Radiative Properties of Gases

Abstract

The solution of the radiative transfer equation is challenging, especially in the presence of a participating medium, wavelength- and direction-dependent properties, or a complex geometry. The Monte Carlo method that relies on statistical sampling of photon bundles using pseudorandom numbers and probability distributions which are derived based on physical laws is a powerful and robust approach to solving the radiative transfer equation. While the method is computationally demanding even for simple surface exchange problems, introducing complex phenomena does not significantly increase formulation complexity or the required computational power. Therefore, the method has become one of the most widely adopted solution techniques with the increasing computation capacity in the last decades. This chapter introduces the method, presenting general guidelines to adopt it for solution of radiative transfer problems, discussing how to introduce further phenomena such as wavelength- or direction-dependent properties, and improving computational performance. The method is known for its flexibility and can be applied in many different ways. Different strategies are discussed, considering advantages or disadvantages of each for different problems.