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| <a href="/#about">← Back to Delta-V</a> | |
| <p class="eyebrow">TECHNICAL NOTE · 11 SEPTEMBER 2026 · PROTOTYPE 3</p> | |
| <h1>What the original model demo tests</h1> | |
| <p> | |
| Delta-V is a system for learned engineering surrogates built one | |
| physical-domain lane at a time; fluid dynamics is lane 1 and the only | |
| lane served today. Within that lane it compares one neural next-step | |
| prediction with the recorded next snapshot, and offers a separate | |
| table-based estimator of overall fluid outcomes. The six original | |
| examples show training-data behavior. | |
| Three additional official-test clips (rollout-test- IDs) provide f0–f10 | |
| references for autoregressive playback. A separate six-window | |
| official-test check is reported below; broad generalization and a | |
| learned-adapter advantage are not established. | |
| </p> | |
| <h2>Model and artifacts</h2> | |
| <p> | |
| The original demo uses the epoch 59 model from | |
| <a | |
| href="https://huggingface.co/datasets/KrishMalik/deltav-fluid/tree/7bf3f989dcfab6d0f43ea482ab8f26ddbdec3752" | |
| >the published checkpoint revision</a | |
| >. The checkpoint was trained across turbulent radiative layer 2D, | |
| Rayleigh–Bénard convection and shear flow, with turbulent radiative | |
| layer as the primary set and the other two as joint co-training sets. | |
| Training used bounded slices of The Well at prototype budget, not the | |
| full trajectory sets; this training scale, rather than the | |
| architecture, is the main limit on current accuracy and rollout | |
| horizon. The FNO uses 32 × 32 spectral modes and 128 hidden channels. | |
| The live epoch is shown on the Model page. Runtime artifact downloads | |
| are pinned to the linked revision, so the served weights cannot change | |
| under the deployment without a code change. | |
| </p> | |
| <h2>Inputs, outputs and preprocessing</h2> | |
| <p> | |
| Four consecutive snapshots are mapped to density/buoyancy/tracer (the | |
| shared scalar channel), pressure, horizontal velocity and vertical | |
| velocity. Per-system means and standard deviations normalize each | |
| channel as (x − mean)/(std + 10⁻⁶). Bilinear resampling with | |
| align_corners=False produces 256 × 256 fields. The model receives | |
| [batch,16,256,256] and produces [batch,4,256,256]. Outputs are | |
| denormalized using the same statistics. | |
| </p> | |
| <p> | |
| These are fixed data mappings, not learned adapters. Native grids are | |
| 128 × 384 for radiative cooling, 512 × 128 for convection and 256 × 512 | |
| for shear flow. Displays preserve each physical domain’s aspect ratio | |
| and use simulation code units. | |
| </p> | |
| <h2>Measured quantities</h2> | |
| <ul> | |
| <li> | |
| <strong>Relative L2:</strong> ‖prediction − reference‖₂ / | |
| ‖reference‖₂. Undefined for a zero-norm reference. | |
| </li> | |
| <li> | |
| <strong>RMSE:</strong> square root of mean squared error, in the | |
| field’s code units. | |
| </li> | |
| <li> | |
| <strong>SSIM:</strong> scikit-image structural_similarity with the | |
| reference’s maximum minus minimum as data_range and library defaults | |
| (7 × 7 window). Undefined for constant reference fields. | |
| </li> | |
| </ul> | |
| <p> | |
| All scores use floating-point fields before quantization and a reference | |
| resampled to the model grid. The self-imposed v1 policy is strictly | |
| relative L2 <15% for scalar and pressure; velocities have no | |
| quantitative target. SSIM is an image-structure measure and does not | |
| establish physical conservation. See the | |
| <a href="/#about">24-row measured results table</a> and | |
| <a href="/quality">machine-readable scores</a>. | |
| </p> | |
| <h2>Data provenance and time</h2> | |
| <p> | |
| Six bundled windows, two per served system, contain four input snapshots | |
| and one next-step reference. They come from training slices. | |
| The sample catalogue records window IDs, dial values, start | |
| indices, times and shapes. These bundled files lack complete original | |
| trajectory identifiers and are not used as the new test set. Moving a | |
| time control shows recorded snapshots; it is not a model rollout. Moving | |
| parameter sliders estimates aggregate outcomes from tables and does not | |
| change the field’s initial condition. | |
| </p> | |
| <h2>Transport, caching and timing</h2> | |
| <p> | |
| Predictions are computed once during startup and cached. The display | |
| endpoints send lossless grayscale PNG atlases of the same quantized | |
| 8-bit values previously transported in NumPy arrays; the browser | |
| reconstructs the channel arrays before applying the established color | |
| maps. Full-precision quality scores accompany the images. Binary | |
| <code>/samples/{id}</code> and <code>/samples/{id}/predict</code> remain | |
| available. <code>POST /predict/field</code> returns floating-point | |
| predictions for correctly formatted inputs. | |
| </p> | |
| <p> | |
| The Settings page separates server startup, browser readiness, first | |
| comparison including sample load, and repeat cache retrieval. Original | |
| model computation is labeled separately. Timing varies by network and | |
| hardware; a 200 ms network response is not guaranteed. | |
| </p> | |
| <h2 id="evaluation">Held-out evaluation and fourth-system protocol</h2> | |
| <p> | |
| <strong>Notebook audit:</strong> the supplied training export reads only | |
| the official training split. Its joint-model validation uses | |
| a seeded random split of sliding windows, so neighboring windows from | |
| one trajectory can appear in both sets. Normalization is estimated | |
| before that split. The old validation loss is not trajectory-held-out. | |
| New tooling assigns whole trajectories before training and rejects | |
| overlap and validation/test data in normalization. | |
| </p> | |
| <p> | |
| <strong>Small official-test check:</strong> six predeclared windows, two | |
| source files per system, from the official test split. Each uses trajectory 0, | |
| four input snapshots and the fifth as reference. The selected starts are | |
| 40 (radiative), 100 (convection), and 60 (shear). No training or tuning | |
| used these results. The checkpoint-to-notebook lineage is | |
| owner-supplied, not cryptographically established. This limited check | |
| does not replace a new fixed train/validation/test training run. | |
| <a href="heldout-results.json" | |
| >All scores, source revisions, identifiers and hashes</a | |
| > | |
| are published, including failed targets. See <a href="/#about">About</a> | |
| for the readable table. | |
| </p> | |
| <p> | |
| The evaluation tooling groups all windows from the same source | |
| trajectory, rejects overlap between train/validation/test, verifies | |
| local file hashes, and requires explicit checkpoint-exposure records | |
| before accepting held-out evaluation. Hold the test set fixed, select | |
| checkpoints using validation only, and report all four channels by | |
| trajectory and system. Test results must not guide tuning. | |
| </p> | |
| <p> | |
| The fourth research system is <code>euler_multi_quadrants_openBC</code>. | |
| Its source includes density, energy, pressure and momentum components; | |
| the fixed preprocessing derives velocities from momentum/density. | |
| Compare scratch training, full fine-tuning and a frozen backbone with | |
| learned 1 × 1 input/output projections. Use nested training fractions | |
| 1%, 5%, 10%, 25%, 50%, 100%, identical splits and validation budgets, | |
| and report trainable parameters, wall time and per-channel errors. The | |
| supplied notebook excludes Euler from joint training, but includes a | |
| scratch-versus-full-fine-tuning experiment on fresh models. The owner | |
| subsequently supplied the converged 30-epoch two-arm result: losses | |
| 0.0089 versus 0.0107, with a reported 16.3% lower final training loss | |
| for the pretrained start. These training measurements are not live API | |
| results. On real OpenFOAM data (October 2026) a pretrained start gave no | |
| help over training from scratch, so pretraining is on the roadmap. | |
| Only one gamma value was represented instead of four intended, due to a | |
| selection bug. No fine-tuned checkpoints were saved. See the | |
| <a href="/#probe">Generalization probe</a> for provenance and | |
| limitations. The new learned-adapter arm has 292 trainable real | |
| parameters; the three-arm runner is implemented but has not been run. | |
| Target normalization is fitted only on each training fraction, | |
| identically for all arms. Complete exposure records remain required for | |
| that experiment. | |
| </p> | |
| <h2>Inspect the results</h2> | |
| <p>Open the <a href="/#simulator">original model demo</a> to select a sample and compare its prediction with the recorded solver field. For the study workflow, visit <a href="/#evidence">Research</a>.</p> | |
| <h2>Anonymous usage counts</h2> | |
| <p> | |
| Event tracking stores only aggregate counts of fixed event names, with | |
| no user/session identifiers or arrays; it respects browser privacy | |
| signals and the Settings opt-out. Counts are public, can include | |
| automated traffic, and reset on restart. They cannot measure unique | |
| users or a person-level funnel. The host may independently retain | |
| access logs. | |
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