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Journal Articles

Machine-Learning Clustering Methods Applied to Detection of Noise Sources in Low-Speed Axial Fan

Lorenzo Tieghi, Stefan Becker, Alessandro Corsini, Giovanni Delibra, Stefan Schoder, Felix Czwielong

J. Eng. Gas Turbines Power. March 2023, 145(3): 031020.

Paper No: GTP-22-1291

DOI: https://doi.org/10.1115/1.4055417

Published Online: December 8, 2022

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Topics: Algorithms, Blades, Flow (Dynamics), Machine learning, Noise (Sound), Simulation, Optimization, Pressure, Turbulence, Computation

Proceedings Papers

Machine-Learning Clustering Methods Applied to Detection of Noise Sources in Low-Speed Axial Fan

Lorenzo Tieghi, Stefan Becker, Alessandro Corsini, Giovanni Delibra, Stefan Schoder, Felix Czwielong

Proc. ASME. GT2022, Volume 5: Education; Electric Power; Fans and Blowers, V005T10A008, June 13–17, 2022

Paper No: GT2022-82116

DOI: https://doi.org/10.1115/GT2022-82116

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Topics: Machine learning, Noise (Sound), Algorithms, Design, Fans, Simulation, Acoustics, Aerodynamic noise, Blades, Density

Proceedings Papers

Cascade With Sinusoidal Leading Edges: Identification And Quantification of Deflection With Unsupervised Machine Learning

Alessandro Corsini, Giovanni Delibra, Lorenzo Tieghi, Francesco Aldo Tucci

Proc. ASME. GT2021, Volume 1: Aircraft Engine; Fans and Blowers; Marine; Wind Energy; Scholar Lecture, V001T10A006, June 7–11, 2021

Paper No: GT2021-59277

DOI: https://doi.org/10.1115/GT2021-59277

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Topics: Cascades (Fluid dynamics), Deflection, Machine learning

Journal Articles

A Machine-Learnt Wall Function for Rotating Diffusers

Lorenzo Tieghi, Alessandro Corsini, Giovanni Delibra, Francesco Aldo Tucci

J. Turbomach. August 2021, 143(8): 081012.

Paper No: TURBO-20-1368

DOI: https://doi.org/10.1115/1.4050442

Published Online: May 3, 2021

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Topics: Algorithms, Computer simulation, Diffusers, Flow (Dynamics), Machinery, Modeling, Reynolds-averaged Navier–Stokes equations, Simulation, Turbulence, Machine learning

Journal Articles

Assessment of MULTALL as Computational Fluid Dynamics Code for the Analysis of Tube-Axial Fans

Piero Danieli, Massimo Masi, Giovanni Delibra, Alessandro Corsini, Andrea Lazzaretto

J. Turbomach. July 2021, 143(7): 071005.

Paper No: TURBO-20-1338

DOI: https://doi.org/10.1115/1.4050445

Published Online: April 9, 2021

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Topics: Computational fluid dynamics, Rotors, Turbulence, Fans, Density

Proceedings Papers

Prediction of Ventilation Effectiveness for LM9000 Package With Machine Learning

Alessandro Corsini, Giovanni Delibra, Marco Giovannelli, Gabriele Lucherini, Stefano Minotti, Stefano Rossin, Lorenzo Tieghi

Proc. ASME. GT2020, Volume 9: Oil and Gas Applications; Organic Rankine Cycle Power Systems; Steam Turbine, V009T21A006, September 21–25, 2020

Paper No: GT2020-14916

DOI: https://doi.org/10.1115/GT2020-14916

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Topics: Machine learning, Ventilation, Computational fluid dynamics, Artificial neural networks, Simulation, Gas turbines, Acoustics, Algorithms, Explosions, Flanges

Proceedings Papers

Assessment of MULTALL As CFD Code for the Analysis of Tube-Axial Fans

Piero Danieli, Massimo Masi, Giovanni Delibra, Alessandro Corsini, Andrea Lazzaretto

Proc. ASME. GT2020, Volume 1: Aircraft Engine; Fans and Blowers, V001T10A006, September 21–25, 2020

Paper No: GT2020-14963

DOI: https://doi.org/10.1115/GT2020-14963

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Topics: Axial flow, Computational fluid dynamics, Fans

Proceedings Papers

Identification of Losses in Turbomachinery With Machine Learning

Gino Angelini, Alessandro Corsini, Giovanni Delibra, Marco Giovannelli

Proc. ASME. GT2020, Volume 1: Aircraft Engine; Fans and Blowers, V001T10A008, September 21–25, 2020

Paper No: GT2020-15337

DOI: https://doi.org/10.1115/GT2020-15337

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Topics: Machine learning, Turbomachinery, Cascades (Fluid dynamics), Experimental design, Flow (Dynamics), Algorithms, Artificial neural networks, Boundary layers, Computational fluid dynamics, Design

Proceedings Papers

Machine Learnt Synthetic Turbulence for LES Inflow Conditions

Alessandro Corsini, Giovanni Delibra, Marco Giovannelli, Stefania Traldi

Proc. ASME. GT2020, Volume 1: Aircraft Engine; Fans and Blowers, V001T10A009, September 21–25, 2020

Paper No: GT2020-15338

DOI: https://doi.org/10.1115/GT2020-15338

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Topics: Inflow, Machinery, Turbulence

Proceedings Papers

A Machine-Learnt Wall Function for Rotating Diffusers

Lorenzo Tieghi, Alessandro Corsini, Giovanni Delibra, Francesco Aldo Tucci

Proc. ASME. GT2020, Volume 1: Aircraft Engine; Fans and Blowers, V001T10A010, September 21–25, 2020

Paper No: GT2020-15353

DOI: https://doi.org/10.1115/GT2020-15353

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Topics: Diffusers, Machinery, Flow (Dynamics), Boundary layers, Machine learning, Turbomachinery, Turbulence, Computational fluid dynamics, Kinetic energy, Modeling

Journal Articles

Assessment of a Machine-Learnt Adaptive Wall-Function in a Compressor Cascade With Sinusoidal Leading Edge

Lorenzo Tieghi, Alessandro Corsini, Giovanni Delibra, Gino Angelini

J. Eng. Gas Turbines Power. December 2020, 142(12): 121011.

Paper No: GTP-20-1311

DOI: https://doi.org/10.1115/1.4048568

Published Online: December 1, 2020

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Topics: Airfoils, Algorithms, Artificial neural networks, Turbulence, Cascades (Fluid dynamics), Simulation, Compressors

Proceedings Papers

Modelling of Sonic Jets for Gas Leak Applications

Stefano Minotti, Alessandro Corsini, Giovanni Delibra, Gabriele Lucherini, Stefano Rossin, Lorenzo Tieghi, Stefania Traldi

Proc. ASME. GT2019, Volume 9: Oil and Gas Applications; Supercritical CO2 Power Cycles; Wind Energy, V009T27A024, June 17–21, 2019

Paper No: GT2019-91199

DOI: https://doi.org/10.1115/GT2019-91199

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Topics: Jets, Leakage, Modeling, Gaseous fuels, Computational fluid dynamics, Engineering simulation, Gas turbines, Simulation, Design, Explosives

Proceedings Papers

Assessment of a Machine-Learnt Adaptive Wall-Function in a Compressor Cascade With Sinusoidal Leading Edge

Lorenzo Tieghi, Alessandro Corsini, Giovanni Delibra, Gino Angelini

Proc. ASME. GT2019, Volume 1: Aircraft Engine; Fans and Blowers; Marine; Honors and Awards, V001T09A004, June 17–21, 2019

Paper No: GT2019-91238

DOI: https://doi.org/10.1115/GT2019-91238

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Topics: Cascades (Fluid dynamics), Compressors, Machinery, Artificial neural networks, Simulation, Computation, Boundary layers, Flow (Dynamics), Aerodynamic noise, Airfoils

Proceedings Papers

A Multi-Dimensional Extension of Balje Chart for Axial Flow Turbomachinery Using Artificial Intelligence Based Meta-Models

Gino Angelini, Alessandro Corsini, Giovanni Delibra, Lorenzo Tieghi

Proc. ASME. GT2019, Volume 1: Aircraft Engine; Fans and Blowers; Marine; Honors and Awards, V001T09A009, June 17–21, 2019

Paper No: GT2019-91588

DOI: https://doi.org/10.1115/GT2019-91588

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Topics: Artificial intelligence, Axial flow, Blades, Computer software, Design, Kinematics, Machine learning, Principal component analysis, Rotors, Turbomachinery

Proceedings Papers

Identification of Poorly Ventilated Zones in Gas-Turbine Enclosures With Machine Learning

Alessandro Corsini, Giovanni Delibra, Marco Giovannelli, Gabriele Lucherini, Stefano Minotti, Stefano Rossin, Lorenzo Tieghi

Proc. ASME. GT2019, Volume 1: Aircraft Engine; Fans and Blowers; Marine; Honors and Awards, V001T09A003, June 17–21, 2019

Paper No: GT2019-91198

DOI: https://doi.org/10.1115/GT2019-91198

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Topics: Gas turbines, Machine learning, Artificial neural networks, Computation, Flow (Dynamics), Gaseous fuels, Leakage, Reynolds-averaged Navier–Stokes equations, Ventilation, Air flow

Journal Articles

A Multidimensional Extension of Balje Chart for Axial Flow Turbomachinery Using Artificial Intelligence-Based Meta-Models

Gino Angelini, Alessandro Corsini, Giovanni Delibra, Lorenzo Tieghi

J. Eng. Gas Turbines Power. November 2019, 141(11): 111012.

Paper No: GTP-19-1439

DOI: https://doi.org/10.1115/1.4044935

Published Online: October 16, 2019

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Topics: Axial flow, Blades, Cascades (Fluid dynamics), Design, Principal component analysis, Turbomachinery, Fans, Flow (Dynamics), Artificial neural networks, Chords (Trusses)

Proceedings Papers

A Meta-Model for Aerodynamic Properties of a Reversible Profile in Cascade With Variable Stagger and Solidity

Gino Angelini, Tommaso Bonanni, Alessandro Corsini, Giovanni Delibra, Lorenzo Tieghi, David Volponi

Proc. ASME. GT2018, Volume 1: Aircraft Engine; Fans and Blowers; Marine, V001T09A009, June 11–15, 2018

Paper No: GT2018-76363

DOI: https://doi.org/10.1115/GT2018-76363

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Topics: Cascades (Fluid dynamics), Computer software, Computational fluid dynamics, Simulation, Drag (Fluid dynamics), Reynolds number, Airfoils, Blades, Reynolds-averaged Navier–Stokes equations

Proceedings Papers

Development and Validation of a Novel Synthetic Blade Model for Axial Flow Fans in Unsteady CFD

Tommaso Bonanni, Alessandro Corsini, Giovanni Delibra, David Volponi

Proc. ASME. GT2017, Volume 1: Aircraft Engine; Fans and Blowers; Marine; Honors and Awards, V001T09A005, June 26–30, 2017

Paper No: GT2017-63952

DOI: https://doi.org/10.1115/GT2017-63952

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Topics: Axial flow, Blades, Computational fluid dynamics, Fans, Actuators, Disks, Momentum, Deflection, Fluids, Rotation

Proceedings Papers

Design of a Single Stage Variable Pitch Axial Fan

Tommaso Bonanni, Alessandro Corsini, Giovanni Delibra, David Volponi, Anthony G. Sheard, Mark Bublitz

Proc. ASME. GT2017, Volume 1: Aircraft Engine; Fans and Blowers; Marine; Honors and Awards, V001T09A011, June 26–30, 2017

Paper No: GT2017-64517

DOI: https://doi.org/10.1115/GT2017-64517

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Topics: Design, Blades, Computational fluid dynamics, Design methodology, Fans, Vortices, Aerospace industry, Airfoils, Chords (Trusses), Experimental design

Proceedings Papers

Derivative Design of Axial Fan Range: From Academia to Industry

Tommaso Bonanni, Lucio Cardillo, Alessandro Corsini, Giovanni Delibra, Anthony G. Sheard, David Volponi

Proc. ASME. GT2016, Volume 6: Ceramics; Controls, Diagnostics and Instrumentation; Education; Manufacturing Materials and Metallurgy, V006T07A006, June 13–17, 2016

Paper No: GT2016-57469

DOI: https://doi.org/10.1115/GT2016-57469

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Topics: Design, Blades, Design methodology, Modal assurance criterion, Actuators, Diffusion (Physics), Disks, Education, Errors, Fans

Journal citation

NARROW

Machine-Learning Clustering Methods Applied to Detection of Noise Sources in Low-Speed Axial Fan

Machine-Learning Clustering Methods Applied to Detection of Noise Sources in Low-Speed Axial Fan

Cascade With Sinusoidal Leading Edges: Identification And Quantification of Deflection With Unsupervised Machine Learning

A Machine-Learnt Wall Function for Rotating Diffusers

Assessment of MULTALL as Computational Fluid Dynamics Code for the Analysis of Tube-Axial Fans

Prediction of Ventilation Effectiveness for LM9000 Package With Machine Learning

Assessment of MULTALL As CFD Code for the Analysis of Tube-Axial Fans

Identification of Losses in Turbomachinery With Machine Learning

Machine Learnt Synthetic Turbulence for LES Inflow Conditions

A Machine-Learnt Wall Function for Rotating Diffusers

Assessment of a Machine-Learnt Adaptive Wall-Function in a Compressor Cascade With Sinusoidal Leading Edge

Modelling of Sonic Jets for Gas Leak Applications

Assessment of a Machine-Learnt Adaptive Wall-Function in a Compressor Cascade With Sinusoidal Leading Edge

A Multi-Dimensional Extension of Balje Chart for Axial Flow Turbomachinery Using Artificial Intelligence Based Meta-Models

Identification of Poorly Ventilated Zones in Gas-Turbine Enclosures With Machine Learning

A Multidimensional Extension of Balje Chart for Axial Flow Turbomachinery Using Artificial Intelligence-Based Meta-Models

A Meta-Model for Aerodynamic Properties of a Reversible Profile in Cascade With Variable Stagger and Solidity

Development and Validation of a Novel Synthetic Blade Model for Axial Flow Fans in Unsteady CFD

Design of a Single Stage Variable Pitch Axial Fan

Derivative Design of Axial Fan Range: From Academia to Industry

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