The effects of hydrodynamic strain on diffusivethermal instabilities at low Lewis number were studied experimentally using a counterflow slot-jet apparatus with H 2 -O 2 -N 2 mixtures. Three configurations were examined:single premixed, twin premixed and nonpremixed flames. For all three configurations a wide variety of nonplanar flame structures were observed. Two extinction limits, one at very high strain (corresponding to a residence time limitation) and one at low strain (corresponding to a heat loss extinction) were found.For premixed flames, nonplanar structures occurred for a wide range of mixtures. In many cases, near extinction the flame structures reduced to a single "flame tube" elongated in the direction of extensional strain. An examination of stoichiometry effects revealed a critical equivalence ratio for instability similar to that known to exist for flame balls. At low flow velocities a transition to flames attached to the jet exits in complicated ways was noted, and at high flow velocities transition to turbulent flow was noted. For nonpremixed flames, nonplanar flame structures were observed only for near-extinction conditions, but the resulting flame shapes were quite similar to those of premixed flames. These results are compared to recent theoretical predictions.

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State and parameter estimation is essential for process monitoring and control. Observability plays an important role in both state and parameter estimation. In simultaneous state and parameter estimation, the parameters are often augmented as extra states of the original system. When the augmented system is observable, various existing state estimation approaches may be used to estimate the states and parameters simultaneously. However, when the augmented system is not observable, how we should proceed to maximally extract the information contained in the measured outputs is not clear. This paper concerns the simultaneous state and parameter estimation when the augmented system is not fully observable. Specifically, we first show how sensitivity analysis is related to observability of a dynamic system and then illustrate how it may be used to select variables for simultaneous estimation. We also propose a moving horizon state estimation (MHE) design that can use the variable selection results in a natural way. Extensive simulations are carried out to show the efficiency of the proposed approach.