Validation of a mixture-averaged thermal diffusion model for premixed lean hydrogen flames

Abstract

The mixture-averaged thermal diffusion model originally proposed by Chapman and Cowling is validated using multiple flame configurations. Simulations using detailed hydrogen chemistry are done on one-, two-, and three-dimensional flames. The analysis spans flat and stretched, steady and unsteady, and laminar and turbulent flames. Quantitative and qualitative results using the thermal diffusion model compare very well with the more complex multicomponent diffusion model. Comparisons are made using flame speeds, surface areas, species profiles, and chemical source terms. Once validated, this model is applied to three-dimensional laminar and turbulent flames. For these cases, thermal diffusion causes an increase in the propagation speed of the flames as well as increased product chemical source terms in regions of high positive curvature. The results illustrate the necessity for including thermal diffusion, and the accuracy and computational efficiency of the mixture-averaged thermal diffusion model.

Keywords:

• hydrogen combustion
• thermal diffusion
• flame instability
• Soret effect
• turbulent flames

Acknowledgements

The authors would like to thank Robert Pitz and Carl Hall at Vanderbilt University for providing thoughtful discussions and experimental data concerning the cellular tubular flames.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The authors gratefully acknowledge funding from the US Department of Energy–Basic Energy Sciences (DE-SC0006591) under the supervision of Dr Wade Sisk, and funding from the Air Force Office of Scientific Research [FA9550-12-1-0472 and FA9550-16-1-0510] under the supervision of Dr Chiping Li. This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the US Department of Energy [Contract No. DE-AC02-05CH11231]. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by the National Science Foundation [grant number ACI-1053575].