As a promising strategy to mitigate carbon emissions, hydrogen enrichment of conventional
fuels is gaining increasing interest, but can lead to increased propensity to damaging …

This paper demonstrates the ability of recurrent neural networks (RNNs) to predict the linear
and the nonlinear response of a premixed laminar flame to incoming velocity perturbations …

In this computational paper, we model acoustic dynamics in space and time from synthetic
sensor data. The tasks are (i) to predict and extrapolate the spatiotemporal dynamics and (ii) …

Identifying the governing parameters of self-sustained oscillation is crucial for the diagnosis,
prediction and control of thermoacoustic instabilities. In this paper, we propose and validate …

This paper demonstrates the ability of the neural network trained on frequency-sweeping
signals with different amplitudes to reconstruct the flame nonlinear response. The neural …

Modelling the flame response of turbulent flames via data-driven approaches is challenging
due, among others, to the presence of combustion noise. Neural network methods have …

In this work, we present a parsimonious set of ordinary differential equations (ODEs),
describing with good precision and over a wide range of frequencies the linear and …

In this work we present a parsimonious set of ordinary differential equations (ODEs) that
describes with satisfactory precision the linear and non-linear dynamics of a typical laminar …

This work investigates the nonlinear response of a conical premixed flame to dual-frequency
excitation through experiments and G-equation analysis. In addition to the responses at …

A nonlinear phenomenological model of two coupled oscillators is proposed, which is able
to describe the rich nonlinear behaviour stemming from an unstable pure intrinsic thermo …