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Mathematics
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Advances in Computational Fluid Dynamics
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Advances in Computational Fluid Dynamics

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Dynamical Systems".

Deadline for manuscript submissions: closed (15 April 2024) | Viewed by 7203

Special Issue Editor

Dr. Yufei Zhang

E-Mail Website
Guest Editor
School of Aerospace Engineering, Tsinghua University, Beijing 100084, China
Interests: aerodynamics; optimization; turbulence simulation

Special Issue Information

Dear Colleagues,

In this Special Issue, we invite papers with significant advances in computational fluid dynamics. Additionally, computational theories, techniques, and applications are welcomed. The topics of this Special Issue include, but are not limited to:

  • Numerical scheme (including time advancing, spatial scheme, high-order scheme, etc.);
  • Turbulence simulation (including RANS, LES, DNS, hybrid method);
  • Aerodynamic optimization (including optimization based on steady or unsteady CFD, evolutionary algorithm or adjoint method, etc.);
  • Grid technique (including structured or unstructured grid technique, automatic grid generation, grid adaption, etc.);
  • Computational aeroacoustics (including aeroacoustics of direct method, hybrid method, etc.);
  • Artificial intelligence in CFD (artificial intelligence technique used for turbulence modeling, grid generation, flow control, etc.);
  • Parallel computation (including parallel computation based on CPU/GPU, etc.);

Industrial application of CFD (including aerospace engineering, vehicle engineering, etc.).

Dr. Yufei Zhang
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (5 papers)

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Research

14 pages, 8958 KiB  
Article
Nonlinear Phenomena of Fluid Flow in a Bioinspired Two-Dimensional Geometric Symmetric Channel with Sudden Expansion and Contraction
by Liquan Yang, Mo Yang and Weijia Huang
Mathematics 2024, 12(4), 553; https://doi.org/10.3390/math12040553 - 12 Feb 2024
Viewed by 597
Abstract
Inspired by the airway for phonation, fluid flow in an idealized model within a sudden expansion and contraction channel with a geometrically symmetric structure is investigated, and the nonlinear behaviors of the flow therein are explored via numerical simulations. Numerical simulation results show [...] Read more.
Inspired by the airway for phonation, fluid flow in an idealized model within a sudden expansion and contraction channel with a geometrically symmetric structure is investigated, and the nonlinear behaviors of the flow therein are explored via numerical simulations. Numerical simulation results show that, as the Reynolds number (Re = U0H/ν) increases, the numerical solution undergoes a pitchfork bifurcation, an inverse pitchfork bifurcation and a Hopf bifurcation. There are symmetric solutions, asymmetric solutions and oscillatory solutions for flows. When the sudden expansion ratio (Er) = 6.00, aspect ratio (Ar) = 1.78 and Re ≤ Rec1 (≈185), the numerical solution is unique, symmetric and stable. When Rec1 < Re ≤ Rec2 (≈213), two stable asymmetric solutions and one symmetric unstable solution are reached. When Rec2 < Re ≤ Rec3 (≈355), the number of numerical solution returns one, which is stable and symmetric. When Re > Rec3, the numerical solution is oscillatory. With increasing Re, the numerical solution develops from periodic and multiple periodic solutions to chaos. The critical Reynolds numbers (Rec1, Rec2 and Rec3) and the maximum return velocity, at which reflux occurs in the channel, change significantly under conditions with different geometry. In this paper, the variation rules of Rec1, Rec2 and Rec3 are investigated, as well as the maximum return velocity with the sudden expansion ratio Er and the aspect ratio Ar. Full article
(This article belongs to the Special Issue Advances in Computational Fluid Dynamics)
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23 pages, 11272 KiB  
Article
Physics-Informed Neural Networks with Periodic Activation Functions for Solute Transport in Heterogeneous Porous Media
by Salah A. Faroughi, Ramin Soltanmohammadi, Pingki Datta, Seyed Kourosh Mahjour and Shirko Faroughi
Mathematics 2024, 12(1), 63; https://doi.org/10.3390/math12010063 - 24 Dec 2023
Cited by 4 | Viewed by 1222
Abstract
Simulating solute transport in heterogeneous porous media poses computational challenges due to the high-resolution meshing required for traditional solvers. To overcome these challenges, this study explores a mesh-free method based on deep learning to accelerate solute transport simulation. We employ Physics-informed Neural Networks [...] Read more.
Simulating solute transport in heterogeneous porous media poses computational challenges due to the high-resolution meshing required for traditional solvers. To overcome these challenges, this study explores a mesh-free method based on deep learning to accelerate solute transport simulation. We employ Physics-informed Neural Networks (PiNN) with a periodic activation function to solve solute transport problems in both homogeneous and heterogeneous porous media governed by the advection-dispersion equation. Unlike traditional neural networks that rely on large training datasets, PiNNs use strong-form mathematical models to constrain the network in the training phase and simultaneously solve for multiple dependent or independent field variables, such as pressure and solute concentration fields. To demonstrate the effectiveness of using PiNNs with a periodic activation function to resolve solute transport in porous media, we construct PiNNs using two activation functions, sin and tanh, for seven case studies, including 1D and 2D scenarios. The accuracy of the PiNNs’ predictions is then evaluated using absolute point error and mean square error metrics and compared to the ground truth solutions obtained analytically or numerically. Our results demonstrate that the PiNN with sin activation function, compared to tanh activation function, is up to two orders of magnitude more accurate and up to two times faster to train, especially in heterogeneous porous media. Moreover, PiNN’s simultaneous predictions of pressure and concentration fields can reduce computational expenses in terms of inference time by three orders of magnitude compared to FEM simulations for two-dimensional cases. Full article
(This article belongs to the Special Issue Advances in Computational Fluid Dynamics)
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18 pages, 7139 KiB  
Article
Heat Transfer Enhancement of MHD Natural Convection in a Star-Shaped Enclosure, Using Heated Baffle and MWCNT–Water Nanofluid
by Sardar Bilal, Imtiaz Ali Shah, Kaouther Ghachem, Abdelkarim Aydi and Lioua Kolsi
Mathematics 2023, 11(8), 1849; https://doi.org/10.3390/math11081849 - 13 Apr 2023
Cited by 6 | Viewed by 1262
Abstract
Fluids have played and still play a vital role in attaining an optimized output from industrial processes. However, due to technological advancement, fluids with high hydrothermal characteristics are required. In order to overcome these challenges, researchers have developed fluids with dispersed nanoparticles, which [...] Read more.
Fluids have played and still play a vital role in attaining an optimized output from industrial processes. However, due to technological advancement, fluids with high hydrothermal characteristics are required. In order to overcome these challenges, researchers have developed fluids with dispersed nanoparticles, which are recognized as nanofluids. Various types of nanoparticles can be added to base fluids to produce thermally enhanced liquids. Among these, the addition of multi-walled carbon nanotubes (MWCNTs) is considered the best due to the considerable enhancement of thermophysical properties and the stability of the solution. Thus, in the present investigation, an analysis of the heat transfer characteristics of an MWCNT–water nanofluid included in a star-shaped cavity equipped with a hot rectangular baffle is conducted. In addition, a uniform magnetic field is applied along the x-direction to oppose the convective flow generated by variations in density. Mathematical formulations under assumed boundary conditions and physical assumptions are established in the form of dimensionless PDEs. The finite-element-method-based software “COMSOL” is used to execute the numerical simulations. PARADISO is employed to resolve the developed non-linear system of equations. The effects of the governing parameters on the velocity and temperature fields are presented through streamlines and isotherms. The Nusselt number is evaluated to depict the impact of the addition of nanoparticles (MWCNTs) on the heat transfer enhancement. Changes in the horizontal and vertical components of velocity are also evaluated against the Rayleigh number and nanoparticle volume fraction via cutline representation. Full article
(This article belongs to the Special Issue Advances in Computational Fluid Dynamics)
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19 pages, 4381 KiB  
Article
Numerical Investigation of the Double Diffusive Convection in 3D Trapezoidal Solar Still Equipped with Conductive Fins
by Lioua Kolsi, Kaouther Ghachem, Samia Larguech and Ghada AlNemer
Mathematics 2022, 10(12), 2115; https://doi.org/10.3390/math10122115 - 17 Jun 2022
Cited by 2 | Viewed by 1079
Abstract
In this paper a numerical investigation on the double diffusive natural convection in a finned solar still is performed using the finite volume method. The 3D vector potential-vorticity formalism is used to eliminate the gradient pressure terms and due to the complex shape [...] Read more.
In this paper a numerical investigation on the double diffusive natural convection in a finned solar still is performed using the finite volume method. The 3D vector potential-vorticity formalism is used to eliminate the gradient pressure terms and due to the complex shape of the cavity the blocked-off-region method is adopted. After getting the dimensionless governing equations, they are written in a generalised form then discretised. The effects of the buoyancy ratio, conductivity ratio and Rayleigh number of the flow structure, temperature field and heat and mass transfer are studied. The results show that the increase of conductivity ratio and Rayleigh number leads to an enhancement of the heat and mass transfer. Full article
(This article belongs to the Special Issue Advances in Computational Fluid Dynamics)
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24 pages, 12786 KiB  
Article
Prediction of Airfoil Stall Based on a Modified k−v2¯−ω Turbulence Model
by Chenyu Wu, Haoran Li, Yufei Zhang and Haixin Chen
Mathematics 2022, 10(2), 272; https://doi.org/10.3390/math10020272 - 16 Jan 2022
Viewed by 2101
Abstract
The accuracy of an airfoil stall prediction heavily depends on the computation of the separated shear layer. Capturing the strong non-equilibrium turbulence in the shear layer is crucial for the accuracy of a stall prediction. In this paper, different Reynolds-averaged Navier–Stokes turbulence models [...] Read more.
The accuracy of an airfoil stall prediction heavily depends on the computation of the separated shear layer. Capturing the strong non-equilibrium turbulence in the shear layer is crucial for the accuracy of a stall prediction. In this paper, different Reynolds-averaged Navier–Stokes turbulence models are adopted and compared for airfoil stall prediction. The results show that the separated shear layer fixed k−v2¯−ω (abbreviated as SPF k−v2¯−ω) turbulence model captures the non-equilibrium turbulence in the separated shear layer well and gives satisfactory predictions of both thin-airfoil stall and trailing-edge stall. At small Reynolds numbers (Re~105), the relative error between the predicted CL,max of NACA64A010 by the SPF k−v2¯−ω model and the experimental data is less than 3.5%. At high Reynolds numbers (Re~106), the CL,max of NACA64A010 and NACA64A006 predicted by the SPF k−v2¯−ω model also has an error of less than 5.5% relative to the experimental data. The stall of the NACA0012 airfoil, which features trailing-edge stall, is also computed by the SPF k−v2¯−ω model. The SPF k−v2¯−ω model is also applied to a NACA0012 airfoil, which features trailing-edge stall and an error of CL relative to the experiment at CL>1.0 is smaller than 3.5%. The SPF k−v2¯−ω model shows higher accuracy than other turbulence models. Full article
(This article belongs to the Special Issue Advances in Computational Fluid Dynamics)
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