Oxygen carrier dispersion in inert packed beds to improve performance in chemical looping combustion

Various packed beds of copper-based oxygen carriers (CuO on Al2O3) were tested over 100 cycles of low temperature (673K) Chemical Looping Combustion (CLC) with H2 as the fuel gas. The oxygen carriers were uniformly mixed with alumina (Al2O3) in order to investigate the level of separation necessary to prevent agglomeration. It was found that a mass ratio of 1:6 oxygen carrier to alumina gave the best performance in terms of stable, repeating hydrogen breakthrough curves over 100 cycles. In order to quantify the average separation achieved in the mixed packed beds, two sphere-packing models were developed. The hexagonal close-packing model assumed a uniform spherical packing structure, and based the separation calculations on a hypergeometric probability distribution. The more computationally intensive full-scale model used discrete element modelling to simulate random packing arrangements governed by gravity and contact dynamics. Both models predicted that average 'nearest neighbour' particle separation drops to near zero for oxygen carrier mass fractions of x≥0.25. For the packed bed systems studied, agglomeration was observed when the mass fraction of oxygen carrier was above this threshold. © 2013 Elsevier B.V.

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.