Large Eddy Simulation Combined with System Identification Method to Analyze Non-Premixed Flame Transfer Function

Abstract

ABSTRACT The heat release response (HRR) of the flame is a pivotal aspect of combustion instability investigation, commonly characterized by the Flame Transfer Function (FTF). This study employed a combination of large eddy simulation (LES) and system identification (SI) techniques to derive the FTF for a methane-air non-premixed swirling burner. The influence of memory time and excitation signals within the LES+SI was investigated as only a few studies have been conducted in this direction so far, and validated against experimental data. Variations in memory time led to notable shifts in frequency and amplitude for gain peaks and valleys, with modest effects on phase delay within the 20–140 Hz range. The number of corner frequencies increased with memory time, whereby smaller memory times flattened the gain curve and underestimated phase delay, and larger memory times intensified curve undulations, distorting finer details. By minimizing the Mean Relative Error (MRE) between LES+SI results and experimental data, the optimized memory time of 0.017 s was identified, which closely aligned with the convection time of 0.0167 s. Consequently, convection time could be referenced in a priori estimation approach for memory time in a non-premixed swirling burner. In comparing FTF obtained from different excitation signals, the Superimposed Sinusoidal Signal (SINE) excelled in the gain curve within the 20–100 Hz range, accurately capturing the 30 Hz gain peak and 80 Hz valley, while the Broadband White Noise (BBWN) excelled in the phase curve within the same range, both yielding a smaller mean relative error (MRE). However, the Discrete Random Binary Signal (DRBS) demonstrated the best consistency with experimental data within the 100–190 Hz range, and boasted an MRE of 38.01% and 28.55% respectively for the gain and phase curve within the entire frequency range. Consequently, we inferred that DRBS functioned as the excitation signal with the most minimal identification error.