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Proceedings Papers

Data Fusion: A Project Update & Pathway Forward

Salvatore Della Villa, Jr., Robert Steele, Dongwon Shin, Sangkeun (Matt) Lee, Travis Johnston, Yong Liu, Youhai Wen, David Alman, Christopher Perullo
Proc. ASME. GT2021, Volume 4: Controls, Diagnostics, and Instrumentation; Cycle Innovations; Cycle Innovations: Energy Storage; Education; Electric Power, V004T09A003, June 7–11, 2021
Paper No: GT2021-58933
DOI: https://doi.org/10.1115/GT2021-58933
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Topics: Data fusion, Turbines, Teams, Failure, Bone, Collaboration, Combustion, Design, Energy generation, Engineering disciplines
Proceedings Papers

Detection of Machinery Failure Signs From Big Time-Series Data Obtained by Flow Simulation of Intermediate-Pressure Steam Turbines

Kazuhiko Komatsu, Hironori Miyazawa, Cheng Yiran, Masayuki Sato, Takashi Furusawa, Satoru Yamamoto, Hiroaki Kobayashi
Proc. ASME. GT2021, Volume 4: Controls, Diagnostics, and Instrumentation; Cycle Innovations; Cycle Innovations: Energy Storage; Education; Electric Power, V004T09A002, June 7–11, 2021
Paper No: GT2021-58698
DOI: https://doi.org/10.1115/GT2021-58698
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Topics: Failure, Flow simulation, Machinery, Pressure, Steam turbines, Time series
Proceedings Papers

Application of Ultra-Low NOx Combustor to the MHPS Existing Gas Turbine

Takashi Nishiumi, Hirofumi Ohara, Kotaro Miyauchi, Sosuke Nakamura, Toshishige Ai, Masahito Kataoka
Proc. ASME. GT2021, Volume 4: Controls, Diagnostics, and Instrumentation; Cycle Innovations; Cycle Innovations: Energy Storage; Education; Electric Power, V004T09A001, June 7–11, 2021
Paper No: GT2021-02403
DOI: https://doi.org/10.1115/GT2021-02403
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Topics: Combustion chambers, Gas turbines, Nitrogen oxides, Design, Emissions, Combustion, Control systems, High pressure (Physics), Nozzles, Temperature
Proceedings Papers

The EPRI Gas Turbine Digital Twin – a Platform for Operator Focused Integrated Diagnostics and Performance Forecasting

Jamie Lim, Christopher A. Perullo, Joe Milton, Rachel Whitacre, Chris Jackson, Chris Griffin, David Noble, Lea Boche, Steve Seachman, Leonard Angello, Susan Maley, Timothy C. Lieuwen
Proc. ASME. GT2021, Volume 4: Controls, Diagnostics, and Instrumentation; Cycle Innovations; Cycle Innovations: Energy Storage; Education; Electric Power, V004T09A009, June 7–11, 2021
Paper No: GT2021-59572
DOI: https://doi.org/10.1115/GT2021-59572
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Topics: Gas turbines, Maintenance, Stress, Combined cycle gas turbines, Computer software, Emissions, Pattern recognition, Physics, Power stations, Sensors
Proceedings Papers

GT36 Turbine Development and Full-Scale Validation

S. Naik, B. Stephan, M. Henze
Proc. ASME. GT2021, Volume 4: Controls, Diagnostics, and Instrumentation; Cycle Innovations; Cycle Innovations: Energy Storage; Education; Electric Power, V004T09A008, June 7–11, 2021
Paper No: GT2021-59470
DOI: https://doi.org/10.1115/GT2021-59470
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Topics: Cooling, Gas turbines, Turbines, Temperature, Instrumentation, Metals, Power stations, Turbine blades, Aerodynamics, Airfoils
Proceedings Papers

Turn-Down Capability of Ansaldo Energia’s GT26

Ralf Jakoby, Jörg Rinn, Christoph Appel, Adrien Studerus
Proc. ASME. GT2021, Volume 4: Controls, Diagnostics, and Instrumentation; Cycle Innovations; Cycle Innovations: Energy Storage; Education; Electric Power, V004T09A007, June 7–11, 2021
Paper No: GT2021-59457
DOI: https://doi.org/10.1115/GT2021-59457
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Topics: Combined cycles, Combustion chambers, Combustion systems, Compressors, Cycles, Emissions, Energy generation, Engines, Flow (Dynamics), Fuels
Proceedings Papers

Experimental Development of On-Line Flame Transfer Function Measurements for Fielded Gas Turbines

Austin Matthews, Anna Cobb, Subodh Adhikari, David Wu, Tim Lieuwen, Jim Blust, Benjamin Emerson
Proc. ASME. GT2021, Volume 4: Controls, Diagnostics, and Instrumentation; Cycle Innovations; Cycle Innovations: Energy Storage; Education; Electric Power, V004T09A006, June 7–11, 2021
Paper No: GT2021-59317
DOI: https://doi.org/10.1115/GT2021-59317
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Topics: Flames, Gas turbines, Transfer functions
Proceedings Papers

Achieving Better Power Plant Guarantees Through a New Exergy-Based Approach for the HRSG

Raub W. Smith
Proc. ASME. GT2021, Volume 4: Controls, Diagnostics, and Instrumentation; Cycle Innovations; Cycle Innovations: Energy Storage; Education; Electric Power, V004T09A005, June 7–11, 2021
Paper No: GT2021-59291
DOI: https://doi.org/10.1115/GT2021-59291
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Topics: Exergy, Heat recovery steam generators, Power stations
Proceedings Papers

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

Vipul Goyal, Mengyu Xu, Jayanta Kapat, Ladislav Vesely
Proc. ASME. GT2021, Volume 4: Controls, Diagnostics, and Instrumentation; Cycle Innovations; Cycle Innovations: Energy Storage; Education; Electric Power, V004T09A004, June 7–11, 2021
Paper No: GT2021-59082
DOI: https://doi.org/10.1115/GT2021-59082
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Topics: Blades, Combustion, Combustion systems, Cooling systems, Flow (Dynamics), Fuels, Gas turbines, Machine learning, Modeling, Power stations
Proceedings Papers

Analytical Formulation of the Performance of the Allam Power Cycle

Yousef Haseli
Proc. ASME. GT2020, Volume 6: Education; Electric Power, V006T09A003, September 21–25, 2020
Paper No: GT2020-15070
DOI: https://doi.org/10.1115/GT2020-15070
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Topics: Temperature, Thermodynamic power cycles, Turbines
Proceedings Papers

Quality Key Numbers of Gas Turbine Combined Cycles

Hans E. Wettstein
Proc. ASME. GT2020, Volume 6: Education; Electric Power, V006T09A002, September 21–25, 2020
Paper No: GT2020-14508
DOI: https://doi.org/10.1115/GT2020-14508
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Topics: Combined cycles, Gas turbines, Cycles, Exergy, Design, Turbines, Compressors, Cooling, Aerodynamics, Condensation
Proceedings Papers

Improving the Safety of Power Plants by Developing a Digital Twin and an Expert System for Adaptive-Predictive Analysis of the Operability of Gas Turbine Units

Roman Polyakov, Eugenii Paholkin, Igor Kudryavcev, Nikolay Krupenin
Proc. ASME. GT2020, Volume 6: Education; Electric Power, V006T09A001, September 21–25, 2020
Paper No: GT2020-14217
DOI: https://doi.org/10.1115/GT2020-14217
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Topics: Artificial neural networks, Construction, Expert systems, Failure, Gas turbines, Modeling, Power stations, Safety, Security, Turbogenerators
Proceedings Papers

A Toolbox of Hardware and Digital Solutions for Increased Flexibility

Nicolas Demougeot, Alexander Steinbrenner, Alfredo Cires, Marc Paskin
Proc. ASME. GT2020, Volume 6: Education; Electric Power, V006T09A005, September 21–25, 2020
Paper No: GT2020-15289
DOI: https://doi.org/10.1115/GT2020-15289
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Topics: Hardware, Stress, Energy generation, Engines, Cavities, Combined cycles, Cooling, Disks, Exhaust systems, Gas turbines
Proceedings Papers

Prediction of Gas Turbine Performance Using Machine Learning Methods

Vipul Goyal, Mengyu Xu, Jayanta Kapat, Ladislav Vesely
Proc. ASME. GT2020, Volume 6: Education; Electric Power, V006T09A004, September 21–25, 2020
Paper No: GT2020-15232
DOI: https://doi.org/10.1115/GT2020-15232
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Topics: Artificial neural networks, Gas turbines, Machine learning, Algorithms, Failure, Temperature, Blades, Flow (Dynamics), Fuels, Power stations
Proceedings Papers

Balancing a High-Renewables Electric Grid With Hydrogen-Fuelled Combined Cycles: A Country Scale Analysis

Paolo Colbertaldo, Giulio Guandalini, Elena Crespi, Stefano Campanari
Proc. ASME. GT2020, Volume 6: Education; Electric Power, V006T09A006, September 21–25, 2020
Paper No: GT2020-15570
DOI: https://doi.org/10.1115/GT2020-15570
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Topics: Combined cycles, Hydrogen, Renewable energy sources, Natural gas, Storage, Emissions, Energy generation, Energy storage, Fuel cells, Batteries
Proceedings Papers

Assessment of Current Capabilities and Near-Term Availability of Hydrogen-Fired Gas Turbines Considering a Low-Carbon Future

Benjamin Emerson, David Wu, Tim Lieuwen, Scott Sheppard, David Noble, Leonard Angello
Proc. ASME. GT2020, Volume 6: Education; Electric Power, V006T09A007, September 21–25, 2020
Paper No: GT2020-15714
DOI: https://doi.org/10.1115/GT2020-15714
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Topics: Carbon, Combustion, Gas turbines, Hydrogen
Proceedings Papers

An Ensemble of Recurrent Neural Networks for Real Time Performance Modelling of Three-Spool Aero-Derivative Gas Turbine Engine

Ibrahem M. A. Ibrahem, Ouassima Akhrif, Hany Moustapha, Martin Staniszewski
Proc. ASME. GT2020, Volume 6: Education; Electric Power, V006T09A008, September 21–25, 2020
Paper No: GT2020-15756
DOI: https://doi.org/10.1115/GT2020-15756
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Topics: Artificial neural networks, Gas turbines, Modeling
Proceedings Papers

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
Proc. ASME. GT2020, Volume 6: Education; Electric Power, V006T09A009, September 21–25, 2020
Paper No: GT2020-15788
DOI: https://doi.org/10.1115/GT2020-15788
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Topics: Combustion, Dynamics (Mechanics), Emissions, Gas turbines, Machine learning, Nitrogen oxides, Power stations
Proceedings Papers

Disappearing Thermo-Economic Sanity in Gas Turbine Combined Cycle Ratings: A Critique

S. Can Gülen
Proc. ASME. GT2019, Volume 3: Coal, Biomass, Hydrogen, and Alternative Fuels; Cycle Innovations; Electric Power; Industrial and Cogeneration; Organic Rankine Cycle Power Systems, V003T08A003, June 17–21, 2019
Paper No: GT2019-90883
DOI: https://doi.org/10.1115/GT2019-90883
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Topics: Combined cycles, Gas turbines, Thermoeconomics, Turbines, Pressure, Cycles, Temperature, Thermal efficiency, Air flow, Brayton cycle
Proceedings Papers

Use of Vector Autoregressive Model for Anomaly Detection in Utility Gas Turbines

Vipul Goyal, Mengyu Xu, Jayanta Kapat
Proc. ASME. GT2019, Volume 3: Coal, Biomass, Hydrogen, and Alternative Fuels; Cycle Innovations; Electric Power; Industrial and Cogeneration; Organic Rankine Cycle Power Systems, V003T08A004, June 17–21, 2019
Paper No: GT2019-90995
DOI: https://doi.org/10.1115/GT2019-90995
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Topics: Gas turbines, Time series, Combined cycles, Modeling, Power stations, Steam turbines, Turbines