| Papers |
| Conference |
Year |
Paper Title |
Paper Author |
Page Number |
Other |
| IGTI |
2020 |
Interactive Learning Platform for Turbine Design Using Reduced Order Methods |
Igor Oliveira, George Patton Silva, Daniel Tonon, Cleverson Bringhenti, Jesuino Takachi Tomita |
GT2020-16028 |
|
| IGTI |
2020 |
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 |
GT2020-14217 |
|
| IGTI |
2020 |
Quality Key Numbers of Gas Turbine Combined Cycles |
Hans E. Wettstein |
GT2020-14508 |
|
| IGTI |
2020 |
Analytical Formulation of the Performance of the Allam Power Cycle |
Yousef Haseli |
GT2020-15070 |
|
| IGTI |
2020 |
Prediction of Gas Turbine Performance Using Machine Learning Methods |
Vipul Goyal, Mengyu Xu, Jayanta Kapat, Ladislav Vesely |
GT2020-15232 |
|
| IGTI |
2020 |
A Toolbox of Hardware and Digital Solutions for Increased Flexibility |
Nicolas Demougeot, Alexander Steinbrenner, Alfredo Cires, Marc Paskin |
GT2020-15289 |
|
| IGTI |
2020 |
Balancing a High-Renewables Electric Grid With Hydrogen-Fuelled Combined Cycles: A Country Scale Analysis |
Paolo Colbertaldo, Giulio Guandalini, Elena Crespi, Stefano Campanari |
GT2020-15570 |
|
| IGTI |
2020 |
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 |
GT2020-15714 |
|
| IGTI |
2020 |
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 |
GT2020-15756 |
|
| IGTI |
2020 |
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 |
GT2020-15788 |
|