Search Results (329)

The fast and accurate calculation of the internal temperature rise in the oil-immersed transformer is the premise to realize the thermal health management and load energy evaluation of the in-service transformer. In view of the influence of nanofluids on the heat transfer process of transformer, a numerical simulation algorithm based on lattice Boltzmann method (LBM) and finite difference method (FDM) is proposed to study the heat and mass transfer process inside nano-modified oil-immersed transformer. Firstly, the D2Q9 lattice model is used to solve the fluid and thermal lattice Boltzmann equations inside the oil-immersed transformer at the mesoscopic scale, and the temperature field and velocity field are obtained by macroscopic transformation. Secondly, the electric field distribution inside the oil-immersed transformer is calculated by FDM. The viscous resistance in LBM analysis and the electric field force in FDM analysis, as well as the gravity and buoyancy of particles, are used to explore the motion characteristics of nanoparticles and metal particles. Finally, compared with the thermal ring method and the finite volume method (FVM), the relative error is less than 5%, which verifies the effectiveness of the numerical model and provides a method for studying the internal electrothermal convection of nano-modified oil-immersed transformers. Full article

Compared with a traditional distribution transformer with silicon steel sheet as the core material, the no-load loss of an amorphous alloy transformer is greatly reduced due to its core using iron-based amorphous metal material, which has been applied in many countries. However, due to the brittleness of its amorphous strip, an amorphous alloy transformer is prone to debris in the process of production, transportation and work. The charge and migration characteristics of these debris will reduce the insulation strength of the transformer oil and endanger the safe operation of the transformer. In this paper, a charge measurement platform of amorphous alloy debris is set up, and the charging characteristics of amorphous alloy core debris under different flow velocities, particle radius and plate electric field strength are obtained. The results show that with an increase in pipeline flow velocity, the charge-to-mass ratio of the debris increases first and then decreases. With an increase in electric field strength, the charge-to-mass ratio of the debris increases; with an increase in the number of debris, the charge-to-mass ratio of the debris decreases; with an increase in debris size, the charge-to-mass ratio of the debris increases. The debris with different charge-to-mass ratios and types obtained from the above experiments are added to the simulation model of an amorphous alloy transformer. The lattice Boltzmann method (LBM) coupled with the discrete element method (DEM) is used to simulate the migration process of metal particles in an amorphous alloy transformer under the combined action of gravity, buoyancy, electric field force and oil flow resistance under electrothermal excitation boundary. The results show that the trajectory of the debris is related to the initial position, electric field strength and oil flow velocity. The LBM–DEM calculation model and charge measurement platform proposed in this paper can provide a reference for studying the charge mechanism and migration characteristics of amorphous alloy core debris in insulating oil. Full article

A review of the development of grid technologies and corresponding numerical approaches based on the lattice Boltzmann method (LBM) is performed in the present study. The history of the algorithmic development and practical applications is presented and followed by a short introduction of the basic theory of LBM, especially the classic lattice Bhatnagar–Gross–Krook LBGK D2Q9 model. In reality, all the different grid technologies reported aim to solve one but very important problem, the local grid refinement, which largely influences the stability, efficiency, accuracy, and flexibility of the conventional LBM. The improvement of these numerical properties after employing various grid technologies is analyzed. Several grid technologies, such as body-fitted grid, multigrid, non-uniform rectangular grid, quadtree Cartesian square grid, unstructured grid and meshless discrete points, as well as the corresponding numerical approaches are compared and discussed. Full article

The present study investigates passive microdroplet generation in a T-junction microchannel using microscopic observations, microscale particle image velocimetry (Micro-PIV) visualization, and lattice Boltzmann simulations. The key flow regimes, i.e., dripping, threading, and parallel flow, are characterized by analyzing the balance between hydrodynamic forces and surface tension, revealing the critical role of the flow rate ratio of the continuous to dispersed fluids in regime transitions. Micro-PIV visualizes velocity fields and vortex structures during droplet formation, while a lattice Boltzmann model with wetting boundary conditions captures interface deformation and flow dynamics, showing good agreement with experiments in the dripping and threading regimes but discrepancies in the parallel flow regime due to neglected surface roughness. The present experimental results highlight non-monotonic trends in the maximum head interface and breakup positions of the dispersed fluid under various flow rates, reflecting the competition between the squeezing and shearing forces of the continuous fluid and the hydrodynamic and surface tension forces of the dispersed fluid. Quantitative analysis shows that the droplet size increases with the flow rate of continuous fluid but decreases with the flow rate of dispersed fluid, while generation frequency rises monotonically with the flow rate of dispersed fluid. The dimensionless droplet length correlates with the flow rate ratio, enabling tunable control over droplet size and flow regimes. This work enhances understanding of T-junction microdroplet generation mechanisms, offering insights for applications in precision biology, material fabrication, and drug delivery. Full article

The Kuroshio Current’s flow velocity imposes exacting requirements on underwater vehicle propulsive systems. Ecological preservation necessitates low-noise propeller designs to mitigate operational disturbances. As technological evolution advances toward greater intelligence and system integration, intelligent unmanned systems are positioning themselves as a critical frontier in marine innovation. In recent years, the global research community has increased its efforts towards the development of high-maneuverability underwater vehicles. However, propeller design optimization ignores the key balance between acoustic performance and hydrodynamic efficiency, as well as the appropriate speed threshold for blade rotation. In order to solve this problem, the propeller design of the NACA 65A010 airfoil is optimized by using OpenProp v3.3.4 and XFlow 2022 software, aiming at innovating the propulsion system of shallow water agile submersibles. The study presents an integrated design framework combining lattice Boltzmann method (LBM) simulations synergized with fully Lagrangian-LES modeling, implementing rotational speed thresholds to detect cavitation inception, followed by advanced acoustic propagation analysis. Through rigorous comparative assessment of hydrodynamic metrics, we establish an optimization protocol for propeller selection tailored to littoral zone operational demands. Studies have shown that increasing the number of propeller blades can reduce the single-blade load and delay cavitation, but too many blades will aggravate the complexity of the flow field, resulting in reduced efficiency and noise rebound. It is concluded that the propeller with five blades, a diameter of 234 mm, and a speed of 500 RPM exhibits the best performance. Under these conditions, the water efficiency is 69.01%, and the noise is the lowest, which basically realizes the balance between hydrodynamic efficiency and acoustic performance. This paradigm-shifting research carries substantial implications for next-generation marine vehicles, particularly in optimizing operational stealth and energy efficiency through intelligent propulsion architecture. Full article

As with wind turbines, marine tidal turbines are expected to be deployed in arrays of multiple turbines. To optimize these arrays, a more profound understanding of the interactions between turbines is necessary. This paper employs the Actuator Line Method alongside the Lattice Boltzmann Method and Large Eddy Simulation to develop a numerical model of tidal turbine arrays. It studies a vertical-axis turbine manufactured by HydroQuest/CMN that is equipped with two counter-rotating columns, each comprising two rotors. The ambient turbulence and upstream velocity profiles correspond to the characteristics of a tidal site such as the Alderney Race. Six turbine layouts are modeled: three aligned layouts with three turbines and three staggered layouts with four turbines. The spacing between turbines varies depending on the layout. This study yields several observations regarding array configuration. A minimum distance of 300 m, or $12D_{eq}$, between aligned turbines is necessary for full wake recovery. At shorter distances, the accumulation of velocity deficits significantly decreases the efficiency of the third turbine in the array. Pairs of counter-rotating vortices are observed in the wake of turbines. The evolution of these vortices and their influence on the wake depend greatly on the array configuration. An optimal configuration is observed in which the overall averaged power is not impaired by the interactions. Full article

Cadmium (Cd) accumulation by benthic organisms poses a significant threat to aquatic environmental safety. Both vegetation and water velocity in rivers could influence this process, yet their coupled interaction mechanisms remain unclear. This study used laboratory flume experiments to simulate four scenarios: static water (C0), pure water velocity (C+H), vegetation-water velocity (V+H), and coexistence of vegetation-water velocity-Corbicula fluminea (C. fluminea) (C+V+H). The dynamics of Cd release from sediment to overlying water and its bioaccumulation within C. fluminea were investigated. A mathematical model coupling Cd release, diffusion, and C. fluminea bioaccumulation was developed based on the lattice Boltzmann method (LBM). The results showed that compared to the non-vegetation group (C+H), the presence of vegetation (V+H, C+V+H) initially reduced sediment resuspension and Cd release. However, the turbulence induced by vegetation significantly increased the Cd diffusion coefficient and equilibrium concentration in the water. Consequently, Cd accumulation in C. fluminea within the vegetation-water velocity group (C+V+H) was significantly higher than in the pure water velocity group (C+H). The established LBM model exhibited good simulation accuracy (for overlying water Cd concentration: R² = 0.8201–0.942; for C. fluminea Cd concentration: R² = 0.7604–0.8191) and successfully reproduced the processes of Cd release and bioaccumulation under varying vegetation-water velocity conditions. This study elucidates the mechanism by which vegetation promotes Cd accumulation in C. fluminea by altering water velocity structure and diffusion characteristics, providing crucial theoretical parameters for multi-media migration and transformation models of heavy metals in complex water velocity environments and for early warning systems concerning Cd accumulation risks in riverine organisms. Full article

Fluids that exhibit self-rewetting properties, such as aqueous long-chain alcohol solutions, display a unique quadratic relationship between surface tension and temperature and are marked by a positive gradient. This characteristic leads to distinctive patterns of thermocapillary convection and associated interfacial dynamics, setting self-rewetting fluids apart from normal fluids (NFs). The potential to improve heat transfer using self-rewetting fluids (SRFs) is garnering interest for use in various technologies, including low-gravity conditions and microfluidic systems. Our research aims to shed light on the contrasting behaviors of SRFs in comparison to NFs regarding interfacial transport phenomena. This study focuses on the thermocapillary convection in SRF layers with a deformable interface enclosed inside a closed container modeled as a square cavity, which is subject to nonuniform heating, represented using a Gaussian profile for the heat flux variation on one of its sides, in the absence of gravity. To achieve this, we have enhanced a central-moment-based lattice Boltzmann method (LBM) utilizing three distribution functions for tracking interfaces, computing two-fluid motions with temperature-dependent surface tension and energy transport, respectively. Through numerical simulations, the impacts of several characteristic parameters, including the viscosity and thermal conductivity ratios, as well as the surface tension–temperature sensitivity parameters, on the distribution and magnitude of the thermocapillary-driven motion are examined. In contrast to that in NFs, the counter-rotating pair of vortices generated in the SRF layers, due to the surface tension gradient at the interface, is found to be directed toward the SRF layers’ hotter zones. Significant interfacial deformations are observed, especially when there are contrasts in the viscosities of the SRF layers. The thermocapillary convection is found to be enhanced if the bottom SRF layer has a higher thermal conductivity or viscosity than that of the top layer or when distributed, rather than localized, heating is applied. Furthermore, the higher the magnitude of the effect of the dimensionless quadratic surface tension sensitivity coefficient on the temperature, or of the effect of the imposed heat flux, the greater the peak interfacial velocity current generated due to the Marangoni stresses. In addition, an examination of the Nusselt number profiles reveals significant redistribution of the heat transfer rates in the SRF layers due to concomitant nonlinear thermocapillary effects. Full article

Porous media have great application prospects, such as transpiration cooling for the aerospace industry. The main challenge for the prediction of gas permeability includes the geometrical complexity and high Knudsen number of gas flow at the nano-scale to micro-scale, leading to failure of the conventional Darcy’s law. To address these issues, the Quartet Structure Generation Set (QSGS) method is improved to construct anisotropic and heterogeneous three-dimensional porous media, and the lattice Boltzmann method (LBM) with the multiple relaxation time (MRT) collision operator is adopted. Using MRT-LBM, the pressure boundary conditions at the inlet and outlet are firstly dealt with using the moment-based boundary conditions, demonstrating good agreement with the analytical solutions in two benchmark tests of three-dimensional Poiseuille flow and flow through a body-centered cubic array of spheres. Combined with the Bosanquet-type effective viscosity model and Maxwellian diffuse reflection boundary condition, the gas flow at high Knudsen (Kn) numbers in three-dimensional porous media is simulated to study the relationship between pore-scale anisotropy, heterogeneity and Kn, and permeability and micro-scale slip effects in porous media. The slip factor is positively correlated with the anisotropic factor, which means that the high Kn effect is stronger in anisotropic structures. There is no obvious correlation between the slip factor and heterogeneity factor. Full article

Understanding tortuosity is essential for accurately modeling fluid flow in complex porous media, particularly in the sub-surface reservoir rock; therefore, tortuosity estimation was evaluated using three approaches: Streamline streamline simulations via the Lattice Boltzmann Method (LBM), geometric pathfinding using Dijkstra’s algorithm, and empirical modeling based on pore-structure parameters. The analysis encompassed 1963 micro-Computed Tomography (micro-CT) images of Brazilian pre-salt carbonate and sandstone samples, with the effective porosity extracted from LBM velocity fields, isolating flow-contributing pores, establishing streamline tortuosity as the reference standard. Sandstones exhibited relatively narrow tortuosity ranges (Dijkstra: 1.29–1.75; Streamline: 1.18–2.61; Empirical: 1.18–4.42), whereas carbonates display greater heterogeneity (Dijkstra: 1.00–3.18; Streamline: 1.00–3.68; Empirical: 1.59–4.93). Model performance assessed using the corrected Akaike Information Criterion (AICc) revealed that the best agreement with the data was achieved by the semi-empirical model incorporating coordination number and minimum throat length (AICc = −113.11), followed by the Dijkstra-based geometrical approach (−99.74) and the empirical porosity-based model (202.23). There was a nonlinear inverse correlation between tortuosity and effective porosity across lithologies. This comprehensive comparison underscores the importance of incorporating multiple pore-scale parameters for robust tortuosity prediction, improving the understanding of flow behavior in heterogeneous reservoir rocks. Full article

A mesoscopic lattice Boltzmann method based on the BGK model is proposed to solve a class of two-dimensional second-order nonlinear partial differential equations by incorporating an amending function. The model provides an efficient and stable framework for simulating initial value problems of second-order nonlinear partial differential equations and is adaptable to various nonlinear systems, including strongly nonlinear cases. The numerical characteristics and evolution patterns of these nonlinear equations are systematically investigated. A D2Q4 lattice model is employed, and the kinetic moment constraints for both local equilibrium and correction distribution functions are derived in the four velocity directions. Explicit analytical expressions for these distribution functions are presented. The model is verified to recover the target macroscopic equations in the continuous limit via Chapman–Enskog analysis. Numerical experiments using exact solutions are performed to assess the model’s accuracy and stability. The results show excellent agreement with exact solutions and demonstrate the model’s robustness in capturing nonlinear dynamics. Full article

Urban ventilation corridors play a critical role in improving wind environments, mitigating the urban heat island (UHI) effect, and enhancing urban climate resilience. Traditional Computational Fluid Dynamics (CFD) methods offer high accuracy in simulating wind fields but are computationally intensive and inefficient for large-scale, multi-scenario urban planning tasks. To address this limitation, this study proposes a morphology-driven, machine learning-based framework for ventilation corridor identification. The method integrates Lattice Boltzmann Method (LBM) simulations, neighborhood-based feature normalization, and a random forest regression model to establish a predictive relationship between morphological indices and wind speed distributions under prevailing wind conditions. Input features include raw and log-transformed LBM values, neighborhood-normalized indicators within multiple radii (100–2000 m), and porosity statistics. The model is trained and validated using CFD-simulated wind speeds, with the dataset randomly divided into training (80%), validation (10%), and testing (10%) subsets. The results show that the proposed method can accurately predict spatial wind speed patterns and identify both primary and secondary ventilation corridors. Primary corridors are closely aligned with large rivers and lakes, while secondary corridors are shaped by arterial roads and localized open spaces. Compared with conventional approaches such as FAI classification, Least Cost Path (LCP), and circuit theory models, the proposed framework offers higher spatial resolution and better alignment with the CFD results while significantly reducing computational cost. This study demonstrates the feasibility of using morphological and data-driven approaches to support efficient and scalable urban ventilation analysis, providing valuable guidance for climate-responsive urban design. Full article

The dramatic increase in domestic and industrial waste over recent centuries has significantly polluted water bodies, threatening aquatic life and human activities such as drinking, recreation, and commerce. Understanding pollutant dispersion is essential for designing effective waste management systems, employing both experimental and computational techniques. Among Computational Fluid Dynamics (CFD) techniques, the Lattice Boltzmann Method (LBM) has emerged as a novel approach based on a discretized Boltzmann equation. The versatility and parallelization capability of this method makes it particularly attractive for fluid dynamics simulations using high-performance computing. Motivated by its successful application across various scientific disciplines, this study explores the potential of LBM to model pollutant mixing and dilution from outfalls into surface water bodies, focusing specifically on vertical dense jets in crossflow (JICF), a key scenario for the diffusion of brine from desalination plants. A full-LBM scheme is employed to model both the hydrodynamics and the transport of the saline concentration field, and Large Eddy Simulations (LES) are employed in the framework of LBM to reduce computational costs typically associated with turbulence modeling, together with a recursive regularization procedure for the collision operator to achieve greater stability. Several key aspects of vertical dense JICF are considered. The simulations successfully capture general flow characteristics corresponding to jets with varying crossflow parameter $u_{r}F$ and most of the typical vortical structures associated with JICF. Relevant quantities such as the terminal rise height, the impact distance, the dilution at the terminal rise height, and the dilution at the impact point are compared with experimental results and semi-empirical relations. The results show a systematic underestimation of these quantities, but the key trends are successfully captured, highlighting LBM’s promise as a tool for simulating wastewater dispersion in aquatic environments. Full article

Slat noise poses a significant challenge during aircraft landing. Slat gap filler (SGF) technology has shown promise in mitigating slat noise, yet its noise reduction mechanisms and characteristics remain unclear. This study numerically investigates the noise reduction mechanisms of SGF and analyzes its noise characteristics using the high-lift common research model (CRM-HL). The lattice Boltzmann solver simulates the unsteady flow field, and the Ffowcs-Williams and Hawkings (FW-H) equation predicts far-field noise. The computed results exhibit a satisfactory concordance with experimental measurements. Furthermore, the near-field flow dynamics have been elucidated through proper orthogonal decomposition. The findings demonstrate that the SGF alters the distribution patterns of flow dynamics and pressure fluctuations, thereby effectively attenuating the mode energy. Moreover, our findings demonstrate that SGF significantly reduces slat noise. The noise reduction mechanism can be attributed to decreased surface pressure fluctuations on the leading edge of the main wing, and a shifted broadband noise peak to a lower frequency due to the enlarged slat cove flow vortex caused by SGF. Finally, a scaling analysis of the slat noise spectra indicates that the SGF noise spectra align well with baseline slat noise spectra when the characteristic length scale is determined by the vortex structure. Full article

This study investigates biofilm–flow interactions in gravel-bed rivers using a novel numerical model. Traditional hydrodynamic models often overlook biofilm-induced roughness coupling, prompting the development of a mesoscopic Lattice Boltzmann Method (LBM) framework that dynamically links biofilm thickness to equivalent roughness. Key insights include a dual-phase mechanism: moderate biofilm growth reduces hydraulic resistance by smoothing gravel pores, while excessive growth increases resistance via flow obstruction. Validated against 65-day flume experiments, the model accurately predicted biomass (ash-free dry mass) and velocity profiles. Current limitations involve reliance on empirical biofilm formulas, lack of natural river validation (non-uniform substrates, dynamic flows), and computational barriers in 3D large-scale simulations. Future directions include integrating biogeochemical factors (temperature, nutrients), multiscale microbial-morphology frameworks, and GPU-accelerated high-resolution modeling. Full article