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Research Papers: Gas Turbines: Vehicular and Small Turbomachines

Performance Characterization of Twin-Scroll Turbine Stage for Vehicular Turbocharger Under Unsteady Pulsating Flow Environment

[+] Author and Article Information
Jinwook Lee

Gas Turbine Laboratory,
Department of Aeronautics and Astronautics,
Massachusetts Institute of Technology,
Cambridge, MA 02139
e-mail: jinwook@mit.edu

Choon S. Tan

Gas Turbine Laboratory,
Department of Aeronautics and Astronautics,
Massachusetts Institute of Technology,
Cambridge, MA 02139

Borislav T. Sirakov, Hong-Sik Im, Martin Babak, Denis Tisserant

Honeywell Turbo Technologies,
Torrance, CA 90504

Chris Wilkins

SpaceX,
Hawthorne, CA 90250

1Corresponding author.

Contributed by the Vehicular and Small Turbomachines Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received December 2, 2016; final manuscript received December 8, 2016; published online February 28, 2017. Editor: David Wisler.

J. Eng. Gas Turbines Power 139(7), 072701 (Feb 28, 2017) (9 pages) Paper No: GTP-16-1561; doi: 10.1115/1.4035629 History: Received December 02, 2016; Revised December 08, 2016

Unsteady three-dimensional computations have been implemented on a turbocharger twin-scroll turbine system (volute–turbine wheel–diffuser). The flow unsteadiness in a turbocharger turbine system is essentially driven by a highly pulsating flow from the upstream combustor which causes a pulsating stagnation pressure boundary condition at the inlet to the turbine system. Computed results have been postprocessed and interrogated in depth in order to infer the significance of the induced flow unsteadiness on performance. The induced flow unsteadiness could be deemed important, since the reduced frequency of the turbine system (based on the time scale of the inlet flow fluctuation and the flow through time) is higher than unity. Thus, the computed time-accurate pressure field and the loss generation process have been assessed to establish the causal link to the induced flow unsteadiness in the turbine system. To do this consistently both for the individual subcomponents and the system, a framework of characterizing the operation of the turbine system linked to the fluctuating inlet stagnation pressure is proposed. The framework effectively categorizes the operation of the unsteady turbine system in both spatial and temporal dimensions; such a framework would facilitate determining whether the loss generation process in a subcomponent can be approximated as unsteady (e.g., volute) or as locally quasi-steady (LQS) (e.g., turbine wheel) in response to the unsteady inlet pulsation in the inlet-to-outlet stagnation pressure ratios of the two inlets. The notion that a specific subcomponent can be approximated as locally quasi-steady while the entire turbine system in itself is unsteady is of interest as it suggests a strategy for an appropriate flow modeling and scaling as well as for the turbine system performance improvement. Also, computed results are used to determine situations where the flow effects in a specific subcomponent can be approximated as quasi-one-dimensional; thus, for instance, the flow mechanisms in the volute can reasonably be approximated on an unsteady one-dimensional basis. For a turbine stage with sudden-expansion type diffuser, the framework for integrating subcomponent models into a turbine system is formulated. The effectiveness and generality of the proposed framework are demonstrated by applying it to three distinctly different turbocharger operating conditions. The estimated power from the integrated turbine system model is in good agreement with the full unsteady computational fluid dynamics (CFD) results for all three situations. The formulated framework will be generally applicable for assessing the new design configurations as long as the corresponding high-fidelity steady CFD results are utilized to determine the quasi-steady (or acoustically compact) behavior of each new subcomponent.

Copyright © 2017 by ASME
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References

Aymanns, R. , Scharf, J. , Uhlmann, T. , and Lückmann, D. , 2011, “ A Revision of Quasi Steady Modelling of Turbocharger Turbines in the Simulation of Pulse Charged Engines,” 16th Supercharging Conference, Dresden, Germany, Sept. 29–30.
Copeland, C. D. , Newton, P. , Martinez-Botas, R. F. , and Seiler, M. , 2012, “ A Comparison of Timescales Within a Pulsed Flow Turbocharger Turbine,” Tenth International Conference on Turbochargers and Turbocharging, Londona, May 15–16, pp. 389–404.
Cao, T. , Xu, L. , Yang, M. , and Martinez-Botas, R. F. , 2013, “ Radial Turbine Rotor Response to Pulsating Inlet Flows,” ASME Paper No. GT2013-95182.
Padzillah, M. H. , Yang, M. , Zhuge, W. , and Martinez-Botas, R. F. , 2014, “ Numerical and Experimental Investigation of Pulsating Flow Effect on a Nozzled and Nozzleless Mixed Flow Turbine for an Automotive Turbocharger,” ASME Paper No. GT2014-26152.
Yang, M. , Martinez-Botas, R. , and Rajoo, S. , 2014, “ Influence of Volute Cross-Sectional Shape of a Nozzleless Turbocharger Turbine Under Pulsating Flow Conditions,” ASME Paper No. GT2014-26150.
Costall, A. W. , McDavid, R. M. , Martinez-Botas, R. F. , and Baines, N. C. , 2011, “ Pulse Performance Modeling of a Twin Entry Turbocharger Turbine Under Full and Unequal Admission,” ASME J. Turbomach., 133(2), p. 021005. [CrossRef]
Baines, N. C. , 2010, “ Turbocharger Turbine Pulse Flow Performance and Modelling—25 Years On,” 9th International Conference on Turbochargers and Turbocharging Congress, London, May 19–20, pp. 347–362.
Chiong, M. S. , Rajoo, S. , Romagnoli, A. , Costall, A. W. , and Martinez-Botas, R. F. , 2015, “ Assessment of Partial-Admission Characteristics in Twin Entry Turbine Pulse Performance Modelling,” ASME Paper No. GT2015-42687.
Lee, J. , 2015, “ Aerothermodynamics and Operation of Turbine System Under Unsteady Pulsating Flow,” M.Sc. thesis, Massachusetts Institute of Technology, Cambridge, MA.
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Lee, J. , Tan, C. S. , Sirakov, B. T. , Wilkins, C. , Im, H.-S. , Babak, M. , and Tisserant, D. , 2016, “ Performance Metric for Turbine Stage Under Unsteady Pulsating Flow Environment,” ASME Paper No. GT2016-56343.
Greitzer, E. M. , Tan, C. S. , and Graf, M. B. , 2004, Internal Flow, Cambridge University Press, Cambridge, UK.

Figures

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Fig. 1

Inlet pressure ratio boundary conditions—The pair of pressure ratios in (a) constitutes a locus (green line) on 2D parameter space in (b). (a) Pressure ratio versus time to provide inlet boundary conditions for time-accurate simulation of flow in turbine system. (b) A set of steady inlet conditions (discrete points) encompassing the locus of unsteady inlet condition (green continuous line).

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Fig. 2

Outline of research—The entire unsteady system can be seen as the integration of steady or unsteady subcomponents

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Fig. 3

Diffuser mixing loss modeling—Control volume analysis is applied on a sudden expansion with rankine vortex type flow with side wall static pressure modeling

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Fig. 4

Quasi-steady diffuser loss model is in good agreement with computed lost power from unsteady CFD

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Fig. 5

Quasi-1D unsteady diffuser model—Diffuser outlet mass flow fluctuation associated with static pressure recovery is estimated with diffuser modeling during inlet 1 side pulse

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Fig. 6

Quasi-steady wastegate port loss model is in good agreement with computed lost power from unsteady CFD

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Fig. 7

Quasi-steady turbine wheel performance model is in good agreement with computed power from unsteady CFD

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Fig. 8

Quasi-1D volute model is in good agreement with computed mass flow at the end of volute from unsteady CFD

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Fig. 9

Quasi-1D volute model is in good agreement with computed pressure ratio at the end of volute from unsteady CFD

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Fig. 10

Volute outlet condition model is in good agreement with computed static pressure ratio from unsteady CFD—Static pressure ratio means the ratio of static pressure to atmospheric pressure

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Fig. 11

Turbine angle model is in good agreement with computed flow angles from unsteady CFD—βturb is relative incidence angle to turbine wheel, and γturb is the angle from the plane of volute to axis of rotation of turbine wheel

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Fig. 12

Integrated model is in good agreement with computed power from unsteady CFD for the case of operation A

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Fig. 13

Integrated model is in good agreement with computed power from unsteady CFD for the case of operation B

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Fig. 14

Integrated model is in good agreement with computed power from unsteady CFD for the case of operation C

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Fig. 15

Procedure of reducing the number of steady cases guided by NIR. (a) Normalized interpolation resolution—Blue and red cells indicate locally sparse and dense regions, respectively. (b) Reduced number of steady cases—The number of steady cases is reduced from 68 to 12.

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Fig. 16

Quasi-steady turbine wheel performance model is in good agreement with computed power from unsteady CFD—Blue line is turbine wheel model based on reduced number of steady cases

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