Search Results (20)

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

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

Static mixers have been widely used in marine research fields, such as marine control systems, ballast water treatment systems, and seawater desalination, due to their high efficiency, low energy consumption, and broad applicability. However, the turbulent mixing process and fluid–wall interactions involving complex structures make the mixing transport characteristics of static mixers complex and nonlinear, which affect the mixing efficiency and stability of the fluid control device. Here, the modeling and design optimization of the two-phase flow mixing and transport dynamics of a static mixer face many challenges. This paper proposes a modeling and problem-solving method for the two-phase flow transport dynamics of static mixers, based on the lattice Boltzmann method (LBM) and large eddy simulation (LES). The characteristics of the two-phase flow mixing dynamics and design optimization strategies for complex component structures are analyzed. First, a two-phase flow transport dynamics model for static mixers is set up, based on the LBM and a multiple-relaxation-time wall-adapting local eddy (MRT-WALE) vortex viscosity coupling model. Using octree lattice block refinement technology, the interaction mechanism between the fluid and the wall during the mixing process is explored. Then, the design optimization strategies for the flow field are analyzed under different flow rates and mixing element configurations to improve the mixing efficiency and stability. The research results indicate that the proposed modeling and problem-solving methods can reveal the dynamic evolution process of mixed-flow fields. Blade components are the main driving force behind the increased turbulent kinetic energy and induced vortex formation, enhancing the macroscopic mixing effect. Moreover, variations in the flow velocity and blade angles are important factors affecting the system pressure drop. If the inlet velocity is 3 m/s and the blade angle is 90°, the static mixer exhibits optimized overall performance. The quantitative analysis shows that increasing the blade angle from 80° to 100° reduces the pressure drop by approximately 44%, while raising the inlet velocity from 3 m/s to 15 m/s lowers the outlet COV value by about 70%, indicating enhanced mixing uniformity. These findings confirm that an inlet velocity of 3 m/s combined with a 90° blade angle provides an optimal trade-off between mixing performance and energy efficiency. Full article

Picking fruits from tall fruit trees manually is laborious and inefficient. Rotary-wing drones, a low-altitude carrier platform, can enhance the picking efficiency for tall fruit trees when combined with picking robotic arms. However, during the operation of rotary-wing drones, the wind field changes dramatically, and the center of gravity of the drone shifts at the moment of picking, leading to poor aerodynamic stability and making it difficult to achieve optimized attitude control. To address the aforementioned issues, this paper constructs a drone and wind field testing platform and employs the Lattice Boltzmann Method and Large Eddy Simulation (LBM-LES) algorithm to solve the high-dynamic, rapidly changing airflow field during the transient picking process of the drone. The aerodynamic structure of the drone is optimized by altering the rotor spacing and duct intake ratio of the harvesting drone. The simulation results indicate that the interaction of airflow between the drone’s rotors significantly affects the stability of the aerodynamic structure. When the rotor spacing is 2.8R and the duct ratio is 1.20, the lift coefficient is increased by 11% compared to the original structure. The test results from the drone and wind field experimental platform show that the rise time ($t_r$) of the drone is shortened by 0.3 s, the maximum peak time ($t_p$) is reduced by 0.35 s, and the adjustment time ($t_s$) is accelerated by 0.4 s. This paper, by studying the transient wind field of the harvesting drone, clarifies the randomness of the transient wind field and its complex vortex structures, optimizes the aerodynamic structure of the harvesting drone, and enhances its aerodynamic stability. The research findings can provide a reference for the aerodynamic optimization of other types of drones. Full article

In this paper, the D3Q19 multiple-relaxation-time (MRT) lattice Boltzmann method (LBM) for large eddy simulation (LES) was employed to optimize the shape of the vortex generator in a triangular vortex flowmeter. The optimization process focused on the vortex shedding frequency, lift force per unit area, and symmetry of the vortex street. The optimal shape of the vortex generator was determined to feature a 180° incoming flow surface, a concave arc side with a curvature radius of 25 mm, and a fillet radius of 4 mm at the end. Numerical simulations revealed that the optimized vortex generator achieves a 2.72~13.8% increase in vortex shedding frequency and a 17.2~53.9% reduction in pressure drop and can adapt to the flow conditions of productivity fluctuations (6.498 × 10⁵ ≤ Re ≤ 22.597 × 10⁵) in the gas well production. The results demonstrated significant advantages, including low pressure loss, minimal secondary vortex generation, high vortex shedding frequency, and substantial lift force. These findings underscore the robustness and efficiency of the LBM-LES method in simulating complex flow dynamics and optimizing vortex generator designs. Full article

The gear transmission system occupies a core position in mechanical equipment due to its numerous advantages such as high efficiency, high reliability, and long durability, making it an indispensable key component. Investigating the distribution mechanism of the two-phase flow field in gear transmission systems and its optimization design strategies is crucial for enhancing the efficiency and reliability of gearboxes. This paper couples the Lattice Boltzmann Method (LBM) with Large Eddy Simulation (LES) to construct a dynamic modeling and solution method suitable for the lubrication flow field of high-speed gears with baffles. The core objective is to explore the distribution mechanism and dynamic characteristics of the lubrication flow field in gears with baffles. Based on the LBM–LES coupled model, this paper sets up a two-phase flow dynamic model for the high-speed gear lubrication flow field. By conducting a detailed analysis of the dynamic evolution of the lubrication process in the gearbox with the presence of baffles, this study reveals the changing patterns of flow field dynamics under different flow velocities and configurations of mixing components. The research findings indicate that when the radial speed of the gears reaches 8 m/s, a stable oil film can be formed on the gear surface, which is crucial for ensuring smooth operation and reducing wear. Additionally, it has been confirmed that larger baffle diameters and hole diameters can effectively increase the enthalpy of the fluid, thereby optimizing energy transfer and thermal performance. However, it is noted that a larger baffle diameter is not always better; when it exceeds a certain limit, the performance improvement effect gradually diminishes, indicating the existence of an optimal baffle diameter value. By optimizing the design of the baffle, the flow characteristics and energy dissipation of the fluid within the gearbox can be controlled, improving thermal management and lubrication performance. These research findings provide valuable references for the lubrication design and optimization of gear transmission systems in high-tech fields such as aviation and aerospace. They can help relevant technicians gain a deeper understanding of the complex mechanisms involved in the lubrication process, allowing for the design of more efficient and reliable lubrication systems, effectively enhancing the performance of the entire transmission system, and promoting progress and development in related technological fields. Full article

With the rapid development of the new energy vehicle market, the demand for efficient, low-noise, low-energy consumption, high-strength, and durable gear transmission systems is continuously increasing. Therefore, it has become imperative to conduct in-depth research into the fluid heat transfer and lubrication dynamics within gearboxes. In gear systems, the interaction between fluids and solids leads to complex nonlinear heat transfer characteristics between gears and lubricants, making the development and resolution of gearbox thermodynamic models highly challenging. This paper proposes a gear lubrication heat transfer dynamics model based on LBM-LES coupling to study the dynamic laws and heat transfer characteristics of the gear lubrication process. The research results indicate that the interaction between gears and the intense shear effects caused by high speeds generate vortices, which are particularly pronounced on larger gears. The fluid mixing effect in these high vortex regions is better, achieving a more uniform heat dissipation effect. Furthermore, the flow characteristics of the lubricant are closely related to speed and temperature. Under high-temperature conditions (such as 100 °C), the diffusion range of the lubricant increases, forming a wider oil film, but its viscosity significantly decreases, leading to greater stirring losses. By optimizing the selection of lubricants and stirring parameters, the efficiency and reliability of the gear transmission system can be further improved, extending its service life. This study provides a comprehensive analytical framework for the thermodynamic characteristics of multi-stage transmission systems, clarifying the heat transfer mechanisms within the gearbox and offering new insights and theoretical foundations for future research and engineering applications in this field. Full article

In a gear transmission system in a closed space, the heat transfer between gears and fluids presents highly nonlinear characteristics due to the complex physical processes involved in heat exchange and fluid motion, and constructing and solving the thermodynamic model of the gearbox becomes a task that involves considerable difficulty. This paper takes a conical–cylindrical two-stage gearbox as the research object, proposes a fluid–solid coupled dynamics model based on the lattice Boltzmann (LBM) combined with the large eddy simulation (LES) method, and the adopted lattice model is the D3Q27 velocity model, which is used to numerically simulate the distribution of the flow field inside the gearbox and undertake in-depth research on the fluid motion law of the complex gear transmission system in the enclosed space. The model is solved to reveal the laws determining the gear speed and the effects of the lubricant’s dynamic viscosity and thermal conductivity coefficient on the gear heat dissipation efficiency. By adopting the lattice Boltzmann method, we can simulate the fluid flow and heat transfer inside the gearbox more efficiently, which provides a new way to closely understand the thermodynamic behavior of closed complex gear transmission systems. The application of this method is expected to provide strong support for thermal performance optimization and the design of gear transmission systems. Full article

In this paper, the spatiotemporal evolution of wind turbine (WT) wake characteristics is studied based on lattice Boltzmann method-large eddy simulations (LBM-LES) and grid adaptive encryption at different incoming flow velocities. It is clearly captured that secondary flow occurs in the vortex ring under shear force in the incoming flow direction, the S-wave and the Kelvin–Helmholtz instability occur in the major vortex ring mainly due to the unstable vortex ring interface with small disturbance of shear velocity along the direction of flow velocity. The S-wave and Kelvin–Helmholtz instability are increasingly enhanced in the main vortex ring, and three-dimensional disturbances are inevitable along the mainstream direction when it evolves along the flow direction. With increasing incoming flow, the S-wave and Kelvin–Helmholtz instability are gradually enhanced due to the increasing shear force in the flow direction. This is related to the nonlinear growth mechanism of the disturbance. The analysis of the velocity signal, as well as the pressure signal with a fast Fourier transform, indicates that the interaction between the vortices effectively accelerates the turbulence generation. In the near-field region of the wake, the dissipation mainly occurs at the vortex at the blade tip, and the velocity distribution appears asymmetric around the turbine centerline under shear and the mixing of fluids with different velocities in the wake zone also leads to asymmetric distributions. Full article

In this paper, the parameters of a prototype runner of an axial flow pump are optimized by using the immersion boundary–lattice Boltzmann numerical method based on a large-eddy simulation (LES-IB-LBM). A fish-friendly axial flow pump with a leading-edge thickness of 11.4 mm and blade cutting angle of 18° is proposed. Through experiments, the living conditions of many kinds of fish in extremely positive and negative pressure environments are explored, and the probability of damage caused by pump to fish is analyzed by taking −40 kPa as the low-pressure damage threshold. The flow passage of the fish-friendly axial flow pump effectively guides the fish to low-risk areas, reducing the risk of friction, shear, and impact damage to the fish. The total impact mortality ratio of runners before and after the axial flow pump optimization is close to 7:1. Full article

As an improved method of the lattice Boltzmann method (LBM), the regularized lattice Boltzmann method (RLBM) has been widely used to simulate fluid flow. For solving high Reynolds number problems, large eddy simulation (LES) and RLBM can be combined. The computation of fluid flow problems often requires a large number of computational grids and large-scale parallel clusters. Therefore, the high scalability parallel algorithm of RLBM with LES on a large-scale cluster has been proposed in this paper. The proposed parallel algorithm can solve complex flow problems with large-scale Cartesian grids and high Reynolds numbers. In order to achieve computational load balancing, the domain decomposition method (DDM) has been used in large-scale mesh generation. Three mesh generation strategies are adopted, namely 1D, 2D and 3D. Then, the buffer on the grid interface is introduced and the corresponding 1D, 2D and 3D parallel data exchange strategies are proposed. For the 3D lid-driven cavity flow and incompressible flow around a sphere under a high Reynolds number, the given parallel algorithm is analyzed in detail. Experimental results show that the proposed parallel algorithm has a high scalability and accuracy on hundreds of thousands of cores. Full article

This study aims to investigate the aerodynamic analysis of a Darrieus-type vertical axis wind turbine (VAWT) using the Lattice Boltzmann Method (LBM). The objective is to assess the accuracy and performance of the meshless LBM approach in predicting torque coefficients, velocity, turbulence intensity, and vorticity distributions for VAWT aerodynamic analysis. Two turbulence modelling approaches, Large Eddy Simulation (LES) and Reynolds-Averaged Navier-Stokes (RANS), are employed to model the flow domain. The central problem revolves around comparing the performance of different turbulence models based on their agreement with experimental results for power and torque coefficients. The findings demonstrate the effectiveness of the WALE turbulence model in achieving the best agreement with experimental data. Overall, the study provides valuable insights into applying LBM in VAWT aerodynamic analysis and highlights the advantages of the meshless approach compared to traditional CFD methods. Full article

Most bubble breakage models have been developed for multiphase simulations using Euler-Euler (EE) approaches. Commonly, they are linked with population balance models (PBM) and are validated by making use of Reynolds-averaged Navier-Stokes (RANS) turbulence models. The latter, however, may be replaced by alternate approaches such as Large Eddy simulations (LES) that play a pivotal role in current developments based on lattice Boltzmann (LBM) technologies. Consequently, this study investigates the possibility of transferring promising bubble breakage models from the EE framework into Euler-Lagrange (EL) settings aiming to perform LES. Using our own model, it was possible to reproduce similar bubble size distributions (BSDs) for EL and EE simulations. Therefore, the critical Weber (We_crit) number served as a threshold value for the occurrence of bubble breakage events. We_crit depended on the bubble daughter size distribution (DSD) and a set minimum time between two consecutive bubble breakage events. The commercial frameworks Ansys Fluent and M-Star were applied for EE and EL simulations, respectively. The latter enabled the implementation of LES, i.e., the use of a turbulence model with non-time averaged entities. By properly choosing We_crit, it was possible to successfully transfer two commonly applied bubble breakage models from EE to EL. Based on the mechanism of bubble breakage, We_crit values of 7 and 11 were determined, respectively. Optimum We_crit were identified as fitting the shape of DSDs, as this turned out to be a key criterion for reaching optimum prediction quality. Optimum We_crit values hold true for commonly applied operational conditions in aerated bioreactors, considering water as the matrix. Full article

We report on the development and validation of a 3D hybrid Lattice Boltzmann Model (LBM), with Large Eddy Simulation (LES), to simulate the interactions of incompressible turbulent flows with ocean structures. The LBM is based on a perturbation method, in which the velocity and pressure are expressed as the sum of an inviscid flow and a viscous perturbation. The far- to near-field flow is assumed to be inviscid and represented by potential flow theory, which can be efficiently modeled with a Boundary Element Method (BEM). The near-field perturbation flow around structures is modeled by the Navier–Stokes (NS) equations, based on a Lattice Boltzmann Method (LBM) with a Large Eddy Simulation (LES) of the turbulence. In the paper, we present the hybrid model formulation, in which a modified LBM collision operator is introduced to simulate the viscous perturbation flow, resulting in a novel perturbation LBM (pLBM) approach. The pLBM is then extended for the simulation of turbulence using the LES and a wall model to represent the viscous/turbulent sub-layer near solid boundaries. The hybrid model is first validated by simulating turbulent flows over a flat plate, for moderate to large Reynolds number values, Re $\in [3.7\times {10}^4;1.2\times {10}^6]$; the plate friction coefficient and near-field turbulence properties computed with the model are found to agree well with both experiments and direct NS simulations. We then simulate the flow past a NACA-0012 foil using a regular LBM-LES and the new hybrid pLBM-LES models with the wall model, for Re = $1.44\times {10}^6$. A good agreement is found for the computed lift and drag forces, and pressure distribution on the foil, with experiments and results of other numerical methods. Results obtained with the pLBM model are either nearly identical or slightly improved, relative to those of the standard LBM, but are obtained in a significantly smaller computational domain and hence at a much reduced computational cost, thus demonstrating the benefits of the new hybrid approach. Full article

Aerodynamic performances of ground vehicle continuously improve and a lot of both wind tunnel measurements and Computational Fluid Dynamics (CFD) investigations contribute in the identification of local zones where shape deformation can lead to drag force reduction. Gradient-based optimization with optimal system involving CFD models is one of the powerful methods for shape optimization, but a genetic algorithm applied on the surrogate model can also explore a large design space in a reasonable period of computation time. In this paper, we present an aerodynamic optimization technique using a Kriging model in order to perform CFD simulations of different front air dam geometries situated below the front bumper of a reduced scale road vehicle. A first design-of-experiment (DoE) is undertaken with Large Eddy Simulations (LES), involving height geometric parameters for radial-basis-function of the front air dam, utilizing a Sobol algorithm. Then, a multi-objective-genetic-algorithm (MOGA) is applied on the constituted surrogate model, depending on the geometric parameters of the front air dam, in order to reach a minimum drag coefficient value by considering pressure constraints. Results show that a front air dam can increase the pressure at the rear of the tailgate, especially by slowing the airflow below the underfloor, but an optimum balance is necessary in order to not increase the stagnation pressure on the air dam, leading to the loss of this benefit. The Sobol technique driven by the Kriging model enables the retrieval of optimum airdam shapes found with wind tunnel tests, even with relatively coarse numerical meshes used for CFD simulations. Full article