A laser-induced breakdown spectroscopy method to assess the stochasticity of plasma-flame transition in sprays

Abstract

<jats:title>Abstract</jats:title> <jats:p>An experimental approach is presented to evaluate the impact of plasma composition arising from pulse-to-pulse energy and mixture fluctuations on the non-resonant laser-induced ignition of sprays. This allows for spark events to be conditioned on the successful or failed establishment of a flame kernel, a phase dominated by plasma decomposition and recombination reactions and the on-set of combustion reactions, that is, independent of the subsequent flame growth phase controlled by propagation phenomena only, such as fuel availability and turbulent strain. For that, laser-induced breakdown spectroscopy of the spark-generated plasma is carried out, followed by OH<jats:inline-formula> <jats:tex-math><?CDATA $^*$?></jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msup> <mml:mi /> <mml:mo>∗</mml:mo> </mml:msup> </mml:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="mstac7436ieqn1.gif" xlink:type="simple" /> </jats:inline-formula> high-speed imaging of the kernel. Exploratory experiments in spatially uniform and polydisperse kerosene droplet distributions in a jet suggest that the hydrogen concentration in the plasma deriving from the fuel dissociated by the spark is closely related to the generated OH<jats:inline-formula> <jats:tex-math><?CDATA $^*$?></jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msup> <mml:mi /> <mml:mo>∗</mml:mo> </mml:msup> </mml:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="mstac7436ieqn2.gif" xlink:type="simple" /> </jats:inline-formula> radicals levels and, in turn, with the success of establishing a flame kernel. This suggests that the ignition process is heavily controlled by mixture fluctuations at the spark, inherent of spray flows. The instantaneous mixture at the spark is estimated with a stochastic model, with the probability density function of the equivalence ratio exhibiting values higher than twice the mean value, while the highest probability occurs at lean conditions between the gaseous equivalence ratio and the overall equivalence ratio. The findings corroborate insights on the early-phase ignition obtained from direct numerical simulations, and the framework paves the way for the development of smart online engine-health tools to assess relight capability in future aeroengines.</jats:p>