Computational Engineering / Computation for low-carbon structural design
Does the ranking survive?
The factors are uncertain. Test whether the conclusion depends on them — because that is the only result worth acting on.
Lesson review: expert verification remains open
This lesson has received a full-context editorial review and a check of its technical explanations. Selected arithmetic has been checked separately. This is not independent engineering sign-off.
Checks needed for project use
- A computational engineering reviewer must check algorithms, convergence claims, statistical assumptions and numerical examples beyond the cases explicitly recorded.
- Verify quantity rates and factor set against current project-appropriate EPDs and whole-life methodology. Review biogenic carbon, exclusions, joint uncertainty, foundation effects and service integration before any project use.
These are educational models and exercises. Check their assumptions before using the results. The full technical content and every diagram have not yet been independently verified.
Concrete and steel calculations retain their stated first-generation Eurocode teaching basis. Use the standards and amendments specified for your project; do not mix generations without an appropriate design basis.
Read the lesson register and outstanding review notesWhy this matters
A carbon comparison depends on quantities, factor sources and the assessment boundary. This lesson tests the effect of changing individual factors. It also distinguishes what that test shows from the verification still needed for a project decision.
By the end of this lesson you should be able to
- Perturb each factor and test whether the ranking changes
- Distinguish a robust ranking from a fragile one
- Say what to do in each case
- State the provenance requirement for any figure leaving the course
Test the ranking
Starting from the base comparison, increase and decrease each material factor by a stated amount, one at a time, then compare the rankings. Record which changes affect the preferred option.
In this teaching example, the CLT hybrid remains first under the ten single-factor trials at ±30%. That establishes insensitivity to those trials only. It does not verify the base factors, quantity estimates, system boundaries or the range chosen. Changes in several factors together may produce a different result.
Choose a defensible range
The ±30% range here is an illustrative exercise. It is not a standard uncertainty allowance for all materials. A project study needs ranges supported by applicable product data, procurement scenarios and assessment guidance.
Report conditional conclusions
If a ranking changes, identify the factor and threshold responsible. Obtain suitable verified data and consider plausible combinations of changes. A stable ranking in a limited trial is useful evidence for further investigation, but it is insufficient on its own to recommend a real structural scheme.
Keep the provenance with the result
Record the factor set and date, assessment scope, quantity basis, exclusions and sensitivity method. The course factors remain illustrative and require verification. Project assessments also need a consistent treatment of life-cycle stages, biogenic carbon and uncertainty under the applicable methodology.
Worked example
Testing the ranking against its own uncertainty
Given
- The four-scheme comparison at a 9 m grid: CLT 447, band beam 666, steel 782, flat slab 866 tCO₂e
- Five material factors: steel, reinforcement, concrete, CLT and glulam
- Each perturbed by ±30 %, one at a time, and the comparison re-run
Find
Whether the winner changes in the specified single-factor trials
Practice
The lowest-carbon scheme is 447 tCO₂e and the next is 666. Holding the next scheme unchanged, by what percentage must the lowest total rise to reach a tie?
Practice
Five material factors are each perturbed up and down, one at a time. How many re-rankings does that require?
Check yourself
A carbon ranking changes winner when the steel factor is perturbed by 20 %. What should the report say?
Check yourself
A scheme ranking survives ten trials that vary each carbon factor by ±30%, one at a time. What does that justify?
Summary
- Perturb each factor, re-rank, and count the changes of winner
- The winner is unchanged in the ten ±30% single-factor trials in this example
- A stable sensitivity result does not verify the factors or justify a project recommendation by itself
- State the threshold when a ranking is conditional — it tells procurement what to secure
- One-at-a-time testing does not cover combinations, and should say so
- Factor set, scope, quantities, exclusions and robustness all travel with the number