Integration of computational fluid-particle dynamics techniques for the instantaneous estimation of particle erosion damage on axial fan blade sections

Castorrini, Alessio and Venturini, Paolo and Corsini, Alessandro (2021) Integration of computational fluid-particle dynamics techniques for the instantaneous estimation of particle erosion damage on axial fan blade sections. In: Volume 1. Aircraft Engine; Fans and Blowers. Proceedings of the ASME Turbo Expo . American Society of Mechanical Engineers (ASME), Virtual, Online. ISBN 9780791884058

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Abstract

In the last decade, the authors focused their research in the development and implementation of accurate numerical tools and methods able to predict the erosion and deposit on turbomachinery blades operating with particle-laden flows. These models and methods give complete three-dimensional description of the phenomenon, but their application is limited to a single working condition of the blade. The present paper covers the first step in the definition of a general methodology to extend the applicability of these tools to a full range of the machines operating conditions. The method aims to obtain an instantaneous prediction of the expected damage pattern for a blade section, given its local working condition in terms of relative fluid-particle flow. The final result is based on a precomputed database associated to the blade section, where the single element is obtained by computing the erosion damage using the aforementioned numerical tools. This paper will show the methodology to obtain the database associated to the midspan section of an induced draft fan subjected to erosion due to coal ash particle. The final database is then used to predict the damage state of the section associated to a given point in the characteristic curve of the fan.

Item Type:
Contribution in Book/Report/Proceedings
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2200
Subjects:
ID Code:
158343
Deposited By:
Deposited On:
07 Oct 2022 15:15
Refereed?:
Yes
Published?:
Published
Last Modified:
21 Nov 2022 17:36