Active subspaces for the optimal meanline design of unconventional turbomachinery

• Published in: Applied thermal engineering 2017-12, Vol.127, p.1108-1118
• Main Authors: Bahamonde, Sebastian, Pini, Matteo, Servi, Carlo De, Colonna, Piero
• Format: Article
• Language: English
• Subjects: Active subspaces; Alternative energy; Carbon dioxide; Compressibility; Compressible fluids; Computational fluid dynamics; Computing time; Design standards; Electric power generation; Electric power plants; Energy conversion efficiency; Energy efficiency; Fluid dynamics; Genetic algorithms; Ideal gas; Inlet temperature; Mathematical models; Model reduction; Organic Rankine Cycle; Parameter sensitivity; Power plants; Rankine cycle; Reduced-order model; Renewable energies; Sensitivity analysis; Studies; Subspaces; Thermodynamic cycles; Turbine preliminary design; Turbines; Turbomachinery; Working fluids
• ISSN: 1359-4311; 1873-5606
• DOI: 10.1016/j.applthermaleng.2017.08.093

•A reduced-order model is proposed for the design of unconventional turbomachinery.•The surrogate combines fluid selection, cycle configuration, and turbine geometry.•The surrogate outperforms the standard model with negligible computational cost.•The new response surface reveals the dominant inputs for turbine performance. The preliminary fluid dynamic design of turbomachinery operating with non-standard working fluids and unusual operating conditions and specifications can be very challenging because of the lack of know-how and guidelines. Examples are the design of turbomachinery for small-capacity organic Rankine cycle and supercritical CO2 cycle power plants, whereby the efficiency of turbomachinery components has also a strong influence on the net conversion efficiency of the system. These machines operate with the fluid in thermodynamic states which, for part of the process, largely deviate from those obeying to the ideal gas law. This in turn implies the presence of so-called non-ideal compressible fluid dynamics effects. Active subspaces, a model reduction technique, is at the basis of the methodology presented here, which is aimed at the optimal meanline design of unconventional turbomachinery. The resulting surrogate model depends on a very small set of non-physical variables, called active variables. The procedure integrates into a single constrained optimization framework the selection of the working fluid, the thermodynamic cycle calculation and the preliminary sizing of the turbomachinery component. As a demonstration of the advantages of the proposed approach, the design of a 10kW mini organic Rankine cycle turbine with a turbine inlet temperature of 240°C is illustrated. In this case, approximately the same maximum efficiency is estimated for three dissimilar turbines operating with different working fluids and rather different thermodynamic cycles. The use of active subspaces allows the seamless evaluation of the sensitivity of results to input parameters, both those related to the machine and the working fluid. The novel design procedure is compared in terms of computational efficiency to a conventional approach based on the coupling of a genetic algorithm directly with a meanline code. Results show that the calculation based on the use of surrogate models is more than two orders of magnitude faster. The surrogate can be used to solve any design problem within the specified boundaries of the design envelope. Results are affected by uncer