Thank you for the precious code, which is very helpful to me.
In the paper in JCP, you wrote as below:
Given the nature of the model, with velocity and the pressure fields as unknowns, we show the adaptability of the architecture to vector problems. Thus, we consider a monolithic approach, where the three fields are concatenated as features for each node, rather than a partitioned one, where we recover independently each field.
As I understood, the GCA-ROM in your paper predicted the u,v,p at the same time with the single GCA-ROM model.
However, in the NS codes in the tutorial folder, we have to train each GCA-ROM to predict u,v,p, respectively.
- Could you please share the original code that predicts u,v,p all at once with the single GCA-ROM?
Also, additional question.
- The current GCA-ROM framework seems to be only trained and tested on the same number of nodes (N_h in the paper), due to its conv nature. Do you have any plan to extend this framework so that it can be applied to various graphs with different numbers of nodes?