Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
3.4
1.8
Journals
Fluids
Special Issues
Fluid Dynamics in Biological, Bio-Inspired, and Environmental Systems
share announcement

Fluid Dynamics in Biological, Bio-Inspired, and Environmental Systems

A special issue of Fluids (ISSN 2311-5521).

Deadline for manuscript submissions: closed (30 November 2024) | Viewed by 6570

Special Issue Editors

Prof. Dr. Xing Zhang

E-Mail Website
Guest Editor
The State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, China
Interests: computational fluid dynamics; bio-inspired flow and fluid-structure interactions; turbulence simulation; parallel computing
Special Issues, Collections and Topics in MDPI journals
Dr. Yaqing Jin

E-Mail Website
Guest Editor
Department of Mechanical Engineering, The University of Texas at Dallas, Richardson, TX 75080, USA
Interests: fluid mechanics; renewable energy; fluid–structure interactions; turbulent flow; energy-efficient locomotion
Special Issues, Collections and Topics in MDPI journals
Dr. Qiang Zhong

E-Mail Website
Guest Editor
Department of Mechanical Engineering, Iowa State University, Ames, IA 50010, USA
Interests: unsteady fluid mechanics; bioinspired propulsion; robotics; energy harvesting; flow perception
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Fluid dynamics problems are omnipresent in biological, bio-inspired, and environmental systems. This is a vibrant research area in which newly developed tools have provided us with the capability to tackle more challenging problems. This Special Issue is dedicated to recent advances in theoretical, numerical, and experimental investigations of those systems. The topics of interest include, but are not limited to, animal and bio-inspired locomotion, bio-inspired flow sensing and energy harvesting, cardiovascular flow and flow in the respiratory system, the physical dynamics of coastal and estuarine processes, atmospheric flow and air pollution dispersion, groundwater flow and contaminant transport, and canopy flow.

Prof. Dr. Xing Zhang
Dr. Yaqing Jin
Dr. Qiang Zhong
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. Fluids is an international peer-reviewed open access monthly 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 1800 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 dynamics in flying and swimming
  • bio-inspired propulsion, flow sensing and energy harvesting
  • cardiovascular flow and flow in respiratory system
  • tide, atmospheric flow and canopy flow
  • application of machine learning methods to fluid dynamics problems

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

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

Published Papers (3 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

32 pages, 10282 KiB  
Article
Three-Dimensional Physics-Informed Neural Network Simulation in Coronary Artery Trees
by Nursultan Alzhanov, Eddie Y. K. Ng and Yong Zhao
Fluids 2024, 9(7), 153; https://doi.org/10.3390/fluids9070153 - 27 Jun 2024
Cited by 1 | Viewed by 1921
Abstract
This study introduces a novel approach using 3D Physics-Informed Neural Networks (PINNs) for simulating blood flow in coronary arteries, integrating deep learning with fundamental physics principles. By merging physics-driven models with clinical datasets, our methodology accurately predicts fractional flow reserve (FFR), addressing challenges [...] Read more.
This study introduces a novel approach using 3D Physics-Informed Neural Networks (PINNs) for simulating blood flow in coronary arteries, integrating deep learning with fundamental physics principles. By merging physics-driven models with clinical datasets, our methodology accurately predicts fractional flow reserve (FFR), addressing challenges in noninvasive measurements. Validation against CFD simulations and invasive FFR methods demonstrates the model’s accuracy and efficiency. The mean value error compared to invasive FFR was approximately 1.2% for CT209, 2.3% for CHN13, and 2.8% for artery CHN03. Compared to traditional 3D methods that struggle with boundary conditions, our 3D PINN approach provides a flexible, efficient, and physiologically sound solution. These results suggest that the 3D PINN approach yields reasonably accurate outcomes, positioning it as a reliable tool for diagnosing coronary artery conditions and advancing cardiovascular simulations. Full article
(This article belongs to the Special Issue Fluid Dynamics in Biological, Bio-Inspired, and Environmental Systems)
►▼ Show Figures

Figure 1

13 pages, 2193 KiB  
Article
Fly by Feel: Flow Event Detection via Bioinspired Wind-Hairs
by Alecsandra Court and Christoph Bruecker
Fluids 2024, 9(3), 74; https://doi.org/10.3390/fluids9030074 - 15 Mar 2024
Cited by 1 | Viewed by 2058
Abstract
Bio-inspired flexible pillar-like wind-hairs show promise for the future of flying by feel by detecting critical flow events on an aerofoil during flight. To be able to characterise specific flow disturbances from the response of such sensors, quantitative PIV measurements of such flow-disturbance [...] Read more.
Bio-inspired flexible pillar-like wind-hairs show promise for the future of flying by feel by detecting critical flow events on an aerofoil during flight. To be able to characterise specific flow disturbances from the response of such sensors, quantitative PIV measurements of such flow-disturbance patterns were compared with sensor outputs under controlled conditions. Experiments were performed in a flow channel with an aerofoil equipped with a 2D array of such sensors when in uniform inflow conditions compared to when a well-defined gust was introduced upstream and was passing by. The gust was generated through the sudden deployment of a row of flaps on the suction side of a symmetric wing that was placed upstream of the aerofoil with the sensors. The resulting flow disturbance generated a starting vortex with two legs, which resembled a horseshoe-type vortex shed into the wake. Under the same tunnel conditions, PIV measurements were taken downstream of the gust generator to characterise the starting vortex, while further measurements were taken with the sensing pillars on the aerofoil in the same location. The disturbance pattern was compared to the pillar response to demonstrate the potential of flow-sensing pillars. It was found that the pillars could detect the arrival time and structural pattern of the flow disturbance, showing the characteristics of the induced flow field of the starting vortex when passing by. Therefore, such sensor arrays can detect the “footprint” of disturbances as temporal and spatial signatures, allowing us to distinguish those from others or noise. Full article
(This article belongs to the Special Issue Fluid Dynamics in Biological, Bio-Inspired, and Environmental Systems)
►▼ Show Figures

Figure 1

13 pages, 4382 KiB  
Article
Characterization of the Wing Tone around the Antennae of a Mosquito-like Model
by Yongtao Wang, Zhiteng Zhou and Zhuoyu Xie
Fluids 2024, 9(2), 31; https://doi.org/10.3390/fluids9020031 - 24 Jan 2024
Viewed by 1766
Abstract
Mosquitoes’ self-generated air movements around their antennae, especially at the wing-beat frequency, are crucial for both obstacle avoidance and mating communication. However, the characteristics of these air movements are not well clarified. In this study, the air movements induced by wing tones (sound [...] Read more.
Mosquitoes’ self-generated air movements around their antennae, especially at the wing-beat frequency, are crucial for both obstacle avoidance and mating communication. However, the characteristics of these air movements are not well clarified. In this study, the air movements induced by wing tones (sound generated by flapping wings in flight) around the antennae of a mosquito-like model (Culex quinquefasciatus, male) are investigated using the acoustic analogy method. Both the self-generated wing tone and the wing tone reflected from the ground are calculated. Given that the tiny changes in direction and magnitude of air movements can be detected by the mosquito’s antennae, a novel method is introduced to intuitively characterize the air movements induced by the wing tone. The air movements are decomposed into two basic modes (oscillation and revolution). Our results show that, without considering the scattering on the mosquito’s body, the self-generated sound wave of the wing-beat frequency around the antennae mainly induces air oscillation, with the velocity amplitude exceeding the mosquito’s hearing threshold of the male wingbeat frequency by two orders of magnitude. Moreover, when the model is positioned at a distance from the ground greater than approximately two wing lengths, the reflected sound wave at the male wingbeat frequency attenuates below the hearing threshold. That is, the role of reflected wing tone in the mosquito’s obstacle avoidance mechanism appears negligible. Our findings and method may provide insight into how mosquitoes avoid obstacles when their vision is unavailable and inspire the development of collision avoidance systems in micro-aerial vehicles. Full article
(This article belongs to the Special Issue Fluid Dynamics in Biological, Bio-Inspired, and Environmental Systems)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-3
Back to TopTop