Robust optimization of turbine cascades for Organic Rankine Cycles operating with siloxane MDM

Nassim Razaaly (1) , Giulio Gori (1) , Olivier Le Maitre (2) , Gianluca Iaccarino (3) , Pietro Marco Congedo (1)

1 DeFI - Shape reconstruction and identification
2 LIMSI - Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur
3 CTR - Center for Turbulence Research [Stanford]

This work presents the application of a robust optimization approach to improve the efficiency of an Organic Rankine Cycle (ORC) cascade subject to uncertain operating conditions. The optimization algorithm is based on the minimization of a high quantile of a random cost function. The system under consideration employs siloxane MDM (Oc-tamethyltrisiloxane) as a working fluid. The thermodynamic behavior of MDM requires the utilization of complex Equations-of-State (EoS) that rely on material-dependent parameters. Discussed here are the aleatory uncertainties affecting both the cascade operating conditions and the fluid model parameters. An uncertainty quantification framework is used to forward propagate the considered uncertainties to some performance estima-tors. The performances of the robust blade design are compared against performances characterizing the optimal design obtained using a deterministic optimization approach. Results show that the quantile-based approach yields to a significant improvement in cascade performance in variable operating conditions.

Domains: Mechanical engineering [physics.class-ph]

Nassim Razaaly, Giulio Gori, Olivier Le Maitre, Gianluca Iaccarino, Pietro Marco Congedo. Robust optimization of turbine cascades for Organic Rankine Cycles operating with siloxane MDM. Center for Turbulence Research 17th biennial Summer Program, Jun 2018, Stanford, CA, United States. pp.2015-214. ⟨hal-02105300⟩