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CFD-CRN validation study for NO x emission prediction in lean premixed gas turbine combustor

机译:瘦预混燃气涡轮燃烧器中NO <下标> X /下标>排放预测的CFD-CRN验证研究

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AbstractNumerical prediction of NOxformation in combustion device is becoming more important because of stringent legislation. This work describes the validation of CFD-CRN (Computational fluid dynamics-Chemical reactor network) method for NOxemission predictions for a gas turbine combustor design. Steady state 3-D CFD models of the gas turbine combustor were generated using ANSYS FLUENT v14.5. The results of 3-D CFD simulation were presented, which gave insight into the flow field, temperature, and equivalence ratio distribution of the gas turbine combustor operating natural gas (CH4). The Chemical reactor networks (CRN) with 4 PSRs for simple model and 12 PSRs for detailed model were developed based on Computational fluid dynamics (CFD). The predictions of the exhaust emissions in the CRN model were carried out using CHEMKIN code and full GRI 3.0 chemical kinetic mechanism. This paper discussed the validation of the CFD simulation and CFD-CRN method by comparing the predicted temperature and chemical species of both models. Model combustor tests were conducted at various equivalence ratios. The CFD-CRN predicted NOxemissions at the combustor exit were compared with experimental values. The detailed CRN predictions of NOxemissions showed better agreement with experimental values compared with the simple CRN predictions. However, the simple CRN also showed reasonable predictions. Also, the NO formation pathway analysis was carried out to gain deeper understanding of the relative contributions of the four NO formation mechanisms.]]>
机译: X /下标>排放预测的CFD-CRN(计算流体动力学 - 化学反应器网络)方法的验证。使用ANSYS流畅的V14.5产生燃气轮机燃烧器的稳态3-D CFD型号。提出了3-D CFD仿真的结果,这使得进入流场,温度和燃气轮机燃烧器的流场,温度和等效比分布操作天然气(CH <下标> 4 )。基于计算流体动力学(CFD)开发了具有4 PSR的化学反应器网络(CRN),用于简单模型和12PSR的详细模型。使用Chemkin码和全GRI 3.0化学动力学机制进行CRN模型中排气的预测。本文讨论了通过比较两种模型的预测温度和化学品种来验证CFD仿真和CFD-CRN方法。模型燃烧器测试以各种等值比进行。将CFD-CRN预测NO <下标> x 与实验值进行了燃烧器出口的排放。与简单的CRN预测相比,NO <下标> x 排放的详细CRN预测显示了与实验值更好的协议。然而,简单的CRN也显示出合理的预测。此外,没有进行NO形成途径分析,以更深入地了解四个无形成机制的相对贡献。]>

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