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znetsixe 6d19038784 docs: initialize project wiki from production hardening session

12 pages covering architecture, findings, and metrics from the
rotatingMachine + machineGroupControl hardening work:

- Overview: node inventory, what works/doesn't, current scale
- Architecture: 3D pump curves, group optimization algorithm
- Findings: BEP-Gravitation proof (0.1% of optimum), NCog behavior,
  curve non-convexity, pump switching stability
- Metrics: test counts, power comparison table, performance numbers
- Knowledge graph: structured YAML with all data points and provenance
- Session log: 2026-04-07 production hardening
- Tools: query.py, search.sh, lint.sh

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

2026-04-07 16:36:08 +02:00

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3D Pump Curve Prediction

Data Structure

A family of 2D curves indexed by pressure (f-dimension):

X-axis: control position (0-100%)
Y-axis: flow (nq) or power (np) in canonical units
F-dimension: pressure (Pa) — the 3rd dimension

Raw curves are in curve units (m3/h, kW, mbar). _normalizeMachineCurve() converts to canonical (m3/s, W, Pa).

Interpolation

Monotonic cubic spline (Fritsch-Carlson) in both dimensions:

X-Y splines: at each discrete pressure level
F-splines: across pressure levels for intermediate pressure interpolation

Prediction Flow

predict.y(x):
  1. Clamp x to [currentFxyXMin, currentFxyXMax]
  2. Normalize x to [normMin, normMax]
  3. Evaluate spline at normalized x for current fDimension
  4. Return y in canonical units (m3/s or W)

Unit Conversion Chain

Raw curve (m3/h, kW, mbar)
  → _normalizeMachineCurve → canonical (m3/s, W, Pa)
  → predict class → canonical output
  → MeasurementContainer.getCurrentValue(outputUnit) → output units

No double-conversion. Clean separation: specificClass handles units, predict handles normalization/interpolation.

Three Predict Instances per Machine

predictFlow: control % → flow (nq curve)
predictPower: control % → power (np curve)
predictCtrl: flow → control % (reversed nq curve)

Boundary Behavior

Below/above curve X range: flat extrapolation (clamped)
Below/above f-dimension range: clamped to min/max pressure level

Performance

y(x): O(log n), effectively O(1) for 5-10 data points
buildAllFxyCurves: sub-10ms for typical curves
Full caching of normalized curves, splines, and calculated curves

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