1-7 of 7
Machine learning
Close
Save search
Follow your search
Access your saved searches in your account
Would you like to receive an alert when new items match your search?
Close Modal
Sort by
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

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 Article titled, On Using the Distributor as a Multi Degree-of-Freedom System to Mitigate the Pressure Pulsation in an Axial Turbine at Speed-No-Load
Open the PDF for On Using the Distributor as a Multi Degree-of-Freedom System to Mitigate the Pressure Pulsation in an Axial Turbine at Speed-No-Load in another window
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

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 Article titled, Numerical Simulation of Free Surface Water Waves Around Wavy Hydrofoils: Prediction of Hydrodynamic Coefficients Using Machine Learning
Open the PDF for Numerical Simulation of Free Surface Water Waves Around Wavy Hydrofoils: Prediction of Hydrodynamic Coefficients Using Machine Learning in another window
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

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 Article titled, A Machine Learning Approach to Predicting Unsteady Transonic Flow of Pitching Airfoils
Open the PDF for A Machine Learning Approach to Predicting Unsteady Transonic Flow of Pitching Airfoils in another window
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

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 Article titled, Machine-Learning-Based Reconstruction of Turbulent Vortices From Sparse Pressure Sensors in a Pump Sump
Open the PDF for Machine-Learning-Based Reconstruction of Turbulent Vortices From Sparse Pressure Sensors in a Pump Sump in another window
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)

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 Article titled, Verification, Validation, and Uncertainty Quantification in Thermal Hydraulics, Freeman Scholar Lecture (2019)
Open the PDF for Verification, Validation, and Uncertainty Quantification in Thermal Hydraulics, Freeman Scholar Lecture (2019) in another window
Topics: Uncertainty, Uncertainty quantification, Computers, Machine learning, Thermal hydraulics
Journal Articles

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

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 Article titled, Flow Pattern Transition in Pipes Using Data-Driven and Physics-Informed Machine Learning
Open the PDF for Flow Pattern Transition in Pipes Using Data-Driven and Physics-Informed Machine Learning in another window
Topics: Flow (Dynamics), Machine learning, Physics, Pipes, Databases, Algorithms
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
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 Article titled, Implementing Artificial Intelligence in Predicting Metrics for Characterizing Laser Propagation in Atmospheric Turbulence
Open the PDF for Implementing Artificial Intelligence in Predicting Metrics for Characterizing Laser Propagation in Atmospheric Turbulence in another window
Topics: Algorithms, Lasers, Machine learning, Simulation, Turbulence, Refractive index, Trains, Waves, Artificial intelligence, Artificial neural networks