Stall is a type of flow instability in compressors that sets the low-flow limit for compressor operation. During the past few decades, efforts to develop a reliable stall warning system have had limited success. This paper focuses on the small nonlinear disturbances prior to deep surge and introduces a new approach to identify these disturbances using nonlinear feature extraction algorithms including phase-reconstruction of time-series signals and evaluation of a parameter called approximate entropy. To the best of our knowledge, this is the first time approximate entropy has been used for stall warning, and thus, its definition and utility are presented in detail. The technique is applied to stall data sets from two different compressors: a high-speed centrifugal compressor that unexpectedly entered rotating stall during a speed transient and a multistage axial compressor with both modal- and spike-type stall inception. In both cases, nonlinear disturbances appear, in terms of spikes in approximate entropy, prior to surge. The presence of these presurge spikes indicates the potential of using the approximate entropy parameter for small disturbance detection and stall warning. The details of the nonlinear feature extraction algorithm, including guidelines for its application as well as results from applying the algorithm to rig-level data, are presented.

The flow in shrouded stator cavities can be quite complex with axial, radial, and circumferential variations. As the leakage flow recirculates and is re-injected into the main flow path upstream of the stator, it deteriorates the near-hub flow field and, thus, degrades the overall aerodynamic performance of the compressor. In addition, the windage heating in the cavity can raise thermal-mechanical concerns. Fully understanding the details of the shrouded-hub cavity flow in a multistage environment can enable better hub cavity designs. In the first part of the paper, the influence of the hub leakage flow on compressor performance and its interactions with the primary flow were investigated. While the impact of hub leakage flow on the primary passage is readily available in the open literature, details inside the cavity geometry are scarce due to the difficulties in instrumenting that region for an experiment or modeling the full cavity geometry. To shed light on this topic, the flow physics in the stator cavity inlet and outlet wells are investigated in this paper using a coupled computational fluid dynamics model with the inclusion of the stator cavity wells for the Purdue 3-stage (P3S) axial compressor, which is representative of the rear stages of a high-pressure-compressor in core engines. At the inlet cavity, the presence of at least one pair of vortices influences the trajectory of the cavity leakage flow. The amount of leakage flow also determines the size of the vortical structures, with larger clearances creating a smaller vortex and vice versa. After passing through the labyrinth seals, the leakage flow travels along the stator landing first and then transitions to the rotor drum. In general, a flow path closer to the rotor drum achieves higher circumferential velocity but also exhibits significant temperature rise. A rise in circumferential velocity directly corresponds to a rise in temperature. In addition, the windage heating increases with increasing seal clearance. Furthermore, the inlet well contributes the most to overall windage, nearly 50% of the total windage heating, while the labyrinth seals and outlet well account for very little.

Since isentropic efficiency is widely used in evaluating the performance of compressors, it is essential to accurately calculate this parameter from experimental measurements. Quantifying realistic bounds of uncertainty in experimental measurements are necessary to make meaningful comparisons to computational fluid dynamics simulations. This paper explores how the gas model utilized for air can impact not only the efficiency calculated in an experiment, but also the uncertainty associated with that calculation. In this paper, three different gas models are utilized: the perfect gas model, the ideal gas model, and the real gas model. A commonly employed assumption in calculating compressor efficiency is the perfect gas assumption, in which the specific heat, is treated as a constant and is independent of temperature and pressure. Results show significant differences in both calculated efficiency and the resulting uncertainty in efficiency between the perfect gas model and the real gas model. The calculated compressor efficiency from the perfect gas model is overestimated, while the resulting uncertainties from the perfect gas model are underestimated. The ideal gas model agrees well with the real gas model, however. Including the effect of uncertainty in gas properties results in very large uncertainties in isentropic efficiency, on the order of ten points, for low pressure ratio machines.

Extensive research studying tip clearance effects on compressor performance has been conducted during the past few decades with significant progress achieved. However, most of the previous investig...