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Novel Advances in Fluid Mechanics

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

Deadline for manuscript submissions: 30 July 2026 | Viewed by 2614

Special Issue Editor


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Guest Editor
Fluid Mechanics Department, Universitat Politècnica de Catalunya, 08034 Barcelona, Spain
Interests: active flow control; aerodynamics; compressible flow; fluid mechanics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue welcomes the submission of articles that present recent advances in the field of Fluid Mechanics. This Special Issue will address subsonic and supersonic flows, optimization methodologies, boundary layer evolution and the application of time-dependent aerodynamic forces and active and passive flow control  in order to delay/promote boundary layer separation while decreasing the peak to peak amplitude of dynamic forces. Both experimental work and computational simulations are within the scope of this Special Issue, as well as articles that consider optimization and machine learning techniques as these minimize the number of computational simulations while gathering the most appropriate set of parameters in any given application. Finally, papers that consider the application of flow control technology in order to enhance heat transfer or reduce cavitation in water turbines, for example, will be included in this Special Issue.

Researchers are encouraged to submit high-quality and novel papers that will be published after being peer reviewed by specialists in the field.

Dr. Josep Maria Bergadà
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 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

  • supersonic flow
  • boundary layer
  • active flow control
  • aerodynamics
  • optimization
  • machine learning
  • heat transfer
  • cavitation

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Published Papers (2 papers)

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Research

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29 pages, 8940 KB  
Article
Feature Extraction from Flow Fields: Physics-Based Clustering and Morphing with Applications
by Riccardo Margheritti, Onofrio Semeraro, Maurizio Quadrio and Giacomo Boracchi
Appl. Sci. 2025, 15(23), 12421; https://doi.org/10.3390/app152312421 - 23 Nov 2025
Viewed by 978
Abstract
The high dimensionality of flow fields obtained from Computational Fluid Dynamics (CFD) poses major challenges for Machine Learning (ML), especially when the scarcity of training data combines with strong geometric variability. Most existing ML approaches for inference from CFD data rely on expert-defined [...] Read more.
The high dimensionality of flow fields obtained from Computational Fluid Dynamics (CFD) poses major challenges for Machine Learning (ML), especially when the scarcity of training data combines with strong geometric variability. Most existing ML approaches for inference from CFD data rely on expert-defined features, primarily quantities computed over manually selected regions. However, this strategy does not scale well, since regions must be redefined for each new geometry, requiring expert knowledge and significant effort. To overcome this limitation, we introduce two complementary methods to extract features from CFD flow fields: the first identifies meaningful flow regions by clustering features derived from the governing equations; the second employs mesh morphing to align each flow field onto a common reference geometry, enabling consistent use of expert-defined regions across cases. Both require minimal human intervention on new samples and ensure scalability across diverse CFD scenarios. We validate our methods on two distinct applications: first, by accurately identifying airfoil shapes and geometric defects; second, by classifying nasal pathologies from 3D CFD simulations of human upper airways reconstructed from CT scans. Both methods show robustness and high accuracy, highlighting their potential for automated, generalizable, and scalable CFD analysis within ML frameworks. Full article
(This article belongs to the Special Issue Novel Advances in Fluid Mechanics)
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Review

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60 pages, 4918 KB  
Review
DBD Plasma Actuators for Aerodynamic Flow Control: A Review
by Mohammad Saemian, Miguel Cota, Lena Sabidussi, Zeinab Rida, Ahmad Nabhani and Josep M. Bergada
Appl. Sci. 2026, 16(4), 1888; https://doi.org/10.3390/app16041888 - 13 Feb 2026
Viewed by 1280
Abstract
Dielectric barrier discharge (DBD) plasma actuators (PAs) are devices used to control airflow. DBD actuators generate an electric field that accelerates ionized air particles, inducing localized flow modifications. Among other applications, they are particularly effective for enhancing cooling, for aerodynamic drag reduction, and [...] Read more.
Dielectric barrier discharge (DBD) plasma actuators (PAs) are devices used to control airflow. DBD actuators generate an electric field that accelerates ionized air particles, inducing localized flow modifications. Among other applications, they are particularly effective for enhancing cooling, for aerodynamic drag reduction, and for lift enhancement, therefore capable of improving stall characteristics. In addition, they offer several distinct advantages, such as rapid response time, low power consumption, and no moving parts. The present review paper aims to summarize the main governing equations associated with the most common phenomenological PA Computational Fluid Dynamics (CFD) models, Shyy and Suzen-Huang, as well as highlight the major applications to flat plates, wind turbine airfoils and entire wind turbines. The application of DBD plasma actuators on individual wind turbine blades, as well as dynamic horizontal and vertical axis wind turbines, is reviewed, drawing from key numerical and experimental investigations. The simulated performance of various configurations of single and multiple PAs on representative airfoils at different chordwise locations is discussed. The overall findings indicate that the chordwise location of the actuators on airfoils and their optimum spanwise placement on small and large wind turbine blades, along with the geometry and excitation parameters of the actuators, play a crucial role in their performance, affecting the boundary layer and the flow pattern. The reader shall obtain an overall idea of the most recent aerodynamic applications of PAs as well as their expected efficiency. Full article
(This article belongs to the Special Issue Novel Advances in Fluid Mechanics)
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