C_R_G和C_R_RG的有什么区别？

caobaoxi

C_R_G和C_R_RG的区别是什么？以及他们的适用范围。
谢谢

caobaoxi

FLUENT calculates the gradient of flow in a cell (based on the divergence theory) and stores this value in the variable identified by the suffix _G. For example cell temperature is stored in the variable C_T, and the temperature gradient of the cell is stored in C_T_G. The gradients stored in variables with the _G suffix are non-limited values and if used to reconstruct values within the cell (at faces, for example), may potentially result in values that are higher (or lower) than values in the surrounding cells. Therefore, if your UDF needs to compute face values from cell gradients, you should use the reconstruction gradient (RG) values instead of non-limited gradient (G) values. Reconstruction gradient variables are identified by the suffix _RG, and use the limiting method that you have activated in your FLUENT model to limit the cell gradient values.

caobaoxi

FLUENT calculates the gradient of flow in a cell (based on the divergence theory) and stores this value in the variable identified by the suffix _G. For example cell temperature is stored in the variable C_T, and the temperature gradient of the cell is stored in C_T_G. The gradients stored in variables with the _G suffix are non-limited values and if used to reconstruct values within the cell (at faces, for example), may potentially result in values that are higher (or lower) than values in the surrounding cells. Therefore, if your UDF needs to compute face values from cell gradients, you should use the reconstruction gradient (RG) values instead of non-limited gradient (G) values. Reconstruction gradient variables are identified by the suffix _RG, and use the limiting method that you have activated in your FLUENT model to limit the cell gradient values.