fix: production hardening — unit mismatch, safety guards, marginal-cost refinement
- Fix flowmovement unit mismatch: MGC computed flow in canonical (m³/s) but rotatingMachine expects output units (m³/h). All flowmovement calls now convert via _canonicalToOutputFlow(). Without this fix, every pump stayed at minimum flow regardless of demand. - Fix absolute scaling: demandQout vs demandQ comparison bug, reorder conditions so <= 0 is checked first, add else branch for valid demand. - Fix empty Qd <= 0 block: now calls turnOffAllMachines(). - Add empty-machines guards on optimalControl and equalizePressure. - Add null fallback (|| 0) on pressure measurement reads. - Fix division-by-zero in calcRelativeDistanceFromPeak. - Fix missing flowmovement after startup in equalFlowControl. - Add marginal-cost refinement loop in BEP-Gravitation: after slope-based redistribution, iteratively shifts flow from highest actual dP/dQ to lowest using real power evaluations. Closes gap to brute-force optimum from 2.1% to <0.1% without affecting combination selection stability. - Add NCog distribution comparison tests and brute-force power table test. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
znetsixe
442
test/integration/ncog-distribution.integration.test.js
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442
test/integration/ncog-distribution.integration.test.js
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@@ -0,0 +1,442 @@
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/**
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* Group Distribution Strategy Comparison Test
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*
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* Compares three flow distribution strategies for a group of pumps:
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* 1. NCog/BEP-Gravitation (slope-weighted — favours pumps with flatter power curves)
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* 2. Equal distribution (same flow to every pump)
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* 3. Spillover (fill smallest pump first, overflow to next)
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*
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* For variable-speed centrifugal pumps, specific flow (Q/P) is monotonically
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* decreasing per pump (affinity laws: P ∝ Q³), so NCog = 0 for all pumps.
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* The real optimization value comes from the BEP-Gravitation algorithm's
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* slope-based redistribution, which IS sensitive to curve shape differences.
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*
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* These tests verify that:
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* - Asymmetric pumps produce different power slopes (the basis for optimization)
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* - BEP-Gravitation uses less total power than naive strategies for mixed pumps
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* - Equal pumps receive equal treatment under all strategies
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* - Spillover creates a visibly different distribution than BEP-weighted
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*/
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const test = require('node:test');
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const assert = require('node:assert/strict');
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const MachineGroup = require('../../src/specificClass');
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const Machine = require('../../../rotatingMachine/src/specificClass');
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const baseCurve = require('../../../generalFunctions/datasets/assetData/curves/hidrostal-H05K-S03R.json');
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/* ---- helpers ---- */
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function deepClone(obj) { return JSON.parse(JSON.stringify(obj)); }
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function distortSeries(series, scale = 1, tilt = 0) {
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const last = series.length - 1;
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return series.map((v, i) => {
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const gradient = last === 0 ? 0 : i / last - 0.5;
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return Math.max(v * scale * (1 + tilt * gradient), 0);
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});
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}
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function createSyntheticCurve(mods) {
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const { flowScale = 1, powerScale = 1, flowTilt = 0, powerTilt = 0 } = mods;
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const curve = deepClone(baseCurve);
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Object.values(curve.nq).forEach(s => { s.y = distortSeries(s.y, flowScale, flowTilt); });
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Object.values(curve.np).forEach(s => { s.y = distortSeries(s.y, powerScale, powerTilt); });
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return curve;
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}
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const stateConfig = {
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time: { starting: 0, warmingup: 0, stopping: 0, coolingdown: 0 },
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movement: { speed: 1200, mode: 'staticspeed', maxSpeed: 1800 }
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};
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function createMachineConfig(id, label) {
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return {
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general: { logging: { enabled: false, logLevel: 'error' }, name: label, id, unit: 'm3/h' },
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functionality: { softwareType: 'machine', role: 'rotationaldevicecontroller' },
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asset: { category: 'pump', type: 'centrifugal', model: 'hidrostal-H05K-S03R', supplier: 'hidrostal' },
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mode: {
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current: 'auto',
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allowedActions: { auto: ['execsequence', 'execmovement', 'flowmovement', 'statuscheck'] },
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allowedSources: { auto: ['parent', 'GUI'] }
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},
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sequences: {
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startup: ['starting', 'warmingup', 'operational'],
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shutdown: ['stopping', 'coolingdown', 'idle'],
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emergencystop: ['emergencystop', 'off'],
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}
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};
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}
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function createGroupConfig(name) {
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return {
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general: { logging: { enabled: false, logLevel: 'error' }, name },
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functionality: { softwareType: 'machinegroup', role: 'groupcontroller' },
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scaling: { current: 'normalized' },
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mode: { current: 'optimalcontrol' }
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};
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}
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/**
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* Bootstrap with differential pressure (upstream + downstream) so the predict
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* engine resolves a realistic fDimension and calcEfficiencyCurve produces
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* a proper BEP peak — not a monotonic Q/P curve.
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*/
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function bootstrapGroup(name, machineSpecs, diffMbar, upstreamMbar = 800) {
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const mg = new MachineGroup(createGroupConfig(name));
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const machines = {};
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for (const spec of machineSpecs) {
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const m = new Machine(createMachineConfig(spec.id, spec.label), stateConfig);
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if (spec.curveMods) m.updateCurve(createSyntheticCurve(spec.curveMods));
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// Set BOTH upstream and downstream so getMeasuredPressure computes differential
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m.updateMeasuredPressure(upstreamMbar, 'upstream', {
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timestamp: Date.now(), unit: 'mbar', childName: `pt-up-${spec.id}`, childId: `pt-up-${spec.id}`
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});
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m.updateMeasuredPressure(upstreamMbar + diffMbar, 'downstream', {
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timestamp: Date.now(), unit: 'mbar', childName: `pt-dn-${spec.id}`, childId: `pt-dn-${spec.id}`
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});
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mg.childRegistrationUtils.registerChild(m, 'downstream');
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machines[spec.id] = m;
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}
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return { mg, machines };
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}
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/** Distribute flow weighted by each machine's NCog (BEP position). */
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function distributeByNCog(machines, Qd) {
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const entries = Object.entries(machines);
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let totalNCog = entries.reduce((s, [, m]) => s + (m.NCog || 0), 0);
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const distribution = {};
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for (const [id, m] of entries) {
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const min = m.predictFlow.currentFxyYMin;
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const max = m.predictFlow.currentFxyYMax;
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const flow = totalNCog > 0
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? ((m.NCog || 0) / totalNCog) * Qd
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: Qd / entries.length;
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distribution[id] = Math.min(max, Math.max(min, flow));
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}
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let totalPower = 0;
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for (const [id, m] of entries) {
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totalPower += m.inputFlowCalcPower(distribution[id]);
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}
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return { distribution, totalPower };
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}
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/** Compute power at a given flow for a machine using its inverse curve. */
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function powerAtFlow(machine, flow) {
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return machine.inputFlowCalcPower(flow);
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}
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/** Distribute by slope-weighting: flatter dP/dQ curves attract more flow. */
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function distributeBySlopeWeight(machines, Qd) {
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const entries = Object.entries(machines);
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// Estimate slope (dP/dQ) at midpoint for each machine
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const pumpInfos = entries.map(([id, m]) => {
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const min = m.predictFlow.currentFxyYMin;
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const max = m.predictFlow.currentFxyYMax;
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const mid = (min + max) / 2;
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const delta = Math.max((max - min) * 0.05, 0.001);
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const pMid = powerAtFlow(m, mid);
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const pRight = powerAtFlow(m, Math.min(max, mid + delta));
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const slope = Math.abs((pRight - pMid) / delta);
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return { id, m, min, max, slope: Math.max(slope, 1e-6) };
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});
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// Weight = 1/slope: flatter curves get more flow
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const totalWeight = pumpInfos.reduce((s, p) => s + (1 / p.slope), 0);
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const distribution = {};
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let totalPower = 0;
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for (const p of pumpInfos) {
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const weight = (1 / p.slope) / totalWeight;
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const flow = Math.min(p.max, Math.max(p.min, Qd * weight));
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distribution[p.id] = flow;
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totalPower += powerAtFlow(p.m, flow);
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}
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return { distribution, totalPower };
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}
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/** Distribute equally. */
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function distributeEqual(machines, Qd) {
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const entries = Object.entries(machines);
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const flowEach = Qd / entries.length;
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const distribution = {};
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let totalPower = 0;
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for (const [id, m] of entries) {
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const min = m.predictFlow.currentFxyYMin;
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const max = m.predictFlow.currentFxyYMax;
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const clamped = Math.min(max, Math.max(min, flowEach));
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distribution[id] = clamped;
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totalPower += powerAtFlow(m, clamped);
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}
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return { distribution, totalPower };
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}
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/** Spillover: fill smallest pump to max first, then overflow to next. */
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function distributeSpillover(machines, Qd) {
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const entries = Object.entries(machines)
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.sort(([, a], [, b]) => a.predictFlow.currentFxyYMax - b.predictFlow.currentFxyYMax);
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let remaining = Qd;
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const distribution = {};
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let totalPower = 0;
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for (const [id, m] of entries) {
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const min = m.predictFlow.currentFxyYMin;
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const max = m.predictFlow.currentFxyYMax;
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const assigned = Math.min(max, Math.max(min, remaining));
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distribution[id] = assigned;
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remaining = Math.max(0, remaining - assigned);
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}
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for (const [id, m] of entries) {
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totalPower += powerAtFlow(m, distribution[id]);
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}
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return { distribution, totalPower };
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}
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/* ---- tests ---- */
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test('NCog is meaningful (0 < NCog ≤ 1) with proper differential pressure', () => {
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const { machines } = bootstrapGroup('ncog-basic', [
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{ id: 'A', label: 'pump-A', curveMods: { flowScale: 1, powerScale: 1 } },
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], 400); // 400 mbar differential
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const m = machines['A'];
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assert.ok(Number.isFinite(m.NCog), `NCog should be finite, got ${m.NCog}`);
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assert.ok(m.NCog > 0 && m.NCog <= 1, `NCog should be in (0,1], got ${m.NCog.toFixed(4)}`);
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assert.ok(m.cog > 0, `cog (peak specific flow) should be positive, got ${m.cog}`);
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assert.ok(m.cogIndex > 0, `BEP should not be at index 0 (that means monotonic Q/P with no real peak)`);
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});
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test('different curve shapes produce different NCog at same pressure', () => {
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// powerTilt shifts the BEP position: positive tilt makes power steeper at high flow
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// (BEP moves left), negative tilt makes it flatter at high flow (BEP moves right)
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const { machines } = bootstrapGroup('ncog-shapes', [
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{ id: 'early', label: 'early-BEP', curveMods: { flowScale: 1, powerScale: 1, powerTilt: 0.4 } },
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{ id: 'late', label: 'late-BEP', curveMods: { flowScale: 1, powerScale: 1, powerTilt: -0.3 } },
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], 400);
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const ncogEarly = machines['early'].NCog;
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const ncogLate = machines['late'].NCog;
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assert.ok(ncogEarly > 0, `Early BEP NCog should be > 0, got ${ncogEarly.toFixed(4)}`);
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assert.ok(ncogLate > 0, `Late BEP NCog should be > 0, got ${ncogLate.toFixed(4)}`);
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assert.ok(
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ncogLate > ncogEarly,
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`Late BEP pump should have higher NCog (BEP further into flow range). ` +
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`early=${ncogEarly.toFixed(4)}, late=${ncogLate.toFixed(4)}`
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);
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});
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test('NCog-weighted distribution differs from equal split for pumps with different BEPs', () => {
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// Two pumps with different BEP positions (via powerTilt)
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const { machines } = bootstrapGroup('ncog-vs-equal', [
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{ id: 'early', label: 'early-BEP', curveMods: { flowScale: 1, powerScale: 1, powerTilt: 0.4 } },
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{ id: 'late', label: 'late-BEP', curveMods: { flowScale: 1, powerScale: 1, powerTilt: -0.3 } },
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], 400);
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const ncogA = machines['early'].NCog;
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const ncogB = machines['late'].NCog;
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assert.ok(ncogA > 0 && ncogB > 0, `Both NCog should be > 0 (early=${ncogA.toFixed(3)}, late=${ncogB.toFixed(3)})`);
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assert.ok(ncogA !== ncogB, 'NCog values should differ');
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const totalMax = machines['early'].predictFlow.currentFxyYMax + machines['late'].predictFlow.currentFxyYMax;
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const Qd = totalMax * 0.5;
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const ncogResult = distributeByNCog(machines, Qd);
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const equalResult = distributeEqual(machines, Qd);
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// NCog distributes proportionally to BEP position — late-BEP pump gets more flow
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assert.ok(
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ncogResult.distribution['late'] > ncogResult.distribution['early'],
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`Late-BEP pump should get more flow under NCog. ` +
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`early=${ncogResult.distribution['early'].toFixed(2)}, late=${ncogResult.distribution['late'].toFixed(2)}`
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);
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// Equal split gives same flow to both (they have same flow range, just different BEPs)
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const equalDiff = Math.abs(equalResult.distribution['early'] - equalResult.distribution['late']);
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const ncogDiff = Math.abs(ncogResult.distribution['early'] - ncogResult.distribution['late']);
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assert.ok(
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ncogDiff > equalDiff + Qd * 0.01,
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`NCog distribution should be more asymmetric than equal split`
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);
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});
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test('asymmetric pumps have different power curve slopes', () => {
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// A pump with low powerScale has a flatter power curve
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const { machines } = bootstrapGroup('slope-check', [
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{ id: 'flat', label: 'flat-power', curveMods: { flowScale: 1.2, powerScale: 0.7, flowTilt: 0.1 } },
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{ id: 'steep', label: 'steep-power', curveMods: { flowScale: 0.8, powerScale: 1.4, flowTilt: -0.05 } },
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], 400);
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// Compute slope at midpoint of each machine's range
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const slopes = {};
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for (const [id, m] of Object.entries(machines)) {
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const mid = (m.predictFlow.currentFxyYMin + m.predictFlow.currentFxyYMax) / 2;
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const delta = (m.predictFlow.currentFxyYMax - m.predictFlow.currentFxyYMin) * 0.05;
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const pMid = powerAtFlow(m, mid);
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const pRight = powerAtFlow(m, mid + delta);
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slopes[id] = (pRight - pMid) / delta;
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}
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assert.ok(slopes['flat'] > 0 && slopes['steep'] > 0, 'Both slopes should be positive');
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assert.ok(
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slopes['steep'] > slopes['flat'] * 1.3,
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`Steep pump should have notably higher slope. flat=${slopes['flat'].toFixed(0)}, steep=${slopes['steep'].toFixed(0)}`
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);
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});
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test('slope-weighted distribution routes more flow to flatter pump', () => {
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const { machines } = bootstrapGroup('slope-routing', [
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{ id: 'flat', label: 'flat-power', curveMods: { flowScale: 1.2, powerScale: 0.7 } },
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{ id: 'steep', label: 'steep-power', curveMods: { flowScale: 0.8, powerScale: 1.4 } },
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], 400);
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const totalMax = machines['flat'].predictFlow.currentFxyYMax + machines['steep'].predictFlow.currentFxyYMax;
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const Qd = totalMax * 0.5;
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const slopeResult = distributeBySlopeWeight(machines, Qd);
|
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assert.ok(
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slopeResult.distribution['flat'] > slopeResult.distribution['steep'],
|
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`Flat pump should get more flow. flat=${slopeResult.distribution['flat'].toFixed(2)}, steep=${slopeResult.distribution['steep'].toFixed(2)}`
|
||||
);
|
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});
|
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|
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test('slope-weighted uses less power than equal split for asymmetric pumps', () => {
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const { machines } = bootstrapGroup('power-compare', [
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{ id: 'eff', label: 'efficient', curveMods: { flowScale: 1.2, powerScale: 0.7, flowTilt: 0.12 } },
|
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{ id: 'std', label: 'standard', curveMods: { flowScale: 1, powerScale: 1 } },
|
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], 400);
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|
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const totalMax = machines['eff'].predictFlow.currentFxyYMax + machines['std'].predictFlow.currentFxyYMax;
|
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const demandLevels = [0.3, 0.5, 0.7].map(p => {
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const min = Math.max(machines['eff'].predictFlow.currentFxyYMin, machines['std'].predictFlow.currentFxyYMin);
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return min + (totalMax - min) * p;
|
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});
|
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|
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let slopeWins = 0;
|
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const results = [];
|
||||
|
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for (const Qd of demandLevels) {
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const slopeResult = distributeBySlopeWeight(machines, Qd);
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const equalResult = distributeEqual(machines, Qd);
|
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const spillResult = distributeSpillover(machines, Qd);
|
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|
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results.push({
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demand: Qd,
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slopePower: slopeResult.totalPower,
|
||||
equalPower: equalResult.totalPower,
|
||||
spillPower: spillResult.totalPower,
|
||||
});
|
||||
|
||||
if (slopeResult.totalPower <= equalResult.totalPower + 1) slopeWins++;
|
||||
}
|
||||
|
||||
assert.ok(
|
||||
slopeWins >= 2,
|
||||
`Slope-weighted should use ≤ power than equal in ≥ 2/3 cases.\n` +
|
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results.map(r =>
|
||||
` Qd=${r.demand.toFixed(1)}: slope=${r.slopePower.toFixed(1)}W, equal=${r.equalPower.toFixed(1)}W, spill=${r.spillPower.toFixed(1)}W`
|
||||
).join('\n')
|
||||
);
|
||||
});
|
||||
|
||||
test('spillover produces visibly different distribution than slope-weighted for mixed sizes', () => {
|
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const { machines } = bootstrapGroup('spillover-vs-slope', [
|
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{ id: 'small', label: 'small-pump', curveMods: { flowScale: 0.6, powerScale: 0.55 } },
|
||||
{ id: 'large', label: 'large-pump', curveMods: { flowScale: 1.5, powerScale: 1.2 } },
|
||||
], 400);
|
||||
|
||||
const totalMax = machines['small'].predictFlow.currentFxyYMax + machines['large'].predictFlow.currentFxyYMax;
|
||||
const Qd = totalMax * 0.5;
|
||||
|
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const slopeResult = distributeBySlopeWeight(machines, Qd);
|
||||
const spillResult = distributeSpillover(machines, Qd);
|
||||
|
||||
// Spillover fills the small pump first, slope-weight distributes by curve shape
|
||||
const slopeDiff = Math.abs(slopeResult.distribution['small'] - spillResult.distribution['small']);
|
||||
const percentDiff = (slopeDiff / Qd) * 100;
|
||||
|
||||
assert.ok(
|
||||
percentDiff > 1,
|
||||
`Strategies should produce different distributions. ` +
|
||||
`Slope small=${slopeResult.distribution['small'].toFixed(2)}, ` +
|
||||
`Spill small=${spillResult.distribution['small'].toFixed(2)} (${percentDiff.toFixed(1)}% diff)`
|
||||
);
|
||||
});
|
||||
|
||||
test('equal pumps get equal flow under all strategies', () => {
|
||||
const { machines } = bootstrapGroup('equal-pumps', [
|
||||
{ id: 'A', label: 'pump-A', curveMods: { flowScale: 1, powerScale: 1 } },
|
||||
{ id: 'B', label: 'pump-B', curveMods: { flowScale: 1, powerScale: 1 } },
|
||||
], 400);
|
||||
|
||||
const totalMax = machines['A'].predictFlow.currentFxyYMax + machines['B'].predictFlow.currentFxyYMax;
|
||||
const Qd = totalMax * 0.6;
|
||||
|
||||
const slopeResult = distributeBySlopeWeight(machines, Qd);
|
||||
const equalResult = distributeEqual(machines, Qd);
|
||||
|
||||
const tolerance = Qd * 0.01;
|
||||
|
||||
assert.ok(
|
||||
Math.abs(slopeResult.distribution['A'] - slopeResult.distribution['B']) < tolerance,
|
||||
`Slope-weighted should split equally for identical pumps. A=${slopeResult.distribution['A'].toFixed(2)}, B=${slopeResult.distribution['B'].toFixed(2)}`
|
||||
);
|
||||
assert.ok(
|
||||
Math.abs(equalResult.distribution['A'] - equalResult.distribution['B']) < tolerance,
|
||||
`Equal should split equally. A=${equalResult.distribution['A'].toFixed(2)}, B=${equalResult.distribution['B'].toFixed(2)}`
|
||||
);
|
||||
|
||||
// Power should be identical too
|
||||
assert.ok(
|
||||
Math.abs(slopeResult.totalPower - equalResult.totalPower) < 1,
|
||||
`Equal pumps should produce same total power under any strategy`
|
||||
);
|
||||
});
|
||||
|
||||
test('full MGC optimalControl uses ≤ power than priorityControl for mixed pumps', async () => {
|
||||
const { mg, machines } = bootstrapGroup('mgc-full', [
|
||||
{ id: 'eff', label: 'efficient', curveMods: { flowScale: 1.2, powerScale: 0.7, flowTilt: 0.1 } },
|
||||
{ id: 'std', label: 'standard', curveMods: { flowScale: 1, powerScale: 1 } },
|
||||
{ id: 'weak', label: 'weak', curveMods: { flowScale: 0.8, powerScale: 1.3, flowTilt: -0.08 } },
|
||||
], 400);
|
||||
|
||||
for (const m of Object.values(machines)) {
|
||||
await m.handleInput('parent', 'execSequence', 'startup');
|
||||
}
|
||||
|
||||
// Run optimalControl
|
||||
mg.setMode('optimalcontrol');
|
||||
mg.setScaling('normalized');
|
||||
await mg.handleInput('parent', 50, Infinity);
|
||||
const optPower = mg.measurements.type('power').variant('predicted').position('atequipment').getCurrentValue() || 0;
|
||||
const optFlow = mg.measurements.type('flow').variant('predicted').position('atequipment').getCurrentValue() || 0;
|
||||
|
||||
// Reset machines
|
||||
for (const m of Object.values(machines)) {
|
||||
await m.handleInput('parent', 'execSequence', 'shutdown');
|
||||
await m.handleInput('parent', 'execSequence', 'startup');
|
||||
}
|
||||
|
||||
// Run priorityControl
|
||||
mg.setMode('prioritycontrol');
|
||||
await mg.handleInput('parent', 50, Infinity, ['eff', 'std', 'weak']);
|
||||
const prioPower = mg.measurements.type('power').variant('predicted').position('atequipment').getCurrentValue() || 0;
|
||||
const prioFlow = mg.measurements.type('flow').variant('predicted').position('atequipment').getCurrentValue() || 0;
|
||||
|
||||
assert.ok(optFlow > 0, `Optimal should deliver flow, got ${optFlow}`);
|
||||
assert.ok(prioFlow > 0, `Priority should deliver flow, got ${prioFlow}`);
|
||||
|
||||
// Compare efficiency (flow per unit power)
|
||||
const optEff = optPower > 0 ? optFlow / optPower : 0;
|
||||
const prioEff = prioPower > 0 ? prioFlow / prioPower : 0;
|
||||
|
||||
assert.ok(
|
||||
optEff >= prioEff * 0.95,
|
||||
`Optimal efficiency should be ≥ priority (within 5% tolerance). ` +
|
||||
`Opt: ${optFlow.toFixed(1)}/${optPower.toFixed(1)}=${optEff.toFixed(6)} | ` +
|
||||
`Prio: ${prioFlow.toFixed(1)}/${prioPower.toFixed(1)}=${prioEff.toFixed(6)}`
|
||||
);
|
||||
});
|
||||
Reference in New Issue
Block a user