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Mauro Venturini
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Journal Articles

Data-Driven Generative Model Aimed to Create Synthetic Data for the Long-Term Forecast of Gas Turbine Operation

Enzo Losi, Lucrezia Manservigi, Pier Ruggero Spina, Mauro Venturini
Journal: Journal of Engineering for Gas Turbines and Power
Publisher: ASME
Article Type: Research-Article
J. Eng. Gas Turbines Power. March 2025, 147(3): 031006.
Paper No: GTP-24-1503
https://doi.org/10.1115/1.4066360
Published Online: October 3, 2024
View Article titled, Data-Driven Generative Model Aimed to Create Synthetic Data for the Long-Term Forecast of Gas Turbine Operation
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Topics: Compressors, Errors, Gas turbines, Generative adversarial networks, Generators, Reliability, Trains, Artificial neural networks
Proceedings Papers

Analysis of Pumped Hydro Storage Using Mines As Hydro Reservoirs

Giulia Anna Maria Castorino, Erik Dahlquist, Konstantinos Kyprianidis, Enzo Losi, Lucrezia Manservigi, Michele Pinelli, Avinash Renuke, Pier Ruggero Spina, Mauro Venturini
Proc. ASME. GT2024, Volume 6: Education; Electric Power; Energy Storage; Fans and Blowers, V006T09A001, June 24–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: GT2024-121988
https://doi.org/10.1115/GT2024-121988
View Paper titled, Analysis of Pumped Hydro Storage Using Mines As Hydro Reservoirs
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Topics: Reservoirs, Storage, Energy / power systems, Economics , Energy storage, Hydroelectric power stations, Hydropower, Nuclear power stations, Power grids, Solar power stations
Proceedings Papers

Energy and Economic Optimization of the Design and Operation of Hybrid Energy Plants Under Current and Future Economic Scenarios

Giulia Anna Maria Castorino, Enzo Losi, Lucrezia Manservigi, Michele Pinelli, Pier Ruggero Spina, Mauro Venturini
Proc. ASME. GT2024, Volume 8: Heat Transfer: Internal Air Systems; Heat Transfer: Internal Cooling; Industrial and Cogeneration, V008T16A002, June 24–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: GT2024-121980
https://doi.org/10.1115/GT2024-121980
View Paper titled, Energy and Economic Optimization of the Design and Operation of Hybrid Energy Plants Under Current and Future Economic Scenarios
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Topics: Design, Economics , Optimization, Renewable energy, Absorption, Algorithms, Energy / power systems, Heat pumps, Boilers, Carbon dioxide
Proceedings Papers

Unsupervised Methodology for the Prognostics of Gas Turbine Abrupt Faults

Enzo Losi, Mauro Venturini, Lucrezia Manservigi, Giovanni Bechini
Proc. ASME. GT2024, Volume 9: Manufacturing Materials and Metallurgy; Microturbines, Turbochargers, and Small Turbomachines; Oil & Gas Applications; Steam Turbine, V009T19A007, June 24–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: GT2024-122163
https://doi.org/10.1115/GT2024-122163
View Paper titled, Unsupervised Methodology for the Prognostics of Gas Turbine Abrupt Faults
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Topics: Artificial neural networks, Gas turbines
Proceedings Papers

Data-Driven Generative Model Aimed to Create Synthetic Data for the Long-Term Forecast of Gas Turbine Operation

Enzo Losi, Lucrezia Manservigi, Pier Ruggero Spina, Mauro Venturini
Proc. ASME. GT2024, Volume 9: Manufacturing Materials and Metallurgy; Microturbines, Turbochargers, and Small Turbomachines; Oil & Gas Applications; Steam Turbine, V009T19A006, June 24–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: GT2024-122162
https://doi.org/10.1115/GT2024-122162
View Paper titled, Data-Driven Generative Model Aimed to Create Synthetic Data for the Long-Term Forecast of Gas Turbine Operation
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Topics: Gas turbines
Journal Articles

Methodology to Monitor Early Warnings Before Gas Turbine Trip

Enzo Losi, Mauro Venturini, Lucrezia Manservigi, Giovanni Bechini
Journal: Journal of Engineering for Gas Turbines and Power
Publisher: ASME
Article Type: Research-Article
J. Eng. Gas Turbines Power. May 2024, 146(5): 051005.
Paper No: GTP-23-1524
https://doi.org/10.1115/1.4063720
Published Online: December 8, 2023
View Article titled, Methodology to Monitor Early Warnings Before Gas Turbine Trip
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Topics: Gas turbines, Reliability, Probability, Testing, Artificial neural networks
Proceedings Papers

Concurrent Design and Operation Optimization of a Multi-Generation Energy System by Using a SMO-MILP Hybrid Algorithm

Giulia Anna Maria Castorino, Enzo Losi, Lucrezia Manservigi, Michele Pinelli, Pier Ruggero Spina, Mauro Venturini
Proc. ASME. GT2023, Volume 8: Industrial and Cogeneration; Manufacturing Materials and Metallurgy, V008T16A002, June 26–30, 2023
Publisher: American Society of Mechanical Engineers
Paper No: GT2023-101205
https://doi.org/10.1115/GT2023-101205
View Paper titled, Concurrent Design and Operation Optimization of a Multi-Generation Energy System by Using a SMO-MILP Hybrid Algorithm
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Topics: Algorithms, Design, Optimization, Energy / power systems, Fossil fuels, Renewable energy, Absorption, Boilers, Cogeneration systems, Compression
Proceedings Papers

Methodology to Monitor Early Warnings Before Gas Turbine Trip

Enzo Losi, Mauro Venturini, Lucrezia Manservigi, Giovanni Bechini
Proc. ASME. GT2023, Volume 9: Microturbines, Turbochargers, and Small Turbomachines; Oil and Gas Applications, V009T19A004, June 26–30, 2023
Publisher: American Society of Mechanical Engineers
Paper No: GT2023-101701
https://doi.org/10.1115/GT2023-101701
View Paper titled, Methodology to Monitor Early Warnings Before Gas Turbine Trip
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Topics: Gas turbines, Reliability, Maintenance
Proceedings Papers

Prediction of Gas Turbine Trip by Combining Gas Path Measurements and Vibration Signals

Enzo Losi, Mauro Venturini, Lucrezia Manservigi, Giovanni Bechini
Proc. ASME. GT2023, Volume 9: Microturbines, Turbochargers, and Small Turbomachines; Oil and Gas Applications, V009T19A005, June 26–30, 2023
Publisher: American Society of Mechanical Engineers
Paper No: GT2023-101703
https://doi.org/10.1115/GT2023-101703
View Paper titled, Prediction of Gas Turbine Trip by Combining Gas Path Measurements and Vibration Signals
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Topics: Gas turbines, Signals, Vibration, Reliability, Artificial neural networks, Sensors, Testing
Proceedings Papers

Application of Transfer Learning for the Prediction of Gas Turbine Trip

Enzo Losi, Mauro Venturini, Lucrezia Manservigi, Giovanni Bechini
Proc. ASME. GT2023, Volume 9: Microturbines, Turbochargers, and Small Turbomachines; Oil and Gas Applications, V009T19A006, June 26–30, 2023
Publisher: American Society of Mechanical Engineers
Paper No: GT2023-101704
https://doi.org/10.1115/GT2023-101704
View Paper titled, Application of Transfer Learning for the Prediction of Gas Turbine Trip
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Topics: Gas turbines, Artificial neural networks, Maintenance
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
Journal: Journal of Engineering for Gas Turbines and Power
Publisher: ASME
Article Type: Research-Article
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
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Topics: Gas turbines, Statistical analysis, Turbines, Machine learning, Time series
Journal Articles

Detection of the Onset of Trip Symptoms Embedded in Gas Turbine Operating Data

Enzo Losi, Mauro Venturini, Lucrezia Manservigi, Giovanni Bechini
Journal: Journal of Engineering for Gas Turbines and Power
Publisher: ASME
Article Type: Research-Article
J. Eng. Gas Turbines Power. March 2023, 145(3): 031023.
Paper No: GTP-22-1318
https://doi.org/10.1115/1.4055904
Published Online: December 8, 2022
View Article titled, Detection of the Onset of Trip Symptoms Embedded in Gas Turbine Operating Data
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Topics: Artificial neural networks, Gas turbines, Probability, Reliability
Journal Articles

Ensemble Learning Approach to the Prediction of Gas Turbine Trip

Enzo Losi, Mauro Venturini, Lucrezia Manservigi, Giovanni Bechini
Journal: Journal of Engineering for Gas Turbines and Power
Publisher: ASME
Article Type: Research-Article
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
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Topics: Gas turbines, Machine learning, Reliability, Support vector machines, Artificial neural networks, Testing, Algorithms, Probability
Proceedings Papers

Detection of the Onset of Trip Symptoms Embedded in Gas Turbine Operating Data

Enzo Losi, Mauro Venturini, Lucrezia Manservigi, Giovanni Bechini
Proc. ASME. GT2022, Volume 7: Industrial and Cogeneration; Manufacturing Materials and Metallurgy; Microturbines, Turbochargers, and Small Turbomachines; Oil & Gas Applications, V007T19A004, June 13–17, 2022
Publisher: American Society of Mechanical Engineers
Paper No: GT2022-80666
https://doi.org/10.1115/GT2022-80666
View Paper titled, Detection of the Onset of Trip Symptoms Embedded in Gas Turbine Operating Data
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Topics: Gas turbines, Artificial neural networks, Failure, Maintenance, Sensors, Service life (Equipment)
Proceedings Papers

Statistical Rule Extraction for Gas Turbine Trip Prediction

Giovanni Bechini, Enzo Losi, Lucrezia Manservigi, Giovanni Pagliarini, Guido Sciavicco, Ionel Eduard Stan, Mauro Venturini
Proc. ASME. GT2022, Volume 7: Industrial and Cogeneration; Manufacturing Materials and Metallurgy; Microturbines, Turbochargers, and Small Turbomachines; Oil & Gas Applications, V007T19A012, June 13–17, 2022
Publisher: American Society of Mechanical Engineers
Paper No: GT2022-82915
https://doi.org/10.1115/GT2022-82915
View Paper titled, Statistical Rule Extraction for Gas Turbine Trip Prediction
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Topics: Gas turbines, Artificial intelligence, Computers, Industrial gases, Machine learning, Statistical analysis, Turbines
Proceedings Papers

Analysis of a Multi-Generation Renewable Energy System with Hydrogen-Fueled Gas Turbine

Hilal Bahlawan, Enzo Losi, Lucrezia Manservigi, Mirko Morini, Pier Ruggero Spina, Mauro Venturini
Proc. ASME. GT2022, Volume 7: Industrial and Cogeneration; Manufacturing Materials and Metallurgy; Microturbines, Turbochargers, and Small Turbomachines; Oil & Gas Applications, V007T16A004, June 13–17, 2022
Publisher: American Society of Mechanical Engineers
Paper No: GT2022-81082
https://doi.org/10.1115/GT2022-81082
View Paper titled, Analysis of a Multi-Generation Renewable Energy System with Hydrogen-Fueled Gas Turbine
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Topics: Gas turbines, Hydrogen fuels, Renewable energy, Solar energy, Hydrogen, Hydrogen storage, Renewable energy sources, Absorption, Climate change, Cooling
Proceedings Papers

Ensemble Learning Approach to the Prediction of Gas Turbine Trip

Enzo Losi, Mauro Venturini, Lucrezia Manservigi, Giovanni Bechini
Proc. ASME. GT2022, Volume 7: Industrial and Cogeneration; Manufacturing Materials and Metallurgy; Microturbines, Turbochargers, and Small Turbomachines; Oil & Gas Applications, V007T19A002, June 13–17, 2022
Publisher: American Society of Mechanical Engineers
Paper No: GT2022-80372
https://doi.org/10.1115/GT2022-80372
View Paper titled, Ensemble Learning Approach to the Prediction of Gas Turbine Trip
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Topics: Gas turbines, Machine learning, Reliability, Artificial neural networks, Robustness, Support vector machines
Journal Articles

Analysis of a Multi-Generation Renewable Energy System With Hydrogen-Fueled Gas Turbine

Hilal Bahlawan, Enzo Losi, Lucrezia Manservigi, Mirko Morini, Pier Ruggero Spina, Mauro Venturini
Journal: Journal of Engineering for Gas Turbines and Power
Publisher: ASME
Article Type: Research-Article
J. Eng. Gas Turbines Power. November 2022, 144(11): 111020.
Paper No: GTP-22-1359
https://doi.org/10.1115/1.4055456
Published Online: September 23, 2022
View Article titled, Analysis of a Multi-Generation Renewable Energy System With Hydrogen-Fueled Gas Turbine
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Topics: Cooling, Gas turbines, Hydrogen, Hydrogen fuels, Hydrogen storage, Optimization, Renewable energy, Solar energy, Thermal energy, Proton exchange membranes
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
Journal: Journal of Engineering for Gas Turbines and Power
Publisher: ASME
Article Type: Research-Article
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
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Topics: Gas turbines, Reliability, Machine learning, Time series, Temperature, Compressors, Image segmentation, Natural, scientific and engineering processes and practices, Sensors, Thermocouples
Proceedings Papers

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
Proc. ASME. GT2021, Volume 8: Oil and Gas Applications; Steam Turbine, V008T20A005, June 7–11, 2021
Publisher: American Society of Mechanical Engineers
Paper No: GT2021-58916
https://doi.org/10.1115/GT2021-58916
View Paper titled, Prediction of Gas Turbine Trip: a Novel Methodology Based on Random Forest Models
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Topics: Gas turbines, Machine learning, Case studies, Data mining, Image segmentation, Natural, scientific and engineering processes and practices, Profitability, Sensors, Service life (Equipment), Time series