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Energies
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Methods and Numerical Applications in Fluid Mechanics
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Methods and Numerical Applications in Fluid Mechanics

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "J: Thermal Management".

Deadline for manuscript submissions: closed (10 October 2021) | Viewed by 24120

Special Issue Editors

Prof. Dr. Eusebio Valero

E-Mail Website
Guest Editor
Applied Mathematics to Aerospace Engineering, Center of Computational Simulation, Universidad Politecnica de Madrid, Madrid, Spain
Interests: computational fluid mechanics; numerical methods for fluid mechanics; high order schemes; discontinuous galerking methods; flow stability; sensitivity analysis and flow control; data assimiliation; feature extraction; large-scale computations
Prof. Dr. Javier de Vicente

E-Mail Website
Guest Editor
Applied Mathematics to Aerospace Engineering, Center of Computational Simulation, Universidad Politecnica de Madrid, Madrid, Spain
Interests: computational fluid mechanics; numerical methods for fluid mechanics; high order schemes; discontinuous galerking methods; flow stability; sensitivity analysis and flow control; data assimiliation; feature extraction; large-scale computations

Special Issue Information

Dear Colleagues,

This Special Issue aims to cover ongoing advances in numerical and computational methods for fluid mechanics. This broad goal encloses not only the development of standard numerical schemes for the integration of the Navier Stokes equations, but also state-of-the-art Lattice Boltzmann or the difficulties and progress in the application of high-order schemes to more realistic industrial configurations, in particular the implementation of prevailing methods in present and future computational platforms, with an eye on exascale computing.

Moreover, the huge amount of data generated by numerical tools needs further postprocessing: data assimilation methods or data mining, and flow sensitivity, linked to stability and eventually optimization and control, can provide very valuable information about flow. Several algorithms, such as DMD, POD, and SPOD, can obtain very important information that can help to identify relevant features, which is critical to understand the flow behaviour, and eventually can provide information about how to control it.  

Besides those topics, this Issue is open to any contribution that could improve the application of numerical methods to understand and solve fluid dynamics problems.

Prof. Dr. Eusebio Valero
Prof. Dr. Javier de Vicente
Guest Editors

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. Energies 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.

Keywords

  • Computational fluid mechanics.
  • Numerical methods for fluid mechanics.
  • High order schemes.
  • Lattice Boltzmann methods.
  • Discontinuous Galerkin methods.
  • Under-resolved turbulence schemes.
  • Flow stability.
  • Bifurcations.
  • Flow sensitivity of highly unsteady or chaotic flows.
  • Optimization and control of flow configurations.
  • Data assimilation algorithms.
  • Data mining.
  • Feature extraction in fluid mechanics. POD, DMD, SPOD, etc.
  • Efficient implementation of large scale computations.
  • Toward exascale computing.

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Published Papers (7 papers)

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Research

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27 pages, 8254 KiB  
Article
Computational Studies of Air-Mist Spray Cooling in Continuous Casting
by Vitalis Anisiuba, Haibo Ma, Armin Silaen and Chenn Zhou
Energies 2021, 14(21), 7339; https://doi.org/10.3390/en14217339 - 4 Nov 2021
Cited by 5 | Viewed by 4350
Abstract
Due to the significant reduction in water droplet size caused by the strong air-water interaction in the spray nozzle, air-mist spray is one of the promising technologies for achieving high-rate heat transfer. This study numerically analyzed air-mist spray produced by a flat-fan atomizer [...] Read more.
Due to the significant reduction in water droplet size caused by the strong air-water interaction in the spray nozzle, air-mist spray is one of the promising technologies for achieving high-rate heat transfer. This study numerically analyzed air-mist spray produced by a flat-fan atomizer using three-dimensional computational fluid dynamics simulations, and a multivariable linear regression was used to develop a correlation to predict the heat transfer coefficient using the casting operating conditions such as air-pressure, water flow rate, casting speed, and standoff distance. A four-step simulation approach was used to simulate the air-mist spray cooling capturing the turbulence and mixing of the two fluids in the nozzle, droplet formation, droplet transport and impingement heat transfer. Validations were made on the droplet size and on the VOF-DPM model which were in good agreement with experimental results. A 33% increase in air pressure increases the lumped HTC by 3.09 ± 2.07% depending on the other casting parameters while an 85% increase in water flow rate reduces the lumped HTC by 4.61 ± 2.57%. For casting speed, a 6.5% decrease in casting speed results in a 1.78 ± 1.42% increase in the lumped HTC. The results from this study would provide useful information in the continuous casting operations and optimization. Full article
(This article belongs to the Special Issue Methods and Numerical Applications in Fluid Mechanics)
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13 pages, 1017 KiB  
Article
Wavy Walls, a Passive Way to Control the Transition to Turbulence. Detailed Simulation and Physical Explanation
by Andrés Mateo-Gabín, Miguel Chávez, Jesús Garicano-Mena and Eusebio Valero
Energies 2021, 14(13), 3937; https://doi.org/10.3390/en14133937 - 30 Jun 2021
Cited by 4 | Viewed by 2047
Abstract
Inducing spanwise motions in the vicinity of solid boundaries alters the energy, mass and/or momentum transfer. Under some conditions, these motions are such that drag is reduced and/or transition to turbulence is delayed. There are several possibilities to induce those spanwise motions, be [...] Read more.
Inducing spanwise motions in the vicinity of solid boundaries alters the energy, mass and/or momentum transfer. Under some conditions, these motions are such that drag is reduced and/or transition to turbulence is delayed. There are several possibilities to induce those spanwise motions, be it through active imposition a predefined velocity distribution at the walls or by careful design of the wall shape, which corresponds to passive control.In this contribution, we investigate the effect that wavy walls might have on delaying transition to turbulence. Direct Numerical Simulation of both planar and wavy-walled channel flows at laminar and turbulent regimes are conducted. A pseudo laminar regime that remains stable until a Reynolds number 20% higher that the critical is found for the wavy-walled simulations. Dynamic Mode Decomposition applied to the simulation data reveals that in these configurations, modes with wavelength and frequency compatible with the surface undulation pattern appear. We explain and visualize the appearance of these modes. At higher Reynolds numbers we show that these modes remain present but are not dominant anymore. This work is an initial demonstration that flow control strategies that trigger underlying stable modes can keep or conduct the flow to new configurations more stable than the original one. Full article
(This article belongs to the Special Issue Methods and Numerical Applications in Fluid Mechanics)
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17 pages, 1713 KiB  
Article
Analysis of the Magnetohydrodynamic Behavior of the Fully Developed Flow of Conducting Fluid
by Wellington da Silva Fonseca, Ramon C. F. Araújo, Marcelo de Oliveira e Silva and Daniel Onofre de A. Cruz
Energies 2021, 14(9), 2463; https://doi.org/10.3390/en14092463 - 26 Apr 2021
Cited by 9 | Viewed by 2968
Abstract
Important industrial applications are based on magnetohydrodynamics (MHD), which concerns the flow of electrically conducting fluids immersed in external magnetic fields. Using the Finite Volume Method, we performed a 3D numerical study of the MHD flow of a conducting fluid in a circular [...] Read more.
Important industrial applications are based on magnetohydrodynamics (MHD), which concerns the flow of electrically conducting fluids immersed in external magnetic fields. Using the Finite Volume Method, we performed a 3D numerical study of the MHD flow of a conducting fluid in a circular duct. The flow considered was laminar and fully developed. Along the initial section of the duct, there were magnets placed around the duct producing magnetic fields in the radial direction. Two arrangements of magnetic field orientation were considered: fields pointing toward and away from the duct’s center alternately, and all fields pointing toward the duct’s center. For each arrangement of magnets, various intensities of magnetic fields were considered to evaluate two effects: the influence of the magnetic field on the flow velocity, and the influence of the flow velocity on magnetic field induction. It was found that for the second arrangement of magnets and Hartmann numbers larger than 10, the flow velocity was reduced by as much as 35%, and the axial magnetic induction was as high as the field intensity applied by each magnet. Those effects were negligible for the first arrangement and low fields because of the distribution of field lines inside the duct for these situations. Full article
(This article belongs to the Special Issue Methods and Numerical Applications in Fluid Mechanics)
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19 pages, 5748 KiB  
Article
Prediction of Deflagrative Explosions in Variety of Closed Vessels
by Wojciech Rudy, Andrzej Pekalski, Dmitriy Makarov, Andrzej Teodorczyk and Vladimir Molkov
Energies 2021, 14(8), 2138; https://doi.org/10.3390/en14082138 - 11 Apr 2021
Cited by 3 | Viewed by 2025
Abstract
In this paper the multi-phenomena deflagration model is used to simulate deflagrative combustion of several fuel–air mixtures in various scale closed vessels. The experimental transient pressure of methane–air, ethane–air, and propane–air deflagrations in vessels of volume 0.02 m3, 1 m3 [...] Read more.
In this paper the multi-phenomena deflagration model is used to simulate deflagrative combustion of several fuel–air mixtures in various scale closed vessels. The experimental transient pressure of methane–air, ethane–air, and propane–air deflagrations in vessels of volume 0.02 m3, 1 m3, and 6 m3 were simulated. The model includes key mechanisms affecting propagation of premixed flame front: the dependence of laminar burning velocity of concentration, pressure, and temperature; the effect of preferential diffusion in the corrugated flame front or leading point concept; turbulence generated by flame front itself or Karlovitz turbulence; increase of the flame front area with flame radius by fractals; and turbulence in the unburned mixture. Laminar velocity dependence on concentration, pressure, and temperature were calculated using CANTERA software. Various scale and geometry of used vessels induces various combustion mechanism. Simulations allow insight into the dominating mechanism. The model demonstrated an acceptable predictive capability for a variety of fuels and vessel sizes. Full article
(This article belongs to the Special Issue Methods and Numerical Applications in Fluid Mechanics)
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22 pages, 2903 KiB  
Article
Data Mining and Machine Learning Techniques for Aerodynamic Databases: Introduction, Methodology and Potential Benefits
by Esther Andrés-Pérez
Energies 2020, 13(21), 5807; https://doi.org/10.3390/en13215807 - 6 Nov 2020
Cited by 11 | Viewed by 3016
Abstract
Machine learning and data mining techniques are nowadays being used in many business sectors to exploit the data in order to detect trends, discover certain features and patters, or even predict the future. However, in the field of aerodynamics, the application of these [...] Read more.
Machine learning and data mining techniques are nowadays being used in many business sectors to exploit the data in order to detect trends, discover certain features and patters, or even predict the future. However, in the field of aerodynamics, the application of these techniques is still in the initial stages. This paper focuses on exploring the benefits that machine learning and data mining techniques can offer to aerodynamicists in order to extract knowledge from the CFD data and to make quick predictions of aerodynamic coefficients. For this purpose, three aerodynamic databases (NACA0012 airfoil, RAE2822 airfoil and 3D DPW wing) have been used and results show that machine-learning and data-mining techniques have a huge potential also in this field. Full article
(This article belongs to the Special Issue Methods and Numerical Applications in Fluid Mechanics)
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22 pages, 4660 KiB  
Article
Simulations of Aerodynamic Separated Flows Using the Lattice Boltzmann Solver XFlow
by M. Chávez-Modena, J. L. Martínez, J. A. Cabello and E. Ferrer
Energies 2020, 13(19), 5146; https://doi.org/10.3390/en13195146 - 2 Oct 2020
Cited by 27 | Viewed by 4437
Abstract
We present simulations of turbulent detached flows using the commercial lattice Boltzmann solver XFlow (by Dassault Systemes). XFlow’s lattice Boltzmann formulation together with an efficient octree mesh generator reduce substantially the cost of generating complex meshes for industrial flows. In this work, we [...] Read more.
We present simulations of turbulent detached flows using the commercial lattice Boltzmann solver XFlow (by Dassault Systemes). XFlow’s lattice Boltzmann formulation together with an efficient octree mesh generator reduce substantially the cost of generating complex meshes for industrial flows. In this work, we challenge these meshes and quantify the accuracy of the solver for detached turbulent flows. The good performance of XFlow when combined with a Large-Eddy Simulation turbulence model is demonstrated for different industrial benchmarks and validated using experimental data or fine numerical simulations. We select five test cases: the Backward-facing step the Goldschmied Body the HLPW-2 (2nd High-Lift Prediction Workshop) full aircraft geometry, a NACA0012 under dynamic stall conditions and a parametric study of leading edge tubercles to improve stall behavior on a 3D wing. Full article
(This article belongs to the Special Issue Methods and Numerical Applications in Fluid Mechanics)
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Review

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38 pages, 8517 KiB  
Review
On the Experimental, Numerical and Data-Driven Methods to Study Urban Flows
by Pablo Torres, Soledad Le Clainche and Ricardo Vinuesa
Energies 2021, 14(5), 1310; https://doi.org/10.3390/en14051310 - 28 Feb 2021
Cited by 21 | Viewed by 4247
Abstract
Understanding the flow in urban environments is an increasingly relevant problem due to its significant impact on air quality and thermal effects in cities worldwide. In this review we provide an overview of efforts based on experiments and simulations to gain insight into [...] Read more.
Understanding the flow in urban environments is an increasingly relevant problem due to its significant impact on air quality and thermal effects in cities worldwide. In this review we provide an overview of efforts based on experiments and simulations to gain insight into this complex physical phenomenon. We highlight the relevance of coherent structures in urban flows, which are responsible for the pollutant-dispersion and thermal fields in the city. We also suggest a more widespread use of data-driven methods to characterize flow structures as a way to further understand the dynamics of urban flows, with the aim of tackling the important sustainability challenges associated with them. Artificial intelligence and urban flows should be combined into a new research line, where classical data-driven tools and machine-learning algorithms can shed light on the physical mechanisms associated with urban pollution. Full article
(This article belongs to the Special Issue Methods and Numerical Applications in Fluid Mechanics)
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