File size: 2,331 Bytes
0ef4ba2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 | from __future__ import annotations
import torch
from src.t2_denim_conditional import ConditionalDENIM, material_descriptor, rollout
def test_descriptor_hides_incomplete_parameters() -> None:
descriptor = material_descriptor(
{
"material_model": "hidden_three_memory_tabulated_hardening",
"young_pa": 190.0e9,
"poisson": 0.3,
"yield_stress_pa": 280.0e6,
"backstress_c1_pa": 99.0e9,
}
)
assert descriptor.shape == (13,)
assert torch.count_nonzero(descriptor[3:10]) == 0
assert torch.equal(descriptor[-3:], torch.tensor([0.0, 0.0, 1.0]))
def test_conditional_rollout_preserves_hard_constraints() -> None:
torch.manual_seed(7)
model = ConditionalDENIM()
strain = torch.zeros((2, 17, 6), dtype=torch.float32)
strain[:, :, 0] = torch.linspace(0.0, 0.006, 17)
descriptor = torch.stack(
[
material_descriptor(
{
"material_model": "j2_linear_isotropic",
"young_pa": 200.0e9,
"poisson": 0.3,
"yield_stress_pa": 300.0e6,
"hardening_modulus_pa": 2.0e9,
}
),
material_descriptor(
{
"material_model": "chaboche_combined",
"young_pa": 190.0e9,
"poisson": 0.29,
"yield_stress_pa": 280.0e6,
"backstress_c1_pa": 25.0e9,
"backstress_gamma1": 70.0,
"backstress_c2_pa": 8.0e9,
"backstress_gamma2": 12.0,
"isotropic_saturation_pa": 60.0e6,
"isotropic_rate": 8.0,
}
),
]
)
result = rollout(
strain,
torch.tensor([200.0e9, 190.0e9]),
torch.tensor([0.3, 0.29]),
torch.tensor([300.0e6, 280.0e6]),
descriptor,
model,
bisection_iterations=8,
)
assert torch.isfinite(result["stress"]).all()
assert torch.diff(result["peeq"], dim=1).min() >= 0.0
assert result["plastic_strain"][..., :3].sum(dim=-1).abs().max() < 1.0e-6
active = result["plastic_increment"] > 0.0
assert result["yield_residual"][active].abs().max() < 5.0e6
|