Ultra-Fast Gas Turbine Compressor Stall Simulation
Lead Research Organisation:
University of Cambridge
Department Name: Engineering
Abstract
The need for faster computational fluid dynamics simulations of compressor stall will be addressed with a novel computational approach that aims to reduce the run time by one order of magnitude. The approach modifies the way in which flow is passed from rotating to stationary blade rows and will allow the user to specify which flow structures are averaged-out, based on their frequency in the unsteady simulations. Retaining only low-frequency, long length-scale disturbances will allow larger calculation time steps and faster run times. This approach will be validated by comparing simulation results with experimental data from a multi-stage compressor at the Whittle Laboratory.
The motivation for speeding up compressor stall simulations relates to the more flexible use of power generating gas turbines to balance the energy grid as the use of renewable energy increases. This balancing requires gas turbine engines to change their operating conditions more quickly, which places the compressor at risk of stalling. Once validated, the new approach developed in this PhD will be used to investigate the onset of stall as gas turbines are operated more flexibily and develop design and/or operation recommendations for industry. The speed of the computational approach will accelerate industry design improvements and improve the overall understanding of compressor stall.
The motivation for speeding up compressor stall simulations relates to the more flexible use of power generating gas turbines to balance the energy grid as the use of renewable energy increases. This balancing requires gas turbine engines to change their operating conditions more quickly, which places the compressor at risk of stalling. Once validated, the new approach developed in this PhD will be used to investigate the onset of stall as gas turbines are operated more flexibily and develop design and/or operation recommendations for industry. The speed of the computational approach will accelerate industry design improvements and improve the overall understanding of compressor stall.
People |
ORCID iD |
| Endrio Rambelli (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/S023003/1 | 30/09/2019 | 30/03/2029 | |||
| 2892150 | Studentship | EP/S023003/1 | 30/09/2023 | 29/09/2027 | Endrio Rambelli |