Fluid Simulation Research Articles

The Effect of Subglottic Stenosis Severity on Vocal Fold Vibration and Voice Production in Realistic Laryngeal and Airway Geometries Using Fluid–Structure–Acoustics Interaction Simulation

This study investigates the impact of subglottic stenosis (SGS) on voice production using a subject-specific laryngeal and airway model. Direct numerical simulations of fluid–structure–acoustic interaction were employed to analyze glottal flow dynamics, vocal fold vibration, and acoustics under realistic conditions. The model accurately captured key physiological parameters, including the glottal flow rate, vocal fold vibration patterns, and the first four formant frequencies. Simulations of varying SGS severity revealed that up to 75% stenosis, vocal function remains largely unaffected. However, at 90% severity, significant changes in glottal flow and acoustics were observed, with vocal fold vibration remaining stable. At 96%, severe reductions in glottal flow and acoustics, along with marked changes in vocal fold dynamics, were detected. Flow resistance, the ratio of glottal to stenosis area, and pressure drop across the vocal folds were identified as critical factors influencing these changes. The use of anatomically realistic airway and vocal fold geometries revealed that while anatomical variations minimally affect voice production at lower stenosis grades, they become critical at severe stenosis levels (>90%), particularly in capturing distinct anterior–posterior opening patterns and focused jet effects that alter glottal dynamics. These findings suggest that while simplified models suffice for analyzing mild to moderate stenosis, patient-specific geometric details are essential for accurate prediction of vocal fold dynamics in severe cases.

Research and Application of ROM Based on Res-PINNs Neural Network in Fluid System

In the design of fluid systems, rapid iteration and simulation verification are essential, and reduced-order modeling techniques can significantly improve computational efficiency and accuracy. However, traditional Physics-Informed Neural Networks (PINNs) often face challenges such as vanishing or exploding gradients when learning flow field characteristics, limiting their ability to capture complex fluid dynamics. This study presents an enhanced reduced-order model (ROM): Physics-Informed Neural Networks based on Residual Networks (Res-PINNs). By integrating a Residual Network (ResNet) module into the PINN architecture, the proposed model improves training stability while preserving physical constraints. Additionally, the model’s ability to capture and learn flow field states is further enhanced by the design of a symmetric parallel neural network structure. To evaluate the effectiveness of the Res-PINNs model, two classic fluid dynamics problems—flow around a cylinder and Vortex-Induced Vibration (VIV)—were selected for comparative testing. The results demonstrate that the Res-PINNs model not only reconstructs flow field states with higher accuracy but also effectively addresses limitations of traditional PINN methods, such as vanishing gradients, exploding gradients, and insufficient learning capacity. Compared to existing approaches, the proposed Res-PINNs provide a more stable and efficient solution for deep learning-based reduced-order modeling in fluid system design.

Optimization of 3D Printing Nozzle Parameters and the Optimal Combination of 3D Printer Process Parameters for Engineering Plastics with High Melting Points and Large Thermal Expansion Coefficients

Three-dimensional printing is a transformative technology in the manufacturing industry which provides customization and cost-effectiveness for all walks of life due to its fast molding speed, high material utilization, and direct molding of arbitrary complex structural parts. This study aims to improve the molding accuracy of 3D printed polyether ether ketone (PEEK) samples by systematically studying key process parameters, including printing speed, layer thickness, nozzle temperature, and filling rate. The 3D printing nozzle has an important impact on the extrusion rate of the melt, and the fluid simulation of the nozzle was carried out to explore the variation characteristics of the melt flow rate in the nozzle and optimize the nozzle structure parameters. In order to effectively optimize the process, considering its inherent efficiency, robustness, and cost-effectiveness, the L9 orthogonal array experimental design scheme was used to analyze the effects of printing speed, layer thickness, nozzle temperature, and filling rate on the molding accuracy of the test sample, and the optimal combination of process parameters was optimized through the comprehensive weighted scoring method so as to improve the molding accuracy of the 3D printed PEEK sample; finally, the molding accuracy of the components printed using the Sermoon-M1 3D printer with the optimized nozzle structure was printed. The results show that the nozzle structure is optimal when the convergence angle is 120° and the aspect ratio is 2, and the outlet cross-section velocity is increased by 2.5% and 2.7%, respectively. The order of influence strength on the dimensional accuracy of the test sample is layer thickness > filling rate > nozzle temperature > printing speed. The optimal combination of parameters is: a printing speed of 15 mm/s, a layer thickness of 0.1 mm, a nozzle temperature of 420 °C, and a filling rate of 50%. The insights derived from this study pave the way for predicting and implementing the selection of optimal process parameters in the production of 3D printed products, with important implications for the optimal molding accuracy of printed components.

3D fluid simulation of the propagation of a nanosecond discharge in air above a liquid surface: investigation of the pattern formation under various conditions and comparison with experiments

Abstract Plasma-liquid interaction remains one of the fundamental processes influencing the various applications. Understanding the influence of external parameters on discharge properties, particularly the discharge dynamic at the liquid surface, is therefore essential. In previous studies, we investigated the impact of voltage polarity, gap distance, and liquid dielectric permittivity and electrical conductivity on nanosecond discharges initiated in air at atmospheric pressure in a pin-to-liquid configuration. Herein, we present a 3D fluid model, improved with stochastic photoionization, to simulate the discharge dynamics under the previously mentioned conditions. The model outputs are compared with the discharge dynamics measured experimentally. For instance, filamentation and the homogeneous emission over solution’s surface measured in positive and negative discharges, respectively, are well reproduced by the simulation. Furthermore, the simulation allowed us to report other plasma properties not accessible experimentally such as the spatio-temporal distributions of electric field (E-field) and electron density. Notably, we observe that the E-field at the front of the negative surface ionization wave (SIW) is nearly four times lower than that of the positive SIW, which may explain the absence of filaments for negative discharges. Furthermore, we find that increasing solution conductivity or gap distance reduce the radial propagation velocity of the circular SIW front and stopping its expansion before a destabilization can occur. The simulation allowed investigating the influence of photoionization strength, and we find that increasing the number of ionizing photons leads to supress the filamentation while keeping the ionization front circular and propagating at high speed.

Multiparticle collision framework for active polar fluids

Sufficiently dense intrinsically out-of-equilibrium suspensions, such as those observed in biological systems, can be modeled as active fluids characterized by their orientational symmetry. While mesoscale numerical approaches to active nematic fluids have been developed, polar fluids are simulated as either ensembles of microscopic self-propelled particles or continuous hydrodynamic-scale equations of motion. To better simulate active polar fluids in complex geometries or as a solvent for suspensions, mesoscale numerical approaches are needed. In this work, the coarse-graining multiparticle collision dynamics (MPCD) framework is applied to three active particle models to produce mesoscale simulations of polar active fluids. The first active-polar MPCD (AP-MPCD) is a variant of the Vicsek model, while the second and third variants allow the speed of the particles to relax towards a self-propulsion speed subject to Andersen and Langevin thermostats, respectively. Each of these AP-MPCD variants exhibits a flocking transition at a critical activity and banding in the vicinity of the transition point. We leverage the mesoscale nature of AP-MPCD to explore flocking in the presence of external fields, which destroys banding, and anisotropic obstacles, which act as a ratchet that biases the flocking direction. These results demonstrate the capacity of AP-MPCD to capture the known phenomenology of polar active suspensions and its versatility to study active polar fluids in complex scenarios. Published by the American Physical Society 2025

Impact of Rock Cuttings on Downhole Fluid Movement in Polycrystalline Diamond Compact (PDC) Bits, Computational Fluid Dynamics, Simulation, and Optimization of Hydraulic Structures

The flow occurring at the bottom of a polycrystalline diamond compact (PDC) drill bit involves a complex process made up of drilling fluid and the drilled rock cuttings. A thorough understanding of the bottom-hole flow conditions is essential for accurately evaluating and optimizing the hydraulic structure design of the PDC drill bit. Based on a comprehensive understanding of the hydraulic structure and fluid flow characteristics of PDC drill bits, this study integrates computational fluid dynamics (CFD) with rock-breaking simulation methods to refine and enhance the numerical simulation approach for the liquid–solid two-phase flow field of PDC drill bits. This study further conducts a comparative analysis of simulation results between single-phase and liquid–solid two-phase flows, highlighting the influence of rock cuttings on flow dynamics. The results reveal substantial differences in flow behavior between single-phase and two-phase conditions, with rock cuttings altering the velocity distribution, flow patterns, and hydraulic performance near the bottom-hole region of the drill bit. The two-phase flow simulation results demonstrate higher accuracy and provide a more detailed depiction of the bottom-hole flow, facilitating the identification of previously unrecognized issues in the hydraulic structure design. These findings advance the methodology for multiphase flow simulation in PDC drill bit studies, providing significant academic and engineering value by offering actionable insights for optimizing hydraulic structures and extending bit life.

Comparison of aerodynamic characteristics of NACA 2415 and NACA 4415 Aerofoils

This study compared the two-dimensional aerodynamic characteristics of NACA 2415 and NACA 4415 at different angles of attack. In this study, the Reynolds number is 2.3e6, under which the velocity of the air is 33 m/s. The mesh of C-type is established based on ANSYS Meshing; to simplify the calculation, the chord length is set to 1 m. The fluid simulation is done by ANSYS Fluent, and the simulation calculation is performed based on the pressure solver. The N-S equation is used as the governing equation. Velocity inlet and pressure outlet are set as the boundary condition, and the k-omega SST viscous model is chosen for the simulation processing. This study compares the aerodynamics of NACA 2415 and NACA 4415 at different angles of attack, including the pressure and velocity distribution, lift and drag coefficient, and lift-drag ratio. The results of this research would help optimize wing design and develop new aerofoil and testing.

Numerical analysis of aerodynamic performance characteristics of NACA 2412 and NACA 4412 at Re = 4000000

This paper conducts a numerical analysis of the two-dimensional aerodynamic characteristics of the NACA 2412 and NACA 4412 aerofoils at a Reynolds number of Re = 4106. Employing the fluid simulation software Ansys Fluent, which is based on the finite volume method, for numerical analysis. Both the geometric model and mesh of the aerofoil are established by using Fluent Meshing, and the simulation calculation is performed based on the pressure solver. Based on the Navier-Stokes equations, the SST k- turbulence model and coupled algorithm are employed for the simulation processing. The paper systematically compares the aerodynamic characteristics of NACA 2412 and NACA 4412, including the pressure and velocity distributions, as well as the variations in the lift coefficient, drag coefficient, and lift-to-drag ratio concerning the angle of attack. The results indicate that at Re = 4106, the peak value of the lift-to-drag ratio of the NACA 2412 aerofoil is attained under the 8 condition, for the NACA 4412 aerofoil, the lift-to-drag ratio reaches its peak value at a 6 angle of attack. Additionally, the stall angles of both types of aerofoils under the studied operating conditions are 16.

The influence of trailing edge flaps on the aerodynamic characteristics of S1223 aerofoil

The S1223 aerofoil is a low Reynolds number high lift aerofoil. Analysing the aerodynamic characteristics of this aerofoil can provide a theoretical basis for enhancing flight efficiency in the design of small unmanned aerial vehicles. This study employed the k--SST turbulence model in the fluid simulation software (ANSYS Fluent) to conduct two-dimensional numerical aerodynamic simulations on the original aerofoil and its modified versions, which included flaps (deflected 10 at 70% chord length) and slotted flaps (deflected 10 at 70% chord length with a slot width of 1.5% of the chord). The aerofoil's aerodynamic performance was confirmed by comparing lift and drag coefficients at different angles of attack under Reynolds number 5.0105, as well as by analysing the pressure and velocity gradients in the flow field. The results indicate that both the lower flap and the slotted flap can greatly enhance the lift-to-drag ratio. In contrast, slotted flaps delay boundary layer separation, providing greater lift at high angles of attack while reducing the impact on drag.

A Physics-Based Simulation of Fluid–Solid Coupling Scenarios in an Ocean Visual System

In the domain of ocean engineering, the authenticity of visual systems is a major challenge in developing marine simulators. A simulation strategy based on the smoothed particle hydrodynamics (SPH) simulation method is proposed in this study to enhance the realism of fluid–solid coupling scenes in a marine simulator visual system. Based on the SPH method, the water particles are constrained in each iteration according to the two physical fields of velocity divergence and density by setting an intermediate velocity. In the simulation of the fluid–structure interaction scenario, the contribution of the volume of the rigid model to the water particles is represented by a spatial map and then incorporated into the calculation of the pressure from the water particles according to the positional relationship between the water particles and the boundary. This strategy can effectively ensure the realism of the interaction between the rigid body and the waves on the one hand and significantly improve the speed of the marine simulator visual system on the other. The experiments show that this strategy can effectively save a significant amount of time and provide theoretical and technical references for enhancing the realism of a marine simulator visual system.

Efficiency and scalability of fully-resolved fluid-particle simulations on heterogeneous CPU-GPU architectures

Current supercomputers often have a heterogeneous architecture using both conventional Central Processing Units (CPUs) and Graphics Processing Units (GPUs). At the same time, numerical simulation tasks frequently involve multiphysics scenarios whose components run on different hardware due to multiple reasons, e.g., architectural requirements, pragmatism, etc. This leads naturally to a software design where different simulation modules are mapped to different subsystems of the heterogeneous architecture. We present a detailed performance analysis for such a hybrid four-way coupled simulation of a fully resolved particle-laden flow. The Eulerian representation of the flow utilizes GPUs, while the Lagrangian model for the particles runs on conventional CPUs. Two characteristic model situations involving dense and dilute particle systems are used as benchmark scenarios. First, a roofline model is employed to predict the node level performance and to show that the lattice-Boltzmann-based Eulerian fluid simulation reaches very good performance on a single GPU. Furthermore, the GPU-GPU communication for a large-scale Eulerian flow simulation results in only moderate slowdowns. This is due to the efficiency of the CUDA-aware MPI communication, combined with the use of communication hiding techniques. On 1024 A100 GPUs, an overall parallel efficiency of up to 71% is achieved. While the flow simulation has good performance characteristics, the integration of the stiff Lagrangian particle system requires frequent CPU-CPU communications that can become a bottleneck, especially when simulating the dense particle system. Additionally, special attention is paid to the CPU-GPU communication overhead since this is essential for coupling the particles to the flow simulation. However, thanks to our problem-aware co-partitioning, the CPU-GPU communication overhead is found to be negligible. As a lesson learned from this development, four criteria are postulated that a hybrid implementation must meet for the efficient use of heterogeneous supercomputers.

Critical Point Fluctuations in Heavy-Ion Collisions within Molecular Dynamics with Expansion

We analyze particle number fluctuations near the critical endpoint of a first-order phase transition using molecular dynamics simulations of the Lennard-Jones fluid. Building on our previous study [V.A. Kuznietsov et al., Phys. Rev. C 105, 044903 (2022)], we incorporate longitudinal collective flow. The scaled variance of particle number distributions in various coordinate and momentum space acceptances is computed through ensemble averaging, confirming previous time-averaging results. We find that significant collective flow is crucial for observing large fluctuations from the critical point in momentum space. These results are discussed in the context of heavy-ion collisions.

Advanced finite element modeling for dual simulations of Carreau-Yasuda fluid subjected to thermal jump using three-dimensional stretching and shrinking surfaces

Advanced finite element modeling for dual simulations of Carreau-Yasuda fluid subjected to thermal jump using three-dimensional stretching and shrinking surfaces

Monte Carlo analysis of electron transport coefficients and excitation rates of H2X1Σg+(ν) states in hydrogen plasma

In modeling the production of negative hydrogen ions via volume processes, the population of vibrationally excited states, denoted as H2X1Σg+(ν), is a crucial parameter. Additionally, electron swarm kinetic energy and transport coefficients are essential for fluid or hybrid simulations. This research employs the Monte Carlo method to determine electron transport coefficients for a wide range of E/N and the excitation rate of H2X1Σg+(ν) states in hydrogen plasma (for E/N from 5.46 to 260 Td), both in the absence of a magnetic field and under crossed magnetic fields of 0.01, 0.05, 0.1, and 0.2 T. We compare our transport coefficients with those derived from Bolsig+ and experimental data where accessible. Our findings for reduced mobilities, both along the electric field and in the E×B direction, show excellent agreement with Bolsig+ results. In the absence of a magnetic field, at reduced electric fields below 30 Td, the agreement between the present work, Bolsig+, and experimental data for both characteristic energy and mobility is very good. Above 120 Td, deviation from experimental data starts. However, the present simulation does a better job in predicting characteristic energy, which is crucial in obtaining excitation rates.

Effects of the Arrangement and Height Variability of Roughness Obstacles on the Structure and Intensity of Tornado-Like Vortices

Abstract To reveal the effects of surface roughness on the structure and intensity of tornadic flow, we conducted numerical simulations, in which the horizontal density and height of obstacles were controlled independently. Simulation with a low external swirl ratio produced a tornado-like vortex with a narrow core radius. For this low-swirl vortex, when the horizontal density of obstacles was varied while the obstacle height was maintained, the lowest value of maximum tangential wind speed was achieved at a moderate horizontal density; a greater horizontal density led to an increase in the maximum tangential wind speed. By contrast, an increase in obstacle height always resulted in a lower maximum tangential wind speed. The mechanisms underlying such results were considered from the viewpoint of angular momentum depletion. Tall and moderately densely distributed obstacles generated a large amount of depleted angular momentum flux, which thickened the low angular momentum layer inside the corner flow region and the core region of the vortices. As a result, the maximum tangential wind speed decreased in association with the decrease in the radial gradient of angular momentum. Additional simulations were then run with a higher external swirl ratio, which resulted in vortices with a wider core radius. Even the roughness distribution with the highest and moderately dense obstacles did not notably reduce the intensity of the higher-swirl vortex, while the flow structure changed in larger scale. The results of this study suggest that urban roughness with a moderate density of tall buildings may weaken low swirl, thin tornadoes but does not preclude high swirl, wide tornadoes, at least through vortex-scale processes. Significance Statement In this study, we investigate the frictional effects of surface roughness on the intensity and the structure of tornado-like vortices in vortex-scale processes from computational fluid simulations that directly resolve the roughness obstacles. We show that the influence of roughness is maximized when tall obstacles are distributed at a moderate density, such as in urban terrain. This is considered to be because the intensity of the tornado-like vortices is dominated by the angular momentum stratification inside the central region of the vortices, which is strongly influenced by the surface flow at a depth of a similar length scale. This study indicates that small-scale topography, which is not always fully resolved in meteorological models, has a nonnegligible influence on tornado intensity.

Step-by-step enhancement of a graph neural network-based surrogate model for Lagrangian fluid simulations with flexible time step sizes

Step-by-step enhancement of a graph neural network-based surrogate model for Lagrangian fluid simulations with flexible time step sizes

Zonal fields as catalysts and inhibitors of turbulence-driven magnetic islands

A novel coalescence process is shown to take place in plasma fluid simulations, leading to the formation of large-scale magnetic islands that become dynamically important in the system. The parametric dependence of the process on the plasma β and the background magnetic shear is studied, and the process is broken down at a fundamental level, allowing us to clearly identify its causes and dynamics. The formation of magnetic-island-like structures at the spatial scale of the unstable modes is observed quite early in the non-linear phase of the simulation for most cases studied, as the unstable modes change their structure from interchange-like to tearing-like. This is followed by a slow coalescence process that evolves these magnetic structures toward larger and larger scales, adding to the large-scale tearing-like modes that already form by direct coupling of neighboring unstable modes, but remain sub-dominant without the contribution from the smaller scales through coalescence. The presence of the cubic non-linearities retained in the model is essential in the dynamics of this process. The zonal fields are key actors of the overall process, acting as mediators between the competitive mechanisms from which turbulence-driven magnetic islands can develop. The zonal current is found to slow down the formation of large-scale magnetic islands, acting as an inhibitor, while the zonal flow is needed to allow the system to transfer energy to the larger scales, acting as a catalyst for the island formation process.

Preserving positivity in density-explicit field-theoretic simulations.

Field-theoretic simulations are numerical methods for polymer field theory, which include fluctuation corrections beyond the mean-field level, successfully capturing various mesoscopic phenomena. Most field-theoretic simulations of polymeric fluids use the auxiliary field (AF) theory framework, which employs Hubbard-Stratonovich transformations for the particle-to-field conversion. Nonetheless, the Hubbard-Stratonovich transformation imposes significant limitations on the functional form of the non-bonded potentials. Removing this restriction on the non-bonded potentials will enable studies of a wide range of systems that require multi-body or more complex potentials. An alternative representation is the hybrid density-explicit auxiliary field theory (DE-AF), which retains both a density field and a conjugate auxiliary field for each species. While the DE-AF representation is not new, density-explicit field-theoretic simulations have yet to be developed. A major challenge is preserving the real and non-negative nature of the density field during stochastic evolution. To address this, we introduce positivity-preserving schemes that enable the first stable and efficient density-explicit field-theoretic simulations (DE-AF FTS). By applying the new method to a simple fluid, we find thermodynamically correct results at high densities, but the algorithm fails in the dilute regime. Nonetheless, DE-AF FTS is shown to be broadly applicable to dense fluid systems including a simple fluid with a three-body non-bonded potential, a homopolymer solution, and a diblock copolymer melt.

Transition route to elastic and elasto-inertial turbulence in polymer channel flows

Viscoelastic shear flows support additional chaotic states beyond simple Newtonian turbulence. In vanishing Reynolds number flows, the nonlinearity in the polymer evolution equation alone can sustain inertialess “elastic” turbulence (ET) while “elasto-inertial” turbulence (EIT) appears to rely on an interplay between elasticity and finite-Re effects. Despite their distinct phenomenology and industrial significance, transition routes and possible connections between these states are unknown. We identify here a common Ruelle-Takens transition scenario for both of these chaotic regimes in two-dimensional direct numerical simulations of FENE-P fluids in a straight channel. The primary bifurcation is caused by a recently discovered “polymer diffusive instability” associated with small but nonvanishing polymer stress diffusion which generates a finite-amplitude, small-scale traveling wave localized at the wall. This is found to be unstable to a large-scale secondary instability which grows to modify the whole flow before itself breaking down in a third bifurcation to either ET or EIT. The secondary large-scale instability waves resemble “center” and “wall” modes, respectively—instabilities which have been conjectured to play a role in viscoelastic chaotic dynamics but were previously only thought to exist far from relevant areas of the parameter space. Published by the American Physical Society 2024

Quantifying Filter Layer Porosity: A Comparative Study of X-ray Microtomography, Fluid Injection and Fluid Saturation Techniques

Wastewater filtration for reuse is a practice applied to conserve water resources. However, its effectiveness is directly related to the permeability of the filter, which can be compromised by clogging processes due to the retention of suspended particles or by precipitated materials during the process of removing chemical contaminants. This study investigates the porous structure of filter layers by different techniques. The study explores porosity in porous media, emphasizing the importance of pores and the interconnected matrix. To evaluate the porosity, fluid injection techniques, fluid saturation techniques and XR-?CT were employed for porosity determination. It hypothesizes that fluid injection techniques, volumetric measurements, and imaging methods differ in their ability to accurately determine porosity. Nine reference columns of three different porous arrangements were mounted in an acrylic cylinder to study the sensitivity of the techniques to different sizes of matrix arrangements. Finally, the porosity results were compared statistically to determine the error. Fluid injection and saturation techniques are cost-effective methods for determining effective layer porosity. However, experimental studies show that water-based techniques often yield higher porosity values than helium gas porosimetry. This discrepancy may be attributed to operational errors inherent to the experimental method, leading to an overestimation of porosity. XR-?CT and gas porosimetry have been shown to be more suitable for quantifying smaller pores. Furthermore, XR-?CT allows for a deeper characterization of the porous medium, such as the determination of local porosity, and the application of fluid simulation techniques to observe the permeability and tortuosity of the medium.