Item request has been placed! ×
Item request cannot be made. ×
loading  Processing Request

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

Item request has been placed! ×
Item request cannot be made. ×
loading   Processing Request
  • Additional Information
    • Contributors:
      Shape reconstruction and identification (DeFI); Centre de Mathématiques Appliquées de l'Ecole polytechnique (CMAP); Institut National de Recherche en Informatique et en Automatique (Inria)-École polytechnique (X); Institut Polytechnique de Paris (IP Paris)-Institut Polytechnique de Paris (IP Paris)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-École polytechnique (X); Institut Polytechnique de Paris (IP Paris)-Institut Polytechnique de Paris (IP Paris)-Centre National de la Recherche Scientifique (CNRS)-Inria Saclay - Ile de France; Institut National de Recherche en Informatique et en Automatique (Inria); Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur (LIMSI); Université Paris-Sud - Paris 11 (UP11)-Sorbonne Université - UFR d'Ingénierie (UFR 919); Sorbonne Université (SU)-Sorbonne Université (SU)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université Paris Saclay (COmUE); Center for Turbulence Research Stanford (CTR); Stanford University
    • Publication Information:
      HAL CCSD
    • Publication Date:
      2018
    • Subject Terms:
    • Abstract:
      International audience ; 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.
    • Online Access:
      https://hal.science/hal-02105300
      https://hal.science/hal-02105300v1/document
      https://hal.science/hal-02105300v1/file/6_q95Optim_CTRproceedings_081018%20%281%29.pdf
    • Rights:
      info:eu-repo/semantics/OpenAccess
    • Accession Number:
      edsbas.70C4D934