commit 42b9a159c2519f8b9bbea1ed47fef0f0afeaced7
parent 7eb855ee9a8e06429f6f7398db1b1e18eb49f6e8
Author: Vincent Forest <vincent.forest@meso-star.com>
Date: Fri, 25 Feb 2022 10:10:07 +0100
Update the overview part of the README file
Update the explanations on how radiative transfers are handled by
Stardis : non-linearities are now supported through the Picard algorithm.
Diffstat:
1 file changed, 10 insertions(+), 7 deletions(-)
diff --git a/README.md b/README.md
@@ -20,13 +20,16 @@ The hypothesis these algorithms are based upon are the following:
- *convection*: fluid media are supposed to be isothermal, even if their
temperature may vary with time. This hypothesis relies on the assumption of
perfectly agitated fluids.
-- *radiation*: local radiative transfer is linearised, i.e. instead of writing
- the spectrally integrated net flux as a difference of temperatures to the
- power 4, it is assumed of the same form as the convective flux (as a
- difference of temperatures, multiplied by a radiative exchange coefficient).
- In order to be valid, this representation of radiative transfer exchanges
- requires that the temperature at any position and time is close to a known
- reference temperature.
+- *radiation*: local radiative transfer is solved by a iterative numerical
+ method (Picard algorithm) that requires the knowledge of a reference
+ temperature field. At the basic level (one level of recursion), and using a
+ uniform reference temperature field, this algorithm translates into the
+ hypothesis of a linearized radiative transfer. Using a higher order or
+ recursion makes possible to converge the result closer to the solution of a
+ rigorous spectrally-integrated radiative transfer (a difference of
+ temperatures to the power 4 when integrated over the whole spectrum). The
+ higher the recursion order, to better will be the convergence of the
+ algorithm.
In Stardis-Solver the system to simulate is represented by a *scene* whose
geometry defines the contour of the object only: in contrast to legacy thermal
