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System uncertainty due to thermo-fluid modelling Konstantinos G. Kyprianidis Table 4.1: Chemical composition of atmospheric dry air. Constituent Chemical Formula Mole Fraction yi Nitrogen N2 0.780840 Oxygen O2 0.209476 Argon Ar 0.009365 Carbon Dioxide CO2 0.000319 Mass Fraction xi 0.755184 0.231416 0.012916 0.000484 tional time penalties induced by improving the accuracy of the fluid model as well as the validity of the ideal gas assumption for future turbofan engines and novel propulsion cycles are discussed. 4.2 Fluid modelling The fluid model of a gas turbine simulation software generally consists of three types of fluids; the initial working fluid (typically air), the fuel and the products of combustion. The chemical composition of atmospheric dry air that was assumed for the purpose of this study is highlighted in Table 4.1. Conventionally, there are two approaches for implementing technical fluid mod- els in gas turbine performance simulation software. Caloric properties can ei- ther be obtained from linearly - and in some case logarithmically [182] - in- terpolated fluid tables or from polynomial functions. Generating fluid model tables, either from polynomial relationships such as those described in refer- ences [88, 187, 197, 198], and/or chemical equilibrium software such as CEA (Chemical Equilibrium with Applications) [188], Gaseq [199] and CEC (Chem- ical Equilibrium Composition) [200], is far more laborious and time consuming than directly implementing polynomial functions. Nevertheless, fluid tabula- tions offer several key advantages that have been discussed extensively by Sethi et al. [182,201]. Often the need for analysing the effects of different working mediums and alterna- tive fuels on gas turbine performance arises [201–203]. The engine performance module developed for TERA2020 can utilise CHEMKIN-II format libraries of polynomials to rigorously model these effects. The structure of the fluid model 82PDF Image | Multi-disciplinary conceptual design of future jet engine systems
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