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Computational Analysis of Centrifugal Compressor Surge Control Using Air Injection

Alexander Stein, Saeid Niazi and Lakshmi Sankar School of Aerospace Engineering Georgia Institute of Technology Supported by the U.S. Army Research Office Under the Multidisciplinary University Research Initiative (MURI) on Intelligent Turbine Engines

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Computational Analysis of Centrifugal Compressor Surge Control Using Air Injection

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  1. Alexander Stein, Saeid Niazi and Lakshmi Sankar School of Aerospace Engineering Georgia Institute of Technology Supported by the U.S. Army Research Office Under the Multidisciplinary University Research Initiative (MURI) on Intelligent Turbine Engines High Performance Computer Time was Provided by the Major Shared Resource Center of the U.S. Army Engineer Research and Development Center (ERDC MSRC). Computational Analysis of Centrifugal Compressor Surge Control Using Air Injection

  2. Outline of Presentation • Objectives and motivation • Background of compressor control • Introduction of numerical tools • Configuration and validation results • DLR high-speed centrifugal compressor (DLRCC) • Off-design results without control • Surge analysis • Off-design results with air injection control • Steady jets • Pulsed jets • Conclusions and recommendations

  3. Motivation and Objectives Lines of Constant Efficiency Desired Extension of Operating Range Lines of Constant Rotational Speed Total Pressure Rise Surge Limit Choke Limit Flow Rate • Use CFD to explore and understand compressor stall and surge • Develop and test control strategies (air injection) for centrifugal compressors • Apply CFD to compare low-speed and high-speed configurations

  4. Motivation and Objectives Compressor instabilities can cause fatigue and damage to entire engine

  5. Mean Operating Point Pressure Rise Peak Performance Pressure Rise Limit Cycle Oscillations Flow Rate Flow Rate Period of Mild Surge Cycle Period of Deep Surge Cycle Flow Rate Flow Rate Flow Reversal Time Time What is Surge? Mild Surge Deep Surge

  6. Bleed Valves Movable Plenum Walls Guide Vanes Air-Injection How to Alleviate Surge • Diffuser Bleed Valves • Pinsley, Greitzer, Epstein (MIT) • Prasad, Neumeier, Haddad (GT) • Movable Plenum Wall • Gysling, Greitzer, Epstein (MIT) • Guide Vanes • Dussourd (Ingersoll-Rand Research Inc.) • Air Injection • Murray (CalTech) • Weigl, Paduano, Bright (NASA Glenn) • Fleeter, Lawless (Purdue)

  7.       ˆ ˆ ˆ ˆ ˆ ˆ    q dV  E i  F j  G k  n dS  R i  S j  T k  n dS  t  Numerical Formulation (Flow Solver) Reynolds-averaged Navier-Stokes equations in finite volume representation: • q is the state vector. • E, F, and G are the inviscid fluxes (3rd order accurate). R, S, and T are the viscous fluxes (2nd order accurate). • A one-equation Spalart-Allmaras model is used. • Code can handle multiple computational blocks and rotor-stator-interaction.

  8. Boundary Conditions (Flow Solver) Periodic boundary at clearance gap Solid wall boundary at impeller blades Solid wall boundary at compressor casing Inflow boundary Periodic boundary at diffuser Solid wall boundary at compressor hub Outflow boundary (coupling with plenum) Periodic boundary at compressor inlet

  9. Plenum chamber • up(x,y,z) = 0 • pp(x,y,z) = const. • isentropy . mt ap, Vp Outflow boundary . mc Outflow Boundary Condition (Flow Solver) Conservation of mass and isentropic expression for speed of sound:

  10. 40cm DLR High-Speed Centrifugal Compressor • Designed and tested by DLR • High pressure ratio • AGARD test case

  11. DLR High-Speed Centrifugal Compressor • 24 Main blades • 30 Backsweep • Grid 141 x49 x 33 (230,000 nodes) • A grid sensitivity study was done with up to 1.8 Million nodes. • Design Conditions: • 22,360 RPM • Mass flow = 4.0 kg/s • Total pressure ratio = 4.7 • Adiab. efficiency = 83% • Exit tip speed = 468 m/s • Inlet Mrel = 0.92

  12. Validation Results (Design Conditions) Static Pressure Along Shroud • Excellent agreement between CFD and experiment • Results indicate grid insensitivity => Baseline Grid is used subsequently

  13. D C B A Off-Design ResultsPerformance Characteristic Map Computational and experimental data are within 5% Fluctuations at 3.2 kg/sec are 23 times larger than at 4.6 kg/sec

  14. B: 3.8 kg/sec A: 4.6 kg/sec 20 20 10 10 Pressure Rise Fluctuations (%) Pressure Rise Fluctuations (%) 0 0 -10 -10 -20 -20 -30 -20 -10 0 10 20 30 -30 -20 -10 0 10 20 30 Mass Flow Fluctuations (%) Mass Flow Fluctuations (%) C: 3.4 kg/sec D: 3.2 kg/sec 20 20 10 10 Pressure Rise Fluctuations (%) Pressure Rise Fluctuations (%) 0 0 -10 -10 -20 -20 -30 -20 -10 0 10 20 30 -30 -20 -10 0 10 20 30 Mass Flow Fluctuations (%) Mass Flow Fluctuations (%) Off-Design Results (High-Speed) Performance Characteristic Map Large limit cycle oscillations develop near surge line

  15. Off-Design Results (High-Speed) Mass Flow Fluctuations Mild surge cycles develop Surge amplitude grows to 60% of mean flow rate Surge frequency = 90 Hz (1/100 of blade passing frequency)

  16. Casing 0.04RInlet 5° Impeller Compressor Casing RInlet Compressor Face Rotation Axis Injected Fluid Sheet Yaw Angle b Main Flow Air Injection Setup Systematic study: injection rate and yaw angle were identified as the most sensitive parameters. Related work: Rolls Royce, Cal Tech, NASA Glenn /MIT,

  17. Air Injection Results (Steady Jets)Different Yaw Angles, 3% Injected Mass Flow Rate Optimum yaw angle of 7.5deg. yields best result Mass Flow (kg/sec) Rotor Revolutions, wt/2p Reduction in Surge Amplitude (%) Positive yaw angle is measured in opposite direction of impeller rotation Yaw Angle (Degree)

  18. Optimum: Surge amplitude/main flow = 8 % Injected flow/main flow = 3.2 % Yaw angle = 7.5 degrees Air Injection Results (Parametric Study) • An optimum yaw angle exists. • A reasonable amount (~3%) of injected air is sufficient to suppress surge.

  19. With Phase Angle Adjustments Without Phase Angle Adjustments Air Injection Results (Pulsed Jets) • Surge fluctuations decrease as long as the injection phase was lagged 180 deg. relative to the flow => suggests feedback control • reduction in external air requirements by 50% (compared to steady jets) Nondim. Surge Fluctuations (%) Rotor Revolutions, wt/2p

  20. Air Injection Results (Pulsed Jets) • 1.5% injected mass is sufficient to suppress surge • High-frequency jets (winj = 4wsurge) perform better than low-frequency jets (winj = wsurge) Nondim. Surge Fluctuations (%) Rotor Revolutions, wt/2p

  21. Numerical Probe Jet Air Injection Results (Pulsed Jets)Vorticity Magnitudes Near Leading Edge Tip • Increased amounts of mixing enhance the momentum transfer from the injected fluid to the low-kinetic energy particles in the separation zone

  22. Area of Interest Air Injection Results (Pulsed Jets)Shear Stresses Near Leading Edge Tip • High-frequency actuation leads to significantly larger shear stress levels. • Produce smaller but intense turbulent eddies. • Enhances the mixing at small length scales. Jet

  23. Conclusions • A Viscous flow solver has been developed to • obtain a detailed understanding of instabilities in centrifugal compressors. • determine fluid dynamic factors that lead to stall onset. • Steady jets are effective means of controlling surge: • Alter local incidence angles and suppress boundary layer separation. • Yawed jets are more effective than parallel jets. • An optimum yaw angle exists for each configuration. • Pulsed jets yield additional performance enhancements: • Lead to a reduction in external air requirements. • Jets pulsed at higher frequencies perform better than low-frequency jets due to enhanced mixing at small length scales.

  24. Recommendations • Perform studies that link air injection rates to surge amplitude via a feedback control law. • Use flow solver to analyze and optimize other control strategies, e.g. inlet guide vanes, synthetic jets, casing treatments. • Employ multi-passage flow simulations to study rotating stall and appropriate control strategies. • Study inflow distortion and its effects on stall inception. • Improve turbulence modeling of current generation turbomachinery solvers. Analyze the feasibility of LES methods.

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