The development of turbine exit flow in a swan-necked inter-stage diffuser

This paper describes both the migration and dissipation of flow phenomena downstream of a transonic high-pressure turbine stage. The geometry of the HP stage exit duct considered is a swan-necked diffuser similar to those likely to be used in future engine designs. The paper contains results both from an experimental programme in a turbine test facility and from numerical predictions. Experimental data was acquired using three fast-response aerodynamic probes capable of measuring Mach number, whirl angle, pitch angle, total pressure and static pressure. The probes were used to make time-resolved area traverses at two axial locations downstream of the rotor trailing edge. A 3D time-unsteady viscous Navier-Stokes solver was used for the numerical predictions. The unsteady exit flow from a turbine stage is formed from rotordependent phenomena (such as the rotor wake, the rotor trailing edge recompression shock, the tip-leakage flow and the hub secondary flow) and vane-rotor interaction dependant phenomena. This paper describes the time-resolved behaviour and three-dimensional migration paths of both of these phenomena as they convect downstream. It is shown that the inlet flow to a downstream vane is dominated by two corotating vortices, the first caused by the rotor tip-leakage flow and the second by the rotor hub secondary flow. At the inlet plane of the downstream vane the wake is extremely weak and the radial pressure gradient is shown to have caused the majority of the high loss wake fluid to be located between the mid-height of the passage and the casing wall. The structure of the flow indicates that between a high pressure stage and a downstream vane simple two-dimensional blade row interaction does not occur. The results presented in this paper indicate that the presence of an upstream stage is likely to significantly alter the structure of the secondary flow within a downstream vane. The paper also shows that vane-rotor interaction within the upstream stage causes a 10° circumferential variation in the inlet flow angle of the 2nd stage vane.

Internal representations of temporal statistics and feedback calibrate motor-sensory interval timing.

Humans have been shown to adapt to the temporal statistics of timing tasks so as to optimize the accuracy of their responses, in agreement with the predictions of Bayesian integration. This suggests that they build an internal representation of both the experimentally imposed distribution of time intervals (the prior) and of the error (the loss function). The responses of a Bayesian ideal observer depend crucially on these internal representations, which have only been previously studied for simple distributions. To study the nature of these representations we asked subjects to reproduce time intervals drawn from underlying temporal distributions of varying complexity, from uniform to highly skewed or bimodal while also varying the error mapping that determined the performance feedback. Interval reproduction times were affected by both the distribution and feedback, in good agreement with a performance-optimizing Bayesian observer and actor model. Bayesian model comparison highlighted that subjects were integrating the provided feedback and represented the experimental distribution with a smoothed approximation. A nonparametric reconstruction of the subjective priors from the data shows that they are generally in agreement with the true distributions up to third-order moments, but with systematically heavier tails. In particular, higher-order statistical features (kurtosis, multimodality) seem much harder to acquire. Our findings suggest that humans have only minor constraints on learning lower-order statistical properties of unimodal (including peaked and skewed) distributions of time intervals under the guidance of corrective feedback, and that their behavior is well explained by Bayesian decision theory.