CFD-CRN validation study for NOx emission prediction in lean premixed gas turbine combustor

• Published in: Journal of mechanical science and technology 2017, 31(10), , pp.4933-4942
• Main Authors: Nguyen, Truc Huu, Kim, Seunghan, Park, Jungkyu, Jung, Seungchai, Kim, Shaun
• Format: Article
• Language: English
• Subjects: CAD; Combustion chambers; Computational fluid dynamics; Computer aided design; Computer simulation; Control; Dynamical Systems; Emission analysis; Emissions; Engineering; Equivalence ratio; Fluid dynamics; Gas turbine engines; Gas turbines; Industrial and Production Engineering; Legislation; Mathematical models; Mechanical Engineering; Model testing; Natural gas; Nitrogen oxides; Numerical prediction; Simulation; Three dimensional models; Turbines; Vibration; 기계공학
• ISSN: 1738-494X; 1976-3824
• DOI: 10.1007/s12206-017-0942-2

Numerical prediction of NO x formation 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 NO x emission 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 (CH 4 ). 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 NO x emissions at the combustor exit were compared with experimental values. The detailed CRN predictions of NO x emissions 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.