Large-eddy simulation with the thickened flame model (LES/TFM) is conducted to simulate a three-dimensional dual swirl partially premixed methane/air gas turbine model combustor. Finite-rate chemistry is described by a skeletal chemical mechanism consisting of 16 species and 41 reactions. Flame sensors based on formyl radical (HCO) and chemical explosive mode analysis (CEMA) are proposed and implemented within the TFM framework. The two sensors are designed for multi-step chemical kinetic models to avoid thickening the low-intensity heat release rate (HRR) region. One-dimensional freely-propagating laminar premixed flames are first employed to assess the two new sensors. The HCO-based sensor can successfully avoid the low-intensity HRR region for lean flames, but can fail under fuel-rich conditions. The CEMA-based sensor can robustly avoid low-intensity HRR regions under both fuel-lean and fuel-rich conditions. A second test case using a hydrogen/air reheat burner further demonstrates the robustness of the CEMA-based sensor. The two new sensors are subsequently applied to the gas turbine model combustor, and effects of different flame sensors are studied. Baseline results from the HCO-based sensor are first compared with experimental measurements to validate the LES/TFM solver. The mean and r.m.s. velocity, temperature, and mass fractions of O${}_2$ and CO agree reasonably well with the experiment, although the mixture fraction within the inner recirculation zone (IRZ) is under-predicted. The predicted mean and r.m.s. temperature and species profiles are comparable at most locations, except near the IRZ where the CEMA-based sensor predicts the largest fluctuations by only thickening the chemically explosive regions. After optimisation, only 15% of overhead in computational cost is imposed when the CEMA sensor is employed on-the-fly. Future work includes further reduction of the computational cost of the CEMA-based sensor.

使用加厚火焰模型（LES/TFM）进行大涡模拟以模拟三维双涡流部分预混甲烷/空气燃气轮机模型燃烧器。有限速率化学是通过由 16 种物质和 41 个反应组成的骨架化学机制来描述的。在 TFM 框架内提出并实施了基于甲酰基 (HCO) 和化学爆炸模式分析 (CEMA) 的火焰传感器。这两个传感器专为多步化学动力学模型而设计，以避免增厚低强度热释放率 (HRR) 区域。首先采用一维自由传播的层流预混火焰来评估两个新传感器。基于 HCO 的传感器可以成功避开稀薄火焰的低强度 HRR 区域，但在富燃料条件下可能会失效。基于 CEMA 的传感器可以在贫油和富油条件下稳健地避开低强度 HRR 区域。使用氢气/空气再热燃烧器的第二个测试案例进一步证明了基于 CEMA 的传感器的稳健性。随后将这两个新传感器应用于燃气轮机模型燃烧器，并研究了不同火焰传感器的影响。首先将基于 HCO 的传感器的基线结果与实验测量值进行比较，以验证 LES/TFM 求解器。O 的平均和均方根速度、温度和质量分数 并研究了不同火焰传感器的影响。首先将基于 HCO 的传感器的基线结果与实验测量值进行比较，以验证 LES/TFM 求解器。O 的平均和均方根速度、温度和质量分数 并研究了不同火焰传感器的影响。首先将基于 HCO 的传感器的基线结果与实验测量值进行比较，以验证 LES/TFM 求解器。O 的平均和均方根速度、温度和质量分数${}_2$和 CO 与实验相当吻合，尽管内部再循环区 (IRZ) 内的混合物分数被低估了。预测的平均温度和均方根温度以及物种分布在大多数位置都具有可比性，除了在 IRZ 附近，基于 CEMA 的传感器仅通过加厚化学爆炸区域来预测最大的波动。优化后，当 CEMA 传感器在运行中使用时，只施加了 15% 的计算开销。未来的工作包括进一步降低基于 CEMA 的传感器的计算成本。