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Journal Articles

Inverse Design of Compressor/Fan Blade Profiles Based on Conditional Invertible Neural Networks

Available to Purchase
Xinkai Jia, Xiuquan Huang, Shouyong Jiang, Dingxi Wang, Christian Maria Firrone
Journal: Journal of Turbomachinery
Publisher: ASME
Article Type: Research Papers
J. Turbomach. October 2025, 147(10): 101014.
Paper No: TURBO-24-1150
https://doi.org/10.1115/1.4068386
Published Online: May 2, 2025
View Articletitled, Inverse Design of Compressor/Fan Blade Profiles Based on Conditional Invertible Neural Networks
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Topics: Design, Artificial neural networks, Modeling, Blades, Compressors
Journal Articles

DATA-ASSIMILATION OF TRANSITIONAL AND SEPARATED TURBOMACHINERY FLOWS WITH PHYSICS-INFORMED NEURAL NETWORKS

Open Access
Accepted Manuscript
Sean Hanrahan, Melissa Kozul, Richard Sandberg
Journal: Journal of Turbomachinery
Publisher: ASME
Article Type: Research Papers
J. Turbomach.
Paper No: TURBO-24-1059
https://doi.org/10.1115/1.4068396
Published Online: April 9, 2025
View Articletitled, DATA-ASSIMILATION OF TRANSITIONAL AND SEPARATED TURBOMACHINERY FLOWS WITH PHYSICS-INFORMED NEURAL NETWORKS
Open the PDF for DATA-ASSIMILATION OF TRANSITIONAL AND SEPARATED TURBOMACHINERY FLOWS WITH PHYSICS-INFORMED NEURAL NETWORKS in another window
Topics: Artificial neural networks, Flow (Dynamics), Physics, Turbochargers, Turbomachinery, Turbulence, Reynolds-averaged Navier–Stokes equations, Separation (Technology), Computational fluid dynamics, Pressure
Journal Articles

Application of Machine Learning Techniques in Calibration and Data Reduction of Multihole Probes

Available to Purchase
Arman Mirhashemi, Paht Juangphanich, Kenji Miki
Journal: Journal of Turbomachinery
Publisher: ASME
Article Type: Research Papers
J. Turbomach. July 2025, 147(7): 071011.
Paper No: TURBO-24-1179
https://doi.org/10.1115/1.4067123
Published Online: December 16, 2024
View Articletitled, Application of Machine Learning Techniques in Calibration and Data Reduction of Multihole Probes
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Topics: Algorithms, Artificial neural networks, Calibration, Flow (Dynamics), Mach number, Machine learning, Pressure, Probes, Uncertainty
Journal Articles

A Physics-Informed Neural Network for Solving the Inverse Heat Transfer Problem in Gas Turbine Rotating Cavities

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Mark R. Puttock-Brown, Goutham K. M. Bindhu, Colin E. Ashby
Journal: Journal of Turbomachinery
Publisher: ASME
Article Type: Research Papers
J. Turbomach. July 2025, 147(7): 071010.
Paper No: TURBO-24-1208
https://doi.org/10.1115/1.4067125
Published Online: December 13, 2024
View Articletitled, A Physics-Informed Neural Network for Solving the Inverse Heat Transfer Problem in Gas Turbine Rotating Cavities
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Topics: Artificial neural networks, Cavities, Heat, Heat transfer, Physics, Temperature, Temperature profiles, Compressors, Disks, Flux (Metallurgy)
Journal Articles

DEVELOPMENT OF MACHINE-LEARNT TURBULENCE CLOSURES FOR WAKE MIXING PREDICTIONS IN LOW-PRESSURE TURBINES

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Accepted Manuscript
Yuri Frey Marioni, Paolo Adami, Raul Vazquez Diaz, Andrea Cassinelli, Spencer J. Sherwin, Francesco Montomoli
Journal: Journal of Turbomachinery
Publisher: ASME
Article Type: Research Papers
J. Turbomach.
Paper No: TURBO-22-1316
https://doi.org/10.1115/1.4066919
Published Online: October 17, 2024
View Articletitled, DEVELOPMENT OF MACHINE-LEARNT TURBULENCE CLOSURES FOR WAKE MIXING PREDICTIONS IN LOW-PRESSURE TURBINES
Open the PDF for DEVELOPMENT OF MACHINE-LEARNT TURBULENCE CLOSURES FOR WAKE MIXING PREDICTIONS IN LOW-PRESSURE TURBINES in another window
Topics: Machinery, Pressure, Turbines, Turbochargers, Turbulence, Wakes, Artificial neural networks, Computational fluid dynamics, Aircraft engines, Algebra
Journal Articles

High-Dimensional Uncertainty Quantification of High-Pressure Turbine Vane Based on Multifidelity Deep Neural Networks

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Zhihui Li, Francesco Montomoli, Nicola Casari, Michele Pinelli
Journal: Journal of Turbomachinery
Publisher: ASME
Article Type: Research Papers
J. Turbomach. November 2023, 145(11): 111009.
Paper No: TURBO-23-1153
https://doi.org/10.1115/1.4063391
Published Online: October 4, 2023
View Articletitled, High-Dimensional Uncertainty Quantification of High-Pressure Turbine Vane Based on Multifidelity Deep Neural Networks
Open the PDF for High-Dimensional Uncertainty Quantification of High-Pressure Turbine Vane Based on Multifidelity Deep Neural Networks in another window
Topics: Artificial neural networks, Computational fluid dynamics, Design, Flow (Dynamics), Nozzles, Pressure, Turbines, Uncertainty quantification, Turbomachinery, Uncertainty
Journal Articles

Robust Design of Herringbone Grooved Journal Bearings Using Multi-Objective Optimization With Artificial Neural Networks

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Soheyl Massoudi, Jürg Schiffmann
Journal: Journal of Turbomachinery
Publisher: ASME
Article Type: Research Papers
J. Turbomach. November 2023, 145(11): 111010.
Paper No: TURBO-23-1158
https://doi.org/10.1115/1.4063392
Published Online: October 4, 2023
View Articletitled, Robust Design of Herringbone Grooved Journal Bearings Using Multi-Objective Optimization With Artificial Neural Networks
Open the PDF for Robust Design of Herringbone Grooved Journal Bearings Using Multi-Objective Optimization With Artificial Neural Networks in another window
Topics: Artificial neural networks, Bearings, Design, Journal bearings, Manufacturing, Optimization, Pareto optimization, Robustness, Rotors, Clearances (Engineering)
Journal Articles

Using Machine Learning for Loss Prediction in a Hybrid Meanline Modeling Method to Deliver Improved Radial Turbine Performance Prediction

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Pangbo Ren, Charles Stuart, Stephen Spence, Ryosuke Inomata, Takayuki Kobayashi, Isao Morita
Journal: Journal of Turbomachinery
Publisher: ASME
Article Type: Research Papers
J. Turbomach. July 2023, 145(7): 071013.
Paper No: TURBO-22-1300
https://doi.org/10.1115/1.4056777
Published Online: February 10, 2023
View Articletitled, Using Machine Learning for Loss Prediction in a Hybrid Meanline Modeling Method to Deliver Improved Radial Turbine Performance Prediction
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Topics: Computational fluid dynamics, Flow (Dynamics), Geometry, Machine learning, Modeling, Rotors, Turbines, Nozzles, Turbochargers, Artificial neural networks
Journal Articles

An Iterative Neural Operator to Predict the Thermo-Fluid Information in Internal Cooling Channels

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Li Yang, Qi Wang, Yu Rao
Journal: Journal of Turbomachinery
Publisher: ASME
Article Type: Research Papers
J. Turbomach. December 2022, 144(12): 121005.
Paper No: TURBO-22-1128
https://doi.org/10.1115/1.4055335
Published Online: September 15, 2022
View Articletitled, An Iterative Neural Operator to Predict the Thermo-Fluid Information in Internal Cooling Channels
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Topics: Artificial neural networks, Cooling, Errors, Heat flux, Heat transfer, Partial differential equations, Physics, Pressure, Temperature, Thermofluids
Journal Articles

Computer 3D Vision-Aided Full-3D Optimization of a Centrifugal Impeller

Available to Purchase
Cheng Ji, Zhiheng Wang, Guang Xi
Journal: Journal of Turbomachinery
Publisher: ASME
Article Type: Research Papers
J. Turbomach. September 2022, 144(9): 091011.
Paper No: TURBO-21-1228
https://doi.org/10.1115/1.4053744
Published Online: March 4, 2022
View Articletitled, Computer 3D Vision-Aided Full-3D Optimization of a Centrifugal Impeller
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Topics: Artificial neural networks, Blades, Computers, Flow (Dynamics), Impellers, Optimization, Pressure, Design, Shapes
Journal Articles

A New Loss Generation Body Force Model for Fan/Compressor Blade Rows: Application to Uniform and Non-Uniform Inflow in Rotor 67

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Syamak Pazireh, Jeffrey Defoe
Journal: Journal of Turbomachinery
Publisher: ASME
Article Type: Research Papers
J. Turbomach. June 2022, 144(6): 061005.
Paper No: TURBO-21-1022
https://doi.org/10.1115/1.4053231
Published Online: January 28, 2022
View Articletitled, A New Loss Generation Body Force Model for Fan/Compressor Blade Rows: Application to Uniform and Non-Uniform Inflow in Rotor 67
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Topics: Blades, Boundary layers, Compressors, Computation, Flow (Dynamics), Inflow, Pressure, Rotors, Design, Reynolds-averaged Navier–Stokes equations
Journal Articles

Direct and Inverse Model for Single-Hole Film Cooling With Machine Learning

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Haifeng Xing, Lei Luo, Wei Du, Songtao Wang
Journal: Journal of Turbomachinery
Publisher: ASME
Article Type: Research Papers
J. Turbomach. April 2022, 144(4): 041006.
Paper No: TURBO-21-1054
https://doi.org/10.1115/1.4052601
Published Online: November 5, 2021
View Articletitled, Direct and Inverse Model for Single-Hole Film Cooling With Machine Learning
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Topics: Artificial neural networks, Design, Errors, Film cooling, Machine learning, Coolants, Computational fluid dynamics, Density, Turbulence, Modeling
Journal Articles

Global Optimization of a Transonic Fan Blade Through AI-Enabled Active Subspaces

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Diego I. Lopez, Tiziano Ghisu, Shahrokh Shahpar
Journal: Journal of Turbomachinery
Publisher: ASME
Article Type: Research Papers
J. Turbomach. January 2022, 144(1): 011013.
Paper No: TURBO-21-1141
https://doi.org/10.1115/1.4052136
Published Online: September 21, 2021
View Articletitled, Global Optimization of a Transonic Fan Blade Through AI-Enabled Active Subspaces
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Topics: Blades, Design, Optimization, Computational fluid dynamics, Artificial neural networks
Journal Articles

Unsteady Steam Turbine Optimization Using High-Fidelity Computational Fluid Dynamics

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Vahid Iranidokht, Ilias Papagiannis, Anestis I. Kalfas, Reza S. Abhari, Shigeki Senoo, Kazuhiro Momma
Journal: Journal of Turbomachinery
Publisher: ASME
Article Type: Research Papers
J. Turbomach. September 2021, 143(9): 091006.
Paper No: TURBO-20-1367
https://doi.org/10.1115/1.4050441
Published Online: May 5, 2021
View Articletitled, Unsteady Steam Turbine Optimization Using High-Fidelity Computational Fluid Dynamics
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Topics: Computational fluid dynamics, Flow (Dynamics), Geometry, Optimization, Pressure, Rotors, Steam turbines, Blades, Cavities, Turbines
Journal Articles

Rapid Estimate of Wind Turbine Energy Loss Due to Blade Leading Edge Delamination Using Artificial Neural Networks

Available to Purchase
M. Sergio Campobasso, Anna Cavazzini, Edmondo Minisci
Journal: Journal of Turbomachinery
Publisher: ASME
Article Type: Research Papers
J. Turbomach. July 2020, 142(7): 071002.
Paper No: TURBO-19-1260
https://doi.org/10.1115/1.4047186
Published Online: June 26, 2020
View Articletitled, Rapid Estimate of Wind Turbine Energy Loss Due to Blade Leading Edge Delamination Using Artificial Neural Networks
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Topics: Airfoils, Blades, Computational fluid dynamics, Damage, Delamination, Geometry, Turbines, Wind turbines, Artificial neural networks, Energy dissipation
Journal Articles

Predicting the Operability of Damaged Compressors Using Machine Learning

Open Access
J. V. Taylor, B. Conduit, A. Dickens, C. Hall, M. Hillel, R. J. Miller
Journal: Journal of Turbomachinery
Publisher: ASME
Article Type: Research Papers
J. Turbomach. May 2020, 142(5): 051010.
Paper No: TURBO-19-1281
https://doi.org/10.1115/1.4046658
Published Online: April 30, 2020
View Articletitled, Predicting the Operability of Damaged Compressors Using Machine Learning
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Topics: Artificial neural networks, Blades, Compressors, Damage, Machine learning, Pressure, Parametrization
Journal Articles

Improving Pin-Fin Heat Transfer Predictions Using Artificial Neural Networks

Available to Purchase
Jason K. Ostanek
Journal: Journal of Turbomachinery
Publisher: ASME
Article Type: Research-Article
J. Turbomach. May 2014, 136(5): 051010.
Paper No: TURBO-13-1142
https://doi.org/10.1115/1.4025217
Published Online: September 27, 2013
View Articletitled, Improving Pin-Fin Heat Transfer Predictions Using Artificial Neural Networks
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Topics: Artificial neural networks, Heat transfer, Errors
Journal Articles

Optimization of a U-Bend for Minimal Pressure Loss in Internal Cooling Channels—Part I: Numerical Method

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Tom Verstraete, Filippo Coletti, Jérémy Bulle, Timothée Vanderwielen, Tony Arts
Journal: Journal of Turbomachinery
Publisher: ASME
Article Type: Research-Article
J. Turbomach. September 2013, 135(5): 051015.
Paper No: TURBO-12-1006
https://doi.org/10.1115/1.4023030
Published Online: June 28, 2013
View Articletitled, Optimization of a U-Bend for Minimal Pressure Loss in Internal Cooling Channels—Part I: Numerical Method
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Topics: Optimization, Pressure, Artificial neural networks, Design, Pressure drop, Databases, Cooling
Journal Articles

Mistuning Identification of Integrally Bladed Disks With Cascaded Optimization and Neural Networks

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Mehmet Ersin Yumer, Ender Cigeroglu, H. Nevzat Özgüven
Journal: Journal of Turbomachinery
Publisher: ASME
Article Type: Research-Article
J. Turbomach. May 2013, 135(3): 031008.
Paper No: TURBO-11-1259
https://doi.org/10.1115/1.4006667
Published Online: March 25, 2013
View Articletitled, Mistuning Identification of Integrally Bladed Disks With Cascaded Optimization and Neural Networks
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Topics: Artificial neural networks, Disks, Optimization, Blades, Mode shapes
Journal Articles

Multidisciplinary Optimization of a Radial Compressor for Microgas Turbine Applications

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T. Verstraete, Z. Alsalihi, R. A. Van den Braembussche
Journal: Journal of Turbomachinery
Publisher: ASME
Article Type: Research Papers
J. Turbomach. July 2010, 132(3): 031004.
https://doi.org/10.1115/1.3144162
Published Online: March 24, 2010
View Articletitled, Multidisciplinary Optimization of a Radial Compressor for Microgas Turbine Applications
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Topics: Artificial neural networks, Blades, Compressors, Design, Finite element analysis, Optimization, Stress, Databases, Geometry, Impellers