Search Results (551)

Multiphase swirling flows in confined spaces induce highly destructive, nonlinear fluid–structure interaction (FSI) vibrations. Understanding the underlying physical mechanisms is critical for ensuring the safety of industrial operations. This study proposes a mesoscopic multiscale framework coupling the Multi-Relaxation Time Lattice Boltzmann Method with Large Eddy Simulation (MRT-LBM-LES) and the Flügge thin-walled cylindrical shell equations to analyze two-way FSI responses. Variational Mode Decomposition (VMD) and the Hilbert–Huang Transform (HHT) are employed to decouple non-stationary broadband excitation signals. The macroscopic topological evolution of the swirling air core—from initial depression to critical breakthrough—is accurately captured. Dynamic mapping reveals a strict time-domain phase-locking mechanism between macroscopic flow instability and microscopic high-frequency structural excitation caused by cavitation bubble collapse. Furthermore, a dimensionless cross-scale energy cascade index is defined to quantify energy transfer. Results indicate that while higher discharge flow rates delay the critical breakthrough, they trigger a delayed, high-amplitude step mutation in the energy cascade, amplifying the global cumulative excitation energy by nearly 75%. Notably, the dominant high-frequency excitation consistently converges within a narrow band of 760 Hz to 790 Hz, independent of flow rate variations. These findings provide a theoretical foundation for unsteady excitation source localization and targeted vibration reduction in complex industrial pipeline networks. Full article

Coherent vortices alter flapping-foil energy harvesting, but wake-generated vortex properties and timing are coupled to upstream-body kinematics. We use two-dimensional immersed boundary–lattice Boltzmann simulations of a prescribed heaving–pitching NACA0015 foil at $Re=1100$. An independently prescribed Taylor vortex allows nominal encounter phase, body-fixed offset, diameter, and intensity to be varied at fixed kinematics. Production-grid ${\overline{C}}_P$ is within $0.10\%$ of the fine-grid result; the fine-grid diffusion test gives a maximum full-field velocity $L_2$ error of $0.0690\%$ against the analytical solution over $0\le t^{*}\le 4$. For the reference vortex with a pivot-centered nominal target ($D/c=v_{\theta m}/U_{\infty }=1$), nominal-encounter-aligned mean power coefficients of $0.747$, $0.862$, and $0.987$ occur at ${\psi }_e=0.10$, $0.40$, and $0.60$, respectively, compared with $0.832$ without gusts. These define the power-reducing (PR), near-baseline (NB), and power-enhancing (PE) cases. Within the sampled ranges, diameter is associated mainly with disturbance reach and duration, intensity with loading magnitude, and offset with spatial overlap and interaction timing. Power variations are consistent with the timing of vortex-modified loading relative to prescribed foil motion. In three same-sign, once-per-cycle sequences, the PR–NB–PE ordering persists despite residual-wake interactions, with sustained mean power coefficients of $0.763$, $0.916$, and $0.965$, respectively. Nominal encounter phase and foil placement should be considered jointly for repeatable or predictable vortex passages. Full article

Solving the shallow-water equations (SWEs) using the lattice Boltzmann method (LBM) can be computationally expensive on uniform grids. Here we develop a quadtree-based adaptive mesh refinement framework that preserves the Cartesian grid structure while enabling local refinement. A cell-centred data layout is used at coarse–fine interfaces, and hash-table indexing enables efficient neighbour lookup. We evaluate the model using six benchmarks: steady flow over a bed hump, a one-dimensional dam-break wave, rectangular and circular dam-break flows, long-wave resonance in a parabolic basin, and dam-break flow over a triangular sill. We further assess its performance on a natural reach of the lower Minjiang River in Leshan, China, with complex topography. The adaptive model achieves accuracy comparable to that of a uniformly fine grid while substantially reducing the lattice-node count and runtime. This framework provides a practical approach for applying LBM-SWE to moderate-scale real-world problems. Full article

An ovoid is a common particle, which is usually formed by constant extrusion and friction during running water handling. However, there is still debate over how the form of ovoidal particles affects the tortuosity and water permeability of particle packing systems. The tortuosity and permeability of the particle packing system are examined in relation to the shape and volume fraction of the particles in this work. The ovoid particle packing system is built using the Monte Carlo approach, and the tortuosity is obtained numerically. Then, the accuracy of the tortuosity prediction model is evaluated by comparing the theoretical derived tortuosities with the simulated results in this work and other literature. By combining the widely used Kozeny–Carman (K-C) formula with the derived theoretical tortuosity prediction model, we develop a modified K-C formula to predict the permeability of ovoidal particle packing systems. By comparing the model outputs with published experimental data and self-conducted lattice Boltzmann method (LBM) numerical simulations, we verify that the modified K-C formula achieves high prediction accuracy. According to the findings, when the aspect ratio c/a rises, the tortuosity first decreases and then increases, and the permeability first increases and then decreases. Full article

Constitutive models define how physical properties depend on evolving state variables, and consequently have a strong influence on computational simulations. However, material descriptions are commonly embedded within solver implementations, limiting their reusability and exchangeability. We introduce a declarative material layer that separates state-dependent material descriptions from numerical solvers and that integrates material behavior into the generated solver code. Material properties are represented symbolically, allowing constitutive relations to be defined independently of discretization methods and reused across different simulation frameworks without solver-specific modifications. A reference implementation demonstrates the compile-time integration of this approach into code-generated solvers for one reference code generation backend. Flow and thermal diffusion benchmarks show that identical constitutive descriptions can be applied consistently across different numerical methods while preserving physical behavior. Performance measurements reveal that the computational impact depends on the interaction between constitutive model complexity and solver characteristics. The proposed declarative material layer opens up the possibility of reusable and solver-independent integration of state-dependent constitutive models into high-performance simulation workflows. Full article

Constructed wetlands (CWs) are widely used as an ecological technology for wastewater treatment. However, the accumulation of microplastics (MPs) in their substrates may impair long-term performance and threaten the operational sustainability of these nature-based treatment systems. To elucidate the transport behaviour of MPs in wetland substrates, this study developed a numerical model based on the lattice Boltzmann method (LBM) to simulate advection, hydrodynamic dispersion, and reversible first-order adsorption/desorption of MPs in saturated porous media. The model incorporates a salinity-dependent non-linear attachment rate coefficient, which captures the compression of the electrical double layer and the enhanced attachment efficiency with increasing salinity. Pore-scale flow is solved using the LBM with an Ergun-type drag term to represent the resistance of the porous matrix. The model was validated against experimental breakthrough curves from column studies using quartz sand and coastal wetland soils under five salinity levels (0–35 PSU) reported in the literature. Quantitative validation yielded coefficients of determination (R²) ranging from 0.782 to 0.960 (RMSE = 0.024–0.045) for calibration cases and 0.741 to 0.946 (RMSE = 0.027–0.048) for independent validation cases across both substrates, excluding the soil cases at 3.5 and 35 PSU. Here, both observed and simulated effluent concentrations were identically zero, resulting in the statistically forced R² = 1.000 and RMSE = 0, which are mathematical artefacts rather than indicators of predictive performance. The simulations reproduce the observed reduction in peak relative concentration by over 50% in sand and near-complete retention (C/C₀ ≈ 0) in soil at high salinities (3.5 and 35 PSU). Results demonstrate that the model successfully reproduces the differences in MP breakthrough behaviour across different substrate types and salinity levels. By linking salinity-enhanced retention to the risk of irreversible clogging and shortened wetland lifespan, the model provides a predictive tool for evaluating the sustainability of CWs under saline stress. This study offers a scientific basis for optimizing hydraulic management (e.g., flushing strategies) to mitigate microplastic pollution and enhance the long-term sustainability and resilience of constructed wetlands in coastal and saline environments. Full article

Wall-flow filters are used in exhaust gas after treatment systems to reduce particulate matter emissions from internal combustion engines. The particles accumulate on the filter surface during operation, forming a layer that progressively increases the flow resistance and thus the pressure drop. This layer consists mostly of combustible materials but also contains inert ash parts. The pressure drop increase leads to the necessity of regenerating the filter. Filter regeneration may cause particle structure fragments to rearrange within single-filter channels, leading to specific ash deposition patterns that modify the filter’s pressure drop, loading behavior, and separation efficiency. This work advances previous investigations toward application-relevant temperature and inflow-velocity conditions by extending the existing resolved-particle methodology with turbulence and reaction models, enabling temperature-dependent effects on particle-structure fragments to be considered. The rearrangement process is studied in detail. It can be shown that at high velocity, most gas crosses into the outlet channel at the end of the inflow channel, leading to a pressure spike. A fragment-local reaction model was introduced and shows qualitative agreement with the experimental results. These simulations also showed a temperature difference of about 15 K between particles at the beginning and end of the inlet channel, leading to faster oxidation close to the inlet. The presented modeling approach helps to assess the formation of deposition patterns and their influence on filter behavior, engine efficiency, fuel consumption, and long-term filter durability. Full article

Forced imbibition of a wetting liquid into a gas-filled tight rock is often expected to advance as a compact front because the liquid-to-gas viscosity ratio is favorable. This expectation can fail when narrow throats, pore-body/throat mismatch, capillary-valve pinning, and wall-associated wetting pathways reorganize the defending gas before it is displaced as a connected phase. We use a three-dimensional regularized color-gradient lattice Boltzmann model to examine these processes in a single, initially gas-saturated reconstructed tight-sandstone pore space. The simulations sample three capillary numbers, two or three Ohnesorge numbers depending on the capillary number, and two water-phase contact angles while keeping the water-to-gas viscosity ratio fixed at 26.11. The contact angle is measured through the aqueous phase, with θ = 20° representing strongly water-wet conditions and θ = 60° representing weakly water-wet conditions. For θ = 60°, terminal displacement efficiency changes little between the low and intermediate sampled capillary numbers and increases from approximately 0.660 to 0.736 at the highest sampled value. For θ = 20°, strong water-wetness is beneficial only after the bulk meniscus gains enough driving force to compete with precursor corner or wall flow; at a low capillary number, the same wetting affinity is associated with snap-off and premature gas isolation. The sampled Oh dependence is weaker than the Ca dependence and is consistent with conditional modulation of capillary-inertial damping and local interface relaxation; it is not interpreted as a new static entry criterion. Size-resolved and morphology-resolved statistics show contrasting terminal signatures: θ = 20° is associated with more large-pore gas and snap-off-consistent fragmentation, whereas θ = 60° is associated with more persistent small-pore gas and bypassing-consistent retention. Event-resolved phase-field sequences at one low-Ca condition directly show wall-first precursor advance, abrupt pore-body filling, gas-neck closure, persistent component splitting, and bypass-induced local entrapment. These events establish occurrence, not their frequency or dominance across parameter space. Because the study uses one pore-space realization and a sparse, non-factorial parameter matrix, the reported comparisons are restricted to the sampled conditions and do not define a continuous Ca–Oh–θ response surface or quantify structure-to-structure uncertainty. Full article

The lubrication performance of high-speed transmission systems directly affects mechanical power consumption and operational reliability. During high-speed oil-stirring lubrication, strong gas–liquid interfacial shear, liquid-film deformation, droplet splashing, and oil-mist transport generate an unsteady multiphase turbulent flow field. Conventional continuum-based numerical methods often face difficulties in resolving interface breakup and transient turbulent dissipation under high-speed rotational excitation. To address this problem, this study develops a coupled Lattice Boltzmann–Large Eddy Simulation (LBM–LES) method for oil–air two-phase flow in a high-speed oil-stirring lubrication system. The D3Q27 discrete velocity model, cumulant collision operator, WALE subgrid-scale model, free-surface tracking, and local grid refinement are integrated to analyze free-surface deformation, oil-mist evolution, and power-loss characteristics. Taking a notched toothless oil-stirring disk as the reference configuration, the effects of oil immersion depth and disk topology on gas–liquid phase distribution, oil-mist coverage, power consumption, and vortex-induced energy dissipation are investigated. The results indicate that oil immersion depth has a nonlinear influence on lubrication performance and power loss. Among the investigated cases, an immersion depth of 20 mm provides a favorable balance between upper-region oil-mist coverage and lower-region oil-pool stability. At this depth, the notched disk exhibits directional oil delivery and relatively low power consumption, whereas the double-rhombus structure expands the oil-mist coverage but increases the average power consumption to approximately 175 W. These findings provide numerical support for balancing oil-mist coverage, mechanical power consumption, and disk topology design in high-speed transmission lubrication systems. Full article

Quantum algorithms for flow simulation are advancing rapidly, but reproducible wall-bounded benchmarks with classical reference data are still needed to evaluate future quantum and hybrid quantum-classical solvers. This work presents a forced D3Q19 multiple-relaxation-time (MRT) lattice-Boltzmann method (LBM) benchmark for body-force-driven Poiseuille flow in a three-dimensional channel. The solver combines periodic streamwise and spanwise boundaries, halfway bounce-back walls, moment-space relaxation, and body-force forcing with the half-force velocity correction. The solution is verified against the analytical parabolic profile using relative $L_2$ and maximum profile errors, mass conservation, extrapolated wall slip, and wall-normal leakage. A verification study over grid resolution, relaxation time, forcing strength, and initialization demonstrates second-order grid convergence and robust conservation behavior. The verified timestep is then decomposed into quantum-relevant primitives, including streaming, wall reflection, moment transformation, MRT relaxation, equilibrium evaluation, forcing, macroscopic recovery, and measurement. The resulting benchmark connects flow-solver accuracy metrics with operator-level requirements for quantum implementation, providing a compact reference problem for future quantum processing unit (QPU)-assisted, hybrid quantum-classical, and quantum-linear-solver-based computational fluid dynamics (CFD) studies. Performance gains over classical LBM execution are not assessed here. Full article

Rapid surrogate models are attractive for iterative computational fluid dynamics (CFD) design loops, though defining their operating envelope remains crucial. This study proposes RenaNet, a Reynolds-aware convolutional gated recurrent unit (ConvGRU) surrogate, for predicting two-dimensional laminar and transitional flows past cylinder and square obstacles. Using two initial flow snapshots and a Reynolds-number map, the model predicts spatiotemporal flow states up to 2000 time steps into the future, with Lattice Boltzmann Method (LBM) simulations serving as ground truth. Trained on Reynolds numbers of $1\le \mathrm{Re}\le 500$ (cylinder) and $1\le \mathrm{Re}\le 250$ (square), RenaNet achieves a minimum validation mean squared error (MSE) of $1.47\times {10}^{-5}$. A Reynolds-number ablation shows that removing the conditioning channel increases the validation MSE to $1.17\times {10}^{-3}$, while a ConvLSTM baseline gives $9.94\times {10}^{-4}$ with 24% more parameters. RenaNet also uses a direct long-horizon prediction interface for distant target frames. Auxiliary physics diagnostics confirm that predictions trained via MSE maintain acceptable continuity residuals across fitting, interpolation, and extrapolation cases. The average inference time for a 1000-step prediction horizon is approximately 1.25 s, delivering a 500-fold speedup over the reference LBM solver. Interpolation errors range from ${10}^{-4}$ to ${10}^{-2}$ depending on Reynolds number and geometry, while extrapolation beyond the training regime increases errors to the order of ${10}^{-2}$. These results establish RenaNet as a robust, parameter-efficient surrogate for laminar and transitional flows, with a clearly characterized operational boundary that informs future extensions into turbulent regimes. Full article

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