@inproceedings{ba86813e92e24ac188b08adae45a59a3,
title = "A PISTON THEORY-BASED AEROELASTIC STABILITY PREDICTION TOOLBOX FOR RADIAL TURBOMACHINERY",
abstract = "Aircraft intermittent combustion engines often incorporate turbochargers adapted from ground-based applications to improve their efficiency and performance. These turbochargers operate at off-design conditions and experience blade failures brought on by aerodynamically-induced blade vibrations. A previously-developed reduced-order model (ROM) leveraging piston theory to compute the stability of general fluid-structural configurations is first presented and summarized. The ROM has been applied to the high-pressure turbine of a dual-stage turbocharger and the results are reviewed as a baseline for new predictions considered in this work. For each operating condition that is investigated, a computational fluid dynamic (CFD) simulation must be performed to inform the fluid loading predicted by piston theory. Interpolation-based approaches are considered to minimize the numerical expense associated with this requirement. The Gaussian-based Kriging interpolation method is presented and explored. The method provides more accurate estimates for the non-linear behavior of the quantities of interest. Kriging also estimates uncertainty and provides confidence levels as part of the interpolation process. A graphical user interface (GUI) that automates the ROM prediction is presented. The GUI presents a rapid means to alter the turbomachine of interest, predict the aeroelastic response associated with a user-specified flight condition and quantify the uncertainty associated with the prediction.",
keywords = "Aeroelasticity, CFD, Kriging, ROM, confidence levels, flutter, interpolation, toolbox, turbocharger, vibration",
author = "Vincent Iskandar and Kang, {Sang Guk} and Fellows, {David W.} and Pope, {Aaron J.} and Bodony, {Daniel J.} and Kweon, {Chol Bum}",
note = "The authors are grateful to the Army Research Laboratory for the support of this research and for granting permission to publish this paper. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes, notwithstanding any copyright notation herein. This work was supported in part by high-performance computer time and resources from the DoD High-Performance Computing Modernization Program.; ASME Turbo Expo 2023: Turbomachinery Technical Conference and Exposition, GT 2023 ; Conference date: 26-06-2023 Through 30-06-2023",
year = "2023",
doi = "10.1115/GT2023-102051",
language = "English (US)",
series = "Proceedings of the ASME Turbo Expo",
publisher = "American Society of Mechanical Engineers (ASME)",
booktitle = "Turbomachinery - Multidisciplinary Design Approaches, Optimization, and Uncertainty Quantification; Radial Turbomachinery Aerodynamics; Unsteady Flows in Turbomachinery",
}