Session: 34-03 Turbulence modeling, CFD models, and assessment

Paper Number: 152022

Optimisation of SA-PGω Turbulence Model for Multi-Stage Compressor at Off-Design Conditions 

The Spalart-Allmaras (SA) turbulence model is one of the most popular models applied to compressors, but it often over-predicts blockage size and hence under-predicts the stall margin. To address this issue, the SA-PGω model was proposed to improve the prediction of compressor near-stall flow. The modification is based on the dimensionless vortical pressure gradient, which identifies blockage cells featured by 3D swirling, adverse pressure gradient, and low-momentum flows. The SA-PGω model coefficients were originally calibrated using rotor exit radial profile data of NASA Rotor 67 at peak-efficiency and near-stall points. A relatively wide band of suitable coefficients were proposed, and the chosen optimal coefficients demonstrated good accuracy for single-stage compressors compared with the original SA model and its variants. However, it will be shown in this paper that, albeit superior to other SA formulations, the SA-PGω model with originally proposed optimal coefficients led to overpredicted blockage size and premature stall for a multi-stage compressor. In light of this, optimisation of SA-PGω model coefficients was conducted using a data-driven approach. A surrogate model using artificial neural network (ANN) was trained for efficient data generation, which provides aerodynamics performance quantities free of steady state CFD computations. Multi-objective optimisation was conducted to determine the optimal SA-PGω model coefficient combination that maximise the aerodynamic performance prediction accuracy in reference to experimental measurements. The recalibrated SA-PGω model shows significant improvements in stall boundary and stage matching predictions especially at off-design operating conditions. 

Presenting Author: Ryosuke Seki Mitsubishi Heavy Industries, LTD.

Presenting Author Biography: Mr.Ryosuke Seki received B.S. and M.S. degrees in applied mechanics and aerospace engineering from Waseda University, Japan, in 2011 and 2013, respectively. Since 2013, he has been a researcher at Turbomachinery No.2 Laboratory，Turbomachinery Research Department，Research & Innovation Center，Mitsubishi Heavy Industries, Japan．He engages in design of axial compressor for industrial gas turbine，development of CFD codes，application of CFD codes to some kind of turbomachines such as centrifugal compressor ，turbochargers and steam turbine. Since 2021,he is engaged in a wide range of turbomachinery business as a Deputy Manager and Professional Engineer, Japan. From 2022, he got a Professional Simulation Engineer certification in NAFEMS and is active internationally.

Authors:

Ryosuke Seki Mitsubishi Heavy Industries, LTD.
Yuto Terauchi Mitsubishi Heavy Industries, LTD.
Fanzhou Zhao Imperial College London
Xiao He Shanghai Jiao Tong University
Mehdi Vahdati Universidad Politécnica de Madrid