@inbook{343949ce253d486aa5acca8b2d5f14db,
title = "Tolerance Optimization of Supersonic ORC Turbine Stator",
abstract = "The discrepancy between manufactured and design geometry of turbomachinery blades has a detrimental effect on the performance variability. In this work, the authors propose a methodology to reduce the impact of the randomness induced by the manufacturing process: a tolerance optimization is carried out by resorting to an efficient robust optimization method based on quantile regression. Its application to a typical two-dimensional supersonic nozzle cascade for ORC showcases promising preliminary results.",
keywords = "Geometric uncertainty, NICFD, ORC Stator, Quantile regression, Random field, Robust optimization",
author = "Nassim Razaaly and Giacomo Persico and Congedo, \{Pietro Marco\}",
note = "Publisher Copyright: {\textcopyright} 2020, The Author(s), under exclusive license to Springer Nature Switzerland AG.",
year = "2021",
month = jan,
day = "1",
doi = "10.1007/978-3-030-69306-0\_9",
language = "English",
series = "ERCOFTAC Series",
publisher = "Springer Science and Business Media B.V.",
pages = "78--86",
booktitle = "ERCOFTAC Series",
}