Optimization of an axial turbine for a small scale ORC waste heat recovery system

• Published in: Energy (Oxford) 2020-08, Vol.205, p.118059, Article 118059
• Main Authors: Witanowski, Ł., Klonowicz, P., Lampart, P., Suchocki, T., Jędrzejewski, Ł., Zaniewski, D., Klimaszewski, P.
• Format: Article
• Language: English
• Subjects: Algorithms; Axial turbine; Boundary layers; Computational fluid dynamics (CFD); Efficiency; Filtration; Gas turbines; Genetic algorithms; Heat recovery; Heat recovery systems; Objective function; Optimization; Organic rankine cycle (ORC); Parameterization; Parameters; Rankine cycle; Rotor blades; Rotor blades (turbomachinery); Simplex method; Stators; Steam electric power generation; Sweep angle; Toluene; Waste heat recovery; Waste recovery
• ISSN: 0360-5442; 1873-6785
• DOI: 10.1016/j.energy.2020.118059

Low power Organic Rankine Cycle (ORC) turbines are typically characterised by flow efficiencies much smaller than those of large power steam or gas turbines. The paper concentrates on a possibility of improving the flow efficiency of an ORC axial turbine working on toluene using several optimization algorithms such as a simplex method of Nelder-Mead, a hybrid of genetic algorithm with the Nelder-Mead method, as well as implicit filtering. Values of the maximized objective function, which is the isentropic efficiency of the turbine stage, are found from 3D RANS computation of the flowpath geometry changing during the optimization process. Among the optimized geometric parameters are stator and rotor profile parametrization variables, rotor blade twist angle, circumferential lean and axial sweep angles, as well as parameters characterising the shape of endwall contours within the stator and rotor domain. The process of optimization leads to new 3D designs featuring increased efficiency compared to the original design, mainly due to a reduction in secondary and tip leakage flow losses as well as boundary layer, separation and leaving energy losses. The results especially highlight a large potential of the method of implicit filtering in optimizing multi-parameter objective functions. •A 45 kW turbine prepared for a small ORC CHP is shown.•Deterministic and hybrid methods of optimization are applied.•A wide range of variation of ORC turbine flowpath are investigated.•Performance maps for the best results are shown.•Turbine mechanical qualification is performed.