Machine learning methods in CFD for turbomachinery: A review

J Hammond, N Pepper, F Montomoli… - International Journal of …, 2022 - mdpi.com
Computational Fluid Dynamics is one of the most relied upon tools in the design and
analysis of components in turbomachines. From the propulsion fan at the inlet, through the …

Future directions of high fidelity CFD for aerothermal turbomachinery analysis and design

GM Laskowski, J Kopriva, V Michelassi… - 46th AIAA fluid …, 2016 - arc.aiaa.org
Gas turbines are, and will continue to be, the backbone of narrow and wide body aircraft
propulsion. The main reason for the success of gas turbines is their power density, ie thrust …

Aerodynamic analysis and design optimization of a centrifugal compressor impeller considering realistic manufacturing uncertainties

Y Ju, Y Liu, W Jiang, C Zhang - Aerospace Science and Technology, 2021 - Elsevier
Centrifugal compressor impeller blades inevitably suffer from manufacturing uncertainties.
Such manufacturing uncertainties result in geometric deviations of blade profiles, and have …

Uncertainty quantification and sensitivity analysis on the aerodynamic performance of a micro transonic compressor

H Cheng, C Zhou, Z Li, X Lu, S Zhao, J Zhu - Aerospace Science and …, 2023 - Elsevier
Micro gas turbines are inevitably subject to geometric and operational uncertainties, which
are increasingly detrimental to aerodynamic performance and reliability. However, the effect …

[HTML][HTML] Uncertainty analysis of impact of geometric variations on turbine blade performance

X Wang, Z Zou - Energy, 2019 - Elsevier
It is important to accurately estimate the impact of manufacturing geometric variations on the
turbine aerodynamic performance for the engineering design and manufacture. In this …

Data-driven Reynolds-averaged turbulence modeling with generalizable non-linear correction and uncertainty quantification using Bayesian deep learning

H Tang, Y Wang, T Wang, L Tian, Y Qian - Physics of Fluids, 2023 - pubs.aip.org
The past few years have witnessed a renewed blossoming of data-driven turbulence
models. Quantification of the concomitant modeling uncertainty, however, has mostly been …

[PDF][PDF] 航空发动机不确定性设计体系探讨

郑新前, 王钧莹, 黄维娜, 伏宇… - Acta Aeronautica et …, 2023 - turbo.dae.tsinghua.edu.cn
航空发动机全生命周期过程中存在着大量的随机和认知不确定性因素, 往往带来研发迭代周期长
, 制造合格率低, 使用维护困难等一系列问题. 近年来国内外针对不确定性分析已经开展了一系列 …

A data-driven robust design optimization method and its application in compressor blade

H Wang, L Gao, G Yang, B Wu - Physics of Fluids, 2023 - pubs.aip.org
The probability-based robust optimization methods require a large amount of sample data to
build probability distribution models of uncertain parameters. However, it is a common …

Time complexity analysis of quantum difference methods for linear high dimensional and multiscale partial differential equations

S Jin, N Liu, Y Yu - Journal of Computational Physics, 2022 - Elsevier
We investigate time complexities of finite difference methods for solving the high-
dimensional linear heat equation, the high-dimensional linear hyperbolic equation and the …

RANS Capabilities for Transonic Axial Compressor: A Perspective From GPPS Computational Fluid Dynamics Workshop

X He, F Klausmann - Journal of Turbomachinery, 2025 - asmedigitalcollection.asme.org
Abstract Reynolds-averaged Navier–Stokes (RANS) simulations currently serve as the
prevailing industrial method for simulating axial compressor flows, and this status is …