RANS-URANS in axial compressor, a design methodology

Turbomachinery flows are inherently unsteady. Until now during the design process, unsteadiness has been neglected, with resort merely to steady numerical simulations. Despite the assumption involved, the results obtained with steady simulations have been used with success. One of the questions arising in recent years is can unsteady simulations be used to improve the design of turbomachines? In this work the numerical simulation of a multi-stage axial compressor is carried out. Comparison of Reynolds averaged Navier-Stokes (RANS) and unsteady Reynolds averaged Navier-Stokes (URANS) calculation shows that the unsteadiness affects pressure losses and the prediction of stall limit. The unsteady inflow due to the wake passing mainly modifies the losses and whirl angle near the endwalls. The computational cost of the fully unsteady compared with a steady simulation is about four times in terms of mesh dimension and two orders of magnitude as number of iterations. A mixed RANS-URANS solution has been proposed to give the designer the possibility to simulate an unsteady stage embedded in a steady-state simulation. This method has been applied to the simulation of a four-stage axial compressor rig. The mixed RANS-URANS approach has been developed using sliding and mixing planes as interface conditions. The rotor-stator interaction has been captured physically while reducing the computational time and mesh size.

Heat release rate measurement in turbulent flames

The dominant industrial approach for the reduction of NO x emissions in industrial gas turbines is the lean pre-mixed prevaporized concept. The main advantage of this concept is the lean operation of the combustion process; this decreases the heat release rate from the flame and results in a reduction in operating temperature. The direct measurement of heat release rates via simultaneous laser induced fluorescence of OH and CH 2O radicals using planar laser induced fluorescence. The product of the two images correlated with the forward production rate of the HCO radical, which in turn has correlated well with heat release rates from premixed hydrocarbon flames. The experimental methodology of the measurement of heat release rate and applications in different turbulent premixed flames were presented. This is an abstract of a paper presented at the 7th World Congress of Chemical Engineering (Glasgow, Scotland 7/10-14/2005).

Bayesian separation and recovery of convolutively mixed autoregressive sources

In this paper we address the problem of the separation and recovery of convolutively mixed autoregressive processes in a Bayesian framework. Solving this problem requires the ability to solve integration and/or optimization problems of complicated posterior distributions. We thus propose efficient stochastic algorithms based on Markov chain Monte Carlo (MCMC) methods. We present three algorithms. The first one is a classical Gibbs sampler that generates samples from the posterior distribution. The two other algorithms are stochastic optimization algorithms that allow to optimize either the marginal distribution of the sources, or the marginal distribution of the parameters of the sources and mixing filters, conditional upon the observation. Simulations are presented.