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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

https://doi.org/10.1115/GT2021-59082

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

Topics: Blades, Combustion, Combustion systems, Cooling systems, Flow (Dynamics), Fuels, Gas turbines, Machine learning, Modeling, Power stations

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

https://doi.org/10.1115/GT2020-15232

View Paper titled, Prediction of Gas Turbine Performance Using Machine Learning Methods

Topics: Artificial neural networks, Gas turbines, Machine learning, Algorithms, Failure, Temperature, Blades, Flow (Dynamics), Fuels, Power stations

Proceedings Papers

Study of Buoyancy Effects on Supercritical CO 2 Heat Transfer in Circular Pipes

Akshay Khadse, Ladislav Vesely, James Sherwood, Andres Curbelo, Vipul Goyal, Nandhini Raju, Jayanta S. Kapat, Wanjae Kim

Proc. ASME. GT2020, Volume 11: Structures and Dynamics: Structural Mechanics, Vibration, and Damping; Supercritical CO2, V011T31A013, September 21–25, 2020

Paper No: GT2020-15523

https://doi.org/10.1115/GT2020-15523

View Paper titled, Study of Buoyancy Effects on Supercritical CO 2 Heat Transfer in Circular Pipes

Topics: Buoyancy, Heat transfer, Pipes, Supercritical carbon dioxide, Flow (Dynamics), Cooling systems, Thermodynamic power cycles, Computation, Cooling, Cross section (Physics)

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

https://doi.org/10.1115/GT2019-90995

View Paper titled, Use of Vector Autoregressive Model for Anomaly Detection in Utility Gas Turbines

Topics: Gas turbines, Time series, Combined cycles, Modeling, Power stations, Steam turbines, Turbines

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

Transient Analysis of a Supercritical Carbon Dioxide Air Cooler Using IDAES

Transient Analysis of Supercritical Carbon Dioxide Air Cooler With Using IDAES Model

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

Prediction of Gas Turbine Performance Using Machine Learning Methods

Study of Buoyancy Effects on Supercritical CO 2 Heat Transfer in Circular Pipes

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

Journals

Conference Proceedings

eBooks

Resources

Opportunities

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

Transient Analysis of a Supercritical Carbon Dioxide Air Cooler Using IDAES

Transient Analysis of Supercritical Carbon Dioxide Air Cooler With Using IDAES Model

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

Prediction of Gas Turbine Performance Using Machine Learning Methods

Study of Buoyancy Effects on Supercritical CO 2 Heat Transfer in Circular Pipes

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

Journals

Conference Proceedings

eBooks

Resources

Opportunities

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