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Journal Articles

Air Entrainment in Hydraulic Oil: A Comprehensive Study of Influential Parameters Using Computational Fluid Dynamics and Artificial Neural Network

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Accepted Manuscript
Onder Demir, Bartu Isik, Emre Ozen, Timucin Bayram, Ali Olcay
Journal: Journal of Fluids Engineering
Publisher: ASME
Article Type: Research-Article
J. Fluids Eng.
Paper No: FE-25-1062
https://doi.org/10.1115/1.4068619
Published Online: May 9, 2025
View Articletitled, Air Entrainment in Hydraulic Oil: A Comprehensive Study of Influential Parameters Using Computational Fluid Dynamics and Artificial Neural Network
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Topics: Air entrainment, Artificial neural networks, Computational fluid dynamics, Reservoirs, Flow (Dynamics), Machine learning, Modeling, Multiphase flow, Stability, Temperature
Journal Articles

Research on Predicting Gas-Solid Erosion in Series Elbows Using Interpretable Machine Learning

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Accepted Manuscript
Wei Li, Jinkui Feng, Jin Deng, Qianqian Jiao, Zhou Fang
Journal: Journal of Fluids Engineering
Publisher: ASME
Article Type: Research-Article
J. Fluids Eng.
Paper No: FE-25-1139
https://doi.org/10.1115/1.4068620
Published Online: May 9, 2025
View Articletitled, Research on Predicting Gas-Solid Erosion in Series Elbows Using Interpretable Machine Learning
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Topics: Erosion, Machine learning, Pipelines, Computational fluid dynamics, Response surface methodology, Erosion control, Flow (Dynamics), Modeling, Safety
Journal Articles

Advancing Machine Learning-Enhanced Flow Modeling for Collision Phenomena in Total Cavopulmonary Connection

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Yifan Zhang, Zhenglun Alan Wei
Journal: Journal of Fluids Engineering
Publisher: ASME
Article Type: Research-Article
J. Fluids Eng. October 2025, 147(10): 101501.
Paper No: FE-25-1013
https://doi.org/10.1115/1.4068408
Published Online: April 28, 2025
View Articletitled, Advancing Machine Learning-Enhanced Flow Modeling for Collision Phenomena in Total Cavopulmonary Connection
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Topics: Collisions (Physics), Computational fluid dynamics, Flow (Dynamics), Hemodynamics, Simulation, Modeling, Machine learning, Artificial neural networks, Machinery, Boundary-value problems
Journal Articles

On Using the Distributor as a Multi Degree-of-Freedom System to Mitigate the Pressure Pulsation in an Axial Turbine at Speed-No-Load

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Jelle Kranenbarg, Pontus P. Jonsson, Berhanu G. Mulu, Joel Sundström, Michel J. Cervantes
Journal: Journal of Fluids Engineering
Publisher: ASME
Article Type: Research-Article
J. Fluids Eng. February 2025, 147(2): 021501.
Paper No: FE-24-1254
https://doi.org/10.1115/1.4066482
Published Online: September 30, 2024
View Articletitled, On Using the Distributor as a Multi Degree-of-Freedom System to Mitigate the Pressure Pulsation in an Axial Turbine at Speed-No-Load
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Topics: Blades, Computational fluid dynamics, Flow (Dynamics), Guide vanes, Machine learning, Pressure, Simulation, Turbines, Vortices, Stress
Journal Articles

Numerical Simulation of Free Surface Water Waves Around Wavy Hydrofoils: Prediction of Hydrodynamic Coefficients Using Machine Learning

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Ali Tavakoli, Ehsan Roohi, Mohammad Sanaee Namaghi
Journal: Journal of Fluids Engineering
Publisher: ASME
Article Type: Research-Article
J. Fluids Eng. February 2024, 146(2): 021501.
Paper No: FE-23-1244
https://doi.org/10.1115/1.4063078
Published Online: October 11, 2023
View Articletitled, Numerical Simulation of Free Surface Water Waves Around Wavy Hydrofoils: Prediction of Hydrodynamic Coefficients Using Machine Learning
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Topics: Computer simulation, Drag (Fluid dynamics), Hydrofoil, Machine learning, Computational fluid dynamics, Pressure, Fluids, Waves, Turbulence, Water
Journal Articles

A Machine Learning Approach to Predicting Unsteady Transonic Flow of Pitching Airfoils

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Upender K. Kaul
Journal: Journal of Fluids Engineering
Publisher: ASME
Article Type: Research-Article
J. Fluids Eng. February 2023, 145(2): 021501.
Paper No: FE-22-1194
https://doi.org/10.1115/1.4055911
Published Online: November 1, 2022
View Articletitled, A Machine Learning Approach to Predicting Unsteady Transonic Flow of Pitching Airfoils
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Topics: Airfoils, Computational fluid dynamics, Flutter (Aerodynamics), Machine learning, Wings, Transonic flow, Aerodynamics
Journal Articles

Machine-Learning-Based Reconstruction of Turbulent Vortices From Sparse Pressure Sensors in a Pump Sump

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Kai Fukami, Byungjin An, Motohiko Nohmi, Masashi Obuchi, Kunihiko Taira
Journal: Journal of Fluids Engineering
Publisher: ASME
Article Type: Research-Article
J. Fluids Eng. December 2022, 144(12): 121501.
Paper No: FE-22-1251
https://doi.org/10.1115/1.4055178
Published Online: August 23, 2022
View Articletitled, Machine-Learning-Based Reconstruction of Turbulent Vortices From Sparse Pressure Sensors in a Pump Sump
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Topics: Artificial neural networks, Flow (Dynamics), Machine learning, Machinery, Multilayer perceptron, Pressure sensors, Pumps, Sensors, Turbulence, Vortices
Journal Articles

Verification, Validation, and Uncertainty Quantification in Thermal Hydraulics, Freeman Scholar Lecture (2019)

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Upendra S. Rohatgi
Journal: Journal of Fluids Engineering
Publisher: ASME
Article Type: Review Articles
J. Fluids Eng. April 2022, 144(4): 040801.
Paper No: FE-21-1504
https://doi.org/10.1115/1.4053718
Published Online: February 21, 2022
View Articletitled, Verification, Validation, and Uncertainty Quantification in Thermal Hydraulics, Freeman Scholar Lecture (2019)
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Topics: Uncertainty, Uncertainty quantification, Computers, Machine learning, Thermal hydraulics
Journal Articles

Flow Pattern Transition in Pipes Using Data-Driven and Physics-Informed Machine Learning

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André Mendes Quintino, Davi Lôtfi Lavôr Navarro da Rocha, Roberto Fonseca Júnior, Oscar Mauricio Hernandez Rodriguez
Journal: Journal of Fluids Engineering
Publisher: ASME
Article Type: Research-Article
J. Fluids Eng. March 2021, 143(3): 031401.
Paper No: FE-20-1420
https://doi.org/10.1115/1.4048876
Published Online: November 18, 2020
View Articletitled, Flow Pattern Transition in Pipes Using Data-Driven and Physics-Informed Machine Learning
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Topics: Flow (Dynamics), Machine learning, Physics, Pipes, Databases, Algorithms
Journal Articles

Implementing Artificial Intelligence in Predicting Metrics for Characterizing Laser Propagation in Atmospheric Turbulence

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Diego Alberto Lozano Jimenez, V. M.Krushnarao Kotteda, Vinod Kumar, V. S. Rao Gudimetla
Journal: Journal of Fluids Engineering
Publisher: ASME
Article Type: Research-Article
J. Fluids Eng. December 2019, 141(12): 121401.
Paper No: FE-18-1564
https://doi.org/10.1115/1.4043706
Published Online: June 3, 2019
View Articletitled, Implementing Artificial Intelligence in Predicting Metrics for Characterizing Laser Propagation in Atmospheric Turbulence
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Topics: Algorithms, Lasers, Machine learning, Simulation, Turbulence, Refractive index, Trains, Waves, Artificial intelligence, Artificial neural networks