Measurement and Prediction of Centrifugal Compressor Axial Forces During Surge—Part II: Dynamic Surge Model

The force acting on centrifugal compressors is an important parameter to be considered throughout the operating life of these turbomachines. When the compressor is operating in surge conditions, these forces can become highly dangerous for the mechanical and aerodynamic structures. This instability is usually avoided in industrial applications, but the antisurge system may not react in time when emergency shutdowns or power failures take place. During these rapid transients, surge can develop, generating unsteady forces which can harm the close clearance components of the compressor. Therefore, the capability to predict the characteristics and the dynamics of these surge forces would allow the estimation of the off-design fatigue cycles produced on these components by surge. Currently, no validated method exists to predict the frequency and amplitude of the surge forces and determine the potential damage of these components. In this paper, a lumped parameter model, developed by using the bond graph approach to predict the dynamic surge fluid-dynamic oscillations, is presented. The model requires the geometry and the steady-state performance maps of the compressor as inputs, together with the piping system configuration characteristics. The simulator is provided with a supplementary tool to estimate the axial force frequency and amplitude, taking into consideration all the contributions to the axial fluid-dynamic thrust, the stiffness-damping of the thrust bearing, and the mass of the rotor. The model was tuned and validated using the test case axial force data from the Southwest Research Institute (SWRI) facility. The model has shown good agreement with the experimental results which implies that it can offer significant information about the severity of a surge event and the quantification of the machine performance losses together with possible damage to the close clearance components. This study is a first important step that can lead to schedule optimization for maintenance and repair activities.