HaomingLuo/AgentFEM-DENIM

AgentFEM DENIM

Material-conditioned DENIM v2

The conditional_v2/ directory adds an 8,477-parameter material-conditioned DENIM trained with strict roles for all 2,660 trajectories: 1,484 train, 407 validation and 769 test. It reaches 3.308 MPa RMSE on 537 strict held-out J2/ Chaboche trajectories and reduces the incomplete-material long-history RMSE from 10.906 to 4.263 MPa, while retaining 0.798 MPa on the original frozen test.

This checkpoint is a material-point model. The fixed-material agentfem_bundle/ remains the globally verified AgentFEM runtime artifact.

AgentFEM-ready model bundle

agentfem_bundle/ is the recommended runtime artifact. It contains a checksum-authenticated safetensors state dict and an immutable manifest for the generic AgentFEM learned-constitutive interface. Loading is local and offline; the finite-element solve does not deserialize the legacy .pt files or download model assets.

The bundle has been checked with AgentFEM commit 40c965225fc3b8d12a93a68e0d6b01dd35d47d82 and AgentFEM-learning commit 06d454e4ee66a7ee4f4c8a705d5958ff9577d18c:

Runtime gate	Result
Legacy-to-safe material-point maximum stress difference	2.68e-7 Pa
121-step maximum absolute stress	292.547138 MPa
Final PEEQ	0.0095270883
Plastic bar, serial	4/4 increments, converged
Plastic bar, two MPI ranks	4/4 increments, converged
Serial/two-rank maximum-stress difference	5.96e-8 Pa

The elastic tangent passes a strict finite-difference check. Across the audited plastic states, the current automatic-differentiation tangent differs from fixed-old-state central differences by approximately 0.05–0.80%. The reported global tests converge without cutback, while an exact consistent plastic tangent remains an open numerical improvement. See artifacts/agentfem/RUNTIME_VALIDATION.md and artifacts/agentfem/runtime_validation.json.

Boundary-extension checkpoint

This package retains the originally published denim.pt checkpoint and adds denim-expanded.pt, trained after a 500-trajectory capability-boundary extension. The original 32-trajectory test split remains frozen.

The expanded checkpoint and all reported boundary metrics are tied to the immutable dataset revision c84f416e5a71daa157e406c50afc3fc73509b9ca.

Test	Original checkpoint	Expanded checkpoint
Published held-out paths	1.136 MPa	0.714 MPa
New path OOD	1.163 MPa	0.743 MPa
Amplitude OOD	3.091 MPa	2.294 MPa
Long-history stress test	11.261 MPa	10.906 MPa

The long-history result is the present capability boundary: additional ordinary trajectories substantially improve path and amplitude tests but do not remove long-horizon drift. Full metrics and data-quality evidence are in artifacts/model_metrics.json and artifacts/QUALITY_REPORT.md.

DENIM means Discrete-Energy Neural Internal-variable Model. It is a compact gray-box constitutive model for path-dependent small-strain J2 plasticity. Elasticity, yield geometry, associative flow, plastic incompressibility, non-negative plastic increments and the implicit return map remain explicit. Neural components represent only the unknown isotropic and kinematic hardening closure.

Why this checkpoint is an incomplete-physics test

The AgentFEM reference material has three kinematic-memory channels and a piecewise-linear isotropic-hardening table. This checkpoint has only two memory channels and receives neither the reference equations nor parameters. The second learned state must close two unresolved reference time scales.

The model has 918 trainable parameters. On two completely held-out non-proportional path families:

Model	RMSE	R2
Incomplete J2	59.541 MPa	0.730208
GRU (49,254 parameters)	76.988 MPa	0.548933
DENIM	1.136 MPa	0.999902

Research progression

DENIM follows an earlier multiaxial benchmark in the same dataset repository. The results form one research progression, but not one raw-score leaderboard:

Stage	Physics available to the model	Path-OOD stress RMSE	Meaning
MLP / GRU / LSTM / TCN / physics-state GRU	weak or soft physics	60.44–105.81 MPa	sequence fitting generalizes poorly to unseen paths
Physics-integrator NN	correct J2/Chaboche equations and state structure	0.0237 MPa	white-box fusion ceiling when the governing form is known
DENIM	J2 skeleton, but hardening law and one reference memory scale are hidden	1.136 MPa	closes genuinely missing evolution terms and remains FE-deployable

The Physics-integrator and DENIM rows use different frozen protocols. Their absolute RMSE values must not be ranked directly. The progression asks a more useful question: how far can architecture-level physics be retained when the true evolution equations or internal-variable structure are not known?

Coarse/fine path RMSE was 0.944/0.958 MPa. In 12-element notched-bar tests, cyclic and monotonic reaction relative-L2 errors were 0.636% and 0.500%. A severe cyclic case passed with one global trust-region fallback.

Use

import torch
from src.t2_graybox_discrete_energy import DENIM, rollout

checkpoint = torch.load("denim.pt", map_location="cpu", weights_only=False)
model = DENIM(channels=2)
model.load_state_dict(checkpoint["state_dict"])
model.eval()

# strain: [batch, steps, 6], tensor-shear Voigt order xx,yy,zz,xy,yz,xz
result = rollout(strain, young, poisson, yield_stress, model)
stress = result["stress"]

See inference.py for a runnable example. config.json records the known material constants and architecture contract.

For finite-element use, download the agentfem_bundle/ directory and run the examples shipped with the fixed AgentFEM-learning implementation:

python examples/learned_constitutive_denim/case.py \
  --bundle /path/to/agentfem_bundle

python examples/learned_constitutive_denim/global_bar.py \
  --bundle /path/to/agentfem_bundle --displacement 0.008

The fixed source implementation is available at AgentFEM-learning commit 06d454e.

Scope and limitations

• fixed synthetic material; not experimental calibration;
• small-strain, rate-independent, isotropic J2 plasticity;
• trained with high-fidelity internal-state supervision;
• AgentFEM/PyTorch implicit execution is verified, but this is not a compiled or production-certified UMAT;
• implicit return mapping is slower than direct GRU inference;
• the severe cyclic structure test still needed one global fallback;
• the current plastic autodiff tangent is numerically useful but does not meet the strict material-point consistency tolerance used in the runtime audit.

The associated data, source trajectories and evidence are available at AgentFEM-Material-Loading-Memory.

Article evidence v3

See article_evidence_v3/ for ablation, material-family transfer, and AgentFEM global-solve evidence.