This study extends the Pareto-efficient combustion (PEC) framework to adaptive LES combustion simulations of turbulent flames. With the focus on improving predictions of CO emissions, PEC is employed to augment a flamelet/progress variable (FPV) model through local sub-model assignment of a finite-rate chemistry (FRC) model. A series of LES-PEC calculations are performed on a piloted partially-premixed dimethyl ether flame (DME-D), using a combination of FPV and FRC models. The drift term is utilized in the PEC framework to estimate the model error for quantities of interest. The PEC approach is demonstrated to be capable of significantly improving the prediction of CO emissions compared to a monolithic FPV simulation. The improved accuracy is achieved by enriching the FPV model with FRC in regions where the low-order model is determined insufficient through the evaluation of the drift term. The computational cost is reduced by a factor of two in comparison to the full finite-rate calculation, while maintaining the same level of accuracy for CO predictions.

这项研究将帕累托高效燃烧（PEC）框架扩展到湍流火焰的自适应LES燃烧模拟。着眼于改善对CO排放的预测，PEC被用于通过有限速率化学（FRC）模型的局部子模型分配来增强小火焰/进展变量（FPV）模型。使用FPV和FRC模型的组合，对中试的部分预混合的二甲醚火焰（DME-D）进行了一系列的LES-PEC计算。在PEC框架中使用了漂移项来估计感兴趣量的模型误差。与整体式FPV仿真相比，PEC方法被证明能够显着改善CO排放的预测。通过在漂移项的评估确定低阶模型不足的区域中，通过用FRC丰富FPV模型，可以提高精度。与完整的有限速率计算相比，计算成本降低了两倍，同时保持了CO预测的准确性水平相同。