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contributor authorZeng, Hanxuan
contributor authorZheng, Xinqian
contributor authorVahdati, Mehdi
date accessioned2022-05-08T09:18:54Z
date available2022-05-08T09:18:54Z
date copyright1/4/2022 12:00:00 AM
date issued2022
identifier issn0742-4795
identifier othergtp_144_03_031021.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4284977
description abstractThe occurrence of stall and surge in axial compressors has a great impact on the performance and reliability of aero-engines. Accurate and efficient prediction of the key features during these events has long been the focus of engine design processes. In this paper, a new body-force model that can capture the three-dimensional and unsteady features of stall and surge in compressors at a fraction of time required for URANS computations is proposed. To predict the rotating stall characteristics, the deviation of local airflow angle from the blade surface is calculated locally during the simulation. According to this local deviation, the computational domain is divided into stalled and forward flow regions, and the body-force field is updated accordingly
description abstractto predict the surge characteristics, the local airflow direction is used to divide the computational domain into reverse flow regions and forward flow regions. A single-stage axial compressor and a three-stage axial compressor are used to verify the proposed model. The results show that the method is capable of capturing stall and surge characteristics correctly. Compared to the traditional fully three-dimensional URANS method (fRANS), the simulation time for multistage axial compressors is reduced by 1–2 orders of magnitude.
publisherThe American Society of Mechanical Engineers (ASME)
titleA Method of Stall and Surge Prediction in Axial Compressors Based on Three-Dimensional Body-Force Model
typeJournal Paper
journal volume144
journal issue3
journal titleJournal of Engineering for Gas Turbines and Power
identifier doi10.1115/1.4053103
journal fristpage31021-1
journal lastpage31021-11
page11
treeJournal of Engineering for Gas Turbines and Power:;2022:;volume( 144 ):;issue: 003
contenttypeFulltext


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