Emissions prediction of a reverse flow combustor using network models

Abstract

The purpose of this study is to predict the pollutant emissions generated within a 1000 hp turbo-shaft helicopter engine reverse flow combustor using two different approaches; a flow network-based one-dimensional network solver and a Chemical Reactor Network (CRN) model. The one-dimensional network solver is able to estimate mass flow distributions across holes, gas and liner temperatures, heat transfer and pressure drop across the combustion chamber. All are key parameters for a preliminary design. One-dimensional flow network model is also able to predict the emissions by utilizing a number of empirical and semi-empirical correlations. CRN model is based on the division the combustor flow field into a number of specific zones represented by simple chemical reactors such as Perfectly Stirred Reactors (PSR) and Plug Flow Reactors (PFR). CRN is created to estimate the emissions using CHEMKIN software and the reaction mechanism of n-heptane is provided to be used. CRN model receives mass flow rates from the one-dimensional network model. The results of two approaches are compared for three engine power settings for idle, cruise and take-off.