On atmospheric particulate deposition in gas turbines

Particulate deposition has become increasingly concerning for jet engine manufacturers, it can lead to a variety of problems, from stress corrosion cracking and the blocking of cooling holes in the turbine, to reduced stall margins for the engine. This thesis describes the development and validation of quantitative design tools that will enable manufacturers to make engines particulate tolerant. These tools are needed to allow: engines to fly in high concentrations of dust for a limited time; manufacturers to operate a cost of ownership model by predicting damage; and most importantly the safe certification of engines against these risks.
The key capabilities required are the prediction of particulate trajectories through the engine, and their likelihood of adhering to engine components on contact. This thesis focusses on the robust prediction of turbulent particle transport in the context of the highly complex flows encountered in gas turbines. The tools developed are applicable to engine design because of their compatibility with existing design techniques, commercial flow solvers, and their computational efficiency.
A stochastic model of turbophoresis (a Continuous Random Walk, CRW) is developed and a methodology for its application detailed. A model from literature provides the basis of the current transport model. While accurate modelling of turbophoresis has previously been shown to change the likelihood of small particles sticking by several orders of magnitude, compared to the exclusion or inadequate inclusion of turbophoretic effects, these results could only be reliably replicated in simple pipe flows as the models required turbulent flow characteristics determined from Direct Numerical Simulation or experiment. These characteristics are impossible to replicate for complex geometries. Thus, the thesis identifies robust methods to calculate instantaneous turbulent flow fluctuations, seen by the particle in the Lagrangian frame of reference, from Reynolds Averaged Navier Stokes computational fluid dynamic solutions. The model is shown to be equally accurate in simple flows when compared to previous implementations, and requires neither external data nor any a priori assumptions regarding the structure of the turbulence.
The choice of the turbulence model, formulation of the particulate tracking time step, a local cell co-ordinate system to describe the turbulence, and modification of the near-wall Lagrangian timescale are all shown to be critical to the generation of accurate spatially resolved particulate deposition. The method is implemented to interface with a commercial flow solver.
To ensure reliable deposition distribution maps are produced, while maintaining computational efficiency, convergence criteria are developed as well as a methodology to minimise the number of particulate tracking events required in a computational simulation. Here, convergence of particulate tracking based on the well known integral deposition fraction is shown to be insufficient as a measure of convergence of the spatial distribution. Well established metrics for describing variation in multidimensional distributions are compared, and a suitable technique to generate a converged distribution in a computationally efficient way is established.
The revised CRW model has been validated both against existing data in the literature, and further experiments. A difficulty here is the very limited spatially resolved deposition data for which sufficient boundary conditions are available. For more complex, gas turbine relevant flows, no data of sufficient resolution were available in the open literature. A new rig was developed to generate spatially resolved distributions of deposition in accelerating flows, at representative temperatures and flow speeds. The range of tests conducted investigated the effects of geometry curvature, flow speed, and metal temperature.
Finally, the revised CRW model is run according to the methodology developed, which ensures convergence, and these results are compared to the experimental data. As bounce-stick models are still unreliable, to reduce the number of variables considered, both all-stick and all- bounce conditions were simulated and compared. The chosen geometries allowed the effects of curvature and flow speed to be further investigated, with experimental trends well replicated. The mechanisms responsible for these trends were inferred from these simulations. It was found that modelling of turbophoresis was critical to capturing a number of features of deposition that were seen in experiments. The transport model is seen to provide a robust basis for accurate modelling, however, more quantitative comparison requires a similar improvement in the modelling of bounce- stick behaviour.

Keywords: stochastic
transpiration cooling
CRW
sand
volcanic ash
particulate
particles
gas turbine
turbophoresis
Langevin
depositions
Advisor: Gillespie, D
McGilvray, M