The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: TypeError
Message: Couldn't cast array of type
struct<physics_integrator_nn: string>
to
{}
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2312, in cast_table_to_schema
cast_array_to_feature(
~~~~~~~~~~~~~~~~~~~~~^
table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
feature,
^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1861, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
~~~~^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2158, in cast_array_to_feature
raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
TypeError: Couldn't cast array of type
struct<physics_integrator_nn: string>
to
{}Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
- Start here
- What is a loading history, and why does it matter?
- Recommended evaluation metrics
- Releases
- Historical material-conditioned DENIM v2 protocol
- Historical fixed-material DENIM closure
- DENIM capability-boundary extension
- DENIM capability extension v4
- Prospective sealed test v1
- AgentFEM runtime validation
- Multiaxial v2 at a glance
- Reproduction and evidence
- Scope
- Evidence protocol v3
AgentFEM Material Loading Memory
An open, reproducible research dataset for path-dependent material modeling, neural constitutive surrogates and finite-element deployment tests. The repository contains six staged, explicitly separated releases.
Start here
| Goal | Recommended entry |
|---|---|
| Understand the current dataset | This page and the sealed-test data card |
| Train or benchmark a constitutive model | DENIM start guide |
| Reproduce the multiaxial baseline study | Multiaxial v2 guide |
| Reproduce the original loading-memory release | Original v1 guide |
| Use the latest DENIM checkpoint | AgentFEM-DENIM |
Current trajectory accounting:
| Role | Trajectories | Interpretation |
|---|---|---|
| Training | 1,808 | Optimization data for the current v2.2 model |
| Validation | 503 | Checkpoint selection and anti-forgetting guardrails |
| Development test | 1,349 | Frozen historical benchmarks; later aggregate results informed subsequent model design |
| Prospective sealed test | 128 | Published after model freeze; never used for training or selection |
| Total | 3,788 | Complete histories, not exchangeable independent experiments |
What is a loading history, and why does it matter?
A loading history is the ordered sequence of deformation applied to a material. For an elastic spring, only the present deformation matters. For an elastoplastic metal, the route matters as well: loading, unloading, reversing, rotating the loading direction or adding a mean strain changes the material's internal state. Two specimens can therefore arrive at the same current strain with different stresses because they arrived there by different routes.
This dataset varies the history deliberately rather than merely sampling more points on one curve:
| History variation | Question being tested |
|---|---|
| Proportional and reversed cycles | Can the model reproduce yielding, unloading and the Bauschinger effect? |
| Non-proportional and rotating multiaxial paths | Can it track changing stress directions and coupled material memory? |
| Nested minor loops and non-periodic sequences | Can it remember partial unload/reload events instead of resetting its state? |
| Amplitude and mean shifts | Can it extrapolate when the load becomes larger or biased to one side? |
| 100--200-cycle histories | Does a small state error accumulate into long-term drift? |
| Matched coarse/fine discretizations | Is the prediction tied to the physical path or to a particular step size? |
| Material-parameter variation | Can one conditioned model represent a family of materials rather than one fixed curve? |
The scientific object is therefore not an isolated stress value. It is the mapping from material parameters + ordered loading history + current internal state to the next stress and state. Randomly shuffling time steps or mixing related resolution groups across data roles would destroy this meaning.
Recommended evaluation metrics
Report absolute stress RMSE in MPa together with a scale-free metric. MPa is needed for engineering interpretation; a relative metric makes results easier to compare across cohorts and stress levels.
- Relative L2 error (%) =
||stress_pred - stress_ref||2 / ||stress_ref||2 × 100. This is the preferred scale-free trajectory/state metric for signed cyclic stresses. - Yield-normalized RMSE (%) =
RMSE / reference_yield_stress × 100. This answers how large the average error is relative to the 280 MPa reference yield stress used by the sealed protocol. - R2 is useful as a supplementary global fit indicator, but should not replace an engineering error in MPa.
- MAPE is not recommended because cyclic stress repeatedly crosses zero; division by values near zero can make an accurate prediction look arbitrarily poor.
For the sealed reference data, the stress RMS scales are 359.540 MPa for global path OOD, 91.411 MPa for 150/200-cycle histories, 371.687 MPa for amplitude and mean shifts, and 206.814 MPa over all 128 trajectories. These denominators are published so every model can be compared under the same convention. Model scores remain in the model repository to keep this page focused on the data and evaluation contract.
Releases
- T2 v1: 1,008 proportional cyclic J2 trajectories for loading-memory baselines and forward/reversed ordering controls.
- T2 multiaxial v2: 1,024 independently generated J2 and Chaboche trajectories in the complete five-dimensional deviatoric strain space, with ID, path-OOD and parameter-OOD splits.
- T2 DENIM closure v1: 128 multiaxial trajectories from a deliberately richer three-memory, tabulated-hardening reference material. The published two-memory DENIM model must learn the missing internal-variable closure.
- T2 DENIM boundary v1: 500 additional trajectories for training-density, path, amplitude, long-history and integration-resolution boundaries.
- T2 DENIM capability v4: 1,000 trajectories for 100-cycle horizons, full six-component loading, AgentFEM-derived structural paths and paired discretization/noisy-observation tests.
- T2 DENIM sealed test v1: 128 prospectively generated trajectories for globally unseen paths, 150/200-cycle horizons and combined amplitude/mean shift. The DENIM v2.2 weights and evaluation protocol were frozen first.
The original 2,660-role protocol remains frozen; capability v4 adds its own roles and the sealed release adds no optimization data. The six releases form a staged evidence chain and must not be pooled or randomly reshuffled without respecting material, path-family, resolution-group and release boundaries.
Historical Path-OOD labels are protocol-relative: they mean unseen for the
model and training split defined at that release. Some historical test-family
names entered later training releases, so those scores are not global OOD
claims for v2.2. sealed_test_v1 is the current prospective global path-OOD
protocol.
Historical material-conditioned DENIM v2 protocol
All 2,660 trajectories now have a frozen role in the conditional study: 1,484
train, 407 validation and 769 test. The release adds no duplicate data. Shared
known-material pretraining plus incomplete-material replay reduces long-history
RMSE from 10.906 to 4.263 MPa. Reproduction code, exact accounting and complete
metrics are in conditional_v2/.
Historical fixed-material DENIM closure
DENIM stands for Discrete-Energy Neural Internal-variable Model. The reference material contains three kinematic memory channels and a non- exponential tabulated isotropic-hardening curve. DENIM retains only two memory channels and receives none of the reference hardening equations or parameters.
Held-out non-proportional path results:
| Model | Test RMSE | Test R2 |
|---|---|---|
| Incomplete J2, no learned hardening | 59.541 MPa | 0.730208 |
| GRU | 76.988 MPa | 0.548933 |
| DENIM | 1.136 MPa | 0.999902 |
The 918-parameter DENIM also passed coarse/fine increment checks and three notched-bar deployment gates. Cyclic and monotonic reaction relative-L2 errors were 0.636% and 0.500%; the severe cyclic stress test required one global trust-region fallback. This remains a fixed synthetic material study with internal-state supervision, not an experimental calibration or a certified production material.
The standalone weights and model card are published at HaomingLuo/AgentFEM-DENIM.
DENIM capability-boundary extension
The 500-trajectory extension contains 250 training, 50 validation, 80 held-out path, 60 amplitude-extrapolation, 40 long-history and 20 matched-resolution histories. No failed case was silently removed.
| Test | Incomplete J2 | GRU | Frozen DENIM | Expanded DENIM |
|---|---|---|---|---|
| Published held-out paths | 59.541 | 98.260 | 1.136 | 0.714 |
| New path OOD | 58.177 | 96.959 | 1.163 | 0.743 |
| Amplitude OOD | 69.315 | 95.896 | 3.091 | 2.294 |
| Long-history stress test | 54.394 | 90.757 | 11.261 | 10.906 |
Values are stress RMSE in MPa. The long-history result is reported as a current capability boundary, not hidden by the stronger ordinary path results. Expanded-DENIM RMSE on matched 61/121/481/961-state histories was 0.673/0.722/0.761/0.767 MPa.
- Viewer-friendly index:
data/t2_denim_boundary_v1/index.csv - Lossless trajectories:
data/t2_denim_boundary_v1/cohort.h5 - Data card:
data/t2_denim_boundary_v1/README.md - Quality report:
artifacts/t2_denim_boundary_v1/QUALITY_REPORT.md - Full metrics:
artifacts/t2_denim_boundary_v1/model_metrics.json - All-data usage:
docs/T2_ALL_DATA_STAGE_SUMMARY.md
DENIM capability extension v4
The v4 increment adds 1,000 complete trajectories: 300 long-cycle, 300 full six-component non-proportional, 200 AgentFEM-derived local structural paths and 200 matched discretization/observation trajectories. The 100-cycle histories contain 2,001 accepted material states. Fifty continuous paths are integrated at 61, 121, 241 and 481 states and carry explicit group IDs; noisy and sparse observations are fields paired with clean truth, not separately counted cases.
The structure-derived cohort uses local strain bases from twelve AgentFEM
linear-elastic unit-load solves on four perforated/notched plates, followed by
nonlinear reference-material replay. It does not claim coupled elastoplastic
redistribution. See data/t2_denim_capability_v4/README.md for the exact
protocol and artifacts/t2_denim_capability_v4/capability_summary.json for
machine-readable boundary statistics.
Prospective sealed test v1
The 128-trajectory sealed test is a final, non-training extension: 64 globally
unseen path-shape histories, 32 histories with 150 or 200 cycles, and 32
combined amplitude/mean-shift histories. All eight path-family identifiers are
disjoint from training. The reference integrator enforces finite values,
monotone accumulated plastic strain, a relative yield-surface residual below
1e-8, total equivalent strain no greater than 0.0155, and accumulated
equivalent plastic strain no greater than 0.10.
The manifest binds the data to DENIM v2.2 weights SHA-256
d7b848f41aa46616c76c5f0db536d8ecfbc508a5375faa3cbbcc555fb062633b.
These samples are ineligible for training, validation, checkpoint selection or
model redesign. The repository-level protocol audit reports zero exact
cross-role collisions for full model inputs and for input/target pairs. This
dataset release intentionally contains no sealed-test model score; evaluation
is published separately in the model repository.
- Data card:
data/t2_denim_sealed_test_v1/README.md - Lossless trajectories:
data/t2_denim_sealed_test_v1/cohort.h5 - Viewer indexes:
data/t2_denim_sealed_test_v1/index.csvandindex.jsonl - Generation contract:
configs/t2_denim_sealed_test_v1.json - Leakage audit:
artifacts/t2_denim_protocol_audit_v1.json
AgentFEM runtime validation
The expanded DENIM checkpoint is also available as a checksum-authenticated
safetensors bundle in the
AgentFEM-DENIM model repository.
The safe bundle reproduces the legacy implementation on the fixed 121-step
path to a maximum stress difference of 2.68e-7 Pa and identical final PEEQ.
Serial and two-rank AgentFEM implicit plastic-bar runs both completed 4/4
increments, with a reported maximum-stress difference of 5.96e-8 Pa between
the two executions. The current plastic automatic-differentiation tangent has
a documented 0.05–0.80% discrepancy against fixed-old-state finite
differences over the audited plastic states. The demonstrated global cases
converge; an exact consistent plastic tangent remains outside the present
claim boundary.
- Machine evidence:
artifacts/t2_denim_agentfem_v1/runtime_validation.json - Validation note:
artifacts/t2_denim_agentfem_v1/RUNTIME_VALIDATION.md - Data/model handoff:
docs/T2_DATA_MODEL_HANDOFF.md
Multiaxial v2 at a glance
- eight path families, including non-proportional, rotating and random five-direction loading;
- 241 ordered states per trajectory;
- stress, strain, plastic strain, PEEQ, two-family total backstress, plastic increments and physical diagnostics;
- zero quality-gate failures across all 1,024 trajectories;
- six model families evaluated under three frozen protocols;
- element-level deployment in a controlled notched-bar finite-element gate.
Stress RMSE on held-out trajectories:
| Model | ID | Path OOD | Parameter OOD |
|---|---|---|---|
| Pointwise MLP | 83.51 MPa | 105.81 MPa | 82.34 MPa |
| GRU | 17.26 MPa | 76.03 MPa | 19.26 MPa |
| LSTM | 22.67 MPa | 102.54 MPa | 22.89 MPa |
| Causal TCN | 21.82 MPa | 60.44 MPa | 21.99 MPa |
| Physics-state GRU | 23.06 MPa | 66.00 MPa | 24.19 MPa |
| Physics-integrator NN | 0.0128 MPa | 0.0237 MPa | 0.0275 MPa |
The physics-integrator NN predicts a bounded plastic-multiplier correction and then applies differentiable J2/Chaboche consistency corrections while storing plastic strain, PEEQ and two backstress tensors. It passed the mild and severe structural gates with reaction relative-L2 errors of 1.65e-7 and 2.39e-7. The severe case recorded one trust-region fallback at complete unloading.
This is a white-box physics-fusion ceiling: the embedded return-mapping equations match the constitutive families that generated the synthetic data. It demonstrates the benefit of architecture-level physics for this controlled benchmark, but does not establish transfer to unknown materials or misspecified physical models.
Reproduction and evidence
- Dataset details:
data/t2_multiaxial_ood_v2/README.md - Model card:
models/t2_multiaxial_ood_v2/README.md - Quality report:
artifacts/t2_multiaxial_ood_v2/QUALITY_REPORT.md - Full metrics:
artifacts/t2_multiaxial_ood_v2/model_metrics.json - Structural gates:
artifacts/t2_multiaxial_ood_v2/structural_validation/ - Manuscript roadmap:
docs/T2_MULTIAXIAL_RESEARCH_MEMO.md - Literature map:
docs/T2_MULTIAXIAL_LITERATURE.md - Commands:
T2_V2_REPRODUCE.md - DENIM data and evidence:
DENIM_START_HERE.md - DENIM reproduction:
DENIM_REPRODUCE.md
The original multiaxial release used AgentFEM commit
058faecc05aeda143d014fd229401003a9258bbb (0.3.7.dev0). Later release
manifests record their own software revisions and hashes. All quantities use SI
units. Voigt order is xx, yy, zz, xy, yz, xz, with tensor shear.
Scope
The releases are controlled synthetic, small-strain benchmarks for J2/Chaboche families, material-parameter variation and one deliberately hidden three-memory reference material. They are not a general metals database and do not constitute experimental calibration, fatigue-life prediction, damage, finite-strain plasticity or a production-certified learned material. Complete internal states are privileged simulation labels, not quantities normally available from standard material tests. Data are CC BY 4.0; code files are covered by the included code license.
Evidence protocol v3
See article_evidence_v3/ for frozen ablation and leave-one-family-out split definitions.
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