Numerical and Experimental Study of Mixing Properties of Gaseous Fuels Jets Including Hydrogen and Methane Into the non-Swirl Main Flow in a Premixer Configuration.

摘要

The mixing of fuel and air has a significant impact on overall operation efficiency and emissions performance of combustion systems, especially in lean combustion applications. As a result, developing an understanding of the processes associated with the fuel/air mixing is important. In parallel with the evolution of lean combustion, a new generation of fuels is emerging as an alternative to conventional fuels. Thus, it is desirable to study the mixing properties of different fuels from conventional resources, such as methane, as well as from renewable resources, such as hydrogen.;One tool that is available to study mixing in complex (e.g., turbulent and elliptic) flows is computational fluid dynamics (CFD). In the present work, mixing of hydrogen and methane into air, for example, is simulated using various CFD approaches. Fuel is injected either co-flowing to the air flow ("axial injection") or perpendicular to the air flow ("radial injection"). The quality of the simulations is evaluated by comparing the numerical results with experimental measurements. Qualitative and quantitative comparisons are used to evaluate the relative accuracy of different CFD approaches to simulate the mixing characteristics. Reynolds Averaged Navier-Stokes (RANS) turbulent models are utilized to model all the cases as steady turbulent models. Moreover, unsteady turbulent models, such as Unsteady RANS, and Large Eddy Simulation (LES) are used to provide information about unsteady features in selected cases. The sensitivity of numerical predictions to different RANS turbulence models as well as to different turbulent Schmidt numbers are explored. The results indicate more sensitivity to turbulence models for radial injection configurations. However, for the axial configuration, more sensitivity to Sct is observed. In general, the RSM turbulence model with Sc t=0.7 provides the most promising predictions for various combination of different fuels and injection types.