Research Papers

Time-Transformation Simulation of a 1.5 Stage Transonic Compressor

[+] Author and Article Information
Laith Zori

ANSYS, Inc.,
Lebanon, NH 03766

Paul Galpin

ANSYS Canada, Ltd.,
Waterloo, ON N2J 4G8, Canada

Rubens Campregher, Juan Carlos Morales

ANSYS Canada, Ltd.,
Waterloo, ON N2J 4G8, Canada

1Corresponding author.

2Present address: ISimQ, Ltd., Kitchener, ON, Canada.

Contributed by the International Gas Turbine Institute (IGTI) of ASME for publication in the JOURNAL OF TURBOMACHINERY. Manuscript received May 23, 2016; final manuscript received September 1, 2016; published online February 23, 2017. Editor: Kenneth Hall.

J. Turbomach 139(7), 071001 (Feb 23, 2017) (11 pages) Paper No: TURBO-16-1109; doi: 10.1115/1.4035450 History: Received May 23, 2016; Revised September 01, 2016

Time-accurate transient blade row (TBR) simulation approaches are required when there is a close flow coupling between the blade rows, and for fundamentally transient flow phenomena such as aeromechanical analysis. Transient blade row simulations can be computationally impractical when all of the blade passages must be modeled to account for the unequal pitch between the blade rows. In order to reduce the computational cost, time-accurate pitch-change methods are utilized so that only a sector of the turbomachine is modeled. The extension of the time-transformation (TT) pitch-change method to multistage machines has recently shown good promise in predicting both aerodynamic performance and resolving dominant blade passing frequencies for a subsonic compressor, while keeping the computational cost affordable. In this work, a modified 1.5 stage Purdue transonic compressor is examined. The goal is to assess the ability of the multistage time-transformation method to accurately predict the aerodynamic performance and transient flow details in the presence of transonic blade row interactions. The results from the multistage time-transformation simulation were compared with a transient full-wheel simulation. The aerodynamic performance and detailed flow features from the time-transformation solution closely matched the full-wheel simulation at fractional of the computation cost.

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Fig. 1

Profile transformation (PT) interface interaction. IGV, R1, and S1 all have independent pitches. R1 moves physically at a rate of ω × R. The interface profile of R1 is stretched to match the IGV pitch and compressed to match the S1 pitch.

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Fig. 2

1½ stage modified Purdue compressor (20 inlet guide vanes, 18 rotors, and 16 stators)

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Fig. 3

Top: computation grid near rotor leading edge, three sequences of grid density is shown coarse, medium, and fine. Bottom: midspan blade to blade view of the three blade rows assembled using the medium grid.

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Fig. 4

Pressure distribution comparison from steady-state MP solutions on three grid densities on the rotor blade at midspan

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Fig. 5

Comparison of midspan static pressure flow field monitor located near the rotor for three time-step sizes large, medium, and small corresponding to 40, 80, and 120

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Fig. 6

Modified Purdue compressor operating map. Top: pressure-ratio. Bottom: isentropic efficiency. Obtained from steady-state MP simulations (110% = 22 k rpm, 100% = 20 k rpm, 80% = 16 k rpm, and 60% = 12 k rpm).

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Fig. 7

Comparison of predicted performance at 100% speedline for the MP, PT, TT, and Ref solutions. Top: pressure-ratio with two embedded plots for the mass flow rate for last stable operating point and one at the onset for surge. Bottom: isentropic efficiency.

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Fig. 8

Comparison of blade row interaction from TT, Ref, PT, and MP solutions using the contours of temperature at midspan of the 1½ stage modified Purdue compressor

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Fig. 9

Comparison of predicted pressure flow field monitors on the IGV and the rotor from reference solution and one computed from TT pitch-change method. All monitors at midspan (a) in stator at 75% axial location and (b) in rotor at 20% axial location.

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Fig. 10

Comparison of predicted pressure flow field monitors on the rotor from reference solution and one computed from TT pitch-change method. All monitors at midspan (a) in rotor at 50% axial location and (b) in rotor at 95% axial location.

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Fig. 11

Comparison of FFT of the predicted pressure flow field monitors in the IGV and the rotor from reference solution and one computed from TT pitch-change method at OP2. All monitors at midspan (a) in stator at 75% axial location and (b) in rotor at 20% axial.

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Fig. 12

Comparison of FFT of the predicted pressure flow field monitors in the rotor from reference solution and one computed from TT pitch-change method at OP2. All monitors at midspan (a) in rotor at 50% axial location and (b) in rotor at 95% axial location.

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Fig. 13

Comparison of predicted rotor loads from reference solution and from TT pitch-change method. Top: time domain monitor of rotor loads. Mid: signal spectrum from load obtain with reference method. Bottom: signal spectrum from load obtained with TT method.

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Fig. 14

Convergence of reference and TT solutions at OP2. The outlet mass flow rate and pressure-ratio monitors plotted against time, while moving averages are superimposed (center lines). Reference signals are smoother as they are summed over the ½ wheel blading.



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