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Journal Articles

Inverse Aerodynamic Design of Gas Turbine Blades Using Probabilistic Machine Learning

Sayan Ghosh, Govinda Anantha Padmanabha, Cheng Peng, Valeria Andreoli, Steven Atkinson, Piyush Pandita, Thomas Vandeputte, Nicholas Zabaras, Liping Wang

J. Mech. Des. February 2022, 144(2): 021706.

Paper No: MD-21-1275

DOI: https://doi.org/10.1115/1.4052301

Published Online: September 21, 2021

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Topics: Design, Modeling, Machine learning, Blades, Computational fluid dynamics

Proceedings Papers

A Probabilistic Machine Learning Framework for Explicit Inverse Design of Industrial Gas Turbine Blades

Sayan Ghosh, Valeria Andreoli, Govinda A. Padmanabha, Cheng Peng, Steven Atkinson, Piyush Pandita, Thomas Vandeputte, Nicholas Zabaras, Liping Wang

Proc. ASME. GT2021, Volume 9B: Structures and Dynamics — Fatigue, Fracture, and Life Prediction; Probabilistic Methods; Rotordynamics; Structural Mechanics and Vibration, V09BT27A003, June 7–11, 2021

Paper No: GT2021-58842

DOI: https://doi.org/10.1115/GT2021-58842

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Topics: Design, Industrial gases, Machine learning, Turbine blades

Journal Articles

Particle Image Velocimetry in a High-Pressure Turbine Stage at Aerodynamically Engine Representative Conditions

Daniel Inman, David G. Cuadrado, Valeria Andreoli, Jordan Fisher, Guillermo Paniagua, Papa Aye N. Aye-Addo, Lakshya Bhatnagar, Francisco Lozano, Terrence Meyer, Matthew Bloxham

J. Eng. Gas Turbines Power. June 2021, 143(6): 061031.

Paper No: GTP-20-1422

DOI: https://doi.org/10.1115/1.4049448

Published Online: March 31, 2021

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Topics: Flow (Dynamics), Lasers, Particulate matter, Probes, Turbines, High pressure (Physics), Computational fluid dynamics, Engines

Proceedings Papers

Particle Image Velocimetry in a High-Pressure Turbine Stage at Aerodynamically Engine Representative Conditions

Daniel Inman, David G. Cuadrado, Valeria Andreoli, Jordan Fisher, Guillermo Paniagua, Papa Aye N. Aye-Addo, Lakshya Bhatnagar, Francisco Lozano, Terrence Meyer, Matthew Bloxham

Proc. ASME. GT2020, Volume 5: Controls, Diagnostics, and Instrumentation; Cycle Innovations; Cycle Innovations: Energy Storage, V005T05A015, September 21–25, 2020

Paper No: GT2020-15013

DOI: https://doi.org/10.1115/GT2020-15013

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Topics: Engines, High pressure (Physics), Particulate matter, Turbines, Flow (Dynamics), Cascades (Fluid dynamics), Geometry, Calibration, Computer software, Electromagnetic scattering

Journal Articles

Aerothermal Optimization of Fully Cooled Turbine Blade Tips

Valeria Andreoli, James Braun, Guillermo Paniagua, Cis De Maesschalck, Matthew Bloxham, William Cummings, Lawrence Langford

J. Turbomach. June 2019, 141(6): 061007.

Paper No: TURBO-18-1299

DOI: https://doi.org/10.1115/1.4041961

Published Online: January 21, 2019

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Topics: Blades, Flow (Dynamics), Geometry, Heat flux, Optimization, Pressure, Rotors, Turbines, Cooling, Coolants

Journal Articles

Engine-Scalable Rotor Casing Convective Heat Flux Evaluation Using Inverse Heat Transfer Methods

David Gonzalez Cuadrado, Francisco Lozano, Valeria Andreoli, Guillermo Paniagua

J. Eng. Gas Turbines Power. January 2019, 141(1): 011012.

Paper No: GTP-18-1323

DOI: https://doi.org/10.1115/1.4040713

Published Online: September 14, 2018

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Topics: Engines, Heat flux, Heat transfer, Temperature, Rotors, Pressure, Turbines

Proceedings Papers

Engine-Scalable Rotor Casing Convective Heat Flux Evaluation Using Inverse Heat Transfer Methods

David G. Cuadrado, Francisco Lozano, Valeria Andreoli, Guillermo Paniagua

Proc. ASME. GT2018, Volume 6: Ceramics; Controls, Diagnostics, and Instrumentation; Education; Manufacturing Materials and Metallurgy, V006T05A028, June 11–15, 2018

Paper No: GT2018-76906

DOI: https://doi.org/10.1115/GT2018-76906

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Topics: Engines, Heat flux, Heat transfer, Rotors, Temperature, Boundary-value problems, Dimensionless numbers, Exterior walls, Filters, Geometry

Journal Articles

Prediction of the Turbine Tip Convective Heat Flux Using Discrete Green's Functions

Valeria Andreoli, David G. Cuadrado, Guillermo Paniagua

J. Heat Transfer. July 2018, 140(7): 071703.

Paper No: HT-17-1419

DOI: https://doi.org/10.1115/1.4039182

Published Online: March 30, 2018

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Topics: Heat flux, Temperature, Turbines, Flow (Dynamics), Clearances (Engineering), Blades, Wall temperature, Uncertainty, Rotors

Proceedings Papers

Prediction of the Turbine Tip Convective Heat Flux Using Discrete Green Functions

Valeria Andreoli, David G. Cuadrado, Guillermo Paniagua

Proc. ASME. GT2017, Volume 5B: Heat Transfer, V05BT22A011, June 26–30, 2017

Paper No: GT2017-64080

DOI: https://doi.org/10.1115/GT2017-64080

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Topics: Heat flux, Turbines, Temperature, Rotors, Geometry, Convection, Engineering simulation, Flow (Dynamics), Simulation, Wall temperature

Journal citation

NARROW

Inverse Aerodynamic Design of Gas Turbine Blades Using Probabilistic Machine Learning

A Probabilistic Machine Learning Framework for Explicit Inverse Design of Industrial Gas Turbine Blades

Particle Image Velocimetry in a High-Pressure Turbine Stage at Aerodynamically Engine Representative Conditions

Particle Image Velocimetry in a High-Pressure Turbine Stage at Aerodynamically Engine Representative Conditions

Aerothermal Optimization of Fully Cooled Turbine Blade Tips

Engine-Scalable Rotor Casing Convective Heat Flux Evaluation Using Inverse Heat Transfer Methods

Engine-Scalable Rotor Casing Convective Heat Flux Evaluation Using Inverse Heat Transfer Methods

Prediction of the Turbine Tip Convective Heat Flux Using Discrete Green's Functions

Prediction of the Turbine Tip Convective Heat Flux Using Discrete Green Functions

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