Spray visualisation and acoustic analysis in a gas-turbine type burner

This paper presents the characterisation of self-excited oscillations in a kerosene burner. The combustion instability exhibits two different modes and frequencies depending on the air flow rate. Experimental results reveal the influence of the spray to shift between these two modes. Pressure and heat release fluctuations have been measured simultaneously and the flame transfer function has been calculated from these measurements. The Mie scattering technique has been used to record spray fluctuations in reacting conditions with a high speed camera. Innovative image processing has enabled us to obtain fluctuations of the Mie scattered light from the spray as a temporal signal acquired simultaneously with pressure fluctuations. This has been used to determine a transfer function relating the image intensity and hence the spray fluctuations to changes in air velocity. This function has identified the different role the spray plays in the two modes of instability. At low air flow rates, the spray responds to an unsteady air flow rate and the time varying spray characteristics lead to unsteady combustion. At higher air flow rates, effective evaporation means that the spray dynamics are less important, leading to a different flame transfer function and frequency of self-excited oscillation. In conclusion, the combustion instabilities observed are closely related with the fluctuations of the spray motion and evaporation.

Fundamental limits on the suppression of molecular fluctuations.

Negative feedback is common in biological processes and can increase a system's stability to internal and external perturbations. But at the molecular level, control loops always involve signalling steps with finite rates for random births and deaths of individual molecules. Here we show, by developing mathematical tools that merge control and information theory with physical chemistry, that seemingly mild constraints on these rates place severe limits on the ability to suppress molecular fluctuations. Specifically, the minimum standard deviation in abundances decreases with the quartic root of the number of signalling events, making it extremely expensive to increase accuracy. Our results are formulated in terms of experimental observables, and existing data show that cells use brute force when noise suppression is essential; for example, regulatory genes are transcribed tens of thousands of times per cell cycle. The theory challenges conventional beliefs about biochemical accuracy and presents an approach to the rigorous analysis of poorly characterized biological systems.