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Optimal Design of ORC Turbine Blades Under Geometric and Operational Uncertainties

Nassim Razaaly 1 Giacomo Persico 2 Pietro Marco Congedo 1 
1 DeFI - Shape reconstruction and identification
CMAP - Centre de Mathématiques Appliquées - Ecole Polytechnique, Inria Saclay - Ile de France
Abstract : Typical energy sources for Organic Rankine Cycle (ORC) power systems feature variable heat load, hence turbine inlet/outlet thermodynamic conditions. The use of organic compounds with heavy molecular weight introduces uncertainties in the fluid thermodynamic modeling and complexity in the turbomachinery aerodynamics, with supersonic flows and strong shocks, which grow in relevance in the aforementioned off-design conditions. These features also depend strongly on the local blade shape, which can be influenced by the geometric tolerances of the blade manufacturing. This study presents a Robust Optimization (RO) analysis on a typical supersonic nozzle cascade for ORC applications under the combined effect of uncertainties associated to operating conditions and geometric tolerances: a classical formulation consisting in minimizing the mean of a well-suited performance function, constraining the average mass flow rate to be within a prescribed range is addressed, by means of a bi-level Gaussian Process (GP) surrogate-based approach. Influence of the operating conditions range and geometric variability are investigated considering several scenarios, in which the different effects act in combination or separated; results indicate that the combination of different classes of uncertainites has an impact on the robust-optimal blade shape and, in turn, in their response in the frame of uncertain scenarios.
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Submitted on : Monday, December 2, 2019 - 3:56:46 PM
Last modification on : Thursday, January 20, 2022 - 5:27:42 PM
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  • HAL Id : hal-02389654, version 1


Nassim Razaaly, Giacomo Persico, Pietro Marco Congedo. Optimal Design of ORC Turbine Blades Under Geometric and Operational Uncertainties. ORC 2019 - International Seminar on ORC Power Systems 2019, Sep 2019, Athens, Greece. ⟨hal-02389654⟩



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