Session: 32-03 Compressor Design Methods

Paper Number: 101343

101343 - Development and Validation of an Accurate, Minimal-Input Mean-Line Method for the Off-Design Performance Prediction of an Axial Compressor Stage, Using a Compressor-Diffuser Analogy 

The analysis and performance prediction of gas turbines benefits greatly from the use of one‑dimensional mean‑line modelling, as it can provide reasonably accurate results while requiring fewer geometric inputs and significantly lower computational expenses when compared to higher‑order methods such as CFD. However, even mean‑line codes may be limited by the amount of geometric and operational data available, often restricted by Original Equipment Manufacturers (OEMs) for proprietary reasons. This often results in a greater number of assumptions and tuning factors required in order to achieve accurate results. This paper documents the development of a one‑dimensional modelling method which requires minimal geometric inputs and tuning factors for analysing the performance of a transonic axial compressor stage, for use in a gas turbine. The minimal‑input model is achieved through an analogous modelling methodology, whereby the stage’s rotor and stator rows are modelled as simple diffusers with flow areas approximately equal to those in the compressor stage. A design‑point calibration operation is performed to estimate all diffuser flow path areas using a set of industry knowledge‑based assumptions, and blade angles are determined using widely adopted correlations from open literature. The estimated geometries are then used as inputs for an off‑design model, which includes a simplified pressure‑loss model, also obtained from open literature.  The only calibration required is that of a minor area adjustment factor to better match the known compressor performance map. The model was validated against four well documented NASA axial compressor stages with good agreement. The modelling methodology presented an efficient means of predicting compressor stage performance with acceptable accuracy while requiring minimal inputs, thus allowing gas turbine operators and analysts to gain greater insights into the compressor’s off‑design behaviour, with the limited geometric data available to them.

Presenting Author: Daniel Barlin University of Cape Town

Presenting Author Biography: Daniel is a Mechanical Engineering graduate from the University of Cape Town, South Africa, where he is currently in the process of completing his Master's in Mechanical Engineering with the Applied Thermofluid Process Modelling Research Unit (ATProM). Daniel's current research focuses on developing one-dimensional thermofluid models, particularly in the field of turbomachinery, and specifically axial compressors. He also has past experience in Computational Fluid Dynamics, and has published work in that field.

Authors:

Daniel Barlin University of Cape Town
Wim Fuls University of Cape Town