Detonation initiation by compressible turbulence thermodynamic fluctuations

TL;DR

This paper extends the laminar temperature-gradient mechanism to a statistical model predicting detonation initiation in turbulent gases, validated through numerical simulations of compressible turbulence in hydrogen-air mixtures.

Contribution

It introduces a new statistical model that accounts for turbulence-induced thermodynamic fluctuations to predict detonability, expanding beyond idealized laminar conditions.

Findings

The model shows strong potential in predicting detonability due to turbulence.

Numerical simulations support the model's applicability to real turbulent flows.

The approach bridges the gap between laminar theory and turbulent detonation initiation.

Abstract

Theory and computations have established that thermodynamic gradients created by hot spots in reactive gas mixtures can lead to spontaneous detonation initiation. However, the current laminar theory of the temperature-gradient mechanism for detonation initiation is restricted to idealized physical configurations. Thus, it only predicts conditions for the onset of detonations in quiescent gases, where an isolated hot spot is formed on a timescale shorter than the chemical and acoustic timescales of the gas. In this work, we extend the laminar temperature-gradient mechanism into a statistical model for predicting the detonability of an autoignitive gas experiencing compressible isotropic turbulence fluctuations. Compressible turbulence forms non-monotonic temperature fields with tightly-spaced local minima and maxima that evolve over a range of timescales, including those much larger than chemical and acoustic timescales. We examine the utility of the adapted statistical model through direct numerical simulations of compressible isotropic turbulence in premixed hydrogen-air reactants for a range of conditions. We find strong, but not conclusive, evidence that the model can predict the degree of detonability in an autoignitive gas due to turbulence-induced thermodynamic gradients.