Physics-informed neural-network (PINN) surrogate trained on STAR-CCM+ RANS CFD
results (coolant flow). The model maps geometry/coordinate features to the steady
flow fields. Metadata below is auto-extracted from the checkpoint header.
Inputs are Fourier-encoded (8 frequencies, sin+cos) before the MLP.
0. x
1. y
2. z
3. distance_to_inlet
4. distance_to_outlet
5. distance_to_wall
6. axial_inlet_to_outlet
7. radial_to_inlet_outlet_axis
8. signed_distance_proxy
9. wall_proximity
10. source_x_norm
11. source_y_norm
12. source_z_norm
13. source_axis_axial
14. source_axis_lateral_1
15. source_axis_lateral_2
16. source_axis_radial
17. chart_center_x_norm
18. chart_center_y_norm
19. chart_center_z_norm
20. chart_center_axis_axial
21. chart_center_axis_lateral_1
22. chart_center_axis_lateral_2
23. chart_local_x
24. chart_local_y
25. chart_local_z
26. chart_local_axis_axial
27. chart_local_axis_lateral_1
28. chart_local_axis_lateral_2
29. chart_radius
30. chart_log_count
31. chart_wall_distance_mean
32. chart_wall_distance_std
33. chart_cov_eig_1
34. chart_cov_eig_2
35. chart_cov_eig_3
36. chart_anisotropy
37. chart_planarity
38. wall_distance_x_minus
39. wall_distance_x_plus
40. wall_distance_y_minus
41. wall_distance_y_plus
42. wall_distance_z_minus
43. wall_distance_z_plus
44. surface_area
45. fluid_volume
46. surface_area_to_volume_ratio
47. equivalent_hydraulic_diameter
48. surface_genus
49. cross_section_area_min
50. cross_section_area_mean
51. cross_section_area_std
52. cross_section_area_min_ratio
53. number_of_strong_constrictions
54. high_curvature_surface_fraction1 import torch
2 ckpt = torch . load ( "starccm_pinn_model_step_00390000.pt" , map_location = "cpu" , weights_only = False )
3 model_state = ckpt [ "model" ] # field-network weights
4 feature_names = ckpt [ "feature_names" ] # 55 inputs
5 output_order = ckpt [ "output_order" ] # 7 outputs
6 # input standardization: ckpt["feature_mean"], ckpt["feature_scale"]
7 # label standardization: ckpt["label_mean"], ckpt["label_scale"]
