6d19038784
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>
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title, created, updated, status, tags, sources
| title | created | updated | status | tags | sources | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| NCog Behavior and Limitations | 2026-04-07 | 2026-04-07 | evolving |
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NCog — Normalized Center of Gravity
What It Is
NCog is a 0-1 value indicating where on its flow range a pump operates most efficiently. Computed per tick from the current pressure slice of the 3D pump curve.
BEP_flow = minFlow + (maxFlow - minFlow) * NCog
How It's Computed
- Pressure sensors update →
getMeasuredPressure()computes differential fDimensionlocks the 2D slice at current system pressurecalcCog()computes Q/P (specific flow) across the curve- Peak Q/P index →
NCog = (flowAtPeak - flowMin) / (flowMax - flowMin)
When NCog is Meaningful
NCog requires differential pressure (upstream + downstream). With only one pressure sensor, fDimension is the raw sensor value (too high), producing a monotonic Q/P curve and NCog = 0.
| Condition | NCog for H05K | NCog for C5 |
|---|---|---|
| ΔP = 400 mbar | 0.333 | 0.355 |
| ΔP = 1000 mbar | 0.000 | 0.000 |
| ΔP = 1500 mbar | 0.135 | 0.000 |
| ΔP = 2000 mbar | 0.351 | 0.000 |
Why NCog = 0 Happens
For variable-speed centrifugal pumps, Q/P is monotonically decreasing when the affinity laws dominate (P ∝ Q³). At certain pressure levels, the spline interpolation preserves this monotonicity and the peak is always at index 0 (minimum flow).
How the machineGroupControl Uses NCog
The BEP-Gravitation algorithm seeds each pump at its BEP flow, then redistributes using slope-based weights + marginal-cost refinement. Even when NCog = 0, the slope redistribution produces near-optimal results because it uses actual power evaluations.
[!warning] Disproven: NCog as proportional weight Using NCog directly as a flow-distribution weight (
flow = NCog/totalNCog * Qd) is wrong. It starves pumps with NCog = 0 and overloads high-NCog pumps. SeecalcBestCombinationin machineGroupControl.