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Some cutting edge technologies for power generation make use of Supercritical CO2 cycles to improve efficiency and reduce emissions. While all of these technologies are characterized by non-premixed combustion conditions, premixed flames at very high pressure are an almost unexplored field, being concerns on their stability a strong limiting factor. In this study, premixed methane flames in a carbon dioxide atmosphere have been characterized numerically with a one dimensional detailed chemistry solver. Their distinctive characteristics such as flame speed and thickness have been determined at pressures from 100 to 300 bar and at varying CO2 concentration levels, as a first, fundamental step towards the characterization of their stability limits.

The blade solidity, namely the blade chord��to��pitch ratio, largely affects the fluid��dynamic performance of turbomachinery. For turbo��machines operating with air or steam, the optimal value of the solidity which maximizes the efficiency is estimated with empirical correlations such as the ones proposed by Zweifel (1945) and Traupel (1966). However, if the turbomachine operates with unconventional fluids, the accuracy of these correlations becomes questionable. Examples of such working fluids are the non��ideal (dense) vapors of organic compounds (e.g., hydrocarbons, siloxanes) used to operate organic Rankine cycle (ORC) power systems. This study investigates the effect of both the working fluid and the flow compressibility on the optimum pitch��to��chord ratio of turbine stages. A first principle model for the profile losses is developed for this purpose. Charts providing the optimal pitch��to��chord ratio for unconventional turbine stages are then provided. Numerical simulations of the flow over a turbine stator cascade have been conducted to validate the model results and evaluate the influence of both working fluid, flow compressibility, and solidity value on the loss breakdown. The results show that the optimal solidity of turbine cascades value significantly increases with the flow compressibility. Therefore, models providing the optimal solidity based on the estimate of passage loss only are not suited for unconventional turbines.

Secondary flow is a major source of aerodynamic losses in turbines. The mitigation of these losses is critical to enable efficient turbine designs, but the suppression of secondary flow formation mechanisms is challenging due to the complex three - dimensional nature of the flow field. One solution is the use of three - dimensional endwall fence, to reduce secondary flow losses. On the one hand, fences can mitigate secondary flow penetration, reduce the kinetic energy of the crossflow and decrease the mixing out of secondary vortices downstream of the blade passage. On the other hand, the fence addition leads to an increment of wetted area and viscous losses. The design of such devices must be tailored to the specific turbine and is usually obtained via lengthy and time - consuming experimental campaigns. Shape optimization can greatly enhance the design process of these components as it provides a way to investigate the fluid dynamic performance of a multitude of fence geometries at affordable computational cost. This paper presents a shape optimization framework for endwall fences in steam turbines. A surrogate - based optimization is applied to minimize the total pressure losses of a steam turbine cascade. The results of the numerical analysis indicate a reduction of 48 % of the secondary kinetic energy leading to a decrease of 1.96 % in total pressure loss of the optimized design with respect to the empty cascade geometry. The improvement is due to the partition of the passage vorticity; the passage crossflow is reduced and the interaction between the passage vortex and the counter vortex on the blade suction surface is weakened., {"references":["[1] Denton, J., 1993. Loss Mechanisms in Turbomachinery. The 1993 IGTI Scholar Lecture.","[2] Prümper, H., 1972. Application of Boundary Layer Fences in Turbomachinery. AGARD ograph No. 164 on Boundary Layer Effects in Tubomachinery, pp.311 - 332.","[3] Kawai, T., Shinoki, S., Adachi, T., 1989. Secondary Flow Control and Loss Reduction in a Turbine Cascade Using Endwall Fences. JSME international journal. Ser. 2, Fluids engineering, heat transfer, power, combustion, thermophysical properties, 32(3), pp.375 - 387.","[4] T. Tamagawa, K. Fujii, M. Ohto and Y. Kawata, N ovember 2011. Optimization of Secondary Flow Loss Reduction of High Loaded Gas Turbine Cascade. International Gas Turbine Congress 2011, Osaka, Japan .","[5] C. Clark, G. Pullan, E. Curtis, F. Goenega, 2016. Secondary Flow Control in Low Aspect Ratio Vanes Using Splitters, ASME Turbo Expo 2016 .","[6] Sharma, O.P., Butler, T.L., 1987. Predictions of Endwall Losses and Secondary Flows in Axial Flow Turbine Cascades. J. Turbomach, 109(2), pp.229 - 236.","[7] Langston, L. S., 1980 . Crossflow s in a Turbine Cascade Passage. ASME J . Eng. For Power, 102 (4), pp. 866 - 874.","[8] Sieverding, C.H., 1985. Recent Progress in the Understanding of Basic Aspects of Secondary Flows in Turbine Blade Passages. J. Eng. Gas Turbines Power, 107(2), pp. 248 - 257.","[9] Langstom, L.S., 2001. Secondary Flows in Axial Turbines - A Review. Annals New York Academy of Sciences, 934, pp.11 - 26.","[10] Luo, J., Feng, L., McBean, I., 2015 . Turbine Blade Row Optimization Through Endwall Contouring by an AdjointMethod, Journal of Propulsion and Power, 31(2), pp. 505 - 518. https://doi.org/10.2514/1.B35152.","[11] Chung, J. T., Simon, T. W., Buddhavarapu, J., 1991. Three - Dimensional Flow Near the Blade/Endwall Junction of a Gas Turbine: Application of a Boundary Layer Fence. ASME. Turbo Expo: Power for Land, Sea, and Air, Volume 4: Heat Transfer; Electric Power; Industrial and Cogeneration ():V004T09A008.","[12] Chung, J. T., Simon, T. W., 1993. Effectiveness of the Gas Turbine Endwall Fences in Secondary Flow Control at Elevated Freestream Turbulence Levels. ASME Turbo Expo: Power for Land, Sea, and Air, Volume 1: Aircraft Engine; Marine; Turbomachinery; Microturbines and Small Turbomachinery, ():V0 01T03A019.","[13] Aunapu, N. V., Volino, R. J., Flack, K. A., Stoddard, R. M., Secondary Flow Measurements in a Turbine Passage With Endwall Flow Modification. J. Turbomach ., 122(4), pp.651 - 658.","[1 4] Kumar, K.N., Govardhan, M., 2011. Secondary Flow Loss Reduction in a Turbine Cascade with a Linearly Varied Height Streamwise Endwall Fence. International Journal of Rotating Machinery, 2011, Article ID 352819 .","[15] Myers, R.H., Montgomery, D.C., Anderso n - Cook, C. M., 2016. RESPONSE SURFACE METHODOLOGY: Process and Product Optimization Using Designed Experiments, 4th ed., Hoboken, New Jersey: Wiley.","[16] Ansys Helper, Ansys Inc., Release 17.1 .","[17] Shahpar, S., Caloni, S., de Prieëlle, L., 2017. Automatic Design Optimization of Profiled Endwalls Including Real Geometrical Effects to Minimize Turbine Secondary Flows . J. Turbomach., 139, 071010.","[18] Diwekar, U.M., Kalagnanam, J.R., 1997. Efficient sampling technique for optimization under uncertainty. AlChE Journal., 43(2), pp. 44 - 447.","[10] Perdichizzi, A., 1990. Mach Number Effects on Secondary Flow Development Downstream of a Turbine Cascade, J. Turbomach, 112(4), pp. 643 - 651.","[19] Schittkowski, K., 2009 . NLPQLP: A Fortran Implementation of a Sequent ial Quadratic Programming Algorithm with Distributed and Non - Monotone Line Search. Report, Department of Computer Science, University of Bayreuth."]}