Search Results (902)

With the development of the wind power industry, wind turbine blades are increasingly adopting ultra-large-scale designs. However, as the size of blades continues to increase, existing aerodynamic calculation methods struggle to achieve both relatively high computational accuracy and efficiency simultaneously. To tackle this challenge, this research focuses on the low accuracy issues of the traditional Blade Element Momentum theory (BEM) in predicting the aerodynamic performance of wind turbine blades. Consequently, a correction framework is proposed, to integrate the Computational Fluid Dynamics (CFD) method with the Multilayer Perceptron (MLP) neural network. In this approach, the CFD method is used to predict the airflow characteristics around the blades, and the MLP neural network is employed to model the intricate functional relationships between multiple influencing factors and key aerodynamic parameters. This process results in high-precision predictive functions for key aerodynamic parameters, which are then used to correct the traditional BEM. When this correction framework is applied to the rotor of the IEA 15 MW wind turbine, the effectiveness of MLP in predicting key aerodynamic parameters is demonstrated. The research findings suggest that this framework can enhance the accuracy of BEM aerodynamic load predictions to a level comparable to that of RANS. Full article

Pathophysiological conditions in arteries, such as stenosis or aneurysms, have a great impact on blood flow dynamics enforcing the numerical study of such pathologies. Computational fluid dynamics (CFD) could provide the means for the calculation and interpretation of pressure and velocity fields, wall stresses, and important biomedical factors in such pathologies. Additionally, most of these pathological conditions are connected with geometric vessel changes. In this study, the numerical solution of the 2D flow in a branching artery and a multiscale model of 3D flow are presented utilizing CFD. In the 3D case, a multiscale approach (3D and 0D–1D) is pursued, in which a dynamically altered velocity parabolic profile is applied at the inlet of the geometry. The obtained waveforms are derived from a 0D–1D mathematical model of the entire arterial tree. The geometries of interest are patient-specific 3D reconstructed abdominal aortic aneurysms after fenestrated (FEVAR) and branched endovascular aneurysm repair (BEVAR). Critical hemodynamic parameters such as velocity, wall shear stress, time averaged wall shear stress, and local normalized helicity are presented, evaluated, and compared. Full article

Constructed wetlands (CWs) are cost-effective and sustainable systems for wastewater treatment, but their hydraulic performance remains a critical challenge. In this study, a lab-scale baffled horizontal subsurface flow constructed wetland was modeled using Computational Fluid Dynamics to investigate the effects of aeration strategies on hydraulic performance, focusing on aeration rates and positions. A gas–liquid two-phase flow system was modeled using the Euler–Euler approach with the Darcy–Forchheimer model in OpenFOAM, simulating 15 cases with varying aeration rates (0.1–0.3 m³/day) and positions (middle of channels vs. bends at the ends of baffles). Results show that the introduction of aeration influenced hydraulic efficiency (HE) and the Morrill Dispersion Index (MDI). Without aeration, the baseline HE was already high (HE = 0.9297) due to the optimized baffle configuration. However, aeration further improved performance, with HE increasing to 0.9594 and MDI decreasing from 1.6087 to 1.4000 when aeration was applied at bends (Position C) at 0.3 m³/day. Aeration at bends was more effective than mid-channel aeration, promoting uniform flow distribution and reducing short-circuiting. These findings highlight the importance of aeration positioning and provide insights for optimizing CW design to balance energy consumption and hydraulic performance. Full article

Solving the Euler equations often requires expensive computations of complex, high-order time derivatives. Although Taylor Discontinuous Galerkin (TDG) schemes are renowned for their accuracy and stability, directly evaluating third-order tensor derivatives can significantly reduce computational efficiency, particularly for large-scale, intricate flow problems. To overcome this difficulty, this paper presents an optimized numerical procedure that combines Taylor series time integration with the Discontinuous Galerkin (DG) approach. By replacing cumbersome tensor derivatives with simpler time derivatives of the Jacobian matrix and finite difference method inside the element to calculate the high-order time derivative terms, the proposed method substantially decreases the computational cost while maintaining accuracy and stability. After verifying its fundamental feasibility in one-dimensional tests, the optimized TDG method is applied to a two-dimensional forward-facing step problem. In all numerical tests, the optimized TDG method clearly exhibits a computational efficiency advantage over the conventional TDG method, therefore saving a great amount of time, nearly 70%. This concept can be naturally extended to higher-dimensional scenarios, offering a promising and efficient tool for large-scale computational fluid dynamics simulations. Full article

Blowers, essential for aerator operation, are pivotal mechanical devices that induce airflow through an impeller. Extensive research has explored impeller geometrical parameters, such as size, angle, and blade count. However, limited attention has been paid to the synergic effect of optimizing the bell mouth of the blower inlet and the nose cone of the impeller eye. This study utilized computational fluid dynamics (CFDs) to analyze the impact of the bell mouth and nose cone on the blower through a geometric case study and evaluate the synergy between these components. A bell mouth decreases the wake by 91.76%, and a nose cone decreases the stagnation at the impeller eye and expands the effective impeller area by 76.29%. Moreover, this study demonstrated a significant synergistic effect between the bell mouth and nose cone, which reduced the head loss by 81.4% compared with the base model. This study presents a simple and effective method to improve blower efficiency and reduce power consumption by applying aerodynamically designed bell mouths and nose cones to blowers. Full article

In the present study, a numerical simulation and optimization combined approach is applied to investigate the thermal performance of a solar air heater (SAH). Numerical simulation of the solar air heater is performed based on computational fluid dynamics (CFDs) via ANSYS Fluent 2023R1 software. The solar air heater includes a corrugated absorber plate with a Chevron-type design. Present study was conducted in Al-Kharj, Saudi Arabia on August 15. The optimization process is used to enhance the thermal efficiency of the solar system. In the optimization process, several geometric parameters of the solar air heater, including the wave height and pitch length of the corrugated absorber plate and the height of the airflow channel under the absorber plate, have been evaluated. The wave height is between 10 and 20 mm, the pitch length is between 50 and 90 mm, and the channel height is between 70 and 90 mm. Therefore, the design of experiment (DOE) and response surface methodology (RSM) are utilized to estimate temperature rise and thermal efficiency. The thermal analysis shows that increasing the wave height, decreasing the pitch length, and shortening the channel height enhances both the temperature rise coefficient and the thermal efficiency. Full article

Dynamic stability derivatives are critical parameters in the design of trajectories and attitude control systems for flight vehicles, as they directly affect the divergence behavior of vibrations in an aircraft’s open-loop system when subjected to disturbances. This study focuses on the estimation of dynamic stability derivatives using a computational fluid dynamics (CFD)-based force oscillation method. A transient Reynolds-averaged Navier–Stokes solver is utilized to compute the time history of aerodynamic moments for an aircraft model oscillating about its center of gravity. The NASA Common Research Model serves as the reference geometry for this investigation, which explores the impact of pitching, rolling, and yawing oscillations on aerodynamic performance. Periodic oscillatory motions are imposed while using a dynamic mesh technique for CFD analysis. Preliminary steady-state simulations are conducted to validate the computational approach, ensuring the reliability and accuracy of the applied CFD model for transonic flow. The primary goal of this research is to confirm the efficacy of CFD in accurately predicting stability derivative values, underscoring its advantages over traditional wind tunnel experiments at high angles of attack. The study highlights the accuracy of CFD predictions and provides detailed insights into how different oscillations affect aerodynamic performance. This approach showcases the potential for significant cost and time savings in the estimation of dynamic stability derivatives. Full article

In this work, we introduce an innovative analytical–numerical approach to solving nonlinear fractional differential equations by integrating the homotopy perturbation method with the new integral transform. The Kawahara equation and its modified form, which is significant in fluid dynamics and wave propagation, serve as test cases for the proposed methodology. Additionally, we apply the fractional new integral transform–homotopy perturbation method (FNIT-HPM) to a nonlinear system of coupled Burgers’ equations, further demonstrating its versatility. All calculations and simulations are performed using Mathematica 12 software, ensuring precision and efficiency in computations. The FNIT-HPM framework effectively transforms complex fractional differential equations into more manageable forms, enabling rapid convergence and high accuracy without linearization or discretization. By evaluating multiple case studies, we demonstrate the efficiency and adaptability of this approach in handling nonlinear systems. The results highlight the superior accuracy of the FNIT-HPM compared to traditional methods, making it a powerful tool for addressing complex mathematical models in engineering and physics. Full article

The special eddy field of mesoscale vortices plays an important role in the global shipping process. The statistical morphology of mesoscale vortices observed via global satellites and the numerical simulation of the ocean are applied to the simulation of computational fluid dynamics, which can more truly reflect the influence of mesoscale vortices on the motion characteristics of underwater vehicles. In this paper, the ALE (Arbitrary Lagrangian–Eulerian) finite element method is used to simulate the random vortex of a submarine in three dimensions (horizontal x, vertical z, height y) and establish quantitative submarine movement characteristics. Our results show that with an increase in mesoscale vortex strength, the effects on the submarine’s speed and displacement increase, but the overall effect is still limited. In the 300 m transmission simulation, the velocity effect is within ±2 m/s, and the displacement effect is within 4 m. The simulation results can be applied to the route optimization algorithm of underwater vehicle automatic navigation and provide a reference for energy consumption calculations and route safety evaluations. Full article

Accurate prediction of extreme atmospheric conditions is essential for various scientific and engineering applications, ranging from environmental monitoring to space weather forecasting and urban climate resilience. This study introduces an empirical approach to predict maximum atmospheric pressure and temperature using an empirical model based on statistical parameters. The model incorporates key inputs such as the mean value, standard deviation, integral time scale, and a variability factor, denoted as b, to capture application-specific uncertainties. The methodology is applied to two distinct atmospheric scenarios: (i) forecasting maximum atmospheric pressure using data from 29 global monitoring stations, and (ii) predicting maximum temperature around isolated structures within unstable boundary layers, leveraging insights from Large Eddy Simulation (LES) data. The results indicate that the model performs robustly across diverse conditions, with the b parameter exhibiting a wide range of values depending on the specific atmospheric setting. The comparison between model predictions and observed data demonstrates excellent agreement, validating the model’s applicability in extreme value prediction. These findings reinforce the empirical model’s potential for integration into computational fluid dynamics (CFD) simulations, enhancing the predictive capabilities of Reynolds-Averaged Navier-Stokes (RANS) methodologies. Furthermore, the model’s ability to generalize across different atmospheric processes highlights its significance in advancing our understanding of meteorological extremes. Full article

The accurate, robust, and efficient prediction of transition in viscous flows is a significant challenge in computational fluid dynamics. We present a coupled high-fidelity iterative approach that leverages the FUN3D flow solver and the LASTRAC stability code to predict transition in low-disturbance environments, initiated by the linear growth of boundary-layer instability modes. Our method integrates the ability of FUN3D to compute mixed laminar–transitional–turbulent mean flows via transition-sensitized Reynolds-Averaged Navier–Stokes equations with the ability of LASTRAC to perform linear stability analysis, all within an automated framework that requires no intermediate user involvement. Unlike conventional frameworks that rely on classical stability theory or reduced-order metamodels, our approach employs parabolized stability equations to provide more accurate and reliable estimates of disturbance growth for multiple instability mechanisms, including Tollmien–Schlichting, Kelvin–Helmholtz, and crossflow modes. By accounting for the effects of mean-flow nonparallelism as well as the surface curvature, this approach lays the foundation for improved N-factor correlations for transition onset prediction in a broad class of flows. We apply this method to three distinct flow configurations: (1) flow over a zero-pressure-gradient flat plate, (2) the NLF-0416 airfoil with both natural and separation-induced transition, and (3) a 6:1 prolate spheroid, where transition is primarily driven by crossflow instability. For two-dimensional cases, a formulated intermittency distribution is used to model the transition zone between the laminar and fully turbulent flows. The results include comparisons with experimental measurements, similar numerical approaches, and transport-equation-based models, demonstrating good agreement in surface pressure coefficients, transition onset locations, and skin-friction coefficients for all three configurations. In addition to contributing a couple of new insights into boundary-layer transition in these canonical cases, this study presents a powerful tool for transition modeling in both research and design applications in aerodynamics. Full article

The investigation of the wake field and nominal wake fraction in shallow water is critical for understanding ship hydrodynamics in confined environments. While extensive research has been conducted on deep water wake behavior, limited studies have addressed the effects of shallow water and scale on wake characteristics. This study systematically examines the influence of water depth and scale on wake field and nominal wake fraction through a combined approach of experimental model testing and computational fluid dynamics (CFD) simulations. A series of towing tank experiments were conducted in shallow water conditions using the Aframax hull form, and the results were validated by numerical simulations performed with the CFD solver STAR-CCM+. The findings highlight a significant impact on wake fraction due to scale effects, revealing nonlinear trends across different Reynolds numbers. Based on these observations, a predictive equation for nominal wake fraction in shallow water is proposed. The applicability of the equation was assessed by applying it to the KVLCC2 benchmark hull form, demonstrating its potential for use with other similar hull forms. These findings enhance the understanding of wake field dynamics in confined waters, enabling more precise ship design, improved performance predictions, and greater overall efficiency. Full article

For computational fluid dynamic (CFD) modeling of advanced combustion engines, the cylinder is usually considered a closed system in which the initial conditions are estimated based on the experimental data. Most of these approximations hinder observing the effect of design parameters on engine performance and emissions accurately, and most studies are limited to a few design parameters. An approach is proposed based on the combination of a 1D gas dynamic and a 3D CFD model to simulate the whole engine with as few simplifications as possible. The impact of changing the in-cylinder initial conditions, injection strategy (dual direct injection or multiple pulse injections), and piston bowl geometry on a reactivity controlled compression ignition (RCCI) engine’s performance, emissions, and fuel stratification levels was investigated. It was found that applying the dual direct injection (DDI) strategy to the engine can be promising to reach higher load operations by reducing the pressure rise rate and causing stronger stratification levels. Increasing the number of injection pulses leads to lower Soot/NOx emissions. The best reduction in the pressure rise rate was found by the dual direct strategy (38.36% compared to the base experimental case) and higher exhaust gas recirculation (EGR) levels (41.83% reduction in comparison with the base experimental case). With the help of a novel piston bowl design, HC and CO emissions were reduced significantly. This resulted in a reduction of 54.58% in HC emissions and 80.22% in CO emissions. Full article

This work investigates the stirring effect on p-Acetamidobenzoic Acid (p -AABA) crystal morphology through single crystal cultivation, crystal face growth rate, and nucleation supersaturation measurements, molecular simulation (MS), and computational fluid dynamics (CFD). Results show that stirring rate influences nucleation supersaturation, boundary layer thickness on the {101} and {010} faces, and shear stress applied on these two faces. This leads to changes in nucleation rate, nucleus size, and relative growth rates between the {101} and {010} faces, thus affecting crystal morphology. Under low-rate stirring (150 rpm), crystals exhibit a small size, a low aspect ratio, and a clear aggregation phenomenon. Appropriately increasing stirring rate can prevent aggregation and improve particle size and crystal aspect ratio. High-rate stirring leads to a higher shear stress at the corner points of the {101} face, causing crystal fragmentation, which leads to a significant decrease in crystal size and a slow decrease in aspect ratio. Moreover, the growth rates of the {101} and {010} faces exhibit an exponential dependence on supersaturation. The {101} face grows faster than the {010} face, and this growth rate difference widens with the increasing supersaturation. This study provides a theoretical basis and practical guidance for optimizing crystal morphology in stirred solution crystallization. Full article

Densely populated urban areas often experience poor air quality due to high levels of anthropogenic emissions. The population is frequently exposed to harmful gaseous and particulate pollutants, which are directly linked to various health issues, including respiratory diseases. Accurately assessing and predicting pollutant concentrations within urban areas is therefore crucial. This study developed a computational fluid dynamic (CFD) model designed to capture turbulence effects that influence pollutant dispersion in urban environments. The focus was on key pollutants commonly associated with vehicular emissions, such as carbon monoxide (CO), nitrogen oxides (NO_x), volatile organic compounds (VOCs), and particulate matter (PM). The model was applied to the city of Augsburg, Germany, to simulate pollutant behavior at a microscale level. The primary objectives were twofold: first, to accurately predict local pollutant concentrations and validate these predictions against measurement data; second, to evaluate the representativeness of air quality monitoring stations in reflecting the broader pollutant distribution in their vicinity. The approach presented here has demonstrated that when focusing on an area within a specific radius of an air quality station, the representativeness ranges between 10% and 16%. On the other hand, when assessing the representativeness across the street of deployment, the spatial coverage of the sensor ranges between 23% and 80%. This analysis highlights that air quality stations primarily capture pollution levels from high-activity areas directly across their deployment site, rather than reflecting conditions in nearby lower-activity zones. This approach ensures a more comprehensive understanding of urban air pollution dynamics and assesses the reliability of air quality (AQ) monitoring stations. Full article