Abstract Numerical simulations of laminar premixed flames burning hydrogen and methane in spontaneous ignition mode are performed by harmonically exciting the reactants’ temperature at the domain inlet. The results are compared to an analytical model representing the same reactive flow configuration. The model provides a simplified but nevertheless accurate representation of reheat combustion taking place in sequential gas turbine combustors. An analytic expression for autoignition flames transfer functions to entropy waves is derived and used to extend transfer function models from the literature. For validation purposes, results from fully compressible Direct Numerical Simulations (DNS), including a complete representation of the fluctuating acoustic and entropic fields of the reactive flow, are analyzed and compared to incompressible Unsteady Reynolds-Averaged Navier–Stokes (URANS) simulations that only take into account the fluctuating entropic field. Methane flames are found to be more sensitive to entropic forcing than hydrogen flames, featuring nonlinear phenomena even for low excitation amplitudes. In the linear regime, all flames behave as predicted by the analytical model and the URANS simulations are found to correctly predict the fluctuating entropic field. The transition from linear to nonlinear flame response is described in detail and its physical mechanisms are explained. Comparisons with results available in the literature show good prediction capabilities, both in terms of flame describing function and integrated heat release rate. Limitations of the proposed analytical model with respect to real combustion systems are discussed and a simple correction is proposed.

中文翻译：

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再热火焰对熵波响应的一维分析模型的开发和验证研究

摘要 通过协调激发域入口反应物温度，对自燃模式下燃烧氢气和甲烷的层流预混火焰进行数值模拟。将结果与代表相同反应流配置的分析模型进行比较。该模型提供了在顺序燃气轮机燃烧器中发生的再热燃烧的简化但仍然准确的表示。导出了自燃火焰传递函数到熵波的解析表达式，并用于扩展文献中的传递函数模型。出于验证目的，完全可压缩直接数值模拟 (DNS) 的结果，包括反应流波动声场和熵场的完整表示，分析并与仅考虑波动熵场的不可压缩非定常雷诺平均纳维-斯托克斯 (URANS) 模拟进行比较。发现甲烷火焰比氢火焰对熵强迫更敏感，即使在低激发幅度下也具有非线性现象。在线性状态下，所有火焰的行为都与分析模型预测的一样，并且发现 URANS 模拟可以正确预测波动的熵场。详细描述了从线性到非线性火焰响应的转变，并解释了其物理机制。与文献中可用结果的比较显示出良好的预测能力，无论是在火焰描述函数还是综合热释放率方面。