Internal Radiation
Heating or cooling of surfaces and/or heat sources or sinks due to radiation within the fluid can be included in your model. You should include radiative heat transfer in your simulation when the radiant heat flux, Qrad=σ(T4max-T4min), is important to consider compared to the heat transfer rate due to convection or conduction. Typically, this will occur at high temperatures, where the fourth-order dependence of the radiative heat flux on temperature implies that radiation will dominate.
In Discovery, the non-diffracting fluid (also known as surface-to-surface (S2S)) method is used to model radiation. It is used to account for the radiation exchange in an enclosure of gray-diffuse surfaces. The energy exchange between two surfaces depends in part on their size, separation distance, and orientation. These parameters are accounted for by a geometric function called a "view factor".
The S2S method is typically used when the gas medium does not participate significantly in radiative heat transfer. It assumes that any absorption, emission, or scattering of radiation can be ignored, therefore, only "surface-to-surface" radiation is considered. This option is appropriate for applications such as solar collector systems, radiative heaters, electronics cooling, automotive underhood cooling systems, or spacecraft heat rejection systems.
S2S is computationally very expensive when you calculate the radiation and view factors for a large number of surfaces. To reduce the computational time as well as the storage requirement, the number of surfaces is reduced by creating surface "clusters". The surface clusters are made by starting from a face and adding its neighbors and their neighbors until a specified number of faces per surface cluster is collected.
By default, view factors are calculated using a face-to-face basis, in which clustering is used in a limited way only. The boundary faces act as the surfaces for the view factor calculation, and then a cluster view factor is obtained by taking the area-weighted average of the view factors of the faces within the cluster.