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Journal Articles

Virginia Tech Optical Inlet Sensor for Particle Detection: Rolls Royce M250 Turboshaft Demonstration

Brittney Antous, Gwibo Byun, K. Todd Lowe, C. Frederic Smith

Publisher: ASME

J. Eng. Gas Turbines Power.

Paper No: GTP-23-1285

https://doi.org/10.1115/1.4063584

Published Online: September 30, 2023

View Article titled, Virginia Tech Optical Inlet Sensor for Particle Detection: Rolls Royce M250 Turboshaft Demonstration

Topics: Particulate matter, Sensors, Sands, Engines, Damage, Flow (Dynamics), Machine learning, Electromagnetic scattering, Errors, Failure

Journal Articles

Machine Learning Based Optimizer for Tilting Pad Journal Bearing Inlet Flowrate

Edoardo Gheller, Steven Chatterton, Daniele Panara, Gabriele Turini, Paolo Pennacchi

Publisher: ASME

J. Eng. Gas Turbines Power.

Paper No: GTP-23-1323

https://doi.org/10.1115/1.4063532

Published Online: September 29, 2023

View Article titled, Machine Learning Based Optimizer for Tilting Pad Journal Bearing Inlet Flowrate

Topics: Journal bearings, Machine learning, Bearings, Artificial neural networks, Fluid films, Optimization, Compressors, Design, Economics , Energy generation

Journal Articles

Multi-Objective Experimental Combustor Development Using Surrogate Model-Based Optimization

Johann Moritz Reumschüssel, Jakob G.R. von Saldern, Bernhard Cosic, Christian Oliver Paschereit

Publisher: ASME

J. Eng. Gas Turbines Power.

Paper No: GTP-23-1361

https://doi.org/10.1115/1.4063535

Published Online: September 29, 2023

View Article titled, Multi-Objective Experimental Combustor Development Using Surrogate Model-Based Optimization

Topics: Combustion chambers, Optimization, Fuels, Stress, Design, Emissions, Combustion, Combustion systems, Ejectors, Errors

Journal Articles

POD-Based Surrogate Modeling Approximation for Aeroengines Nonlinear Unbalance Responses

Francesco D'alessandro, Hugo Festjens, Gael Chevallier, Scott Cogan, Tariq Benamara, Caroline Sainvitu

Publisher: ASME

J. Eng. Gas Turbines Power.

Paper No: GTP-23-1345

https://doi.org/10.1115/1.4063519

Published Online: September 29, 2023

View Article titled, POD-Based Surrogate Modeling Approximation for Aeroengines Nonlinear Unbalance Responses

Topics: Approximation, Metamodeling, Finite element model, Rotors, Calibration, Computer simulation, Damping, Design, Event history analysis, Experimental design

Journal Articles

Prediction Enhancement of Machine Learning Using Time Series Modeling in Gas Turbines

Vipul Goyal, Mengyu Xu, Jayanta Kapat, Ladislav Veselý

Publisher: ASME

J. Eng. Gas Turbines Power.

Paper No: GTP-23-1306

https://doi.org/10.1115/1.4063459

Published Online: September 16, 2023

View Article titled, Prediction Enhancement of Machine Learning Using Time Series Modeling in Gas Turbines

Topics: Gas turbines, Machine learning, Modeling, Time series, Algorithms, Blades, Combined cycles, Power stations, Quality control charts, Signal to noise ratio

Journal Articles

Supercritical Carbon Dioxide Shock Behaviour Near The Critical Point

Jinhong Wang, Teng Cao, Ricardo F. Martinez-Botas

Publisher: ASME

J. Eng. Gas Turbines Power.

Paper No: GTP-23-1414

https://doi.org/10.1115/1.4063384

Published Online: September 8, 2023

View Article titled, Supercritical Carbon Dioxide Shock Behaviour Near The Critical Point

Topics: Shock (Mechanics), Supercritical carbon dioxide, Fluids, Carbon dioxide, Algorithms, Design, Entropy, Equations of state, Errors, Mach number

Journal Articles

Statistical Rule Extraction for Gas Turbine Trip Prediction

Giovanni Bechini, Enzo Losi, Lucrezia Manservigi, Giovanni Pagliarini, Guido Sciavicco, Ionel Eduard Stan, Mauro Venturini

J. Eng. Gas Turbines Power. May 2023, 145(5): 051017.

Paper No: GTP-22-1408

https://doi.org/10.1115/1.4056287

Published Online: January 10, 2023

View Article titled, Statistical Rule Extraction for Gas Turbine Trip Prediction

Topics: Gas turbines, Statistical analysis, Turbines, Machine learning, Time series

Journal Articles

Machine Learning-Enabled Prediction of Transient Injection Map in Automotive Injectors With Uncertainty Quantification

Sudeepta Mondal, Gina M. Magnotti, Bethany Lusch, Romit Maulik, Roberto Torelli

J. Eng. Gas Turbines Power. April 2023, 145(4): 041015.

Paper No: GTP-22-1451

https://doi.org/10.1115/1.4055777

Published Online: December 13, 2022

View Article titled, Machine Learning-Enabled Prediction of Transient Injection Map in Automotive Injectors With Uncertainty Quantification

Topics: Design, Ejectors, Needles, Porosity, Simulation, Transients (Dynamics), Uncertainty, Uncertainty quantification, Spatiotemporal phenomena, Internal flow

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

https://doi.org/10.1115/1.4055417

Published Online: December 8, 2022

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

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

Journal Articles

Ensemble Learning Approach to the Prediction of Gas Turbine Trip

Enzo Losi, Mauro Venturini, Lucrezia Manservigi, Giovanni Bechini

J. Eng. Gas Turbines Power. February 2023, 145(2): 021009.

Paper No: GTP-22-1319

https://doi.org/10.1115/1.4055905

Published Online: November 28, 2022

View Article titled, Ensemble Learning Approach to the Prediction of Gas Turbine Trip

Topics: Gas turbines, Machine learning, Reliability, Support vector machines, Artificial neural networks, Testing, Algorithms, Probability

Journal Articles

Application of Machine Learning to Forced Response Predictions of an Industrial Axial Compressor Rotor Blade

Giuseppe Bruni, Senthil Krishnababu, Simon Jackson

J. Eng. Gas Turbines Power. January 2023, 145(1): 011019.

Paper No: GTP-22-1341

https://doi.org/10.1115/1.4055634

Published Online: October 21, 2022

View Article titled, Application of Machine Learning to Forced Response Predictions of an Industrial Axial Compressor Rotor Blade

Topics: Artificial neural networks, Blades, Compressors, Computational fluid dynamics, Damping, Design, Machine learning, Mode shapes, Resonance, Modal analysis

Journal Articles

Prediction of Gas Turbine Trip: A Novel Methodology Based on Random Forest Models

Enzo Losi, Mauro Venturini, Lucrezia Manservigi, Giuseppe Fabio Ceschini, Giovanni Bechini, Giuseppe Cota, Fabrizio Riguzzi

J. Eng. Gas Turbines Power. March 2022, 144(3): 031025.

Paper No: GTP-21-1324

https://doi.org/10.1115/1.4053194

Published Online: January 21, 2022

View Article titled, Prediction of Gas Turbine Trip: A Novel Methodology Based on Random Forest Models

Topics: Gas turbines, Reliability, Machine learning, Time series, Temperature, Compressors, Image segmentation, Natural, scientific and engineering processes and practices, Sensors, Thermocouples

Journal Articles

Bayesian Machine Learning for the Prognosis of Combustion Instabilities From Noise

Ushnish Sengupta, Carl E. Rasmussen, Matthew P. Juniper

J. Eng. Gas Turbines Power. July 2021, 143(7): 071001.

Paper No: GTP-20-1599

https://doi.org/10.1115/1.4049762

Published Online: March 29, 2021

View Article titled, Bayesian Machine Learning for the Prognosis of Combustion Instabilities From Noise

Topics: Acoustics, Artificial neural networks, Combustion, Combustion chambers, Machine learning, Noise (Sound), Turbulence

Journal Articles

Combustion Tuning for a Gas Turbine Power Plant Using Data-Driven and Machine Learning Approach

Suhui Li, Huaxin Zhu, Min Zhu, Gang Zhao, Xiaofeng Wei

J. Eng. Gas Turbines Power. March 2021, 143(3): 031021.

Paper No: GTP-20-1699

https://doi.org/10.1115/1.4050020

Published Online: February 24, 2021

View Article titled, Combustion Tuning for a Gas Turbine Power Plant Using Data-Driven and Machine Learning Approach

Topics: Artificial neural networks, Combustion, Combustion chambers, Emissions, Fuels, Gas turbines, Nitrogen oxides, Optimization, Machine learning, Stress

Journal Articles

Water Droplet Erosion Life Prediction Method for Steam Turbine Blade Materials Based on Image Recognition and Machine Learning

Zheyuan Zhang, Tianyuan Liu, Di Zhang, Yonghui Xie

J. Eng. Gas Turbines Power. March 2021, 143(3): 031009.

Paper No: GTP-20-1628

https://doi.org/10.1115/1.4049768

Published Online: February 8, 2021

View Article titled, Water Droplet Erosion Life Prediction Method for Steam Turbine Blade Materials Based on Image Recognition and Machine Learning

Topics: Blades, Drops, Erosion, Machine learning, Steam turbines, Water, Service life (Equipment), Testing, Turbine blades, Data acquisition

Journal Articles

Comparison of Machine Learning Algorithms in the Interpolation and Extrapolation of Flame Describing Functions

Michael McCartney, Matthias Haeringer, Wolfgang Polifke

J. Eng. Gas Turbines Power. June 2020, 142(6): 061009.

Paper No: GTP-19-1608

https://doi.org/10.1115/1.4045516

Published Online: May 29, 2020

View Article titled, Comparison of Machine Learning Algorithms in the Interpolation and Extrapolation of Flame Describing Functions

Topics: Algorithms, Errors, Interpolation, Machine learning, Flames, Splines, Limit cycles

Journal Articles

Using Machine Learning to Predict Core Sizes of High-Efficiency Turbofan Engines

Michael T. Tong

J. Eng. Gas Turbines Power. November 2019, 141(11): 111023.

Paper No: GTP-19-1338

https://doi.org/10.1115/1.4044770

Published Online: October 23, 2019

View Article titled, Using Machine Learning to Predict Core Sizes of High-Efficiency Turbofan Engines

Topics: Algorithms, Engines, Machine learning, Turbofans, Databases

Journal Articles

Evaluating Optimization Strategies for Engine Simulations Using Machine Learning Emulators

Daniel M. Probst, Mandhapati Raju, Peter K. Senecal, Janardhan Kodavasal, Pinaki Pal, Sibendu Som, Ahmed A. Moiz, Yuanjiang Pei

J. Eng. Gas Turbines Power. September 2019, 141(9): 091011.

Paper No: GTP-19-1208

https://doi.org/10.1115/1.4043964

Published Online: June 20, 2019

View Article titled, Evaluating Optimization Strategies for Engine Simulations Using Machine Learning Emulators

Topics: Algorithms, Engines, Optimization, Simulation, Machine learning

Journal Articles

Diesel Engine Acoustic Emission Airflow Clogging Diagnostics With Machine Learning

Jim Cowart, Patrick Moore, Harrison Yosten, Leonard Hamilton, Dianne Luning Prak

J. Eng. Gas Turbines Power. July 2019, 141(7): 071021.

Paper No: GTP-19-1119

https://doi.org/10.1115/1.4043332

Published Online: April 15, 2019

View Article titled, Diesel Engine Acoustic Emission Airflow Clogging Diagnostics With Machine Learning

Topics: Acoustic emissions, Acoustics, Air flow, Artificial neural networks, Combustion, Diesel engines, Engines, Machine learning, Microphones, Laptop computers

Journal citation

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Manuscript

Virginia Tech Optical Inlet Sensor for Particle Detection: Rolls Royce M250 Turboshaft Demonstration

Machine Learning Based Optimizer for Tilting Pad Journal Bearing Inlet Flowrate

Multi-Objective Experimental Combustor Development Using Surrogate Model-Based Optimization

POD-Based Surrogate Modeling Approximation for Aeroengines Nonlinear Unbalance Responses

Prediction Enhancement of Machine Learning Using Time Series Modeling in Gas Turbines

Supercritical Carbon Dioxide Shock Behaviour Near The Critical Point

Statistical Rule Extraction for Gas Turbine Trip Prediction

Machine Learning-Enabled Prediction of Transient Injection Map in Automotive Injectors With Uncertainty Quantification

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

Ensemble Learning Approach to the Prediction of Gas Turbine Trip

Application of Machine Learning to Forced Response Predictions of an Industrial Axial Compressor Rotor Blade

Prediction of Gas Turbine Trip: A Novel Methodology Based on Random Forest Models

Bayesian Machine Learning for the Prognosis of Combustion Instabilities From Noise

Combustion Tuning for a Gas Turbine Power Plant Using Data-Driven and Machine Learning Approach

Water Droplet Erosion Life Prediction Method for Steam Turbine Blade Materials Based on Image Recognition and Machine Learning

Comparison of Machine Learning Algorithms in the Interpolation and Extrapolation of Flame Describing Functions

Using Machine Learning to Predict Core Sizes of High-Efficiency Turbofan Engines

Evaluating Optimization Strategies for Engine Simulations Using Machine Learning Emulators

Diesel Engine Acoustic Emission Airflow Clogging Diagnostics With Machine Learning

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