Recent Advances in Engineering Applications of Computational Fluid Dynamics

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Fluid Science and Technology".

Deadline for manuscript submissions: 20 December 2024 | Viewed by 4434

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Guest Editor
Department of Engineering Mechanics, Zhejiang University, Hangzhou 310027, China
Interests: fictitious domain methods; numerical methods; particle-laden flows; turbulent flows; fluid–structure interaction
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Special Issue Information

Dear Colleagues,

Computational fluid dynamics (CFD) is an approach to solve fluid mechanics problems using computer simulations, and has been widely used in engineering applications in various fields of aeronautic, civil, environmental, hydraulic, chemical and mechanical engineering.

This Special Issue welcomes the original high-quality works on engineering applications of CFD. The works on novel numerical methods or models, such as machine-learning aided CFD, high fidelity CFD, turbulence and multiphase flow models are also welcome.

Prof. Dr. Zhaosheng Yu
Guest Editor

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Keywords

  • computational fluid dynamics
  • numerical simulations
  • numerical computations
  • engineering application
  • fluid mechanics

Published Papers (5 papers)

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Research

20 pages, 12863 KiB  
Article
A Novel Cell-Based Adaptive Cartesian Grid Approach for Complex Flow Simulations
by Canyan Luo, Dan Zhou, Shuang Meng, Lin Bi, Wenzheng Wang, Xianxu Yuan and Zhigong Tang
Appl. Sci. 2024, 14(9), 3692; https://doi.org/10.3390/app14093692 - 26 Apr 2024
Viewed by 561
Abstract
As the need for handling complex geometries in computational fluid dynamics (CFD) grows, efficient and accurate mesh generation techniques become paramount. This study presents an adaptive mesh refinement (AMR) technology based on cell-based Cartesian grids, employing a distance-weighted least squares interpolation for finite [...] Read more.
As the need for handling complex geometries in computational fluid dynamics (CFD) grows, efficient and accurate mesh generation techniques become paramount. This study presents an adaptive mesh refinement (AMR) technology based on cell-based Cartesian grids, employing a distance-weighted least squares interpolation for finite difference discretization and utilizing immersed boundary methods for wall boundaries. This facilitates effective management of both transient and steady flow problems. Validation through supersonic flow over a forward-facing step, subsonic flow around a high Reynolds number NHLP airfoil, and supersonic flow past a sphere demonstrated AMR’s efficacy in capturing essential flow characteristics while wisely refining and coarsening meshes, thus optimizing resource utilization without compromising accuracy. Importantly, AMR simplified the capture of complex flows, obviating manual mesh densification and significantly improving the efficiency and reliability of CFD simulations. Full article
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18 pages, 3620 KiB  
Article
Interactive Airfoil Optimization Using Parsec Parametrization and Adjoint Method
by Marek Belda and Tomáš Hyhlík
Appl. Sci. 2024, 14(8), 3495; https://doi.org/10.3390/app14083495 - 21 Apr 2024
Viewed by 701
Abstract
In the development of interactive aerodynamic optimization tools, the need to reduce the computational complexity of flow calculations has arisen. Computational complexity can be reduced by estimating the flow variables using machine learning, but that approach has a number of hindrances. Avoiding these [...] Read more.
In the development of interactive aerodynamic optimization tools, the need to reduce the computational complexity of flow calculations has arisen. Computational complexity can be reduced by estimating the flow variables using machine learning, but that approach has a number of hindrances. Avoiding these hindrances through lowering the computational complexity by stating the assumptions of inviscid incompressible potential flow is the focus of this article. The assumptions used restrict the applicability of this approach to only specific cases, but in engineering practice, these cases are quite widespread. The assumptions allowed the coupling of the adjoint method with parsec parametrization and the panel method, yielding a highly computationally efficient and robust tool for optimizing an airfoil’s lift coefficient (Cy). The optimization of the NREL S809 airfoil was carried out, and the results were verified using the Xfoil 6.99 software. The Xfoil verification showed that by making minimal changes to the airfoil’s shape, the Cy and lift-to-drag ratios were significantly improved. The improvement magnitude was over 94% for a 0 deg angle of attack (AoA) and over 16% for 6.2 deg AoA. This indicates an improvement in performance that is similar to that of some genetic algorithms, but with computational costs that are many orders of magnitude lower. Full article
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16 pages, 12489 KiB  
Article
Computational Fluid Dynamics Simulation Study on Aerodynamic Characteristics under Unfavorable Conditions during Flight Phase in Ski Jumping
by Qi Hu, Weidi Tang and Yu Liu
Appl. Sci. 2024, 14(4), 1390; https://doi.org/10.3390/app14041390 - 8 Feb 2024
Viewed by 686
Abstract
Objective: The stability of the flight phase in ski jumping is crucial for athletes’ performance and safety. This study aims to investigate the influence of unfavorable conditions on aerodynamic characteristics and flight stability through computational fluid dynamics (CFD) numerical simulations. Methods: The ski [...] Read more.
Objective: The stability of the flight phase in ski jumping is crucial for athletes’ performance and safety. This study aims to investigate the influence of unfavorable conditions on aerodynamic characteristics and flight stability through computational fluid dynamics (CFD) numerical simulations. Methods: The ski jumper and the skis are considered a multi-body system. A detailed three-dimensional (3D) model of this multi-body system under a commonly observed posture during flight is established. The Partially Averaged Navier–Stokes (PANS) turbulence model is employed, and CFD simulations are conducted to predict the aerodynamic characteristics of the multi-body system under lateral environmental wind and asymmetric postures during the flight phase. The conditions of asymmetric postures include yaw rotation and roll rotation. Results: (1) Lateral environmental wind generated a yaw force, yaw moment, and roll moment, which influenced the lift, drag, and pitch moment of the athlete. These forces and moments were relatively small at lower wind speeds (less than 3 m/s) and became more significant at higher wind speeds (greater than 4.5 m/s). (2) Under the influence of yaw rotation or roll rotation, the multi-body system exhibited a noticeable yaw force, yaw moment, and roll moment, all showing a monotonic increasing trend. Moreover, they had a significant impact on the lift, drag, and pitch moment of the multi-body system. Conclusion: (1) The influence of unfavorable conditions was complex, resulting in a significant yaw force, yaw moment, and roll moment on the multi-body system. The adverse effects of roll rotation were generally greater than those of yaw rotation. (2) The multi-body system exhibited self-stabilizing tendencies in yaw and roll. This phenomenon can provide a solution to maintain flight stability by employing appropriate yaw or (and) roll rotation angles, effectively compensating for or even eliminating the adverse effects of lateral environmental wind. (3) Understanding the mechanisms of how unfavorable conditions affect aerodynamic characteristics and stability during flight in ski jumping can provide valuable assistance for real-time prediction and decision making during competitions, as well as scientific guidance for training athletes’ stable flight control and techniques for improving their sport performance. Full article
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18 pages, 3801 KiB  
Article
On the Hard Boundary Constraint Method for Fluid Flow Prediction based on the Physics-Informed Neural Network
by Zixu Xiao, Yaping Ju, Zhen Li, Jiawang Zhang and Chuhua Zhang
Appl. Sci. 2024, 14(2), 859; https://doi.org/10.3390/app14020859 - 19 Jan 2024
Viewed by 1038
Abstract
With the rapid development of artificial intelligence technology, the physics-informed neural network (PINN) has gradually emerged as an effective and potential method for solving N-S equations. The treatment of constraints is vital to the PINN prediction accuracy. Compared to soft constraints, hard constraints [...] Read more.
With the rapid development of artificial intelligence technology, the physics-informed neural network (PINN) has gradually emerged as an effective and potential method for solving N-S equations. The treatment of constraints is vital to the PINN prediction accuracy. Compared to soft constraints, hard constraints are advantageous for the avoidance of difficulties in guaranteeing definite conditions and determining penalty coefficients. However, the principles on the formulation of hard constraints of PINN currently remain to be formed, which hinders the application of PINN in engineering fields. In this study, hard-constraint-based PINN models are constructed for Couette flow, plate shear flow and stenotic/aneurysmal flow with curved geometries. Particular efforts have been devoted to assessing the impact of the model parameters of hard constraints, i.e., degree and scaling factor, on the prediction accuracy of PINN at different Reynolds numbers. The results show that the degree is the most important factor that influences the prediction accuracy, followed by the scaling factor. As for the N-S equations, the degree of hard constraints should be at least two, while the scaling factor is recommended to be maintained around 1.0. The outcomes of the present work are of reference value for the development of PINN methods in fluid mechanics. Full article
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25 pages, 10775 KiB  
Article
Hydrostructural Phenomena in a Wastewater Screening Channel with an Ascendable Sub-Screen Using the Arbitrary Lagrangian–Eulerian Approach
by Shehnaz Akhtar, Safi Ahmed Memon, Hyeon-Bae Chae, Du-Whan Choi and Cheol-Woo Park
Appl. Sci. 2024, 14(1), 76; https://doi.org/10.3390/app14010076 - 21 Dec 2023
Viewed by 823
Abstract
Wastewater invariably accumulates soluble and insoluble waste and requires treatment at a wastewater treatment plant (WTP) to become reusable. The preliminary screening of insoluble waste occurs through a wastewater screening mechanism (WSM) before entering the WTP. The present study computationally investigates the impact [...] Read more.
Wastewater invariably accumulates soluble and insoluble waste and requires treatment at a wastewater treatment plant (WTP) to become reusable. The preliminary screening of insoluble waste occurs through a wastewater screening mechanism (WSM) before entering the WTP. The present study computationally investigates the impact of a WSM, comprising a main screen, sliding sub-screen, and rake, on channel flow distribution, deformation, and stresses. Various sub-screen configurations, fully and partially lowered, are examined. The fluid–structure interaction between sewage water and the WSM was solved using the arbitrary Lagrangian–Eulerian approach. Unlike similar studies in the past which have been conducted in 2D, the present study considers the 3D design and thus captures a greater complexity of the WSM assembly. The velocity distribution inside the channel, structural deformation, and von Mises stresses of WSM components were analyzed for a range of inlet velocities at different stages of the screening process. The results reveal that a fully lowered sub-screen with an inactive rake ensures a uniform flow through the WSM, while a partially lowered sub-screen induces persistent flow separation. Structural analysis reveals significant deformation in the upper mid-region of the sub-screen and fluctuating deformations in the rake, accompanied by elevated von Mises stresses. The study serves as a design guideline for manufacturing and operating a WSM, ensuring the prevention of unfavorable stress and deformation in the WSM and the WTP. Full article
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