Research Papers

Large-Scale Detached-Eddy Simulation Analysis of Stall Inception Process in a Multistage Axial Flow Compressor

[+] Author and Article Information
Kazutoyo Yamada

Department of Mechanical Engineering,
Kyushu University,
Fukuoka 819-0395, Japan
e-mail: k.yamada@mech.kyushu-u.ac.jp

Masato Furukawa

Department of Mechanical Engineering,
Kyushu University,
Fukuoka 819-0395, Japan
e-mail: furu@mech.kyushu-u.ac.jp

Yuki Tamura, Seishiro Saito

Department of Mechanical Engineering,
Kyushu University,
Fukuoka 819-0395, Japan

Akinori Matsuoka

Gas Turbine & Machinery Company,
Kawasaki Heavy Industries, Ltd.,
Akashi 673-8666, Japan
e-mail: matsuoka_a@khi.co.jp

Kentaro Nakayama

Gas Turbine & Machinery Company,
Kawasaki Heavy Industries, Ltd.,
Akashi 673-8666, Japan
e-mail: nakayama_ken@khi.co.jp

Contributed by the International Gas Turbine Institute (IGTI) of ASME for publication in the JOURNAL OF TURBOMACHINERY. Manuscript received August 29, 2016; final manuscript received November 8, 2016; published online February 23, 2017. Editor: Kenneth Hall.

J. Turbomach 139(7), 071002 (Feb 23, 2017) (11 pages) Paper No: TURBO-16-1215; doi: 10.1115/1.4035519 History: Received August 29, 2016; Revised November 08, 2016

This paper describes the flow mechanisms of rotating stall inception in a multistage axial flow compressor of an actual gas turbine. Large-scale numerical simulations of the unsteady have been conducted. The compressor investigated is a test rig compressor that was used in the development of the Kawasaki L30A industrial gas turbine. While the compressor consists of a total of 14 stages, only the front stages of the compressor were analyzed in the present study. The test data show that the fifth or sixth stages of the machine are most likely the ones leading to stall. To model the precise flow physics leading to stall inception, the flow was modeled using a very dense computational mesh, with several million cells in each passage. A total of 2 × 109 cells were used for the first seven stages (3 × 108 cells in each stage). Since the mesh was still not fine enough for large-eddy simulation (LES), a detached-eddy simulation (DES) was used. Using DES, a flow field is calculated using LES except in the near-wall where the turbulent eddies are modeled by Reynolds-averaged Navier–Stokes. The computational resources required for such large-scale simulations were still quite large, so the computations were conducted on the K computer (RIKEN AICS in Japan). Unsteady flow phenomena at the stall inception were analyzed using data mining techniques such as vortex identification and limiting streamline drawing with line integral convolution (LIC) techniques. In the compressor studied, stall started from a separation on the hub side rather than the commonly observed leading-edge separation near the tip. The flow phenomenon first observed in the stalling process is the hub corner separation, which appears in a passage of the sixth stator when approaching the stall point. This hub corner separation grows with time, and eventually leads to a leading-edge separation on the hub side of the stator. Once the leading-edge separation occurs, it rapidly develops into a rotating stall, causing another leading-edge separation of the neighboring blade. Finally, the rotating stall spreads to the upstream and downstream blade rows due to its large blockage effect.

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Fig. 1

Tornado-like separation vortex at the spike stall inception

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Fig. 2

A 30 MW class gas turbine: (a) overview and (b) rig compressor rotor

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Fig. 3

RANS/LES regions at 95% span in the second rotor (yellow: RANS, blue: LES)

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Fig. 4

Computational grid: (a) overview (every three lines) and (b) closeup view of fillet and partial clearance

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Fig. 5

Pressure rise characteristic for each blade row: (a) rotor and (b) stator

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Fig. 6

Performance characteristics (gray dashed lines: surge limits for full 14-stage compressor)

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Fig. 7

Comparison of stage pressure ratio (point A)

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Fig. 8

Pitchwise-averaged entropy distribution (point A)

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Fig. 9

Ensemble-averaged flow fields of fifth and sixth stators (point A): (a) fifth stator and (b) sixth stator

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Fig. 10

Standard deviations of blade passage mass flow (point F)

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Fig. 11

Time-space diagrams of passage mass flow rate (point F): (a) fifth stator, (b) fifth stator, (c) sixth stator, and (d) sixth stator

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Fig. 12

Comparison of axial velocity distribution on rotor/stator exit planes at t = 3.2 (point F): (a) fifth stator, (b) fifth stator, (c) sixth stator, and (d) sixth stator

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Fig. 13

Change of diffusion factor and diffusion parameter

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Fig. 14

Ensemble-averaged flow fields of second stage (point E): (a) rotor and (b) stator

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Fig. 15

Time history of mass flow rate (point F)

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Fig. 16

Time history of total pressure ratio (point F)

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Fig. 17

Time variation of axial velocity distribution on sixth stator exit plane (point F): (a) t = 2.2, (b) t = 2.7, (c) t = 3.2, and (d) t = 3.7

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Fig. 18

Instantaneous limiting streamlines and vortex cores at rotating stall inception (point F). The figure corresponds to the regions surrounded by a dashed border in Fig. 17: (a) t = 2.2, (b) t = 2.7, and (c) t = 3.2.

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Fig. 19

Ensemble-averaged flow fields for separated flow passages (point F): (a) t = 2.7 and (b) t = 3.2

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Fig. 20

Illustration of stall inception process

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Fig. 21

Axial velocity contours at 10% span (point F): (a) t = 3.6, (b) t = 3.7, and (c) t = 3.8




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