Which method is used to solve the equation of Moldflow Rotational Diffusion Modell?

[Anonymous]

Hello everyone,

my name is Rafael. I want to use Moldflow 2019 Insight to predict the fiber orientations. For this purpose, I created the model, configured all the parameters, and am ready to press the "Start Analysis" button. When I press the button, all parameters are transferred to the solver. The solver then simulates the fluid and particle mechanics by solving the differential equations. Is this correct?

The models are listed at the following link:
https://help.autodesk.com/view/MFIA/2018/ENU/?guid=GUID-EC0F471C-A2C5-4461-9C83-B62B85936166
MRD model is listed under the following link:
https://help.autodesk.com/view/MFIA/2018/ENU/?guid=GUID-54ED8884-6EB2-44B9-98F4-9E6817CBF6F5

The solver needs to have a discretized model geometry to solve the differential equations. The result of the discretization is a system of algebraic equations. In theory, there are three discretization methods to choose from:
- Finite difference method
- Finite volume method
- Finite element method

Here come two questions:
"Which of the three methods does Moldflow use to discretize the model, or approximate the differential equations by the system of algebraic equations?"
"Is this the same method for every equation?"

In a further step, the system of algebraic equations is solved numerically. Here is another question:

"What program is used to solve the system of algebraic equations numerically? (Nastran, Ansys?)"

The numerical calculation results are displayed and in Moldflow as "Results."

I have briefly presented here my interpretation of the process of a simulation. If there is a need for additions, I look forward to your comments.

In the end, my last and most important question from the title:
"Which method is used to discretize and solve from Moldflow Rotational Diffusion equation (fiber orientation simulation)?"

Regards
Rafal Zurawik

PS. While writing this article, I used the following book:
Ferziger, J. H.; Perić, M.; Street, R. L.: Computational Fluid Dynamics. Berlin, Heidelberg 2020.