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README.md

@@ -97,9 +97,16 @@ stress = predict_stress(model, coords, normalizer, info)   # (N,) von Mises stre
 
 ### Training Data
 
-Geo-FNO Elasticity (Li et al., 2022): FEM simulations of a hyper-elastic unit cell with a random
-central void (radius 0.2–0.4), 972 nodes per sample, per-node von Mises stress. Split: 1000 train /
-200 test (first-1000 / last-200 of 2000, following the upstream Transolver protocol).
+Geo-FNO Elasticity (Li et al., 2022, arXiv:2207.05209): FEM simulations of an incompressible
+hyper-elastic (Rivlin–Saunders, `C₁=1.86e5`, `C₂=9.79e3`) `[0,1]²` unit cell with a random central
+void (radius 0.2–0.4), 972 nodes per sample; target = per-node von Mises stress. Split: 1000 train /
+200 test (first-1000 / last-200 of 2000, upstream Transolver protocol).
+
+**Fixed boundary conditions (identical for every sample):** the bottom edge is **clamped**
+(zero displacement) and a uniform **tensile traction `t = [0, 100]` is applied on the top edge** (`+y`);
+left/right edges are free. **Units are non-dimensional benchmark units (not MPa).** The model's only
+input is the 972 node coordinates — the loads/supports are *not* inputs (they are constant across the
+dataset; only the void geometry varies).
 
 ### Training Procedure