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3 Commits

Author SHA1 Message Date
znetsixe
f4cb329597 updates 2025-11-25 15:10:36 +01:00
znetsixe
b49f0c3ed2 attempt to fix flow distribution 2025-11-22 21:09:38 +01:00
znetsixe
edcffade75 Added edge case for when 1 pump cant handle the scope 2025-11-20 22:28:49 +01:00
2 changed files with 551 additions and 275 deletions

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@@ -1,288 +1,345 @@
// ...existing code... 'use strict';
const MachineGroup = require('./specificClass.js');
const MachineGroup = require('./specificClass');
const Machine = require('../../rotatingMachine/src/specificClass'); const Machine = require('../../rotatingMachine/src/specificClass');
const Measurement = require('../../measurement/src/specificClass'); const Measurement = require('../../measurement/src/specificClass');
const specs = require('../../generalFunctions/datasets/assetData/curves/hidrostal-H05K-S03R.json'); const baseCurve = require('../../generalFunctions/datasets/assetData/curves/hidrostal-H05K-S03R.json');
const stateConfig = { time:{starting:0,warmingup:0,stopping:0,coolingdown:0}, movement:{speed:1000,mode:"staticspeed"} }; const CONTROL_MODES = ['optimalcontrol', 'prioritycontrol', 'prioritypercentagecontrol'];
const ptConfig = { const MODE_LABELS = {
general:{ logging:{enabled:false,logLevel:"warn"}, name:"testpt", id:"pt-1", unit:"mbar" }, optimalcontrol: 'OPT',
functionality:{ softwareType:"measurement", role:"sensor" }, prioritycontrol: 'PRIO',
asset:{ category:"sensor", type:"pressure", model:"testmodel", supplier:"vega", unit:"mbar" }, prioritypercentagecontrol: 'PERC'
scaling:{ absMin:0, absMax:4000 }
}; };
const testSuite = []; const stateConfig = {
const efficiencyComparisons = []; time: { starting: 0, warmingup: 0, stopping: 0, coolingdown: 0, emergencystop: 0 },
movement: { speed: 1200, mode: 'staticspeed', maxSpeed: 1800 }
};
function logPass(name, details="") { const ptConfig = {
const entry = { name, status:"PASS", details }; general: { logging: { enabled: false, logLevel: 'error' }, name: 'synthetic-pt', id: 'pt-1', unit: 'mbar' },
testSuite.push(entry); functionality: {
console.log(`${name}${details ? `${details}` : ""}`); softwareType: 'measurement',
} role: 'sensor',
function logFail(name, error) { positionVsParent: 'downstream'
const entry = { name, status:"FAIL", details:error?.message || error }; },
testSuite.push(entry); asset: { category: 'sensor', type: 'pressure', model: 'synthetic-pt', supplier: 'lab', unit: 'mbar' },
console.error(`${name}${entry.details}`); scaling: { absMin: 0, absMax: 4000 }
} };
function approxEqual(actual, expected, tolerancePct=1) {
const tolerance = (expected * tolerancePct) / 100;
return actual >= expected - tolerance && actual <= expected + tolerance;
}
async function sleep(ms){ return new Promise(resolve => setTimeout(resolve, ms)); }
function createMachineConfig(id,label) { const scenarios = [
{
name: 'balanced_pair',
description: 'Two identical pumps validate equal-machine behaviour.',
machines: [
{ id: 'eq-1', label: 'equal-A', curveMods: { flowScale: 1, powerScale: 1 } },
{ id: 'eq-2', label: 'equal-B', curveMods: { flowScale: 1, powerScale: 1 } }
],
pressures: [900, 1300, 1700],
flowTargetsPercent: [0.1, 0.4, 0.7, 1],
flowMatchTolerance: 5,
priorityList: ['eq-1', 'eq-2']
},
{
name: 'mixed_trio',
description: 'High / mid / low efficiency pumps to stress unequal-machine behaviour.',
machines: [
{ id: 'hi', label: 'high-eff', curveMods: { flowScale: 1.25, powerScale: 0.82, flowTilt: 0.1, powerTilt: -0.05 } },
{ id: 'mid', label: 'mid-eff', curveMods: { flowScale: 1, powerScale: 1 } },
{ id: 'low', label: 'low-eff', curveMods: { flowScale: 0.7, powerScale: 1.35, flowTilt: -0.08, powerTilt: 0.15 } }
],
pressures: [800, 1200, 1600, 2000],
flowTargetsPercent: [0.1, 0.35, 0.7, 1],
flowMatchTolerance: 8,
priorityList: ['hi', 'mid', 'low']
}
];
function createGroupConfig(name) {
return { return {
general:{ logging:{enabled:false,logLevel:"warn"}, name:label, id, unit:"m3/h" }, general: { logging: { enabled: false, logLevel: 'error' }, name: `machinegroup-${name}` },
functionality:{ softwareType:"machine", role:"rotationaldevicecontroller" }, functionality: { softwareType: 'machinegroup', role: 'groupcontroller' },
asset:{ category:"pump", type:"centrifugal", model:"hidrostal-h05k-s03r", supplier:"hydrostal", machineCurve:specs }, scaling: { current: 'normalized' },
mode:{ mode: { current: 'optimalcontrol' }
current:"auto", };
allowedActions:{ }
auto:["execSequence","execMovement","flowMovement","statusCheck"],
virtualControl:["execMovement","statusCheck"], function sleep(ms) {
fysicalControl:["statusCheck"] return new Promise(resolve => setTimeout(resolve, ms));
}
async function setPressure(pt, value) {
const retries = 6;
for (let attempt = 0; attempt < retries; attempt += 1) {
try {
pt.calculateInput(value);
return;
} catch (error) {
const message = error?.message || String(error);
if (!message.toLowerCase().includes('coolprop is still warming up')) {
throw error;
}
await sleep(50);
}
}
throw new Error(`Unable to update pressure to ${value} mbar; CoolProp did not initialise in time.`);
}
function deepClone(obj) {
return JSON.parse(JSON.stringify(obj));
}
function distortSeries(series = [], scale = 1, tilt = 0) {
if (!Array.isArray(series) || series.length === 0) {
return series;
}
const lastIndex = series.length - 1;
return series.map((value, index) => {
const gradient = lastIndex === 0 ? 0 : index / lastIndex - 0.5;
const distorted = value * scale * (1 + tilt * gradient);
return Number(Math.max(distorted, 0).toFixed(6));
});
}
function createSyntheticCurve(mods = {}) {
const { flowScale = 1, powerScale = 1, flowTilt = 0, powerTilt = 0 } = mods;
const curve = deepClone(baseCurve);
if (curve.nq) {
Object.values(curve.nq).forEach(set => {
set.y = distortSeries(set.y, flowScale, flowTilt);
});
}
if (curve.np) {
Object.values(curve.np).forEach(set => {
set.y = distortSeries(set.y, powerScale, powerTilt);
});
}
return curve;
}
function createMachineConfig(id, label) {
return {
general: { logging: { enabled: false, logLevel: 'error' }, name: label, id, unit: 'm3/h' },
functionality: { softwareType: 'machine', role: 'rotationaldevicecontroller' },
asset: { category: 'pump', type: 'centrifugal', model: 'hidrostal-h05k-s03r', supplier: 'hidrostal', machineCurve: baseCurve },
mode: {
current: 'auto',
allowedActions: {
auto: ['execsequence', 'execmovement', 'flowmovement', 'statuscheck'],
virtualControl: ['execmovement', 'statuscheck'],
fysicalControl: ['statuscheck']
}, },
allowedSources:{ allowedSources: {
auto:["parent","GUI"], auto: ['parent', 'GUI'],
virtualControl:["GUI"], virtualControl: ['GUI'],
fysicalControl:["fysical"] fysicalControl: ['fysical']
} }
}, },
sequences:{ sequences: {
startup:["starting","warmingup","operational"], startup: ['starting', 'warmingup', 'operational'],
shutdown:["stopping","coolingdown","idle"], shutdown: ['stopping', 'coolingdown', 'idle'],
emergencystop:["emergencystop","off"], emergencystop: ['emergencystop', 'off'],
boot:["idle","starting","warmingup","operational"] boot: ['idle', 'starting', 'warmingup', 'operational']
} }
}; };
} }
async function bootstrapGroup() { async function bootstrapScenarioMachines(scenario) {
const groupCfg = { const mg = new MachineGroup(createGroupConfig(scenario.name));
general:{ logging:{enabled:false,logLevel:"warn"}, name:"testmachinegroup" },
functionality:{ softwareType:"machinegroup", role:"groupcontroller" },
scaling:{ current:"normalized" },
mode:{ current:"optimalcontrol" }
};
const mg = new MachineGroup(groupCfg);
const pt = new Measurement(ptConfig); const pt = new Measurement(ptConfig);
for (let idx=1; idx<=2; idx++){ for (const machineDef of scenario.machines) {
const machine = new Machine(createMachineConfig(String(idx),`machine-${idx}`), stateConfig); const machine = new Machine(createMachineConfig(machineDef.id, machineDef.label), stateConfig);
mg.childRegistrationUtils.registerChild(machine,"downstream"); if (machineDef.curveMods) {
machine.childRegistrationUtils.registerChild(pt,"downstream"); machine.updateCurve(createSyntheticCurve(machineDef.curveMods));
}
mg.childRegistrationUtils.registerChild(machine, 'downstream');
machine.childRegistrationUtils.registerChild(pt, 'downstream');
} }
pt.calculateInput(1000);
await sleep(10); await sleep(25);
return { mg, pt }; return { mg, pt };
} }
function captureState(mg,label){ function captureTotals(mg) {
return { const flow = mg.measurements.type('flow').variant('predicted').position('atequipment').getCurrentValue() || 0;
label, const power = mg.measurements.type('power').variant('predicted').position('atequipment').getCurrentValue() || 0;
machines: Object.entries(mg.machines).map(([id,machine]) => ({ const efficiency = mg.measurements.type('efficiency').variant('predicted').position('atequipment').getCurrentValue() || 0;
id, return { flow, power, efficiency };
state: machine.state.getCurrentState(),
position: machine.state.getCurrentPosition(),
predictedFlow: machine.measurements.type("flow").variant("predicted").position("downstream").getCurrentValue() || 0,
predictedPower: machine.measurements.type("power").variant("predicted").position("upstream").getCurrentValue() || 0
})),
totals: {
flow: mg.measurements.type("flow").variant("predicted").position("downstream").getCurrentValue() || 0,
power: mg.measurements.type("power").variant("predicted").position("upstream").getCurrentValue() || 0,
efficiency: mg.measurements.type("efficiency").variant("predicted").position("downstream").getCurrentValue() || 0
}
};
} }
async function testNormalizedScaling(mg,pt){ function computeAbsoluteTargets(dynamicTotals, percentages) {
const label = "Normalized scaling tracks expected flow"; const { flow } = dynamicTotals;
try{ const min = Number.isFinite(flow.min) ? flow.min : 0;
mg.setScaling("normalized"); const max = Number.isFinite(flow.max) ? flow.max : 0;
const dynamic = mg.calcDynamicTotals(); const span = Math.max(max - min, 1);
const checkpoints = [0,10,25,50,75,100]; return percentages.map(percent => {
for (const demand of checkpoints){ const pct = Math.max(0, Math.min(1, percent));
await mg.handleInput("parent", demand); return min + pct * span;
pt.calculateInput(1400); });
await sleep(20);
const totals = mg.measurements.type("flow").variant("predicted").position("downstream").getCurrentValue() || 0;
const expected = dynamic.flow.min + (demand/100)*(dynamic.flow.max - dynamic.flow.min);
if(!approxEqual(totals, expected, 2)){
throw new Error(`Flow ${totals.toFixed(2)} outside expectation ${expected.toFixed(2)} @ ${demand}%`);
}
}
logPass(label);
}catch(err){ logFail(label, err); }
} }
async function testAbsoluteScaling(mg,pt){ async function driveModeToFlow({ mg, pt, mode, pressure, targetFlow, priorityOrder }) {
const label = "Absolute scaling accepts direct flow targets"; await setPressure(pt, pressure);
try{ await sleep(15);
mg.setScaling("absolute");
mg.setMode("optimalcontrol");
const absMin = mg.dynamicTotals.flow.min;
const absMax = mg.dynamicTotals.flow.max;
const demandPoints = [absMin, absMin+20, (absMin+absMax)/2, absMax-20];
for(const setpoint of demandPoints){ mg.setMode(mode);
await mg.handleInput("parent", setpoint); mg.setScaling('normalized'); // required for prioritypercentagecontrol, works for others too
pt.calculateInput(1400);
await sleep(20); const dynamic = mg.calcDynamicTotals();
const flow = mg.measurements.type("flow").variant("predicted").position("downstream").getCurrentValue() || 0; const span = Math.max(dynamic.flow.max - dynamic.flow.min, 1);
if(!approxEqual(flow, setpoint, 2)){ const normalizedTarget = ((targetFlow - dynamic.flow.min) / span) * 100;
throw new Error(`Flow ${flow.toFixed(2)} != demand ${setpoint.toFixed(2)}`);
} let low = 0;
let high = 100;
let demand = Math.max(0, Math.min(100, normalizedTarget || 0));
let best = { demand, flow: 0, power: 0, efficiency: 0, error: Infinity };
for (let attempt = 0; attempt < 4; attempt += 1) {
await mg.handleInput('parent', demand, Infinity, priorityOrder);
await sleep(30);
const totals = captureTotals(mg);
const error = Math.abs(totals.flow - targetFlow);
if (error < best.error) {
best = {
demand,
flow: totals.flow,
power: totals.power,
efficiency: totals.efficiency,
error
};
} }
logPass(label);
}catch(err){ logFail(label, err); } if (totals.flow > targetFlow) {
high = demand;
} else {
low = demand;
}
demand = (low + high) / 2;
}
return best;
} }
async function testModeTransitions(mg,pt){ function formatEfficiencyRows(rows) {
const label = "Mode transitions keep machines responsive"; return rows.map(row => {
try{ const optimal = row.modes.optimalcontrol;
const modes = ["optimalcontrol","prioritycontrol","prioritypercentagecontrol"]; const priority = row.modes.prioritycontrol;
mg.setScaling("normalized"); const percentage = row.modes.prioritypercentagecontrol;
for(const mode of modes){ return {
mg.setMode(mode); pressure: row.pressure,
await mg.handleInput("parent", 50); targetFlow: Number(row.targetFlow.toFixed(1)),
pt.calculateInput(1300); [`${MODE_LABELS.optimalcontrol}_Flow`]: Number(optimal.flow.toFixed(1)),
await sleep(20); [`${MODE_LABELS.optimalcontrol}_Eff`]: Number(optimal.efficiency.toFixed(3)),
const snapshot = captureState(mg, mode); [`${MODE_LABELS.prioritycontrol}_Flow`]: Number(priority.flow.toFixed(1)),
const active = snapshot.machines.filter(m => m.state !== "idle"); [`${MODE_LABELS.prioritycontrol}_Eff`]: Number(priority.efficiency.toFixed(3)),
if(active.length === 0){ [`Δ${MODE_LABELS.prioritycontrol}-OPT_Eff`]: Number(
throw new Error(`No active machines after switching to ${mode}`); (priority.efficiency - optimal.efficiency).toFixed(3)
} ),
} [`${MODE_LABELS.prioritypercentagecontrol}_Flow`]: Number(percentage.flow.toFixed(1)),
logPass(label); [`${MODE_LABELS.prioritypercentagecontrol}_Eff`]: Number(percentage.efficiency.toFixed(3)),
}catch(err){ logFail(label, err); } [`Δ${MODE_LABELS.prioritypercentagecontrol}-OPT_Eff`]: Number(
(percentage.efficiency - optimal.efficiency).toFixed(3)
)
};
});
} }
async function testRampBehaviour(mg,pt){ function summarizeEfficiency(rows) {
const label = "Ramp up/down keeps monotonic flow"; const map = new Map();
try{ rows.forEach(row => {
mg.setMode("optimalcontrol"); CONTROL_MODES.forEach(mode => {
mg.setScaling("normalized"); const key = `${row.scenario}-${mode}`;
const upDemands = [0,20,40,60,80,100]; if (!map.has(key)) {
let lastFlow = 0; map.set(key, {
for(const demand of upDemands){ scenario: row.scenario,
await mg.handleInput("parent", demand); mode,
pt.calculateInput(1500); samples: 0,
await sleep(15); avgFlowDiff: 0,
const flow = mg.measurements.type("flow").variant("predicted").position("downstream").getCurrentValue() || 0; avgEfficiency: 0
if(flow < lastFlow - 1){
throw new Error(`Flow decreased during ramp up: ${flow.toFixed(2)} < ${lastFlow.toFixed(2)}`);
}
lastFlow = flow;
}
const downDemands = [100,80,60,40,20,0];
lastFlow = Infinity;
for(const demand of downDemands){
await mg.handleInput("parent", demand);
pt.calculateInput(1200);
await sleep(15);
const flow = mg.measurements.type("flow").variant("predicted").position("downstream").getCurrentValue() || 0;
if(flow > lastFlow + 1){
throw new Error(`Flow increased during ramp down: ${flow.toFixed(2)} > ${lastFlow.toFixed(2)}`);
}
lastFlow = flow;
}
logPass(label);
}catch(err){ logFail(label, err); }
}
async function testPressureAdaptation(mg,pt){
const label = "Pressure changes update predictions";
try{
mg.setMode("optimalcontrol");
mg.setScaling("normalized");
const pressures = [800,1200,1600,2000];
let previousFlow = null;
for(const p of pressures){
pt.calculateInput(p);
await mg.handleInput("parent", 50);
await sleep(20);
const flow = mg.measurements.type("flow").variant("predicted").position("downstream").getCurrentValue() || 0;
if(previousFlow !== null && Math.abs(flow - previousFlow) < 0.5){
throw new Error(`Flow did not react to pressure shift (${previousFlow.toFixed(2)} -> ${flow.toFixed(2)})`);
}
previousFlow = flow;
}
logPass(label);
}catch(err){ logFail(label, err); }
}
async function comparePriorityVsOptimal(mg, pt){
const label = "Priority vs Optimal efficiency comparison";
try{
mg.setScaling("normalized");
const pressures = [800, 1100, 1400, 1700];
const demands = [...Array(21)].map((_, idx) => idx * 5);
for (const pressure of pressures) {
pt.calculateInput(pressure);
await sleep(15);
for (const demand of demands) {
mg.setMode("optimalcontrol");
await mg.handleInput("parent", demand);
pt.calculateInput(pressure);
await sleep(20);
const optimalTotals = captureState(mg, `optimal-${pressure}-${demand}`).totals;
mg.setMode("prioritycontrol");
await mg.handleInput("parent", demand);
pt.calculateInput(pressure);
await sleep(20);
const priorityTotals = captureState(mg, `priority-${pressure}-${demand}`).totals;
efficiencyComparisons.push({
pressure,
demandPercent: demand,
optimalFlow: Number(optimalTotals.flow.toFixed(3)),
optimalPower: Number(optimalTotals.power.toFixed(3)),
optimalEfficiency: Number((optimalTotals.efficiency || 0).toFixed(4)),
priorityFlow: Number(priorityTotals.flow.toFixed(3)),
priorityPower: Number(priorityTotals.power.toFixed(3)),
priorityEfficiency: Number((priorityTotals.efficiency || 0).toFixed(4)),
efficiencyDelta: Number(((priorityTotals.efficiency || 0) - (optimalTotals.efficiency || 0)).toFixed(4)),
powerDelta: Number((priorityTotals.power - optimalTotals.power).toFixed(3))
}); });
} }
} const bucket = map.get(key);
const stats = row.modes[mode];
logPass(label, "efficiencyComparisons array populated"); bucket.samples += 1;
} catch (err) { bucket.avgFlowDiff += Math.abs(stats.flow - row.targetFlow);
logFail(label, err); bucket.avgEfficiency += stats.efficiency || 0;
} });
});
return Array.from(map.values()).map(item => ({
scenario: item.scenario,
mode: item.mode,
samples: item.samples,
avgFlowDiff: Number((item.avgFlowDiff / item.samples).toFixed(2)),
avgEfficiency: Number((item.avgEfficiency / item.samples).toFixed(3))
}));
} }
async function evaluateScenario(scenario) {
console.log(`\nRunning scenario "${scenario.name}": ${scenario.description}`);
const { mg, pt } = await bootstrapScenarioMachines(scenario);
const priorityOrder =
scenario.priorityList && scenario.priorityList.length
? scenario.priorityList
: scenario.machines.map(machine => machine.id);
async function run(){ const rows = [];
console.log("🚀 Starting machine-group integration tests...");
const { mg, pt } = await bootstrapGroup();
await testNormalizedScaling(mg, pt); for (const pressure of scenario.pressures) {
await testAbsoluteScaling(mg, pt); await setPressure(pt, pressure);
await testModeTransitions(mg, pt); await sleep(20);
await testRampBehaviour(mg, pt);
await testPressureAdaptation(mg, pt);
await comparePriorityVsOptimal(mg, pt);
console.log("\n📋 TEST SUMMARY"); const dynamicTotals = mg.calcDynamicTotals();
console.table(testSuite); const targets = computeAbsoluteTargets(dynamicTotals, scenario.flowTargetsPercent || [0, 0.5, 1]);
console.log("\n📊 efficiencyComparisons:");
console.dir(efficiencyComparisons, { depth:null }); for (let idx = 0; idx < targets.length; idx += 1) {
console.log("✅ All tests completed."); const targetFlow = targets[idx];
const row = {
scenario: scenario.name,
pressure,
targetFlow,
modes: {}
};
for (const mode of CONTROL_MODES) {
const stats = await driveModeToFlow({
mg,
pt,
mode,
pressure,
targetFlow,
priorityOrder
});
row.modes[mode] = stats;
}
rows.push(row);
}
}
console.log(`Efficiency comparison table for scenario "${scenario.name}":`);
console.table(formatEfficiencyRows(rows));
return { rows };
}
async function run() {
const combinedRows = [];
for (const scenario of scenarios) {
const { rows } = await evaluateScenario(scenario);
combinedRows.push(...rows);
}
console.log('\nEfficiency summary by scenario and control mode:');
console.table(summarizeEfficiency(combinedRows));
console.log('\nAll machine group control tests completed successfully.');
} }
run().catch(err => { run().catch(err => {
console.error("💥 Test harness crashed:", err); console.error('Machine group control test harness crashed:', err);
process.exitCode = 1;
}); });
// ...existing code...
// Run all tests
run();

View File

@@ -333,42 +333,71 @@ class MachineGroup {
calcBestCombination(combinations, Qd) { calcBestCombination(combinations, Qd) {
let bestCombination = null; let bestCombination = null;
//keep track of totals
let bestPower = Infinity; let bestPower = Infinity;
let bestFlow = 0; let bestFlow = 0;
let bestCog = 0; let bestCog = 0;
combinations.forEach(combination => {
let flowDistribution = []; // Stores the flow distribution for the best combination combinations.forEach(combination => {
let flowDistribution = [];
let totalCoG = 0; let totalCoG = 0;
let totalPower = 0; let totalPower = 0;
let totalFlow = 0;
// Calculate the total CoG for the current combination // Sum normalized CoG for the combination
combination.forEach(machineId => { totalCoG += ( Math.round(this.machines[machineId].NCog * 100 ) /100 ) ; });
// Calculate the total power for the current combination
combination.forEach(machineId => { combination.forEach(machineId => {
let flow = 0; totalCoG += Math.round((this.machines[machineId].NCog || 0) * 100) / 100;
});
// Prevent division by zero
if (totalCoG === 0) { // Initial CoG-based distribution
// Distribute flow equally among all pumps combination.forEach(machineId => {
flow = Qd / combination.length; let flow = 0;
} else { if (totalCoG === 0) {
// Normal CoG-based distribution flow = Qd / combination.length;
flow = (this.machines[machineId].NCog / totalCoG) * Qd ; } else {
this.logger.debug(`Machine Normalized CoG-based distribution ${machineId} flow: ${flow}`); flow = ((this.machines[machineId].NCog || 0) / totalCoG) * Qd;
} this.logger.debug(`Machine Normalized CoG-based distribution ${machineId} flow: ${flow}`);
totalFlow += flow; }
totalPower += this.machines[machineId].inputFlowCalcPower(flow);
flowDistribution.push({ machineId: machineId,flow: flow }); flowDistribution.push({ machineId, flow });
});
// Clamp to min/max and spill leftover once
const clamped = flowDistribution.map(entry => {
const machine = this.machines[entry.machineId];
const min = machine.predictFlow.currentFxyYMin;
const max = machine.predictFlow.currentFxyYMax;
const clampedFlow = Math.min(max, Math.max(min, entry.flow));
return { ...entry, flow: clampedFlow, min, max, desired: entry.flow };
});
let remainder = Qd - clamped.reduce((sum, entry) => sum + entry.flow, 0);
if (Math.abs(remainder) > 1e-6) {
const adjustable = clamped.filter(entry =>
remainder > 0 ? entry.flow < entry.max : entry.flow > entry.min
);
const weightSum = adjustable.reduce((sum, entry) => sum + entry.desired, 0) || adjustable.length;
adjustable.forEach(entry => {
const weight = entry.desired / weightSum || 1 / adjustable.length;
const delta = remainder * weight;
const next = remainder > 0
? Math.min(entry.max, entry.flow + delta)
: Math.max(entry.min, entry.flow + delta);
remainder -= (next - entry.flow);
entry.flow = next;
});
}
flowDistribution = clamped;
let totalFlow = 0;
flowDistribution.forEach(({ machineId, flow }) => {
totalFlow += flow;
totalPower += this.machines[machineId].inputFlowCalcPower(flow);
}); });
// Update the best combination if the current one is better
if (totalPower < bestPower) { if (totalPower < bestPower) {
this.logger.debug(`New best combination found: ${totalPower} < ${bestPower}`); this.logger.debug(`New best combination found: ${totalPower} < ${bestPower}`);
this.logger.debug(`combination ${JSON.stringify(flowDistribution)}`); this.logger.debug(`combination ${JSON.stringify(flowDistribution)}`);
@@ -382,6 +411,177 @@ class MachineGroup {
return { bestCombination, bestPower, bestFlow, bestCog }; return { bestCombination, bestPower, bestFlow, bestCog };
} }
// Estimate the local dP/dQ slopes around the BEP for the provided machine.
estimateSlopesAtBEP(machine, Q_BEP, delta = 1.0) {
const fallback = {
slopeLeft: 0,
slopeRight: 0,
alpha: 1,
Q_BEP: Q_BEP || 0,
P_BEP: 0
};
const minFlow = machine.predictFlow.currentFxyYMin;
const maxFlow = machine.predictFlow.currentFxyYMax;
const span = Math.max(0, maxFlow - minFlow);
const normalizedCog = Math.max(0, Math.min(1, machine.NCog || 0));
const targetBEP = Q_BEP ?? (minFlow + span * normalizedCog);
const clampFlow = (flow) => Math.min(maxFlow, Math.max(minFlow, flow)); // ensure within bounds using small helper function
const center = clampFlow(targetBEP);
const deltaSafe = Math.max(delta, 0.01);
const leftFlow = clampFlow(center - deltaSafe);
const rightFlow = clampFlow(center + deltaSafe);
const powerAt = (flow) => machine.inputFlowCalcPower(flow); // helper to get power at a given flow
const P_center = powerAt(center);
const P_left = powerAt(leftFlow);
const P_right = powerAt(rightFlow);
const slopeLeft = (P_center - P_left) / Math.max(1e-6, center - leftFlow);
const slopeRight = (P_right - P_center) / Math.max(1e-6, rightFlow - center);
const alpha = Math.max(1e-6, (Math.abs(slopeLeft) + Math.abs(slopeRight)) / 2);
return {
slopeLeft,
slopeRight,
alpha,
Q_BEP: center,
P_BEP: P_center
};
}
//Redistribute remaining demand using slope-based weights so flatter curves attract more flow.
redistributeFlowBySlope(pumpInfos, flowDistribution, delta, directional = true) {
const tolerance = 1e-3; // Small tolerance to avoid infinite loops
let remaining = delta; // Remaining flow to distribute
const entryMap = new Map(flowDistribution.map(entry => [entry.machineId, entry])); // Map for quick access
// Loop until remaining flow is within tolerance
while (Math.abs(remaining) > tolerance) {
const increasing = remaining > 0; // Determine if we are increasing or decreasing flow
// Build candidates with capacity and weight
const candidates = pumpInfos.map(info => {
const entry = entryMap.get(info.id);
if (!entry) { return null; }
const capacity = increasing ? info.maxFlow - entry.flow : entry.flow - info.minFlow; // Calculate available capacity based on direction
if (capacity <= tolerance) { return null; }
const slope = increasing
? (directional ? info.slopes.slopeRight : info.slopes.alpha)
: (directional ? info.slopes.slopeLeft : info.slopes.alpha);
const weight = 1 / Math.max(1e-6, Math.abs(slope) || info.slopes.alpha || 1);
return { entry, capacity, weight };
}).filter(Boolean);
if (!candidates.length) { break; } // No candidates available, exit loop
const weightSum = candidates.reduce((sum, candidate) => sum + candidate.weight * candidate.capacity, 0); // weighted sum of capacities
if (weightSum <= 0) { break; } // Avoid division by zero
let progress = 0;
// Distribute remaining flow among candidates based on their weights and capacities
candidates.forEach(candidate => {
let share = (candidate.weight * candidate.capacity / weightSum) * Math.abs(remaining);
share = Math.min(share, candidate.capacity); // Ensure we don't exceed capacity
if (share <= 0) { return; } // Skip if no share to allocate
if (increasing) {
candidate.entry.flow += share;
} else {
candidate.entry.flow -= share;
}
progress += share; // Track total progress made in this iteration
});
if (progress <= tolerance) { break; }
remaining += increasing ? -progress : progress; // Update remaining flow to distribute
}
}
// BEP-gravitation based combination finder that biases allocation around each pump's BEP.
calcBestCombinationBEPGravitation(combinations, Qd, method = "BEP-Gravitation-Directional") {
let bestCombination = null;
let bestPower = Infinity;
let bestFlow = 0;
let bestCog = 0;
let bestDeviation = Infinity;
const directional = method === "BEP-Gravitation-Directional";
combinations.forEach(combination => {
const pumpInfos = combination.map(machineId => {
const machine = this.machines[machineId];
const minFlow = machine.predictFlow.currentFxyYMin;
const maxFlow = machine.predictFlow.currentFxyYMax;
const span = Math.max(0, maxFlow - minFlow);
const NCog = Math.max(0, Math.min(1, machine.NCog || 0));
const estimatedBEP = minFlow + span * NCog; // Estimated BEP flow based on current curve
const slopes = this.estimateSlopesAtBEP(machine, estimatedBEP);
return {
id: machineId,
machine,
minFlow,
maxFlow,
NCog,
Q_BEP: slopes.Q_BEP,
slopes
};
});
// Skip if no pumps in combination
if (pumpInfos.length === 0) { return; }
// Start at BEP flows
const flowDistribution = pumpInfos.map(info => ({
machineId: info.id,
flow: Math.min(info.maxFlow, Math.max(info.minFlow, info.Q_BEP))
}));
let totalFlow = flowDistribution.reduce((sum, entry) => sum + entry.flow, 0); // Initial total flow
const delta = Qd - totalFlow; // Difference to target demand
if (Math.abs(delta) > 1e-6) {
this.redistributeFlowBySlope(pumpInfos, flowDistribution, delta, directional);
}
let totalPower = 0;
totalFlow = 0;
flowDistribution.forEach(entry => {
const info = pumpInfos.find(info => info.id === entry.machineId);
const flow = Math.min(info.maxFlow, Math.max(info.minFlow, entry.flow));
entry.flow = flow;
totalFlow += flow;
totalPower += info.machine.inputFlowCalcPower(flow);
});
const totalCog = pumpInfos.reduce((sum, info) => sum + info.NCog, 0);
const deviation = pumpInfos.reduce((sum, info) => {
const entry = flowDistribution.find(item => item.machineId === info.id);
const deltaFlow = entry ? (entry.flow - info.Q_BEP) : 0;
return sum + (deltaFlow * deltaFlow) * (info.slopes.alpha || 1);
}, 0);
const shouldUpdate = totalPower < bestPower ||
(totalPower === bestPower && deviation < bestDeviation);
if (shouldUpdate) {
bestCombination = flowDistribution.map(entry => ({ ...entry }));
bestPower = totalPower;
bestFlow = totalFlow;
bestCog = totalCog;
bestDeviation = deviation;
}
});
return {
bestCombination,
bestPower,
bestFlow,
bestCog,
bestDeviation,
method
};
}
// -------- Mode and Input Management -------- // // -------- Mode and Input Management -------- //
isValidActionForMode(action, mode) { isValidActionForMode(action, mode) {
const allowedActionsSet = this.config.mode.allowedActions[mode] || []; const allowedActionsSet = this.config.mode.allowedActions[mode] || [];
@@ -460,7 +660,26 @@ class MachineGroup {
// fetch all valid combinations that meet expectations // fetch all valid combinations that meet expectations
const combinations = this.validPumpCombinations(this.machines, Qd, powerCap); const combinations = this.validPumpCombinations(this.machines, Qd, powerCap);
const bestResult = this.calcBestCombination(combinations, Qd);
if (!combinations || combinations.length === 0) {
this.logger.warn(`Demand: ${Qd.toFixed(2)} -> No valid combination found (empty set).`);
return;
}
// Decide which optimization routine we run. Defaults to BEP-based gravitation with directionality.
const optimizationMethod = this.config.optimization?.method || "BEP-Gravitation-Directional";
let bestResult;
if (optimizationMethod === "NCog") {
bestResult = this.calcBestCombination(combinations, Qd);
} else if (
optimizationMethod === "BEP-Gravitation" ||
optimizationMethod === "BEP-Gravitation-Directional"
) {
bestResult = this.calcBestCombinationBEPGravitation(combinations, Qd, optimizationMethod);
} else {
this.logger.warn(`Unknown optimization method '${optimizationMethod}', falling back to BEP-Gravitation-Directional.`);
bestResult = this.calcBestCombinationBEPGravitation(combinations, Qd, "BEP-Gravitation-Directional");
}
if(bestResult.bestCombination === null){ if(bestResult.bestCombination === null){
this.logger.warn(`Demand: ${Qd.toFixed(2)} -> No valid combination found => not updating control `); this.logger.warn(`Demand: ${Qd.toFixed(2)} -> No valid combination found => not updating control `);
@@ -988,8 +1207,8 @@ class MachineGroup {
} }
module.exports = MachineGroup; module.exports = MachineGroup;
/* /*
const {coolprop} = require('generalFunctions');
const Machine = require('../../rotatingMachine/src/specificClass'); const Machine = require('../../rotatingMachine/src/specificClass');
const Measurement = require('../../measurement/src/specificClass'); const Measurement = require('../../measurement/src/specificClass');
const specs = require('../../generalFunctions/datasets/assetData/curves/hidrostal-H05K-S03R.json'); const specs = require('../../generalFunctions/datasets/assetData/curves/hidrostal-H05K-S03R.json');
@@ -1179,4 +1398,4 @@ async function makeMachines(){
makeMachines(); makeMachines();
//*/ //*/