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

ABSTRACT
Gas turbine combustor performance was explored by utilizing a one-dimensional flow network model. To obtain the preliminary performance of combustion chamber, 3 different flow network solvers were coupled with a chemical reactor network scheme. These flow solvers were developed via simplified, segregated and direct solutions of the nodal equations. Flow models were utilized to predict the flow field, pressure, density and temperature distribution inside the chamber network. The network model followed a segregated flow and chemical network scheme, and could supply information about the pressure drop, nodal pressure, average temperature, species distribution and flow split. For the verification of the model's results, analyses were performed using computational fluid dynamics on a seven-stage annular test combustor from TUSAS Engine Industries, and the results were then compared with actual performance tests of the combustor. The results showed that the preliminary performance predictor code accurately estimated the flow distribution. Pressure distribution was also consistent with the computational fluid dynamics results, but with varying levels of conformity. The same was true for the average temperature predictions of the inner combustor at the dilution and exit zones; however, the reactor network predicted higher elemental temperatures at the entry zones.
KEYWORDS
PAPER SUBMITTED: 2018-06-02
PAPER REVISED: 2018-08-15
PAPER ACCEPTED: 2018-08-16
PUBLISHED ONLINE: 2018-09-30
DOI REFERENCE: https://doi.org/10.2298/TSCI180602246H
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