Publish task-preserving HJ checkpoints and model card
Browse filesThree registered seeds, validation-selected thresholds, aggregate evaluation, limitations, and links to GitHub and supplementary movies.
- LICENSE +22 -0
- MODEL_CARD_LIMITATIONS.md +16 -0
- README.md +67 -0
- aggregate.json +329 -0
- checkpoint_seed20260904.pt +3 -0
- checkpoint_seed20260905.pt +3 -0
- checkpoint_seed20260906.pt +3 -0
- thresholds_seed20260904.json +5 -0
- thresholds_seed20260905.json +5 -0
- thresholds_seed20260906.json +5 -0
LICENSE
ADDED
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MIT License
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Copyright (c) 2026 Ehsan Roohi
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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MODEL_CARD_LIMITATIONS.md
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# Intended use and limitations
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The checkpoints are research artifacts for segmentation of shocks and
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vortex-core candidates in two-dimensional compressible CFD fields following the
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documented input contract. They are not a flow solver, a substitute for CFD
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convergence checks, or a universal detector.
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Training supervision is physics-derived and weak. CFD Dice values measure
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agreement with corrected weak references, not human ground truth. Analytic
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vortex and SU2-ray evaluations are independent bounded controls but do not
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measure complete post-shock vortex accuracy or full-front precision. Sigmoid
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scores are not independently calibrated probabilities. Near-wall vorticity,
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strong shear, contact-like layers, numerical oscillations and unfamiliar grids
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remain possible failure modes. Users must inspect overlays and preserve the
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separation among ML-only, physics-only and hybrid products.
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README.md
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---
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license: mit
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---
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---
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license: mit
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library_name: pytorch
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pipeline_tag: image-segmentation
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tags:
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- computational-fluid-dynamics
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- compressible-flow
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- shock-detection
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- vortex-detection
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- multi-label-segmentation
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- task-preserving-adaptation
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datasets:
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- custom
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metrics:
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- dice
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---
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# Task-Preserving Shock–Vortex Segmentation (HJ)
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This repository contains the three registered checkpoints of the task-preserving
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harmonized joint (HJ) network used for overlapping shock and vortex-core
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segmentation in compressible CFD. The model consumes primitive flow fields plus
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deterministic differential diagnostics and returns independent sigmoid fields;
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shock and vortex labels are therefore allowed to overlap.
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The architecture has a shared encoder with widths `[10, 20, 40, 80]` and
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task-specific shock and vortex decoders. During corrected-target shock
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adaptation, the encoder and complete vortex pathway are frozen. Only the shock
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decoder and projection are updated, giving exact retained-task preservation by
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construction and direct array replay.
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## Registered results
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Means and sample standard deviations over seeds 20260904–20260906:
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| Evaluation | Result |
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|---|---:|
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| Airfoil shock Dice, corrected weak reference | 0.936 ± 0.004 |
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| Cylinder shock Dice, corrected weak reference | 0.939 ± 0.024 |
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| Retained airfoil core Dice | 0.827 ± 0.048 |
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| Retained cylinder core Dice | 0.228 ± 0.020 |
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| Independent analytic-vortex disk Dice | 0.672 ± 0.086 |
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| Independent analytic centre recovery | 0.889 ± 0.192 |
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| Continued-SU2 finite-ray coverage | 1.000 ± 0.000 |
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| Continued-SU2 conditional normal MAE | 0.00284c ± 0.00092c |
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Core probability drift is exactly zero for all three seeds over all 129
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seed–field evaluations. These results do **not** establish human-ground-truth
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accuracy, universal geometry transfer, or complete-front validation. The CFD
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Dice references are physics-derived weak references; the analytic vortex and
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finite SU2 rays are distinct bounded controls.
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## Files
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- `checkpoint_seed2026090X.pt`: task-preserving HJ checkpoint.
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- `thresholds_seed2026090X.json`: validation-selected operating point.
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- `aggregate.json`: complete three-seed aggregate used by the manuscript.
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- `MODEL_CARD_LIMITATIONS.md`: intended use and limitations.
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## Code, media and demo
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- [Source code and reproducibility material](https://github.com/Ehsan-Roohi/ShockVortexML)
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- [Original-quality supplementary movies](https://github.com/Ehsan-Roohi/ShockVortexML/releases/tag/movies-localfront-v2-20260909)
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- [Author’s YouTube channel](https://www.youtube.com/@ehsan_roohi)
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- Interactive Space: linked from this model page after publication.
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## License and citation
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Released under the MIT License. The manuscript is under review/preparation;
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please use the repository citation metadata until a DOI is assigned.
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aggregate.json
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{
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"seeds": [
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20260904,
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20260905,
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+
20260906
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| 6 |
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],
|
| 7 |
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"arms": {
|
| 8 |
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"hj_restricted": {
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| 9 |
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"label": "Task-preserving HJ",
|
| 10 |
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"parameters": 268496,
|
| 11 |
+
"trainable_parameters": 75891,
|
| 12 |
+
"shock_dice": {
|
| 13 |
+
"airfoil": {
|
| 14 |
+
"mean": 0.9357071988455214,
|
| 15 |
+
"sample_sd": 0.004202090216577011,
|
| 16 |
+
"values": [
|
| 17 |
+
0.9344757083049362,
|
| 18 |
+
0.9322584471635962,
|
| 19 |
+
0.9403874410680321
|
| 20 |
+
]
|
| 21 |
+
},
|
| 22 |
+
"cylinder": {
|
| 23 |
+
"mean": 0.9386199049068382,
|
| 24 |
+
"sample_sd": 0.02439132578156726,
|
| 25 |
+
"values": [
|
| 26 |
+
0.9633139318703084,
|
| 27 |
+
0.9380027911530677,
|
| 28 |
+
0.9145429916971386
|
| 29 |
+
]
|
| 30 |
+
}
|
| 31 |
+
},
|
| 32 |
+
"core_dice": {
|
| 33 |
+
"airfoil": {
|
| 34 |
+
"mean": 0.8269258635545622,
|
| 35 |
+
"sample_sd": 0.04765046704785947,
|
| 36 |
+
"values": [
|
| 37 |
+
0.8326573417737513,
|
| 38 |
+
0.8714513644366197,
|
| 39 |
+
0.7766688844533156
|
| 40 |
+
]
|
| 41 |
+
},
|
| 42 |
+
"cylinder": {
|
| 43 |
+
"mean": 0.2277874006486062,
|
| 44 |
+
"sample_sd": 0.02043299476214628,
|
| 45 |
+
"values": [
|
| 46 |
+
0.21611023364740484,
|
| 47 |
+
0.21587098195068724,
|
| 48 |
+
0.25138098634772654
|
| 49 |
+
]
|
| 50 |
+
}
|
| 51 |
+
},
|
| 52 |
+
"core_probability_max_drift_by_seed": [
|
| 53 |
+
0.0,
|
| 54 |
+
0.0,
|
| 55 |
+
0.0
|
| 56 |
+
],
|
| 57 |
+
"core_probability_bit_exact_by_seed": [
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| 58 |
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true,
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| 59 |
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true,
|
| 60 |
+
true
|
| 61 |
+
],
|
| 62 |
+
"analytic_vortex_dice": {
|
| 63 |
+
"mean": 0.6724153508806848,
|
| 64 |
+
"sample_sd": 0.08568023829738895,
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| 65 |
+
"values": [
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| 66 |
+
0.5769273709675609,
|
| 67 |
+
0.697739762255559,
|
| 68 |
+
0.7425789194189347
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| 69 |
+
]
|
| 70 |
+
},
|
| 71 |
+
"analytic_centre_recovery": {
|
| 72 |
+
"mean": 0.8888888888888888,
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| 73 |
+
"sample_sd": 0.1924500897298753,
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| 74 |
+
"values": [
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