Wetness formation in condensing nozzle flow has been well researched and very good agreement has been achieved between theory and experimental measurements. However, condensation in steam turbines is much more complex and optical measurements show a much broader droplet spectrum than in nozzles and steady cascade expansions. The dominant theory explaining this behaviour is that large-scale fluctuations in static temperature (comparable to temperature drop in a turbine stage) are caused by unsteady blade wake segmentation by subsequent blade rows, also known as wake chopping, and have a substantial influence on the condensation process.

To better understand these phenomena, a widely used stochastic wake-chopping model is implemented within a well-established throughflow framework, examining the impact of wake chopping on generated droplet size spectra and thermodynamic relaxation losses. A comprehensive sensitivity study of the predicted droplet spectra to modelling parameters and inlet temperatures (changing the nucleation zone location) is performed to discern the effects of flow phenomena from modelling limitations.

To aid the understanding of how the broadening of droplet spectra affects other phenomena in turbines, a deposition model is implemented, combining inertial and turbulent diffusion contributions. The inertial deposition rate is determined by performing 3D droplet tracking through a representation of the steam flow field while turbulent deposition rate is based on empirical deposition measurements in vertical pipe flow, using a coarse estimate of friction velocity. While the choice of friction velocity model is likely to have a strong impact on the deposition rates, most studies use flat-plate boundary layer equations whose flow assumptions strongly deviate from the flow in turbine blade passages. Therefore, a deposition rate sensitivity study is performed, and a better friction velocity guess is obtained using high-fidelity numerical simulations. Additionally, the impact of wake chopping on deposition rates is studied.

The developed models are integrated within the throughflow framework in an iterative fashion, whereby pressure and efficiency trajectories are provided to the wake chopping model which returns improved droplet spectrum, wetness, and thermodynamic relaxation loss predictions to update the flow field. The model performance is validated against existing experimental measurements and published CFD results for a model four-stage, low-pressure steam turbine, over a broad range of operating conditions. These show impressive agreement between measured and computed turbine performance, with wake chopping calculations capturing even the minute changes in flow parameters. Furthermore, computed droplet size spectra (converted to light extinction) agree remarkably well with light extinction measurements, suggesting that the developed model can be used as a predictive tool for turbine design.