Infrastructure Engineering · Lesson 23 of 24 · 25 minutes
Build an integrated commissioning evidence loop
A completed component test answers a component question. Integrated continuity requires an initial state, expected sequence, instruments, acceptance criteria, stop conditions and recovery boundary that span the service chain. Compare two clocks, then examine the measurement boundary behind an apparently precise efficiency number.
Run this lesson interactivelyLearning objectives
- Build observable cause-and-effect and acceptance records.
- Compare restoration time with electrical and thermal intervals.
- Compute interval energy and first-order PUE standard uncertainty.
Editorial derivation
Write an observable test before a verdict
Record the initiating event, propagation path, affected service, detection, mitigation and required evidence. Utility loss can affect generator start, recharge inhibition, cooling controls, load restoration and network observability. A relay injection does not prove every primary CT connection; a load-bank test does not establish facility transfer; a battery test does not prove every trip contact. Numerical risk scores can organize discussion but do not become physical probabilities simply by multiplying ordinal rankings.
Illustrative assumption
Find the tighter clock
The manuscript’s illustrative sequence uses 2 s detection, 12 s start/acceleration, 3 s qualification and 8 s staged restoration: 25 s total. Against 600 s electrical storage and a 37.5 s thermal interval, the nominal thermal margin is 12.5 s. The timing values and lumped thermal limit are assumptions, not measured facility evidence. Record voltage, frequency, breaker state, load, DC voltage, flow, temperatures and service response at adequate timing resolution.
Editorial derivation
Keep precision separate from the boundary
At constant 20 MW IT and 27 MW facility demand over 8,760 h, the annualized energies are 175,200 and 236,520 MWh. For PUE 1.35 and independent relative standard uncertainties of 1% each, first-order standard uncertainty is about 0.0191. It is not an absolute bound or declared confidence interval. A meter outside the correct boundary is a model error, not merely an instrument-precision problem. Lower PUE also does not alone establish lower operational emissions.
Predict → run → explain
- Read the declared boundary and units. Predict the selected result before calculating.
- Run the starting case and inspect the ledger, assumptions and model limits.
- Apply the challenge, run again, and explain the difference. Export only the last completed inputs and results.
Restoration s = sum of declared stage s; thermal/electrical margin s = corresponding interval s − restoration s; annual IT MWh = IT MW × hours; facility MWh = IT MWh × assumed PUE; standard PUE uncertainty = PUE × sqrt(uFacility² + uIT²), assuming independence.
Declared starting inputs
{
"stageSeconds": [
2,
12,
3,
8
],
"electricalSeconds": 600,
"thermalSeconds": 37.5,
"itMW": 20,
"hours": 8760,
"pue": 1.35,
"facilityRelativeUncertainty": 0.01,
"itRelativeUncertainty": 0.01
}| Quantity | Value | Unit |
|---|---|---|
| restoreSeconds | 25 | s |
| thermalMarginSeconds | 12.5 | s |
| electricalMarginSeconds | 575 | s |
| annualItMWh | 175200 | MWh/year |
| annualFacilityMWh | 236520.00000000003 | MWh/year |
| pueStandardUncertainty | 0.01909188309203679 | ratio |
Challenge
Which teaching constraint fails when staged restoration takes 23 s?
{
"stageSeconds": [
2,
12,
3,
23
]
}Total restoration becomes 40 s: a −2.5 s thermal margin even though electrical margin remains 560 s.
| Quantity | Value | Unit |
|---|---|---|
| restoreSeconds | 40 | s |
| thermalMarginSeconds | -2.5 | s |
| electricalMarginSeconds | 560 | s |
| annualItMWh | 175200 | MWh/year |
| annualFacilityMWh | 236520.00000000003 | MWh/year |
| pueStandardUncertainty | 0.01909188309203679 | ratio |
A synchronized commissioning evidence wall — static equivalent
- Reveal requirement → state → event → expected response.
- Run a labelled restoration timeline alongside electrical and thermal limits.
- Attach instrument records to each acceptance criterion rather than using decoration as evidence.
- Route discrepancies back through correction and retest before baseline acceptance.
Cause-and-effect matrix, timed event ledger and acceptance table with unresolved fields.
Change one stage duration; inspect event timestamps and compare required versus observed values using clearly synthetic records.
Narrative steps are not physical seconds. Essential states and quantities remain available without animation.
Assessment and answer criteria
11.1 · Find annual IT energy for a constant 6 MW over 8,760 h.
Read answer and marking criterion
52,560 MWh.
Criterion: Preserve power versus energy units.
Source: DCIE-R1 Appendix A, PDF pp.59-61
11.2 · At PUE 1.4, find standard uncertainty for independent relative uncertainties of 0.5% and 1%.
Read answer and marking criterion
About 0.01565.
Criterion: Use root-sum-square for the stated independent first-order model.
Source: DCIE-R1 Appendix A, PDF pp.59-61
11.3 · Why does buying a more precise meter not fix the wrong measurement boundary?
Read answer and marking criterion
The omitted or wrongly included load remains a measurement-system/model error.
Criterion: Separate precision from completeness of the boundary.
Source: DCIE-R1 Appendix A, PDF pp.59-61
Source and model boundaries
Data Centre Infrastructure Engineering, reference manuscript revision 1 (DCIE-R1), 11 October 2026, chapter 11, PDF pp.50–53. PDF page 1 includes the cover. manuscript-derived; not independent source verification.
- Synthetic teaching test records, not energization procedures or real commissioning authorization.
- The default uncertainty model assumes independence; covariance must be explicit in any extension.
Original educational adaptation. The private PDF and missing archive are not public downloads. Source statement, Editorial derivation, Illustrative assumption and Unresolved remain distinct.
Result schema: infrastructure-screen-1; content 2.0.0; model 1.0.0. Raw inputs, outputs, units, assumptions, source locators and canonical hashes. No supported in-browser Python verification protocol exists for this result family.