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Advances in Fluid Mechanics Analysis
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Advances in Fluid Mechanics Analysis

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

Deadline for manuscript submissions: 20 July 2025 | Viewed by 2249

Special Issue Editor

Dr. Valente Hernández-Pérez

E-Mail Website
Guest Editor
Tecnológico Nacional de México, Pachuca de Soto 42080, Mexico
Interests: multiphase flow; computational fluid dynamics; optimization of energy systems

Special Issue Information

Dear Colleagues,

Fluid flow phenomena are ubiquitous, both in nature and in industrial processes. The study of such flows is crucial to addressing the ever-changing challenges and needs of society. Advances in fluid mechanics analysis collectively contribute to a deeper understanding of fluid mechanics phenomena and their practical applications across diverse fields, driving innovation and technological progress. These advances have been pivotal in various fields, from engineering and aerospace to environmental science and medicine. Advances in fluid mechanics analysis continue to drive innovation across a wide range of industries, improving efficiency, safety, and sustainability in engineering and scientific endeavors.

This Special Issue, entitled "Advances in Fluid Mechanics Analysis," is aimed at publishing recent advances in areas related to the scope of this Special Issue. The following include some key areas where advances can be reported on in this Special Issue:

  • Computational fluid dynamics (CFD);
  • Multiphase flow modeling;
  • Turbulence modeling;
  • Non-Newtonian fluid dynamics;
  • Fluid–structure interaction (FSI);
  • High-fidelity experimental techniques;
  • Biofluid mechanics;
  • Microfluidics and nanofluidics;
  • Heat and mass transfer in fluids;
  • Aerospace applications;
  • Environmental and oceanographic flows;
  • Chemical and process engineering;
  • Energy systems and renewable resources.

We invite researchers and practitioners to contribute their latest findings and advancements in these areas to foster the continuous development and application of fluid mechanics in solving contemporary problems.

Dr. Valente Hernández-Pérez
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. 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

  • fluid flow
  • fluid dynamics
  • multiphase flow
  • computational fluid dynamics
  • rheology
  • fluid structure interaction
  • aerospace
  • heat transfer
  • biofluids
  • microfluid
  • nanofluids
  • pipe flow
  • bubble dynamics
  • turbulence

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

21 pages, 5158 KiB  
Article
Influence of Chinstrap Stiffness on Cerebrospinal Fluid Dynamics and Brain Stress in Helmet Impacts
by Jonathan Mayer, Daniel Nasef, Molly Bekbolatova, Hallie Zwibel and Milan Toma
Appl. Sci. 2025, 15(10), 5459; https://doi.org/10.3390/app15105459 - 13 May 2025
Viewed by 235
Abstract
This study explores the influence of chinstrap stiffness in baseball helmets on brain stress distribution during high-velocity impacts through a computational biomechanical model integrating neuroanatomical structures and helmet components. Using a framework that combines finite element analysis and smoothed-particle hydrodynamics, this research evaluates [...] Read more.
This study explores the influence of chinstrap stiffness in baseball helmets on brain stress distribution during high-velocity impacts through a computational biomechanical model integrating neuroanatomical structures and helmet components. Using a framework that combines finite element analysis and smoothed-particle hydrodynamics, this research evaluates fluid–structure interactions between cerebrospinal fluid, brain tissue, and six chinstrap configurations ranging from highly flexible to non-stretchable. The results reveal a critical trade-off: highly flexible straps reduce intracranial stress by dissipating energy through viscoelastic deformation but compromise helmet stability, while non-stretchable designs transmit undampened forces directly to the skull base, amplifying stress in vulnerable neurovascular regions. Intermediate stiffness configurations introduce a hazardous instability regime, where partial decoupling between the helmet and mandible causes lateral sliding of the chin guard, concentrating stresses at bony interfaces. The study identifies a nonlinear relationship between material rigidity and neuroprotection, emphasizing that optimal chinstrap design must balance elasticity to absorb impact energy with sufficient rigidity to maintain alignment and prevent stress redirection. Intermediate stiffness thresholds, despite partial energy absorption, paradoxically heighten risks due to incomplete coupling and dynamic instabilities. These findings challenge conventional helmet design paradigms, advocating for material engineering strategies that prioritize energy dissipation pathways while avoiding detrimental intermediate stiffness ranges. The insights advance concussion mitigation by refining chinstrap performance criteria to address both direct force transmission and instability-mediated injury mechanisms. Full article
(This article belongs to the Special Issue Advances in Fluid Mechanics Analysis)
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15 pages, 5537 KiB  
Article
An Analysis of the Factors Influencing Dual Separation Zones on a Plate
by Jiarui Zou, Xiaoqiang Fan and Bing Xiong
Appl. Sci. 2025, 15(8), 4569; https://doi.org/10.3390/app15084569 - 21 Apr 2025
Viewed by 162
Abstract
The shock wave/boundary layer interaction phenomenon in hypersonic inlets, affected by background waves, may induce the formation of multiple separation zones. Existing theories prove insufficient in explaining the underlying flow mechanisms behind complex phenomena arising from multi-separation zone interactions, which necessitates further investigation. [...] Read more.
The shock wave/boundary layer interaction phenomenon in hypersonic inlets, affected by background waves, may induce the formation of multiple separation zones. Existing theories prove insufficient in explaining the underlying flow mechanisms behind complex phenomena arising from multi-separation zone interactions, which necessitates further investigation. To clarify the governing factors in multi-separation zone interactions, this study developed a simplified dual-separation-zone model derived from inlet flow field characteristics. A series of numerical simulations were conducted under an incoming flow at Mach 3 to systematically analyze the effects of internal contraction ratio, the influencing locations of expansion waves, and incident shock wave intensity on the mergence and re-separation of dual separation zones. The results demonstrate that both the expansion wave impingement position and incident shock intensity significantly influence specific transition points in dual-separation-zone flow states, though they do not fundamentally alter the evolutionary patterns governing the merging/re-separating processes. Furthermore, increasing incident shock intensity leads to the expansion of separation zone scales and prolongation of the dual-separation-zone merging distance. Full article
(This article belongs to the Special Issue Advances in Fluid Mechanics Analysis)
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33 pages, 25375 KiB  
Article
Digital Twin Based on CFD Modelling for Analysis of Two-Phase Flows During Pipeline Filling–Emptying Procedures
by Duban A. Paternina-Verona, Oscar E. Coronado-Hernández, Vicente S. Fuertes-Miquel, Manuel Saba and Helena M. Ramos
Appl. Sci. 2025, 15(5), 2643; https://doi.org/10.3390/app15052643 - 28 Feb 2025
Viewed by 1208
Abstract
Pipeline filling and emptying are critical hydraulic procedures involving transient two-phase air–water interactions, which can cause pressure surges and structural risks. Traditional Digital Twin models rely on one-dimensional (1D) approaches, which cannot capture air–water interactions. This study integrates Computational Fluid Dynamics (CFD) models [...] Read more.
Pipeline filling and emptying are critical hydraulic procedures involving transient two-phase air–water interactions, which can cause pressure surges and structural risks. Traditional Digital Twin models rely on one-dimensional (1D) approaches, which cannot capture air–water interactions. This study integrates Computational Fluid Dynamics (CFD) models into a Digital Twin framework for improved predictive analysis. A CFD-based Digital Twin is developed and validated using real-time pressure measurements, incorporating 2D and 3D CFD models, mesh sensitivity analysis, and calibration procedures. Key contributions include a CFD-driven Digital Twin for real-time monitoring and machine learning (ML) techniques to optimise pressure surges. ML models trained with experimental and CFD data reduce reliance on computationally expensive CFD simulations. Among the 31 algorithms tested, decision trees, efficient linear models, and ensemble classifiers achieved 100% accuracy for filling processes, while k-Nearest Neighbours (KNN) provided 97.2% accuracy for emptying processes. These models effectively predict hazardous pressure peaks and vacuum conditions, confirming their reliability in optimising pipeline operations while significantly reducing computational time. Full article
(This article belongs to the Special Issue Advances in Fluid Mechanics Analysis)
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