Advances in Computational and Experimental 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: closed (30 November 2025) | Viewed by 1634
Special Issue Editors
Interests: turbulent flow; computational fluid dynamics; machine learning; experiment; energy
2. Juelich Supercomputing Centre, Jülich, Germany
Interests: computational fluid dynamics; high-performance computing; deep learning; big data
Special Issue Information
Dear Colleagues,
Fluid dynamics research is fundamentally rooted in three key approaches: experimental investigation, analytical modeling, and numerical simulation. In recent years, the rise of artificial intelligence (AI) has introduced powerful new methodologies—both data-driven and physics-informed—that are rapidly transforming the field. These techniques offer valuable tools for uncovering complex flow behaviors, optimizing designs, and enhancing predictive capabilities.
This Special Issue invites researchers from both academia and industry to submit original contributions that advance our understanding and application of computational fluid dynamics (CFD), experimental methods, and AI-based modeling in fluid dynamics. Submissions may explore a wide range of topics, including simulations of compressible and incompressible flows, experimental studies that provide new insights into fluid behavior, and the application of CFD to energy-related systems such as wind, hydrogen, solar, and hydropower.
We are also interested in contributions that address multiphase flows through combined CFD and experimental approaches, and in studies utilizing the Lattice Boltzmann Method (LBM), particularly in scenarios where traditional CFD methods encounter limitations. We are interested in publishing research on CFD; experiments involving turbomachines (pump, turbine, compressor); research on turbulent flows, whether through detailed experiments or high-fidelity simulations; and reduced-order modeling techniques such as proper orthogonal decomposition.
Advances in high-performance computing (HPC) have significantly expanded the capabilities of CFD, allowing for more complex and higher-dimensional simulations. We welcome studies that leverage these computational resources, as well as those investigating particle-laden turbulent flows, flow control strategies, and predictive modeling techniques. Of particular interest are the applications of machine learning and deep learning in fluid dynamics, which use large datasets from experiments and simulations to improve our understanding and accelerate innovation.
Additional topics may include the use of CFD in addressing climate change and meteorological phenomena, as well as its role in oceanographic studies. We are also open to submissions that apply continuum mechanics approaches to better analyze and interpret turbulent flow behavior. Overall, this Issue seeks to highlight innovative, interdisciplinary research that pushes the boundaries of fluid dynamics and offers meaningful contributions to both theoretical knowledge and real-world applications.
Dr. Reza Hassanian
Prof. Dr. Morris Riedel
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. Applied Sciences 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 2400 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
- CFD
- experiment
- turbulent
- machine learning
- deep learning
- Lattice Boltzmann
- energy
- AI-based model
- simulation
- prediction model
- compressible
- incompressible
- fluid dynamics
- high-performance computing
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