85d1222139
- Shift analysis from raw-field q_ctl to correction-field dq_ctl = q_ctl - q_blk - Force/action/signature CCD for illusion 0.75L, 1.0L, 1.5L - Zone-restricted CCD (near_body/body_wake/sensor_zone) with spatial separation evidence - 1.5L identified as special mechanism (low action coupling, phase drift) - Karman reference data collected (q_in, q_blk) - Snapshot POD speedup (96x96 instead of 1310720x96) - Comprehensive report: docs/ccd_correction_field_report.md (412 lines) - Handover document: docs/ccd_handover.md Co-authored-by: Cursor <cursoragent@cursor.com>
110 lines
6.1 KiB
Markdown
110 lines
6.1 KiB
Markdown
# SR-CCD-OID Cross-Pipeline Mapping
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## Purpose
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This document maps the three analysis pipelines (SINDy-SR, CCD, OID) onto a unified chain. They are NOT competing approaches — they answer different questions at different positions along the control-to-signature pathway.
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## Unified Control Analysis Chain
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```
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obs --[SR/SINDy]--> act --[CFD/physics]--> dq_ctl --[CCD/OID]--> force/signature
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^ |
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|_________________________________________________________________________|
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closed loop
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```
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| Link | What happens | Which analysis |
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|------|-------------|----------------|
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| obs -> act | DRL policy maps sensor readings to control actions | **SR/SINDy** (white-box control law extraction) |
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| act -> dq_ctl | Actions modify the flow field; the change relative to uncontrolled baseline is `dq_ctl` | CFD / data collection |
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| dq_ctl -> force | Which correction structures most project to cylinder forces | **CCD** (force line), **OID** |
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| dq_ctl -> signature | Which correction structures most determine future sensor mismatch | **CCD** (signature line), **OID** |
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## Pipeline Comparison Table
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| Aspect | SR / SINDy | CCD | OID / PCD |
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|--------|-----------|-----|-----------|
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| **Primary question** | How does the controller map observations to actions? | Which correction structures correlate most with force/action/signature? | What is the unified low-dimensional coordinate that captures observable-related structure? |
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| **Input data** | Dimensionless obs and actions (time series) | `dq_ctl` fields (N snapshots x 2*NX*NY grid) + observable time series (force/action/sensor error) | POD coefficients of `dq_ctl` + observable time series |
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| **Output** | Sparse symbolic control law (e.g. `a_F = 0.3*sin(u_s1)`) | CCD mode directions W, modal overlaps O_k, compactness m80, LOCO R2 | Low-dimensional coordinate z(t), observable reconstruction error |
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| **Key method** | STLSQ threshold grid, G-equivariant constraints, SIN activation | POD-reduced CCD (Lyu23-inspired) | Observability Gramian / canonical correlation |
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| **Current maturity** | Medium — cross-Re shared backbone found, G-equivariance validated | **Highest** — correction-field framework complete for illusion 0.75L/1.0L/1.5L with force/action/signature lines | Low-medium — framework defined, needs data alignment with CCD |
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| **Validation** | Leave-one-Re-out cross-validation, closed-loop replay | LOCO (4-fold), blocked split, R2_m80 | pending alignment |
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| **Key result** | Karman cloak cross-Re shared backbone exists (R2 > 0.9 for holdout 200) | 1.0L O(dqctl,dqtar)=0.913, m80=1; force/sig separated at tau=0, shared at tau_c | pending |
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## Maturity by Scene
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| Scene | SR/SINDy | CCD | OID |
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|-------|----------|-----|-----|
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| Karman cloak re50/100/200/400 | **Existing** (cross-Re backbone) | Data ready, analysis deferred | Not started |
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| Illusion 0.75L | Existing | **Complete** (force/action/sig) | Partial |
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| Illusion 1.0L | Existing | **Complete** (force/action/sig) | Partial |
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| Illusion 1.5L | Existing | **Complete** (force/action/sig, special mechanism) | Not started |
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| Steady cloak | Existing | Partial (quantitative metrics done) | Not started |
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| Vortex cloak (lamb/taylor) | Existing | Not started | Not started |
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## How They Assemble Into a Paper Chapter
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### Chapter Structure Proposal
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#### 1. Control Law Extraction (SR/SINDy)
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- *Question*: What is the map from sensor observations to cylinder rotations?
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- *Deliverable*: Symbolic control law for each scene, cross-scene comparison of feature usage
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- *Evidence*: Leave-one-out validation, G-equivariance error < 10%
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#### 2. Correction Field Analysis (CCD)
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- *Question*: What flow structures does the controller actually modulate?
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- *Deliverable*:
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- Correction-field decomposition (`dq_ctl`)
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- Force line: O(dqctl,dqtar) across diameters
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- Action line: compactness m80
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- Signature line: force-sig separation at zero lag, convergence at convective delay
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- 1.5L special mechanism
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- *Evidence*: LOCO validation R2 > 0.4 for all lines
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#### 3. Low-Dimensional Coordinate (OID)
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- *Question*: Can we describe controller-relevant structures in a unified low-D coordinate?
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- *Deliverable*: Observable-informed coordinates z for each case, reconstruction error
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- *Evidence*: Reconstruction quality vs POD-baseline
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#### 4. Unified Mechanism Discussion
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- Synthesize findings from all three analyses
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- Key claims to support:
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- Control operates by modifying pinball's existing wake (not generating new flows)
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- Force-relevant correction is low-rank and target-aligned at natural scale
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- Cross-scale illusion uses divergent correction paths
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- Force and signature structures separate at zero lag but converge convectively
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## Current Gaps by Pipeline
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### SR/SINDy Gaps
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- Illusion cross-diameter comparison not yet unified with CCD's correction-field framework
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- Closed-loop validation of extracted control laws needs systematic comparison
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### CCD Gaps
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- Karman cloak analysis deferred (data ready, framework designed)
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- Steady cloak needs closed-loop control to be meaningful
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- Zone-restricted CCD not yet complete (in progress)
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### OID Gaps
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- Data pipeline not yet aligned with CCD's correction-field format
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- No direct comparison of OID coordinates with CCD directions
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- Requires full cross-analysis with existing CCD results
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## Data Compatibility
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All three pipelines ultimately read from the same data sources:
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- `fields_aligned.npz` (96 aligned field snapshots)
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- `controlled.npz` / `sensors.npz` (telemetry)
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- `configs.py` (scene metadata)
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The **correction-field framework** (`dq_ctl = q_ctl - q_blk`) is the standard analysis object across all three. Any analysis that uses raw `q_ctl` instead should be explicitly flagged as a cross-check.
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## Recommendation
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For the next phase of work:
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1. **CCD** consolidates current results and adds zone-restricted analysis
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2. **OID** should adopt CCD's data loading (`compute_correction_fields.py`) and correction-field protocol
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3. **SR/SINDy** should align its cross-diameter comparison with CCD's correction-field O(dqctl,dqtar) results
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4. A unifying figure comparing O(dqctl,dqtar) from CCD with SR control-law similarity across diameters would be powerful
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