A Review on the Applications of Non-gray Gas Radiation Models in Multi-dimensional Systems

Shu Zheng,1 

Ran Sui,2 

Yujia Sun,

Yu Yang1

 Qiang Lu1,*Email

1National Engineering Laboratory for Biomass Power Generation Equipment, North China Electric Power University, Beijing 102206, China

2Department of Mechanical and Aerospace Engineering, Missouri University of Science and Technology, Rolla, MO 65409, USA

3School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing 210044, China


Gas radiation is a major way of heat transfer in flames. It affects temperature distributions and hence causes energy transfer in the combustion gaseous as well as subsequent chemical reactions. Accurate and efficient modeling of radiative heat transfer in multi-dimensional combustion systems is challenging, due to the drastic and rapid change of the radiative properties of the reacting gases in the whole spectrum, and the extensive computational cost for solving the radiative transfer equation (RTE) in multi-dimensional space. Several gas radiation models and RTE solution methods have been proposed to treat non-gray radiation heat transfer in combustion systems. In this paper, we first review the development of spectral line databases, gas radiation models and RTE solution methods. Subsequently, the development of radiation model parameters for different gaseous species is discussed. Next, recent simulation investigations are reviewed for one-dimensional, two-dimensional and three-dimensional systems involving these state-of-the-art radiation models. In addition, we also discuss machine learning approaches for establishing gas radiation models and solving RTEs in non-gray gas radiative problems, an alternative and flexible way to deal with the complex and dynamic systems. Hopefully, this review will provide an up-to-date knowledge about the numerical calculations of gas radiation heat transfers in combustion systems.

A Review on the Applications of Non-gray Gas Radiation Models in Multi-dimensional Systems