research papers in fluid dynamics

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Fluid dynamics articles within Scientific Reports

Article 13 August 2024 | Open Access

Unified framework for laser-induced transient bubble dynamics within microchannels

• Nagaraj Nagalingam
• , Vikram Korede
•  &  Hüseyin Burak Eral

Article 12 August 2024 | Open Access

Effect of liquid level monitor gas injection point size on information source amplitude-frequency characteristics

• , Kailun Quan
•  &  Zhongzhi Hu

Article 09 August 2024 | Open Access

Evaluating the impact of evolving green and grey urban infrastructure on local particulate pollution around city square parks

• Meng-Yi Jin
• , Kiran A Apsunde
•  &  John Gallagher

Article 05 August 2024 | Open Access

Spacing effects on flows around two square cylinders in staggered arrangement via LBM

• Ahmed Refaie Ali
• , Waqas Sarwar Abbasi
•  &  Irshad Ahmad

Article 26 July 2024 | Open Access

Electrical properties determine the liquid flow direction in plasma–liquid interactions

• Calum T. Ryan
• , Anton A. Darhuber
•  &  Ana Sobota

The effect of including dynamic imaging derived airway wall motion in CFD simulations of respiratory airflow in patients with OSA

• , Chamindu Gunatilaka
•  &  Alister Bates

Article 24 July 2024 | Open Access

A 3-DOF caudal fin for precise maneuvering of thunniform-inspired unmanned underwater vehicles

• Cecilia Huertas-Cerdeira
•  &  Morteza Gharib

Article 23 July 2024 | Open Access

Numerical study of cavitation shock wave emission in the thin liquid layer by power ultrasonic vibratory machining

• , Xijing Zhu
•  &  Yingze Fu

Article 22 July 2024 | Open Access

Drag reduction and degradation by sodium alginate in turbulent flow

• Zhensong Cheng
• , Panpan Zhang
•  &  Yuan Lu

Article 17 July 2024 | Open Access

Nu–Gr correlation for laminar natural convection heat transfer from a sphere submitted to a constant heat flux surface

•  &  Hongzhi Wang

Article 15 July 2024 | Open Access

\(\text{Sech}^{2}\) -type solitary waves and the stability analysis for the KdV–mKdV equation

• Zhi-Guo Liu
• , Muhua Liu
•  &  Jinliang Zhang

Optimization of passive micromixers: effects of pillar configuration and gaps on mixing efficiency

• Ali Kheirkhah Barzoki

Article 12 July 2024 | Open Access

Experimental and CFD analysis of fluid flow through nanofiber filter media

• Mehdi Azimian
• , Matin Naderi
•  &  Andreas Wiegmann

Article 10 July 2024 | Open Access

Estimation of the UV susceptibility of aerosolized SARS-CoV-2 to 254 nm irradiation using CFD-based room disinfection simulations

• Marc van der Schans
•  &  Genevieve Martin

Article 09 July 2024 | Open Access

Enhanced carbon dioxide drainage observed in digital rock under intermediate wetting conditions

• Jaione Tirapu Azpiroz
• , Ronaldo Giro
•  &  Mathias B. Steiner

Article 07 July 2024 | Open Access

Performance analysis of linearization schemes for modelling multi-phase flow in porous media

• Abdul Salam Abd
•  &  Ahmad Abushaikha

Article 06 July 2024 | Open Access

Modeling of scour hole characteristics under turbulent wall jets using machine learning

• Jnana Ranjan Khuntia
• , Kamalini Devi
•  &  Mohd Aamir Mumtaz

Article 05 July 2024 | Open Access

Enhancing hydrodynamic forces through miniaturized control of square cylinders using the lattice Boltzmann method

Article 02 July 2024 | Open Access

Physics-informed neural network simulation of thermal cavity flow

• Eric Fowler
• , Christopher J. McDevitt
•  &  Subrata Roy

Article 27 June 2024 | Open Access

Choice of reaction progress variable under preferential diffusion effects in turbulent syngas combustion based on detailed chemistry direct numerical simulations

• Vinzenz Silvester Wehrmann
• , Nilanjan Chakraborty
•  &  Josef Hasslberger

Article 25 June 2024 | Open Access

Establishing the distribution of cerebrovascular resistance using computational fluid dynamics and 4D flow MRI

• Axel Vikström
• , Petter Holmlund
•  &  Anders Eklund

Article 19 June 2024 | Open Access

Research on the influence of pits on the propagation law of explosion shock waves

•  &  Wang Liangquan

Free convection in a square wavy porous cavity with partly magnetic field: a numerical investigation

• Amirmohammad Mirzaei
• , Bahram Jalili
•  &  Davood Domiri Ganji

Article 13 June 2024 | Open Access

Numerical simulation and theoretical study on the impact of wind-sand flow of high-speed trains in long tunnel space

• , Sihui Dong
•  &  Liping Zhou

Article 06 June 2024 | Open Access

Fluid-particle-structure interaction in single shot peening

• Yusuke Mizuno
• , Takashi Misaka
•  &  Yoshiyuki Furukawa

Article 05 June 2024 | Open Access

Equivalent analytical model for liquid sloshing in a 2-D rectangular container with multiple vertical baffles by subdomain partition approach

•  &  Ding Zhou

Article 03 June 2024 | Open Access

A computational fluid dynamics study to assess the impact of coughing on cerebrospinal fluid dynamics in Chiari type 1 malformation

• Sarah Vandenbulcke
• , Paul Condron
•  &  Patrick Segers

Article 31 May 2024 | Open Access

Flow regimes identification of air water counter current flow in vertical annulus using differential pressure signals and machine learning

• , Ruirong Dang
•  &  Zhimeng Sun

Exergoeconomic analysis and optimization of wind power hybrid energy storage system

• Caifeng Wen
• , Yalin Lyu
•  &  Hongliang Hao

Article 30 May 2024 | Open Access

Capillary wave tweezer

• Bethany Orme
• , Hamdi Torun
•  &  Prashant Agrawal

Article 28 May 2024 | Open Access

Experimental and numerical investigations of the water surface profile and wave extrema of supercritical flows in a narrow channel bend

• Subhojit Kadia
• , I. A. Sofia Larsson
•  &  Elena Pummer

Article 17 May 2024 | Open Access

Uncertainty quantification of the lattice Boltzmann method focussing on studies of human-scale vascular blood flow

• Jon W. S. McCullough
•  &  Peter V. Coveney

Article 14 May 2024 | Open Access

AI-based predictive approach via FFB propagation in a driven-cavity of Ostwald de-Waele fluid using CFD-ANN and Levenberg–Marquardt

• , Rashid Mahmood
•  &  Mohamed H. Behiry

Thermal modal analysis of hypersonic composite wing on transient aerodynamic heating

• Kangjie Wang
• , Junli Wang
•  &  Wenyong Quan

Article 08 May 2024 | Open Access

A non-invasive capacitive sensor to investigate the Leidenfrost phenomenon: a proof of concept study

• Abhishek S. Purandare
• , Jelle Rijs
•  &  Srinivas Vanapalli

Article 04 May 2024 | Open Access

Turbulence-induced droplet grouping and augmented rain formation in cumulus clouds

• Siddharth Gumber
• , Sudarsan Bera
•  &  Thara V. Prabhakaran

Predicting the vertical density structure of oceanic gravity current intrusions

• Sévan Rétif
• , Maria Eletta Negretti
•  &  Achim Wirth

Article 22 April 2024 | Open Access

Experimental investigation of drag loss behavior of dip-lubricated wet clutches for building a data-driven prediction model

• Lukas Pointner-Gabriel
• , Max Menzel
•  &  Karsten Stahl

Article 20 April 2024 | Open Access

The air conditioning in the nose of mammals depends on their mass and on their maximal running speed

• Clément Rigaut
• , Alice Giaprakis
•  &  Benoît Haut

Article 16 April 2024 | Open Access

Label-free separation of peripheral blood mononuclear cells from whole blood by gradient acoustic focusing

• Julia Alsved
• , Mahdi Rezayati Charan
•  &  Per Augustsson

Biogeochemical dynamics in a marine storm demonstrates differences between natural and anthropogenic impacts

• Justin Tiano
• , Rob Witbaard
•  &  Karline Soetaert

Article 13 April 2024 | Open Access

Study on dynamic characteristics of cavitation in underwater explosion with large charge

• , Xian-pi Zhang
•  &  Yuan-Qing Xu

Article 09 April 2024 | Open Access

Bubble dynamics and atomization of acoustically levitated diesel and biodiesel droplets using femtosecond laser pulses

• Vishal S. Jagadale
• , Devendra Deshmukh
•  &  Yogeshwar Nath Mishra

Article 08 April 2024 | Open Access

Evaluating the accuracy of cerebrovascular computational fluid dynamics modeling through time-resolved experimental validation

• Claudio A. Luisi
• , Tom L. Witter
•  &  Michael Neidlin

Toward the eco-friendly cosmetic cleansing assisted by the micro-bubbly jet

• , Jooyeon Park
•  &  Hyungmin Park

Article 02 April 2024 | Open Access

Velocity field and turbulence structure of the meandering flow produced by alternating deflectors

• Jie-min Zhan
• , Wing-hong Onyx Wai
•  &  Ying-ying Luo

The impact of a chemical reaction on the heat and mass transfer mechanisms in a dissipative and radiative nanofluid flow over a nonlinear stretching sheet

• , Ahmed M. Megahed
•  &  Eman Fares

Article 31 March 2024 | Open Access

Morphogenesis of a chiral liquid crystalline droplet with topological reconnection and Lehmann rotation

• Jun Yoshioka
•  &  Koji Fukao

Article 30 March 2024 | Open Access

Response spectrum-based analysis of airborne radar random vibration and multi-point control improvement

• , Zezheng Liu
•  &  Libin Du

Article 29 March 2024 | Open Access

High-efficiency and low-hazard artillery recoil reduction technology based on barrel gas reflection

• , Jinsong Dai
•  &  Xiaopeng Su

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JSmol Viewer

Current trends in fluid research in the era of artificial intelligence: a review.

1. Introduction

1.1. data science, 1.2. ai/ml in fluid research, 1.3. reviews and perspectives on fluid research and ml, 1.4. aim and objectives, 2. bridging across scales, 3. fluid properties extraction, 4. physics-based cfd, 5. algorithms for fluid flows, 5.1. multiple linear regression, 5.2. ridge regression, 5.3. lasso regression, 5.4. support vector machines, 5.5. gaussian process regression, 5.6. k-nearest neighbors, 5.7. decision trees, 5.8. random forest, 5.9. gradient boosting, 5.10. artificial neural networks, 5.11. symbolic regression, 5.12. performance metrics, 6. comparative investigation, 7. conclusions and future perspectives, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest, nomenclature.

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Sofos, F.; Stavrogiannis, C.; Exarchou-Kouveli, K.K.; Akabua, D.; Charilas, G.; Karakasidis, T.E. Current Trends in Fluid Research in the Era of Artificial Intelligence: A Review. Fluids 2022 , 7 , 116. https://doi.org/10.3390/fluids7030116

Sofos F, Stavrogiannis C, Exarchou-Kouveli KK, Akabua D, Charilas G, Karakasidis TE. Current Trends in Fluid Research in the Era of Artificial Intelligence: A Review. Fluids . 2022; 7(3):116. https://doi.org/10.3390/fluids7030116

Sofos, Filippos, Christos Stavrogiannis, Kalliopi K. Exarchou-Kouveli, Daniel Akabua, George Charilas, and Theodoros E. Karakasidis. 2022. "Current Trends in Fluid Research in the Era of Artificial Intelligence: A Review" Fluids 7, no. 3: 116. https://doi.org/10.3390/fluids7030116

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Physical Review Fluids

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Data-driven low-dimensional model of a sedimenting flexible fiber

Andrew j. fox and michael d. graham, phys. rev. fluids 9 , 084101 – published 16 august 2024.

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• Supplemental Material
• INTRODUCTION
• FORMULATION
• RESULTS AND DISCUSSION
• CONCLUSIONS
• ACKNOWLEDGMENTS

The dynamics of flexible filaments entrained in flow, important for understanding many biological and industrial processes, are computationally expensive to model with full physics simulations. In this paper, we describe a data-driven technique to create high-fidelity low-dimensional models of flexible fiber dynamics using machine learning; the technique is applied to sedimentation in a quiescent, viscous Newtonian fluid, using results from detailed simulations as the dataset. The approach combines an autoencoder neural network architecture to learn a low-dimensional latent representation of the filament shape, with a neural ordinary differential equation that learns the evolution of the particle in the latent state. The model was designed to model filaments of varying flexibility, characterized by an elastogravitational number B , and was trained on a dataset containing the evolution of fibers beginning at set angles of inclination. For the range of B considered here (100–10 000), the filament shape dynamics can be represented with high accuracy with only four degrees of freedom, in contrast with the 93 present in the original bead-spring model used to generate the dynamic trajectories. We predict the evolution of fibers set at arbitrary angles and demonstrate that our data-driven model can accurately forecast the evolution of a fiber at both trained and untrained elastogravitational numbers.

• Received 16 May 2024
• Accepted 11 July 2024

DOI: https://doi.org/10.1103/PhysRevFluids.9.084101

©2024 American Physical Society

Physics Subject Headings (PhySH)

• Physical Systems

Authors & Affiliations

• Department of Chemical and Biological Engineering, University of Wisconsin-Madison , Madison, Wisconsin 53706, USA
• * Contact author: [email protected]

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Vol. 9, Iss. 8 — August 2024

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A flexible filament of length L settling under an external force F g in a quiescent Newtonian fluid. The filament begins at an arbitrary initial inclination θ 0 relative to the x axis and evolves until it reaches a terminal shape. The fiber is modeled as a series of N beads of radius a connected by springs, with the center bead, which has position c ( t ) , shown in red.

The evolution of the shape of a filament settling in a quiescent Newtonian fluid from an initial orientation to a common terminal shape at B = 1000 for all initial angles of orientation within the training dataset.

The trajectories c ( t ) of the center bead of a filament settling in a quiescent Newtonian fluid at B = 1000 for all initial angles of inclination within the training dataset. The initial positions are denoted by symbol ▾ , and the terminal positions are denoted by the symbol × .

The evolution of the shape of a filament settling in a quiescent Newtonian fluid from a common initial angle of orientation of π / 4 to a terminal shape for all B within the training dataset.

Block diagram for data-driven model combining the autoencoder and temporal-evolution scheme. The temporal-evolution neural network, expanded in red, can be separated into two distinct neural networks forecasting the evolution of latent representation of the shape h ( t + τ ) and the shape-dependent change in position c ; in practice, these can be forecasted by a single neural network.

(a) Loss over the testing data for each autoencoder architecture as a function of latent dimension. Block diagrams for the autoencoder neural network architectures: (b) No B , (c) Encoder B , (d) Decoder B , and (e) Double B .

Evolution of the shape of a filament settling in quiescent Newtonian fluid given an initial orientation from the best and worst forecasts (red) and the true evolution (black) at a given B . Here, B is within the training dataset, and the initial angles of inclination are not.

Evolution of the shape of a filament settling in quiescent Newtonian fluid given an initial orientation from the best and worst forecasts (red) and the true evolution (black) at a given B . Here, neither B nor the initial angles of inclination are within the training dataset.

Trajectory of the center bead c ( t ) a filament settling in quiescent Newtonian fluid given an initial orientation from the best (solid lines) and worst (dashed lines) forecasts and the true evolution at a given B . The initial positions are denoted by symbol ▾ , and the terminal positions are denoted by the symbol × , with the true and predicted positions in black and red, respectively. In (a), B is within the training dataset but, at initial angles of inclination, not within the training data; in (b), neither B nor the initial angles of inclination are within the training data.

Ensemble-average error vs time for forecasts of the evolution of a filament settling in quiescent Newtonian fluid at each B (gray) and averaged over all B (red). In (a), B is within the training dataset but, at initial angles of inclination, not within the training data; in (b), neither B nor the initial angles of inclination are within the training data.

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Hydraulics and Fluid Mechanics, Volume 1

Select Proceedings of HYDRO 2023

• Conference proceedings
• Latest edition
• Manish Pandey 0 ,
• N V Umamahesh 1 ,
• Z. Ahmad 2 ,
• Giuseppe Oliveto 3

Department of Civil Engineering, Indian Institute of Technology Kharagpur, Kharagpur, India

You can also search for this editor in PubMed   Google Scholar

Department of Civil Engineering, National Institute of Technology Warangal, Warangal, India

Department of civil engineering, indian institute of technology roorkee, roorkee, india, school of engineering,, university of basilicata, potenza, italy.

• Presents emerging opportunities and challenges in the field of hydraulics and fluid mechanics
• Covers experimental fluid mechanics, sediment dynamics, environmental impact assessment and pollutant transport
• Deals with addresses fundamental concepts and studies in the field of flood forecasting and hydraulic structures

Part of the book series: Lecture Notes in Civil Engineering (LNCE, volume 547)

Buy print copy

About this book.

This book comprises the proceedings of the 28th International Conference on Hydraulics, Water Resources, River and Coastal Engineering (HYDRO 2023) focusing on broad spectrum of emerging opportunities and challenges in the field of hydraulics and fluid mechanics. It covers a range of topics, including, but not limited to, experimental and computational fluid mechanics, sediment dynamics, environmental impact assessment of water resources projects, environmental flows, pollutant transport, etc. Presenting recent advances in the form of illustrations, tables, and text, it offers readers insights for their own research. In addition, the book addresses fundamental concepts and studies in the field of flood forecasting and hydraulic structures, making it a valuable resource for both beginners and researchers wanting to further their understanding of hydraulics, water resources and coastal engineering.

• Environmental Impact Assessment
• Environmental Flows
• Groundwater Contamination
• Geographic Information Systems
• Remote Sensing
• Hydro-Informatics
• Rainfall and Streamflow Prediction
• Optimization of Water Resources Systems
• Soft Computing Techniques
• Urban Flood Modelling
• Dam Hazard Classification
• Flood Forecasting
• Costal Disasters
• Wave-Structure Interaction
• Costal Structures and Oceanography
• Fluvial Geomorphology
• Sediment Dynamics
• Reservoir Sedimentation
• Alluvial River Problems
• Watershed Management

Editors and Affiliations

Manish Pandey

N V Umamahesh

Giuseppe Oliveto

About the editors

Dr Manish Pandey graduated in Civil Engineering from Uttarakhand Technical University, India. He completed his masters and doctorate from Indian Institute of Technology Roorkee, India. Presently, Dr Pandey is Assistant Professor at Indian Institute of Technology Kharagpur, India since 2013. He has more than 6 years teaching and research experience in experimental hydraulics and water resources engineering. He has authored more than 50 peer-reviewed journal papers and 25+ book chapters and conference proceeding papers.  He has guided 1 PhD and 10 M.Tech students. Presently he is guiding 4 PhD students. He was also awarded MOST postdoctoral research grant in year 2018. He is a member of the editorial board of Journals: Environmental Development and Sustainability, Journal of Water Management Modeling, Water SA, Journal of Applied Science and Engineering and Journal of Applied Water Engineering and Research. He has also handled guest editorship for Fluid MDPI Journal, SI: Journalof Applied Water Engineering and Research and Frontiers in Environmental Science Journal, SI: The Urban Fluvial and Hydro-Environment System. Dr Pandey is an active reviewer in several reputed peer-reviewed journals. 

Prof. N V Umamahesh has more than 35 years of experience as a faculty in the Department of Civil Engineering at NIT, Warangal. His area of specialization is Water Resources Engineering, and his research areas include Hydrological Modelling, Stochastic Hydrology, Hydro-Climatic Extremes, Modelling Impacts of Climate Change, Urban Floods, and Water Resources Systems. He has been well recognized for his analytical and mathematical modelling skills. He guided 13 PhD students and about 100 M.Tech students. He is currently guiding 7 PhD scholars. He has published more than 60 papers in reputed International Journals, and 6 book chapters and presented more than 50 papers in National and International Conferences. He has taken up several sponsored research and consultancy projects. He has held several administrative positions including Chief Warden, Head of the Department of Civil Engineering, Dean (Student Welfare), Dean (Planning and Development), Dean (Academic) and Coordinator of TEQIP-II. He received the Jalamitra Award from the Government of Andhra Pradesh in 2003 for the best implementation of the Watershed Development Program in Warangal District. He received the Best Engineering Faculty Award in 2017. He organized two international conferences and several faculty development programs. 

Prof. Giuseppe Oliveto is Associate Professor of Hydraulic Engineering at the School of Engineering of University of Basilicata (Italy). Since 1992 he has been carrying out theoretical and experimental studies encompassing: evolution and patterns of river networks, fluvial hydraulics, sediment transport, bridge hydraulics, and urban drainage hydraulics. He is author of more than 100 papers in scientific journals and conference proceedings. He currently is Associate Editor of: Journal of Irrigation and Drainage Engineering (ASCE); Water Journal (MDPI), and Advances in Civil Engineering (Hindawi). He has been Leading Guest Editor of the Special Collection “Sediment Transport in Water-Resources Engineering” for Journal of Irrigation and Drainage Engineering (ASCE) and the Special Issue “Bridge Hydraulics: Current State of the Knowledge and Perspectives” for Water Journal (MDPI). He was recognized as: "ASCE Outstanding Reviewer" by Journal of Hydraulic Engineering (ASCE) in 2011; "ASCE Outstanding Reviewer" by Journal of Irrigation and Drainage Engineering (ASCE) in 2018 and 2019; "MDPI-Water Outstanding Reviewer" by Water Journal (MDPI) in 2018, 2019, and 2022. He has been awarded the Robert Alfred Carr Prize by the Council of the Institution of Civil Engineers (ICE) - London (UK) for the paper "Temporal scour evolution at non-uniform bridge piers" published in the Proceedings of the Institution of Civil Engineers - Water Management, Volume 170, October 2017.

Bibliographic Information

Book Title : Hydraulics and Fluid Mechanics, Volume 1

Book Subtitle : Select Proceedings of HYDRO 2023

Editors : Manish Pandey, N V Umamahesh, Z. Ahmad, Giuseppe Oliveto

Series Title : Lecture Notes in Civil Engineering

Publisher : Springer Singapore

eBook Packages : Engineering , Engineering (R0)

Copyright Information : The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025

Hardcover ISBN : 978-981-97-8034-1 Due: 12 December 2024

Softcover ISBN : 978-981-97-8037-2 Due: 12 December 2025

eBook ISBN : 978-981-97-8035-8 Due: 12 December 2024

Series ISSN : 2366-2557

Series E-ISSN : 2366-2565

Edition Number : 1

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