Due to the worldwide increasing demand for energy and the simultaneous need in reduction of CO2 emissions in order to meet global climate goals, the development of clean and low emission energy conversion systems becomes an essential and challenging task within the future clean energy map. In this paper the design process of a highly efficient large scale USC steam turbine is presented. Thereby, automated design space exploration based on an optimization algorithm is applied to support the identification of optimal flow path parameters within the preliminary and the detailed design phases. The optimization algorithm is first integrated with a 1D-mean line design code to automatically identify the optimal major turbine layout in terms of number of stages, reaction degrees, flow path geometry and basic airfoil parameters. Based on a progressive multi-section optimization coupled with a parametric airfoil generator and a CFD code, the profile shapes of each airfoil row are adapted to local flow conditions and systematically optimized to minimize aerodynamic losses in each turbine stage. A final 3D flow simulation of one representative optimized stage confirms the achievement of a highly efficient steam turbine design that fulfills both climatic and economic requirements. KEYWORDS STEAM TURBINE, DESIGN, AUTOMATED DESIGN SPACE EXPLORATION, NOMENCLATURE 1D one dimensional 2D two dimensional 3D three dimensional BC boundary condition c chord length CFD computational fluid dynamics d diameter i incidence M Mach number r radius h blade height h static enthalpy u rotational speed USC ultra-supercritical Greek Symbols absolute flow angle relative flow angle isentropic efficiency (= Δℎ (Δℎ + Δℎ)) ⁄ stagger angle loss coefficient (= 2Δℎ / 2 2) ℎ degree of reaction (ℎ = Δℎ Δℎ ⁄) flow coefficient (= / 2) ℎ stage enthalpy coefficient (ℎ = 2Δℎ/ 2 2)

One common approach for anti-erosion measures in low pressure steam turbines is to equip a hollow stator vane with slots on the airfoil surface in order to remove the water film by suction and consequently reduce the amount of secondary droplets. The purpose of this paper is to build an understanding of the predominant effects in fluid-film interaction and to examine the suitability of modern numerical methods for the design process of such slots. The performance of a suction slot in terms of collection rate and air leakage is investigated numerically in a flatplate setup with upstream injection of water. In order to model the relevant phenomena (film transport, edge stripping of droplets, transport of droplets in the surrounding fluid, wall impingement of droplets) an unsteady Eulerian-Lagrangian simulation setup is applied. The accuracy of the numerical approach is assessed by comparison with experimental measurements. The comparison of four cases with the measured data demonstrates that the chosen simulation approach is able to predict the main features of film flow and interaction with the surrounding fluid. The collection rate as well as fluid film properties show the same qualitative dependency from water mass flow rate and air velocity.

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As a result of an ever-increasing share of volatile renewable energies on the worldwide power generation, conventional thermal power plants face high technical challenges in terms of operational flexibility. Consequently, the number of startups and shutdowns grows, causing high thermal stresses in the thick-walled components and thus reduces lifetime and increases product costs. To fulfill the lifetime requirements, an accurate prediction and determination of the metal temperature distribution inside these components is crucial. Therefore, boundary conditions in terms of local fluid temperatures as well as heat transfer coefficients (HTCs) with sufficient accuracy are required. As modern numerical modeling approaches, like 3D-conjugate-heat-transfer (CHT), provide these thermal conditions with a huge calculation expense for multistage turbines, simplified methods are inevitable. Analytical heat transfer correlations are thus the state-of-the-art approach to capture the heat transport phenomena and to optimize and design high efficient startup curves for flexible power market. The objective of this paper is to understand the predominant basic heat transfer mechanisms such as conduction, convection, and radiation during a startup of an intermediate pressure (IP) steam turbine stage. Convective heat transport is described by means of heat transfer coefficients as a function of the most relevant dimensionless, aero-thermal operating parameters, considering predominant flow structures. Based on steady-state and transient CHT simulations, the heat transfer coefficients are derived during startup procedure and compared to analytical correlations from the literature, which allow the calculation of the heat exchange for a whole multistage in an economic and timesaving way. The simulations point out that the local convective heat transfer coefficient generally increases with increasing axial and circumferential Reynolds' number and is mostly influenced by vortex systems such as passage and horseshoe vortices. The heat transfer coefficients at vane, blade, hub, and labyrinth-sealing surfaces can be modeled with a high accuracy using a linear relation with respect to the total Reynolds' number. The comparison illustrates that the analytical correlations underestimate the convective heat transfer by approximately 40% on average. Results show that special correlation-based approaches from the literature are a particularly suitable and efficient procedure to predict the heat transfer within steam turbines in the thermal design process. Overall, the computational effort can be significantly reduced by applying analytical correlations while maintaining a satisfactory accuracy.

As a result of an ever-increasing share of volatile renewable energies on the world wide power generation, conventional thermal power plants face high technical challenges in terms of operational flexibility. Consequently, the number of startups and shutdowns grows, causing high thermal stresses in the thick-walled components and thus reduces lifetime and increases product costs. To fulfill the lifetime requirements, an accurate prediction and determination of the metal temperature distribution inside these components is crucial. Therefore, boundary conditions in terms of local fluid temperatures as well as heat transfer coefficients with sufficient accuracy are required. As modern numerical modeling approaches, like 3D-Conjugate-Heat-Transfer (CHT), provide these thermal conditions with a huge calculation expense for multistage turbines, simplified methods are inevitable. Analytical heat transfer correlations are thus the state-of-the-art approach to capture the heat transport phenomena and to optimize and design high efficient startup curves for flexible power market. The objective of this paper is to understand the predominant basic heat transfer mechanisms such as conduction, convection and radiation during a startup of an IP steam turbine stage. Convective heat transport is described by means of heat transfer coefficients as a function of the most relevant dimensionless, aero-thermal operating parameters, considering predominant flow structures. Based on steady-state and transient CHT-simulations the heat transfer coefficients are derived during startup procedure and compared to analytical correlations from the literature, which allow the calculation of the heat exchange for a whole multistage in an economic and time-saving way. The simulations point out that the local convective heat transfer coefficient generally increases with increasing axial and circumferential Reynolds’ number and is mostly influenced by vortex systems such as passage and horseshoe vortices. The heat transfer coefficients at vane, blade, hub and labyrinth-sealing surfaces can be modeled with a high accuracy using a linear relation with respect to the total Reynolds’ number. The comparison illustrates that the analytical correlations underestimate the convective heat transfer by approx. 40% on average. Results show that special correlation-based approaches from the literature are a particularly suitable and efficient procedure to predict the heat transfer within steam turbines in the thermal design process. Overall, the computational effort can be significantly reduced by applying analytical correlations while maintaining a satisfactory accuracy.