Session: 04-04: Combustion Modeling I

Paper Number: 82506

82506 - Accurate Prediction of Confined Turbulent Boundary Layer Flashback Through a Critically Strained Flame Model 

A promising path forward for power converting gas turbines that must produce low-to-no carbon emissions is the transition from burning pure natural gas to a mixture that includes cleanly produced hydrogen. However, such a transition also modifies the flame dynamics within the combustor and so must therefore be studied. One important change that occurs with increased hydrogen content is the heightened propensity of boundary layer flashback, wherein the flame propagates upstream through the low velocity region near the wall. Propagation of the flame into the poorly shielded mixing section can have disastrous results, and therefore must be avoided. In this work, a newly developed model to predict the boundary layer flashback limits based on a balance between the extinction limit flame speed and the near-wall velocity is presented. The model is capable of accurately predicting flashback limits in non-swirling burners and can be extended to swirling burners using information about a single flashback event. In addition, inclusion of a mean non-reacting velocity field computed via Large Eddy Simulation allows for a significant increase in the accuracy of the model when applied to swirling flows. Ultimately, this model provides a new pathway for the design of flashback resistant gas turbines, even with the addition of new fuels like hydrogen.

Presenting Author: Alex G. Novoselov ETH Zurich

Presenting Author Biography: Alex Novoselov is currently a Postdoctoral researcher at the Combustion and Acoustics for Power and Propulsion Systems laboratory within the Department of Mechanical and Process Engineering at ETH Zurich. He received his Ph.D. from Princeton University where he developed Large Eddy Simulations for multi-modal combustion and currently simulates and models turbulent boundary layer flashback phenomena with hydrogen addition.

Authors:

Alex G. Novoselov ETH Zurich
Dominik Ebi Paul Scherrer Institute
Nicolas Noiray ETH Zurich