A Coupled flow and chemical reactor network model for predicting gas turbine combustor performance

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2016
Hataysal, Seyfettin Ertan
A 1D flow and chemical reactor network model was developed to predict the performance of a combustor chamber and the model output was verified by the 3D Computational Fluid Dynamics (CFD) analysis and experimental measurements of the chamber. To obtain chamber flow split three different nodal flow network solvers were coupled with a chemical reactor network model. Simplified, segregated and direct solutions of the nodal equations were led to these three different flow solvers. Flow models were utilized to predict the flow, pressure, density and temperature distribution inside the chamber domain. After getting a converged solution, the reactor network processed the incoming data inside its inner loop. The output of the reactor network was fed back to the flow network and the solution is iterated until convergence of the whole system. The network model can supply information about pressure drop, pressure distribution, average temperature distribution, species distribution and flow split. For the verification of the results, a detailed CFD analysis was performed on a seven sector annular test combustor of TEI. Basic performance investigation experiments of the combustor were utilized for comparison of the results. The numerical results were presented for two different detailed chemical mechanisms. The results showed that preliminary code predicted an accurate flow distribution. Pressure distribution also showed consistency with the CFD results however level of predictions was found to change from model to model. Inner temperature profiles got the trend changes at the dilution and exit zones, however developed code predicted higher elemental temperatures at the main combustion zones. Finally the code was modified to include design parameters and thermal prediction feature for the liner cooling. A new design was also made by using this capability of the code. The performance of the new design is also presented.

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Citation Formats
S. E. Hataysal, “A Coupled flow and chemical reactor network model for predicting gas turbine combustor performance,” Ph.D. - Doctoral Program, Middle East Technical University, 2016.