The effect of an upstream turbine on a low-aspect ratio vane

The interaction between a high-pressure rotor and a downstream vane is dominated by vortex-blade interaction. Each rotor blade passing period two co-rotating vortex pairs, the tip-leakage and upper passage vortex and the lower passage and trailing shed vortex, impinge on, and are cut by, the vane leading edge. In addition to the streamwise vortex the tip-leakage flow also contains a large velocity deficit. This causes the interaction of the tip-leakage flow with a downstream vane to differ from typical vortex blade interaction. This paper investigates the effect these interaction mechanisms have on a downstream vane. The test geometry considered was a low aspect ratio second stage vane located within a S-shaped diffuser with large radius change mounted downstream of a shroudless high-pressure turbine stage. Experimental measurements were conducted at engine-representative Mach and Reynolds numbers, and data was acquired using a fast-response aerodynamic probe upstream and downstream of the vane. Time-resolved numerical simulations were undertaken with and without a rotor tip gap in order to investigate the relative magnitude of the interaction mechanisms. The presence of the upstream stage is shown to significantly change the structure of the secondary flow in the vane and to cause a small drop in its performance.

Unsteady ejectors: The effect of driver jet mark-space ratio

mark Unsteady ejectors can be driven by a wide range of driver jets. These vary from pulse detonation engines, which typically have a long gap between each slug of fluid exiting the detonation tube (mark-space ratios in the range 0.1-0.2) to the exit of a pulsejet where the mean mass flow rate leads to a much shorter gap between slugs (mark-space ratios in the range 2-3). The aim of this paper is to investigate the effect of mark-space ratio on the thrust augmentation of an unsteady ejector. Experimental testing was undertaken using a driver jet with a sinusoidal exit velocity profile. The mean value, amplitude and frequency of the velocity profile could be changed allowing the length to diameter ratio of the fluid slugs L/D and the mark-space ratio (the ratio of slug length to the spacing between slugs) L/S to be varied. The setup allowed L/S of the jet to vary from 0.8 to 2.3, while the L/D ratio of the slugs could take any values between 3.5 and 7.5. This paper shows that as the mark-space ratio of the driver jet is increased the thrust augmentation drops. Across the range of mark-space ratios tested, there is shown to be a drop in thrust augmentation of 0.1. The physical cause of this reduction in thrust augmentation is shown to be a decrease in the percentage time over which the ejector entrains ambient fluid. This is the direct result ofthe space between consecutive slugs in the driver jet decreasing. The one dimensional model reported in Heffer et al. [1] is extended to include the effect of varying L/S and is shown to accurately capture the experimentally measured behavior ofthe ejector. Copyright © 2010 by the American Institute of Aeronautics and Astronautics, Inc.

Low-order modelling of ducted flames with temporally varying equivalence ratio in realistic geometries

The interaction between unsteady heat release and acoustic pressure oscillations in gas turbines results in self-excited combustion oscillations which can potentially be strong enough to cause significant structural damage to the combustor. Correctly predicting the interaction of these processes, and anticipating the onset of these oscillations can be difficult. In recent years much research effort has focused on the response of premixed flames to velocity and equivalence ratio perturbations. In this paper, we develop a flame model based on the socalled G-Equation, which captures the kinematic evolution of the flame surfaces, under the assumptions of axisymmetry, and ignoring vorticity and compressibility. This builds on previous work by Dowling [1], Schuller et al. [2], Cho & Lieuwen [3], among many others, and extends the model to a realistic geometry, with two intersecting flame surfaces within a non-uniform velocity field. The inputs to the model are the free-stream velocity perturbations, and the associated equivalence ratio perturbations. The model also proposes a time-delay calculation wherein the time delay for the fuel convection varies both spatially and temporally. The flame response from this model was compared with experiments conducted by Balachandran [4, 5], and found to show promising agreement with experimental forced case. To address the primary industrial interest of predicting self-excited limit cycles, the model has then been linked with an acoustic network model to simulate the closed-loop interaction between the combustion and acoustic processes. This has been done both linearly and nonlinearly. The nonlinear analysis is achieved by applying a describing function analysis in the frequency domain to predict the limit cycle, and also through a time domain simulation. In the latter case, the acoustic field is assumed to remain linear, with the nonlinearity in the response of the combustion to flow and equivalence ratio perturbations. A transfer function from unsteady heat release to unsteady pressure is obtained from a linear acoustic network model, and the corresponding Green function is used to provide the input to the flame model as it evolves in the time domain. The predicted unstable frequency and limit cycle are in good agreement with experiment, demonstrating the potential of this approach to predict instabilities, and as a test bench for developing control strategies. Copyright © 2011 by ASME.

Distributed maximum likelihood for simultaneous self-localization and tracking in sensor networks

We show that the sensor self-localization problem can be cast as a static parameter estimation problem for Hidden Markov Models and we implement fully decentralized versions of the Recursive Maximum Likelihood and on-line Expectation-Maximization algorithms to localize the sensor network simultaneously with target tracking. For linear Gaussian models, our algorithms can be implemented exactly using a distributed version of the Kalman filter and a novel message passing algorithm. The latter allows each node to compute the local derivatives of the likelihood or the sufficient statistics needed for Expectation-Maximization. In the non-linear case, a solution based on local linearization in the spirit of the Extended Kalman Filter is proposed. In numerical examples we demonstrate that the developed algorithms are able to learn the localization parameters. © 2012 IEEE.