional Ni-YSZ anode microstructures, complemented by the development of a multi-physics model that integrates phase-field modeling (PFM) with the Lattice Boltzmann Method (LBM). This coupled PFM-LBM framework is employed to investigate the effects of Ni agglomeration on microstructural evolution and methane-steam mass transport under diverse conditions. The results demonstrate that the initial Ni particle diameter exerts a significant influence on Ni agglomeration dynamics. Furthermore, the mass transport analysis reveals that the necking structures formed during Ni coarsening pose a substantial impediment to mass transfer efficiency. Finally, optimized structural parameters for Ni-YSZ are proposed to enhance anode performance in Ni-based electrodes. Full article

Local scour is a typical hydro-sediment coupled process around near-bed obstacles. Its intensity and spatial distribution are jointly controlled by the surrounding-flow structure, sediment transport, and bed-feedback deformation. To address the relative lack of studies on local scour around non-circular double-obstacle systems, this study conducts a two-dimensional parametric numerical investigation of local scour around double triangular prisms based on an existing DBM-LBM hydro-morphodynamic framework that couples the D2Q16 discrete Boltzmann method with the D2Q9 lattice Boltzmann method. First, a single circular cylinder local-scour experiment is selected as the benchmark case, and a square-pier local-scour case is further introduced as a supplementary validation case to examine the applicability of the adopted framework in reproducing the magnitude of typical local scour and the main bed morphology. Then, three arrangement patterns (tandem, side-by-side, and staggered), two prism orientations (vertex-facing and face-facing), and nine spacing ratios, S/Bp = 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, and 6, are considered for the double triangular prism cases. The local scour responses under different geometric configurations are systematically compared. The results show that, under the present two-dimensional numerical setting, the side-by-side arrangement produces the strongest local-scour amplification, with the peak occurring near S/Bp = 2.5. The tandem arrangement is mainly governed by sheltering suppression, and its group amplification factor is generally lower than 1. The scour intensity of the staggered arrangement lies between those of the side-by-side and tandem arrangements, and asymmetric scour is more likely to occur. Face-facing flow produces a larger scour depth in most cases, but its influence varies with the arrangement pattern and spacing ratio. Therefore, the double triangular-prism cases are interpreted as parametric numerical results within the adopted two-dimensional DBM–LBM framework. The reported effects of arrangement pattern, prism orientation, and spacing ratio should be understood as relative numerical trends rather than direct experimental predictions for this specific geometry. The results can provide a reference for subsequent physical-model experiments, three-dimensional numerical simulations, and scour-protection analysis for non-circular double-obstacle systems. Full article

The SF₆ circuit breaker is an essential piece of high-voltage equipment in ensuring the safe operation of the power grid. Regarding the arc-extinguishing chamber, as the most essential component, its performance is directly related to the breaking capacity of the circuit breaker. This study applies the Double Distribution Function Lattice Boltzmann Method (DDF-LBM), combined with the Smagorinsky sub-grid scale (SGS) model, to systematically simulate the dynamic breaking process of a 252 kV SF₆ arc-extinguishing chamber under 50 kA breaking current conditions. Two independent distribution functions are employed to describe the fluid field and the temperature field, respectively, thereby simulating the physical flow–heat coupling process. A dynamic simulation framework is constructed using the D2Q9 model to describe the mechanical motion of the contacts and the fluid flow. The description of contact movement is achieved by dynamically updating the geometric mesh, thereby realizing fluid–solid transformation. The research results indicate that the proposed method can simulate the pressure variation of the fluid field during the breaking process. The value of the Smagorinsky constant (C_s) exhibits a non-negligible influence on the pressure field predictions. The optimal value of C_s = 0.10 is determined through analysis, and the peak pressures at the upstream and throat measurement points reach 1.11 MPa and 1.37 MPa, respectively. Numerical simulations are conducted on the dynamic breaking process of the arc-extinguishing chamber, revealing the evolution of the pressure field upstream of the nozzle and at the throat regions. This study provides new numerical simulation methods for the investigation of SF₆ arc-extinguishing chambers and establishes a foundation for the application of the Lattice Boltzmann Method in the field of high-voltage electrical appliances. Full article

In this paper, the formulation and method of implementation of boundary conditions for heterogeneous reactions in porous media are elaborated. These are implemented into a previously validated lattice Boltzmann model for the simulation of heterogeneous reactions in porous media, extending it on multiple fronts. The formulation of the boundary conditions is validated thoroughly. The conversion of solid carbon to CO and CO₂ is chosen as a specific case of application. An extensive parametric study is conducted with a specific geometry consisting of spherical substrate particles, coated with a reactive soot layer, to highlight the capability of the code. The code was able to capture the expected evolution of a combustion front and the influence of process parameters onto its propagation velocity. The propagation speed linearly increased with an increase in the reactant mass fraction and exponentially increased with Péclet number. Also, the CO/CO₂ ratio obtained from experimental data could be reproduced with good accuracy. Furthermore, an algorithm for the correct evaluation of the specific surface is presented, which is necessary for evolving solid domains based on realistic geometries containing enclosed cavities. The method of implementation, computational overhead and acceleration technique are discussed. Finally, the model and all boundary conditions are extended to 3D and validated. Full article

The widely applied empirical Darcy’s law in geotechnical engineering faces significant challenges in describing low-velocity flow processes in low-permeability porous media such as tight sandstones containing irreducible water. A deep understanding of low-velocity non-Darcy two-phase flow behavior in low-permeability porous media is essential for evaluating the development of ultra-low-permeability reservoirs. In this study, seven low-permeability three-dimensional digital cores with distinct pore structures were constructed based on realistic ultra-low-permeability sandstones. Using the lattice Boltzmann method, pore-scale investigations of water displacing oil were conducted. Low-velocity two-phase flow behavior under varying wettability conditions, pore structures, and fluid viscosities was simulated. The underlying mechanisms of low-velocity non-Darcy flow in ultra-low-permeability sandstones were examined, leading to a modified low-velocity non-Darcy flow equation. This improved model was subsequently applied to numerical simulations of ultra-low-permeability reservoirs. The results demonstrate that non-Darcy effects manifest primarily as nonlinearities in seepage curves, representing a marked departure from conventional Darcy’s law. Low-velocity non-Darcy (LVND) flow is predominantly constrained by the influence of complex pore-throat structures and capillary forces on fluid distribution. The dynamic equilibrium among capillary forces arising from residual water saturation, viscous forces, and pressure gradients constitutes the fundamental mechanism governing the onset of LVND flow. Enhanced nonlinear behavior is observed with increasing viscosity of the invading phase and elevated capillary forces. Substantial discrepancies in reservoir production dynamics are identified between LVND and classical Darcian regimes. Through pore-scale numerical simulations, this study systematically elucidates LVND behavior during bi-phasic flow in low-permeability porous media, while identifying critical controlling factors. These findings provide scientific rationale and technical support for addressing geological engineering challenges in tight sandstone formations. Full article

Directional solidification technology is the core process for manufacturing single-crystal blades in aero-engines, but transverse grain boundaries caused by the competitive growth of polycrystals severely degrade blade performance. To gain a deeper understanding of polycrystalline competitive growth behavior, this study investigates the competitive growth of polycrystals during directional solidification under natural convection based on the phase field and lattice Boltzmann coupling model. By adjusting the solutal expansion coefficient, grain configuration, and pulling velocity, the influence of the flow field on polycrystalline competitive growth is analyzed. The results indicate that changes in the solutal expansion coefficient affect the dendritic competition process and outcome, particularly for dendrites with larger favorably oriented (FO) angles, which are more likely to be eliminated at higher solutal expansion coefficients. Additionally, grain configurations with greater orientation differences between adjacent dendrites are more sensitive to changes in the solutal expansion coefficient, whereas configurations with smaller orientation differences are less affected. It was also found that as the pulling velocity increases, the primary dendrite arm spacing decreases and the growth direction of the dendrites deflects towards the temperature gradient direction. This leads to a reduction in vortices at the dendrite tips and grain boundaries, thereby decreasing the overall flow field intensity. During dendrite growth, solute is rejected from the solid phase, creating a concentration gradient between the dendrite tips and the liquid region. This induces convection in the liquid phase. The interaction between the flow field and the solute concentration in the liquid phase causes the flow field strength and solute concentration to exhibit periodic fluctuations. Full article

The mechanism by which fish enhance hydrodynamic performance through collective swimming is a research hotspot in the field of underwater bionic robots. This study employs the Immersed Boundary-Lattice Boltzmann Method (IB-LBM) to conduct numerical simulations on a two-dimensional, single-degree-of-freedom (1-DOF) autonomous propulsion bionic fish swarm. It systematically investigates the effects of swarm size and inter-individual spacing on swimming speed and cost of transport (CoT) under two typical configurations: series and parallel arrangements. Findings reveal that hydrodynamic benefits are highly dependent on the spatiotemporal evolution of flow field structures. In the series configuration, an optimal spacing range of 1.5 L to 2.0 L exists within the school, where the “wake capture” effect is pronounced. Trailing fish achieve a maximum speed increase of approximately 41.1% while significantly reducing energy consumption. However, as spacing increases to 2.5 L, the cooperative gain for front and middle-row individuals rapidly diminishes, and the lead fish even experiences significant performance loss. Uniquely, the trailing fish in the four-fish formation exhibits distinct flow field reorganization and performance recovery at the 4.5 L trailing position. In the parallel formation, the “channel effect” and “blocking effect” of the fluid dominate. The study identifies 0.4 L laterally as the critical instability spacing under the investigated kinematic regime, where strong destructive interference causes a sharp deterioration in individual swimming performance. Additionally, the parallel formation exhibits pronounced positional differentiation. Central individuals, constrained by dual lateral flow fields, experience restricted lateral wake expansion and accelerated energy dissipation, resulting in significantly weaker escape capabilities from low-speed conditions compared to marginal individuals. The vortex-dynamic mechanism revealed herein provides theoretical foundations for formation control in multi-fish biomimetic cooperative systems. Full article

The accurate and rapid prediction of hazard gas dispersion fields in urban environments is essential for guiding emergency sensor deployment and enabling real-time risk assessment. However, the computational cost associated with Computational Fluid Dynamics (CFD) simulations hinders their use as real-time forward models, while simplified Gaussian plume models lack the fidelity to resolve building obstruction effects. This study proposes a morphology-guided conditional Generative Adversarial Network (cGAN) framework designed to achieve real-time gas dispersion field modeling in urban environments with complex building configurations. The urban area is discretized into 50 × 50 m grid cells, each characterized by six morphological parameters describing building geometry. K-means clustering categorizes these cells into distinct morphological types. High-fidelity dispersion datasets are then generated for each type using Lattice Boltzmann Method (LBM) simulations. Each sample encodes building geometry, release location, wind speed, and time as multi-channel input images, with the corresponding gas dispersion concentration field is recorded as the output. Two cGAN architectures, Image-to-Image Translation (Pix2Pix) and its high-resolution variant (Pix2PixHD), are employed to learn the mapping from input features to dispersion fields. Model performance is evaluated using four complementary metrics: Fraction within a Factor of Two (FAC2) for prediction accuracy, Normalized Root Mean Square Error (NRMSE) for precision, Fractional Bias (FB) for systematic error, and Structural Similarity Index (SSIM) for spatial pattern fidelity. A case study is conducted across a 1176 km² urban district in China. The results demonstrate that under varying wind speeds (0.5–1.5 m/s) and temporal scales (5–60 s), and across five morphological categories, the Pix2PixHD-based model achieves 92.5% prediction accuracy and reproduces 97.6% of the spatial patterns. The proposed framework accelerates computation by approximately 18,000 times compared to traditional CFD, reducing inference time to under 0.1 s per scenario. This sub-second capability enables real-time concentration field estimation for emergency management, and provides a physically informed, computationally feasible forward model that can potentially support sensor-based gas source localization and detection network planning in complex urban environments. Full article

The prediction of drying kinetics in hygroscopic biological materials remains challenging due to the strong coupling between internal moisture diffusion, evolving surface wettability, material deformation and thermolabile bioactive compounds degradation. In this context, periodic temperature variations are inherent to many industrial and solar drying systems, yet most experimental and modeling studies evaluate product quality under constant-temperature conditions. This work provides a demonstration that periodic drying can alter quality degradation pathways in ways that may not be captured by constant-temperature experiments. A coupled non-isothermal lattice Boltzmann method (LBM) model for heat and moisture transport was integrated with a Weibull kinetic formulation to describe the degradation of total carotenoids, total polyphenols, and antioxidant activity in carrot slices. Validation against experimental data across 50–70 °C demonstrates excellent agreement (R² > 0.96 for moisture ratio; quality retention within ±2% of the literature values). Seven drying scenarios were systematically evaluated: constant temperature (60 °C), fast and slow periodic oscillations, high-amplitude cycles, a mixed strategy combining constant initial drying with subsequent oscillations, and two intermittent ON/OFF profiles. Results reveal that while total polyphenol degradation within the present model is constrained to ~13.3% retention under the adopted kinetic parameters, carotenoid and antioxidant retention are highly sensitive to temperature history. The mixed strategy (60 °C for 2 h followed by 50–60 °C oscillations) achieves the highest quality retention (TC: 51.6%, AA: 34.4%) while requiring the lowest energy input (0.512 kJ), outperforming constant drying (TC: 48.8%, AA: 32.9%, 0.563 kJ). Conversely, high-amplitude intermittent drying (70/25 °C) accelerates carotenoid degradation (TC: 46.7%) despite shorter drying time (8.81 h), and low-amplitude intermittent cycling (65/55 °C) yields the poorest mean quality (31.4%) with the highest energy consumption (0.583 kJ). The framework reveals that oscillation frequency critically determines quality outcomes: slow cycles (8 h period) marginally improve retention, while fast cycles (2 h) offer no benefit over constant drying. These findings provide quantitative insights toward the design of drying strategies, demonstrating that optimal strategies must account for the coupling between temperature history and moisture-dependent vulnerability, with the mixed strategy emerging as the best-performing strategy among the tested scenarios. Full article

Selective laser melting (SLM) is a complex additive manufacturing process involving rapid laser–material interaction, steep thermal gradients, and phase change phenomena. In this work, a two-dimensional thermal model based on the lattice Boltzmann method (LBM) is developed to simulate the SLM process of AlSi10Mg and 316L stainless steel (316L SS) alloys. The model captures the laser–material interaction, layer-by-layer deposition, phase change behavior, and heat transfer mechanisms, including conduction and convection. Experimental observations of melt pool width and depth were also performed on the microstructures of the two SLM alloys in order to compare the results with the numerical predictions. For the AlSi10Mg alloy, good agreement is obtained, with relative errors of 19.13% in melt pool width and 7.58% in depth, accurately capturing melt pool penetration and remelting behavior. In contrast, moderate deviations are observed for 316L SS, indicating a higher sensitivity to thermophysical properties and suggesting that further model refinement is required. Overall, the results demonstrate the capability of the LBM framework as an efficient and robust tool for analyzing thermal behavior in SLM and for supporting process parameter optimization. Full article