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Fluid Dynamics Challenges in Energy Systems: High-Efficiency Design and Control

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "J2: Thermodynamics".

Deadline for manuscript submissions: 25 September 2026 | Viewed by 1165

Special Issue Editors


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Guest Editor
CORIA, UMR 6614, CNRS, Normandy University, UNIROUEN, 76000 Rouen, France
Interests: mechanics of fluids and complex materials; heat and mass transfer; numerical analysis; numerical modeling; topology optimization; fluid/structure interaction
Special Issues, Collections and Topics in MDPI journals
ULR 4515—LGCgE, Laboratoire de Génie Civil et géo-Environnement, University of Lille, Institut Mines-Télécom, Artois University, Junia, F-59000 Lille, France
Interests: CFD; fluid-structure interaction; thermal engineering; heat recovery; optimization; energy efficiency; renewable energy

Special Issue Information

Dear Colleagues,

Fluid dynamics is a game changer when it comes to the control, design and optimization of energy systems. This Special Issue welcomes theoretical, computational and experimental review articles and research papers that focus on fluid dynamics and design, control and optimization of different energy systems and components. Research papers with applications to multi-physics and multi-scale thermofluid problems, such as within multifunctional heat exchangers and reactors, hybrid-renewable thermofluid and energy systems, and control, design and optimization are all welcome. Papers covering different industrial energy systems and applications where coupled fluid and energy flows take place are also welcome (renewable energy, solar energy, geothermal energy, on-shore and off-shore wind energy). Papers addressing the role of artificial intelligence (AI) and machine learning (ML) in the control, prediction and optimization of energy and thermofluid flow systems are also welcome. Research focusing on advanced optimization methods and algorithms within CFD (computational fluid dynamics) using finite volumes (FVM), finite elements (FEM) and lattice Boltzmann (LBM) methods within adjoint, shape and topology optimization techniques to solve complex energy and thermofluid problems are also welcome.

Prof. Dr. Talib Dbouk
Dr. Samer Ali
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 250 words) can be sent to the Editorial Office for assessment.

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

  • energy systems
  • fluid flow
  • heat transfer
  • control and design
  • optimization
  • CFD
  • experimental measurements
  • FEM
  • FVM
  • LBM
  • AI
  • ML

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Published Papers (1 paper)

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Review

30 pages, 1509 KB  
Review
A Review on Theoretical and Computational Fluid Dynamics Modeling of Coupled Heat and Mass Transfer in Fixed Beds of Adsorbing Porous Media
by Mohamad Najib Nadamani, Mostafa Safdari Shadloo and Talib Dbouk
Energies 2025, 18(24), 6418; https://doi.org/10.3390/en18246418 - 8 Dec 2025
Cited by 3 | Viewed by 870
Abstract
Heat exchangers–adsorbers (HEX-As) are emerging as innovative technologies in many applications (CO2 capture, gas purification and separation, thermal energy storage, etc). This review addresses the theoretical challenges within computational fluid dynamics (CFD) in modeling and simulating coupled heat and mass transfer within [...] Read more.
Heat exchangers–adsorbers (HEX-As) are emerging as innovative technologies in many applications (CO2 capture, gas purification and separation, thermal energy storage, etc). This review addresses the theoretical challenges within computational fluid dynamics (CFD) in modeling and simulating coupled heat and mass transfer within gas separation by using adsorbing porous media in fixed beds. Conservation equations of mass, momentum, and energy from different studies (1D, 2D-CFD, and 3D-CFD models) are presented and discussed with an emphasis on their ability to predict the complex multi-physics multi-scale heat and mass transfer phenomena involved, such as the adsorption kinematics, the thermal front propagation, and the multi-component fluid flow dynamics inside the beds. For the fist time, we show that mathematical theoretical modeling in CFD has been differently developed and applied by many authors in the literature in order to model the same physical phenomena. This sheds light on the present challenges and bottlenecks in theoretical and computational fluid dynamics when it comes to complex coupled heat and mass transfer in multi-component gas dynamics in porous media. This review make it easier for readers to understand the different models that exist in the literature for modeling and simulating HEX-As. It also opens questions on how accurately one can model multi-functional heat exchangers–adsorbers using CFD, e.g., physics multi-scale extrapolation from nano- to meso- and then to macro-scale behavior. Full article
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