Numerical Models for Simulation of Water Ingestion in Aeronautical Combustors

P. Di Martino1, G. Cinque2, A. Terlizzi2, F. Gaudino3, A. Santoriello2 1. Ingegneria/R&ST – Discipline Combustione, AVIO S.p.A. Pomigliano d’Arco (NA) - ITALY 2. Ingegneria/Prog. Componenti – Combustori, AVIO S.p.A. Pomigliano d’Arco (NA) - ITALY 3. Centro Sperimentale, AVIO S.p.A. Pomigliano d’Arco (NA) - ITALY

1. Abstract Ingestion of water, in the forms of vapour, condensed droplets, rain, snow, and hail from the atmosphere into the inlet of gas turbine engines can significantly affect their performance, operability and safety during take-off, flight and landing. Therefore, precise understanding of engine responses to ingested water must be established during design and development phases and then verified as part of the engine certification process. Test capabilities are currently available in either ground level test facilities and altitude test facilities to duplicate most of the water ingestion conditions encountered during aircraft operations. The use of recently advanced computer models allows the final combustor configuration to be analysed, thus reducing experimental activities, with positive impact on development costs. In this paper Computational Fluid Dynamics (CFD) numerical models to simulate water ingestion are presented. Comparison with available experimental data, carried out on a an annular straight flow combustor produced at AVIO, has also been performed.

2. Introduction Although gas turbine engines are designed to use dry air as the working fluid, the great demand for air travel at several altitudes and speeds has increased aircraft’s exposure to inclement weather conditions [1]. However, they are required to perform safely under the effect of various meteorological phenomena, as air entering the engine contains water. Up to the early 80’s, several incidents have been reported to the aviation authorities about power loss during flight at inclement weather. It was understood that the rain ingestion into a gas turbine engine influences the performance of the compressor, combustor, turbine and nozzle. This performance deterioration may result in flameout or shutdown of the engine. The aviation authorities and the jet engines manufacturers decided to study the problem in depth and take all the necessary measures [2,3]. By mid-1991, engine modifications had been developed and tested, which aimed to improve the engine’s rain ingestion capability. The aviation authorities issued new water ingestion certification regulations [4] and the engine manufacturers complied with them, showing that the matter was of extreme interest. Many in-flight and on-ground tests have been undertaken by engines manufacturers to establish the water ingestion conditions. These tests were necessary, albeit expensive. The increase of computer capability and the low development cost made feasible the creation of water-ingestion simulation codes. The complexity of the phenomenon has driven to the

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conclusion that only simulation combined with experimental testing can assure the accurate prediction of gas turbine performance. In this study CFD models to simulate water ingestion are presented. Comparison with available experimental data obtained in ground test facility has also been performed. Such models are an example of design-by-analysis tools that are becoming more and more popular in aeroengine industry.

3. Combustor geometry and operating conditions The object of this study is the annular straight flow combustor produced at AVIO plants based in Pomigliano d’Arco. This combustor will be installed on a small jet engine designed to meet more frequent flights requirements and most stringent environmental standards in the growing market of regional transport. The combustor real geometry is considered company confidential, so it is not possible to show any detail. Anyway it is sufficient to look at Fig. 1 to understand the main features of a typical combustor for a civil gas turbine engine.

4. CFD modelling: BODY3D Code Avio in-house code BODY3D [5, 6] was used for reactive CFD analyses. In that code steady fully elliptic density-weighted Navier-Stokes equations describing gas phase, under low Mach number approximation, coupled to the energy and momentum balance equations for the liquid phase, are considered [7]. Turbulence is simulated by means of the standard k-ε, model along with the wall function treatment for the near-wall regions. The conservation equations solved for the gas phase are those for momentum, mass, kinetic energy of turbulence and its dissipation, energy and chemical species. An additional equation for water evolution inside the combustor has been properly implemented in the code. In order to fit the very complex geometries encountered in industrial applications, a body conforming system of coordinates is used. The interaction between turbulence and combustion is based on Arrhenius and Eddy Break Up [8] concepts. The heat release model is given by the following two-step scheme, which allows for calculation of CO (finite rate kinetics): (1) (2) Temperature fluctuations effects on chemical kinetics were also considered by expanding the Arrhenius term in series. The density is provided by the law of perfect gases while temperature is updated from stagnation enthalpy.

4.1. Liquid-phase model The behaviour of fuel droplets and the rate at which they evaporate in the primary zone of a combustion chamber is very important as this affects the degree of homogeneity achieved in mixing the fuel and air, which directly controls the levels of NOx produced. The BODY3D code includes suitable inter-phase interactions for mass, momentum and energy. Droplet transport and evaporation rates are described using the Deterministic Separated Flow model

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(DSF) [9]. This model assumes that the fuel is injected into the combustion chamber as a fully atomized spray, which consists of spherical droplets. A finite number of diameter ranges obeying the Rosin-Rammler distribution is calculated. Finite inter-phase transport rates are considered, but the effects of turbulent fluctuations on particle motion are neglected. Quasi steady conditions are assumed for the gas phase heat and mass transfer. Droplets evaporate according to the fuel vapor concentration gradient and interact only with the mean gas motion. Particles follow deterministic trajectories found by solving their Lagrangian equations of motion. The model takes into account drop heat-up, including the effect of forced convection. The evaporated mass flux is based on the vapour concentration gradient concept. Besides the infinite conductivity hypothesis [10] is used to calculate drop temperature for a Lewis number of unity. The liquid-phase equations are coupled to the equations describing gas-phase through the droplet source terms, which are obtained by calculating what is lost or gained in terms of mass; momentum and energy as the droplets enter and leave volume elements. The set of simultaneous ordinary equations for liquid phase is solved by the fourth order Runge-Kutta method at suitable intervals within the iterative procedure. The time step is dynamically adjusted based on droplet velocity and grid cell size.

4.2 NOx modelling There are three separate routes to NO production: thermal, prompt and nitrous-oxide mechanism. The nitrous oxide route is important in lean conditions [11]. The rates of prompt NO and nitrous oxide have been empirically derived using a low activation energy. The extended Zeldovitch mechanism has been considered for the thermal NO formation.

5. Computational domain and boundary conditions The CFD domain is a periodic angular sector of 20° (Fig. 2). It includes the injection system and the combustor. The structured single block grid has a total number of about 215000 cells. Note that the primary and secondary holes have been perfetly fitted by body conforming grid.

6. Comparison between CFD results and measurements Several CFD calculation have been carried out by varying the inlet water percentage (i.e. the ratio of water mass flow rate to air mass flow rate). In the experimental test campaign performed at Avio Pomigliano d’Arco water was injected both in forms of liquid droplets and in form of vapor. At the moment the CFD analyses considered only water as steam at the same temperature of inlet air. In Fig. 3 the gas temperature in the combustor mid plane is shown for several inlet water percentages. The representation of data is done without figures as this combustor is company confidential. Anyway it can be observed a marked temperature decrease by moving from extreme left (no water injected) to far right (max water percentage). One of the consequences of water injection is the increase of carbon monoxide (CO) content, as a signal of combustion efficiency decreasing. This can be detected in Fig. 4, that shows the CO concentration at the combustor exit plane. Once more CO increases from left to right. A similar behavior occurs for water (Fig. 5). The injected water sums up with the water produced in the combustion process. Several measurements have been taken on a defined angular sector at the combustor exit plane. A five kiels mixed probe was used to supply a gas analysis system that measured the concentration of chemical species. From the above measurements gas temperature has been calculated according to AVIO internal practises. The mean experimental results are shown in

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Figg. 6-10, for several inlet water concentrations. The agreement between CFD calculations and experiments is considered satisfactory. Only the CO model has to be refined, even if the model matches well the trend. If one takes into account the difficulties encountered by all people who model CO formation/oxidation rates, is a good result anyway.

7. Conclusions A CFD model has been set up to simulate water ingestion in combustion chambers. The objective was the development of an analysis tool to reduce the cost of experimental campaign. The model was validated by comparing numerical results with experimental measurements carried out at Pomigliano d’Arco on a single annular combustor. These first results are considered very satisfactory. The next step will be the modelling of water injection as liquid drops.

8. References 1. Kissel, G.: 15th AIAA Annual Meeting and Technical Display, Washington, D.C. (1979). 2. Volk, L.,: Proceedings of Flight Safety Foundation 45th Annual International Air Safety

Seminar, (1992). 3. Russell, R. E., Victor, I. W.: AIAA/AHS/ASEE Aircraft Design Systems and Operating

Meeting, San Diego, California (1984). 4. Jackson, N.: European Propulsion Forum – Design of Aero Engines for Safety,

Reliability, Maintenability and Cost, Berlin, Germany, (1997) 5. Di Martino, P., Colantuoni, S., Cirillo, L, Cinque, G.: ASME Conference, Le Hague, The

Netherlands (1994). 6. Di Martino, P., Cinque, G., Terlizzi, A.: ICLASS 9th International Conference on Liquid

Atomization and Spray Systems, Sorrento, Italy (2003). 7. Gupta, A. K., and Lilley, D. G.: Flow field Modeling and Diagnostic, Abacus Press,

1985. 8. Jones, W. P., Whitelaw, J. H.: Comb. Flame, 48:1 (1982). 9. Aggarwal, S. K., Tong, A. Y., and Sirignano, W. A.: AIAA Journal, 22:1448 (1984). 10. Hubbard, G. L., Denny, V. E., and Mills, A. F.: Int. J. Heat Mass Transfer, 18:1003

(1975). 11. De Soete, G.: Int. 15th Symp on Combustion (1974).

Fig. 1 Schematic of civil gas turbine combustion system.

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Fig. 2 Combustor structured single block grid for CFD analysis (84x44x58 cells).

Fig. 3 Combustor mid-plane non dimensional gas temperature for different inlet water

percentages.

Fig. 4 Combustor exit plane non dimensional CO concentration for different inlet water

percentages.

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Fig. 5 Combustor exit plane non dimensional H2O vapor concentration for different inlet water percentages.

Fig. 6 Combustor exit plane average CO2 Fig. 7 Combustor exit plane average H2O concentration. Calculation vs experiments. concentration. Calculation vs xperiments.

Fig. 8 Combustor exit plane average O2 Fig. 9 Combustor exit plane average CO concentration. Calculation vs experiments. concentration. Calculation vs xperiments.

Fig. 10 Combustor exit plane average gas temperature: calculation vs experiments.

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