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Journal Articles

A Novel Method to Achieve Fast Multi-Objective Optimization of Hydrostatic Porous Journal Bearings Used in Hydraulic Turbomachine

Yandong Gu, Dongcheng Wang, Li Cheng, Artur Schimpf, Martin Böhle

Publisher: ASME

J. Fluids Eng. May 2023, 145(5): 051205.

Paper No: FE-22-1345

https://doi.org/10.1115/1.4057003

Published Online: March 13, 2023

View Article titled, A Novel Method to Achieve Fast Multi-Objective Optimization of Hydrostatic Porous Journal Bearings Used in Hydraulic Turbomachine

Topics: Artificial neural networks, Flow (Dynamics), Journal bearings, Optimization, Pressure, Stress, Bushings, Hydrostatics, Pareto optimization, Turbomachinery

Journal Articles

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

Kai Fukami, Byungjin An, Motohiko Nohmi, Masashi Obuchi, Kunihiko Taira

Publisher: ASME

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

Topics: Artificial neural networks, Flow (Dynamics), Machine learning, Machinery, Multilayer perceptron, Pressure sensors, Pumps, Sensors, Turbulence, Vortices

Journal Articles

Aiding Airway Obstruction Diagnosis With Computational Fluid Dynamics and Convolutional Neural Network: A New Perspective and Numerical Case Study

Pingfan Hu, Changjie Cai, Hang Yi, Jianan Zhao, Yu Feng, Qingsheng Wang

Publisher: ASME

J. Fluids Eng. August 2022, 144(8): 081206.

Paper No: FE-21-1577

https://doi.org/10.1115/1.4053651

Published Online: March 8, 2022

View Article titled, Aiding Airway Obstruction Diagnosis With Computational Fluid Dynamics and Convolutional Neural Network: A New Perspective and Numerical Case Study

Topics: Air flow, Artificial neural networks, Computational fluid dynamics, Lung, Flow (Dynamics), Testing, Databases

Includes: Supplementary data

Journal Articles

Physics Informed Deep Neural Net Inverse Modeling for Estimating Model Parameters in Permeable Porous Media Flows

Amin Pashaei Kalajahi, Isaac Perez-Raya, Roshan M D'Souza

Publisher: ASME

J. Fluids Eng. June 2022, 144(6): 061102.

Paper No: FE-21-1449

https://doi.org/10.1115/1.4053549

Published Online: February 8, 2022

View Article titled, Physics Informed Deep Neural Net Inverse Modeling for Estimating Model Parameters in Permeable Porous Media Flows

Topics: Artificial neural networks, Boundary-value problems, Flow (Dynamics), Fluids, Inverse problems, Permeability, Physics, Porosity, Porous materials, Errors

Journal Articles

Estimation of Vortex-Induced Vibration Based on Observed Wakes Using Computational Fluid Dynamics-Trained Deep Neural Network

Takashi Misaka

Publisher: ASME

J. Fluids Eng. October 2021, 143(10): 104501.

Paper No: FE-20-1767

https://doi.org/10.1115/1.4050974

Published Online: May 28, 2021

View Article titled, Estimation of Vortex-Induced Vibration Based on Observed Wakes Using Computational Fluid Dynamics-Trained Deep Neural Network

Topics: Artificial neural networks, Circular cylinders, Computational fluid dynamics, Flow (Dynamics), Fluids, Oscillations, Vortex-induced vibration, Wakes, Inks, Visualization

Journal Articles

Uncertainty Quantification of Spalart–Allmaras Turbulence Model Coefficients for Simplified Compressor Flow Features

Xiao He, Fanzhou Zhao, Mehdi Vahdati

Publisher: ASME

J. Fluids Eng. September 2020, 142(9): 091501.

Paper No: FE-19-1810

https://doi.org/10.1115/1.4047026

Published Online: May 11, 2020

View Article titled, Uncertainty Quantification of Spalart–Allmaras Turbulence Model Coefficients for Simplified Compressor Flow Features

Topics: Artificial neural networks, Compressors, Flow (Dynamics), Separation (Technology), Shock (Mechanics), Shock waves, Stress, Turbulence, Uncertainty, Uncertainty quantification

Journal Articles

Fluid–Structure Interaction Study and Flowrate Prediction Past a Flexible Membrane Using Immersed Boundary Method and Artificial Neural Network Techniques

Mithun Kanchan, Ranjith Maniyeri

Publisher: ASME

J. Fluids Eng. May 2020, 142(5): 051501.

Paper No: FE-19-1564

https://doi.org/10.1115/1.4045575

Published Online: February 3, 2020

View Article titled, Fluid–Structure Interaction Study and Flowrate Prediction Past a Flexible Membrane Using Immersed Boundary Method and Artificial Neural Network Techniques

Topics: Artificial neural networks, Membranes, Deformation, Stiffness, Fluids, Fluid structure interaction

Journal Articles

Optimization of Flow Control Parameters Over SD7003 Airfoil With Synthetic Jet Actuator

M. Tadjfar, Dj. Kamari

Publisher: ASME

J. Fluids Eng. February 2020, 142(2): 021206.

Paper No: FE-19-1407

https://doi.org/10.1115/1.4044985

Published Online: October 30, 2019

View Article titled, Optimization of Flow Control Parameters Over SD7003 Airfoil With Synthetic Jet Actuator

Topics: Actuators, Airfoils, Design, Flow (Dynamics), Flow control, Genetic algorithms, Optimization, Separation (Technology), Artificial neural networks, Reynolds number

Journal Articles

A Genetic Algorithm Based Multi-Objective Optimization of Squealer Tip Geometry in Axial Flow Turbines: A Constant Tip Gap Approach

H. Maral, C. B. Şenel, K. Deveci, E. Alpman, L. Kavurmacıoğlu, Cengiz Camci

Publisher: ASME

J. Fluids Eng. February 2020, 142(2): 021402.

Paper No: FE-19-1096

https://doi.org/10.1115/1.4044721

Published Online: October 10, 2019

View Article titled, A Genetic Algorithm Based Multi-Objective Optimization of Squealer Tip Geometry in Axial Flow Turbines: A Constant Tip Gap Approach

Topics: Artificial neural networks, Axial flow, Blades, Computational fluid dynamics, Databases, Design, Flow (Dynamics), Genetic algorithms, Geometry, Leakage flows

Journal Articles

A Generalized Reduced-Order Dynamic Model for Two-Phase Flow in Pipes

Majdi Chaari, Afef Fekih, Abdennour C. Seibi, Jalel Ben Hmida

Publisher: ASME

J. Fluids Eng. October 2019, 141(10): 101303.

Paper No: FE-18-1872

https://doi.org/10.1115/1.4043858

Published Online: June 20, 2019

View Article titled, A Generalized Reduced-Order Dynamic Model for Two-Phase Flow in Pipes

Topics: Flow (Dynamics), Fluids, Modeling, Pipes, Pressure, Steady state, Transients (Dynamics), Artificial neural networks, Two-phase flow, Bulk modulus

Journal Articles

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

Diego Alberto Lozano Jimenez, V. M.Krushnarao Kotteda, Vinod Kumar, V. S. Rao Gudimetla

Publisher: ASME

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

Topics: Algorithms, Lasers, Machine learning, Simulation, Turbulence, Refractive index, Trains, Waves, Artificial intelligence, Artificial neural networks

Journal Articles

Multi-Objective Shape Optimization on the Inlet Pipe of a Vertical Inline Pump

Ji Pei, Xingcheng Gan, Wenjie Wang, Shouqi Yuan, Yajing Tang

Publisher: ASME

J. Fluids Eng. June 2019, 141(6): 061108.

Paper No: FE-18-1387

https://doi.org/10.1115/1.4043056

Published Online: April 9, 2019

View Article titled, Multi-Objective Shape Optimization on the Inlet Pipe of a Vertical Inline Pump

Topics: Artificial neural networks, Design, Flow (Dynamics), Genetic algorithms, Impellers, Optimization, Pipes, Pumps, Pareto optimization, Stress

Journal Articles

An Optimized Artificial Neural Network Unifying Model for Steady-State Liquid Holdup Estimation in Two-Phase Gas–Liquid Flow

Majdi Chaari, Abdennour C. Seibi, Jalel Ben Hmida, Afef Fekih

Publisher: ASME

J. Fluids Eng. October 2018, 140(10): 101301.

Paper No: FE-17-1640

https://doi.org/10.1115/1.4039710

Published Online: May 2, 2018

View Article titled, An Optimized Artificial Neural Network Unifying Model for Steady-State Liquid Holdup Estimation in Two-Phase Gas–Liquid Flow

Topics: Artificial neural networks, Flow (Dynamics), Pipes, Multiphase flow, Databases, Steady state

Journal Articles

Optimum Parameter Design of Microbubble Drag Reduction in a Turbulent Flow by the Taguchi Method Combined With Artificial Neural Networks

Kwan Ouyang, Sheng-Ju Wu, Huang-Hsin Huang

Publisher: ASME

J. Fluids Eng. November 2013, 135(11): 111301.

Paper No: FE-12-1396

https://doi.org/10.1115/1.4024930

Published Online: August 7, 2013

View Article titled, Optimum Parameter Design of Microbubble Drag Reduction in a Turbulent Flow by the Taguchi Method Combined With Artificial Neural Networks

Topics: Artificial neural networks, Design, Drag reduction, Flow (Dynamics), Taguchi methods, Turbulence, Drag (Fluid dynamics), Bubbles, Microbubbles

Journal Articles

A Generalized Neural Network Model of Refrigerant Mass Flow Through Adiabatic Capillary Tubes and Short Tube Orifices

Ling-Xiao Zhao, Chun-Lu Zhang, Liang-Liang Shao, Liang Yang

Publisher: ASME

J. Fluids Eng. December 2007, 129(12): 1559–1564.

https://doi.org/10.1115/1.2801352

Published Online: May 29, 2007

View Article titled, A Generalized Neural Network Model of Refrigerant Mass Flow Through Adiabatic Capillary Tubes and Short Tube Orifices

Topics: Artificial neural networks, Flow (Dynamics), Orifices, Refrigerants

Journal Articles

Hydraulic Turbine Diffuser Shape Optimization by Multiple Surrogate Model Approximations of Pareto Fronts

B. Daniel Marjavaara, T. Staffan Lundström, Tushar Goel, Yolanda Mack, Wei Shyy

Publisher: ASME

J. Fluids Eng. September 2007, 129(9): 1228–1240.

https://doi.org/10.1115/1.2754324

Published Online: April 4, 2007

View Article titled, Hydraulic Turbine Diffuser Shape Optimization by Multiple Surrogate Model Approximations of Pareto Fronts

Topics: Approximation, Computational fluid dynamics, Design, Diffusers, Hydraulic turbines, Optimization, Pressure, Artificial neural networks, Evolutionary algorithms, Polynomials

Journal Articles

Finite Element and Neural Network Modeling of Viscoelastic Annular Extrusion

Han-Xiong Huang, Yan-Sheng Miao

Publisher: ASME

J. Fluids Eng. February 2007, 129(2): 218–225.

https://doi.org/10.1115/1.2409357

Published Online: July 25, 2006

View Article titled, Finite Element and Neural Network Modeling of Viscoelastic Annular Extrusion

Topics: Artificial neural networks, Extruding, Finite element analysis, Modeling, Molding, Simulation

Journal Articles

Velocity Field Reconstruction in the Mixing Region of Swirl Sprays Using General Regression Neural Network

K. Ghorbanian, Assistant Professor, M. R. Soltani, Associate Professor, M. R. Morad, Ph.D. Student, M. Ashjaee, Associate Professor,

Publisher: ASME

J. Fluids Eng. January 2005, 127(1): 14–23.

https://doi.org/10.1115/1.1852472

Published Online: March 22, 2005

View Article titled, Velocity Field Reconstruction in the Mixing Region of Swirl Sprays Using General Regression Neural Network

Topics: Artificial neural networks, Ejectors, Sprays, Optimization, Pressure, Errors, Trains, Probability, Design

Journal Articles

Experimental Turbulent Field Modeling by Visualization and Neural Networks

Marko Hocˇevar, Brane Sˇirok, Igor Grabec

Publisher: ASME

J. Fluids Eng. May 2004, 126(3): 316–322.

https://doi.org/10.1115/1.1760534

Published Online: July 12, 2004

View Article titled, Experimental Turbulent Field Modeling by Visualization and Neural Networks

Topics: Artificial neural networks, Modeling, Spectra (Spectroscopy), Turbulence, Vortex street, Visualization, Fluctuations (Physics), Flow visualization

Journal Articles

Prediction of Turbulence Statistics Behind a Square Cylinder Using Neural Networks and Fuzzy Logic

P. K. Panigrahi, Manish Dwivedi, Vinay Khandelwal, Mihir Sen

Publisher: ASME

J. Fluids Eng. March 2003, 125(2): 385–387.

https://doi.org/10.1115/1.1537251

Published Online: March 27, 2003

View Article titled, Prediction of Turbulence Statistics Behind a Square Cylinder Using Neural Networks and Fuzzy Logic

Topics: Artificial neural networks, Cylinders, Fuzzy logic, Statistics, Turbulence, Modeling

Journal citation

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Supplemental Material

A Novel Method to Achieve Fast Multi-Objective Optimization of Hydrostatic Porous Journal Bearings Used in Hydraulic Turbomachine

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

Aiding Airway Obstruction Diagnosis With Computational Fluid Dynamics and Convolutional Neural Network: A New Perspective and Numerical Case Study

Physics Informed Deep Neural Net Inverse Modeling for Estimating Model Parameters in Permeable Porous Media Flows

Estimation of Vortex-Induced Vibration Based on Observed Wakes Using Computational Fluid Dynamics-Trained Deep Neural Network

Uncertainty Quantification of Spalart–Allmaras Turbulence Model Coefficients for Simplified Compressor Flow Features

Fluid–Structure Interaction Study and Flowrate Prediction Past a Flexible Membrane Using Immersed Boundary Method and Artificial Neural Network Techniques

Optimization of Flow Control Parameters Over SD7003 Airfoil With Synthetic Jet Actuator

A Genetic Algorithm Based Multi-Objective Optimization of Squealer Tip Geometry in Axial Flow Turbines: A Constant Tip Gap Approach

A Generalized Reduced-Order Dynamic Model for Two-Phase Flow in Pipes

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

Multi-Objective Shape Optimization on the Inlet Pipe of a Vertical Inline Pump

An Optimized Artificial Neural Network Unifying Model for Steady-State Liquid Holdup Estimation in Two-Phase Gas–Liquid Flow

Optimum Parameter Design of Microbubble Drag Reduction in a Turbulent Flow by the Taguchi Method Combined With Artificial Neural Networks

A Generalized Neural Network Model of Refrigerant Mass Flow Through Adiabatic Capillary Tubes and Short Tube Orifices

Hydraulic Turbine Diffuser Shape Optimization by Multiple Surrogate Model Approximations of Pareto Fronts

Finite Element and Neural Network Modeling of Viscoelastic Annular Extrusion

Velocity Field Reconstruction in the Mixing Region of Swirl Sprays Using General Regression Neural Network

Experimental Turbulent Field Modeling by Visualization and Neural Networks

Prediction of Turbulence Statistics Behind a Square Cylinder Using Neural Networks and Fuzzy Logic

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