Soot formation and evolution are highly sensitive to fuel inlet perturbations, especially in confined turbulent swirling flows, where complex flow dynamics can amplify the impact of the perturbations. In this context, it is essential to quantitatively analyze the sensitivity of soot evolution to the perturbation. To this end, large-eddy simulations with system identification (LES/SI) of an aero-engine model combustor are conducted with state-of-the-art soot models. The sooting swirl flames are modelled as a single-input single-output (SISO) system. Similar to the flame transfer function F, a soot transfer function S is defined to characterise the response of soot to the inflow perturbation. The results show that for sufficiently small perturbations, the system can be assumed to be linear and time-invariant, and hence both F and S can be obtained from the unit impulse response (UIR) by a z-transform. Furthermore, it is found that S exhibits large amplitudes in the low-frequency band (22-150 Hz) and has negligible amplitude after exceeding 400 Hz that corresponds to the characteristic frequency of precessing vortex core (PVC). On the other hand, F exhibits three amplitude extrema at 400 Hz, 800 Hz, and 1200 Hz, respectively. Compared to flame response delay, soot response delay is very sensitive to the perturbation frequency. This work presents an opportunity to investigate soot from a nonlinear dynamics perspective.
The focus of this study is the effects of combustion dynamics, performance optimisation, and emissions profile on compression-ignition (diesel) engines operating on ternary fuel formulations comprising waste cooking oil (WCO), butanol, and conventional petroleum-based (diesel) fuel. The primary physicochemical characteristics of these WCO-butanol-diesel fuel formulations were almost identical to those observed with conventional petroleum-based diesel fuel, thereby conforming to both ASTM D6751 and EN 14214 specifications; these include density, kinematic viscosity, and flash point. The variation of the butanol concentration from 10% to 30%, as well as the volume fractional distribution of the WCO from 10% to 40% vol., resulted in significant differences in the thermodynamic response of the engine test rig used for this lab evaluation. Additionally, the D60B20Bu20 ternary blend produced a 7.14% increase in brake thermal efficiency (BTE), from pure (D100) diesel fuel to the D60B20Bu20 baseline; there was also a corresponding reduction in brake-specific fuel consumption (BSFC) by 6.84% and brake-specific energy consumption (BSEC) by 6.00%. The exhaust gas temperature (EGT) for the alcohol-treated ternary coatings was significantly lower than that of pure diesel due to the high latent heat of vaporisation of butanol. The application of advanced environmental profiles on these results demonstrated significant reductions in emissions of regulated pollutants. The most pronounced results were seen with the use of the D60B20Bu20 formulation, which resulted in the largest reduction in both carbon monoxide (CO) emissions (15.94%), and unburned hydrocarbons (HC) (22.85%), respectively; there was also a significant reduction in smoke opacity at high load operating conditions. In contrast to the above, there was an average overall improvement of 7.74% in thermal nitrogen oxide (NOx) emissions across all blends due to both the very high premixed heating phase and the availability of fuel-bound oxygen. Additionally, transient combustion data demonstrated that the D60B20Bu20 matrix achieved the highest peak in-cylinder pressure, maximum mean gas temperature and greatest sharpness of net heat release rate (HRR). This study provides preliminary evidence that a multi-criteria optimisation framework can be used to identify the best overall compromise between aggressively reducing carbonaceous emissions while achieving improved thermodynamic performance with the D60B20Bu20 blend.
One important issue that arises in the engineering application of reduced-order models of thermoacoustic instabilities is that of obtaining a comprehensive representation of the multidimensional combustion dynamics in the form of a flame describing functions (FDFs) that cover the whole domain of operation. By systematically measuring FDFs over this domain, it was recently shown that it was possible to delineate the unstable region of operation of an annular combustor. However, this instability prediction process requires a comprehensive sweep of operational conditions, which can be challenging and costly in practice. The present study explores the use of a supervised Machine Learning method, specifically Gaussian Process Regression (GPR), to predict FDFs from a subset of experimentally determined FDFs. It is shown that a small number of FDF datasets (typically 7 out of 35) can be used for training to predict the remaining datasets and forecast the FDF ensemble corresponding to the whole domain of operation. The method achieves high accuracy, with $ R<^>2 $ R2 scores exceeding 0.9 for the FDF gain and 0.99 for the phase. A physics-based reduced-order model is then employed to calculate instability growth rate maps, thereby inferring the domain of azimuthal instability of an annular combustor. Comparisons with measured FDFs across all operating points indicate that this method, which requires only a few measured FDFs, suitably determines the growth rates in the domain of operation of the system so that the uncertainties associated with FDF prediction by GPR only have a minor impact on the prediction of the instability domain layout.
In previous experiments, two characteristic regimes of upstream flame propagation were observed in model porous media. At the pore scale, the flame can exhibit oscillations similar to those of a flame with repetitive extinction and ignition (FREI-like oscillations) or demonstrate stepwise propagation. The conditions determining the emergence of one propagation regime or the other remained unknown. This work presents a parametric study investigating the influence of parameters on flame behaviour at the pore scale. A reduced 1D model and a detailed 2D model are used for numerical simulation. The results establish that the flame propagation regime is governed primarily by the inlet flow velocity and the maximum pore channel width. Thermophysical properties and pore arrangement have negligible impact on the emergence of oscillations. Despite its quantitative evaluation limitations, the 1D model successfully reproduces the overall flame behaviour at the pore scale and the regime diagram in good agreement with 2D simulations. Thus, the utility of the reduced 1D model for screening governing parameters in pore-scale combustion dynamics is demonstrated.
