physics

Performance gap

Performance gap is a physics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Performance gap rather than just read about it. In short: A performance gap is a disparity that is found between the energy use predicted and carbon emissions in the design stage of buildings and the energy use of those buildings in operation. Research in the UK suggests that actual carbon emissions from new homes can be 2.5 times the design estimates, on average.

Key takeaways

Performance gap belongs to physics; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Performance gap to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Performance gap from memory before moving on to harder problems.

Reference excerpt

A performance gap is a disparity that is found between the energy use predicted and carbon emissions in the design stage of buildings and the energy use of those buildings in operation. Research in the UK suggests that actual carbon emissions from new homes can be 2.5 times the design estimates, on average. For non-domestic buildings, the gap is even higher - actual carbon emissions as much as 3.8 times the design estimates, on average. There are established tools for reducing the performance gap, by reviewing project objectives, outline and detailed design drawings, design calculations, implementation of designs on site, and post-occupancy evaluation. NEF's Assured Performance Process (APP) is one such tool, which is being used extensively on different sites that form part of East Hampshire's Whitehill and Bordon new town development, one of the largest regeneration projects anywhere in the UK, with high ambitions for both environmental performance and health.

Classification of factors that contribute to the performance gap The performance gap is produced mainly due to uncertainties. Uncertainties are found in any “real-world” system, and buildings are no exception. As early as 1978, Gero and Dudnik wrote a paper presenting a methodology to solve the problem of designing subsystems (HVAC) subjected to uncertain demands. After that, other authors have shown an interest in the uncertainties that are present in building design; Ramallo-González classified uncertainties in building design/construction in three different groups:

Environmental. Uncertainty in weather prediction under changing climate; and uncertain weather data information due to the use of synthetic weather data files: (1) use of synthetic years that do not represent a real year, and (2) use of a synthetic year that has not been generated from recorded data in the exact location of the project but in the closest weather station. Workmanship and quality of building elements. Differences between the design and the real building: Conductivity of thermal bridges, conductivity of insulation, value of infiltration or U-Values of walls and windows. There may be optimism bias by designers, where expectations about what is possible on site are unrealistic, and/or buildability fails to get adequate attention during design. Behavioural. All other parameters linked to human behaviour i.e. door and window opening, heating regimes, use of appliances, occupancy patterns or cooking habits.

Type 1: Environmental uncertainties The type 1 from this grouping, have been divided here into two main groups: one concerning the uncertainty due to climate change; and the other concerning uncertainties due to the use of synthetic weather data files. Concerning the uncertainties due to climate change: buildings have long life spans, for example, in England and Wales, around 40% of the office blocks existing in 2004 were built before 1940 (30% if considered by floor area). and, 38.9% of English dwellings in 2007 were built before 1944. This long life span makes buildings likely to operate with climates that might change due to global warming. De Wilde and Coley showed how important is to design buildings that take into consideration climate change and that are able to perform well in future weathers. Concerning the uncertainties due to the use of synthetic weather data files: Wang et al. showed the impact that uncertainties in weather data (among others) may cause in energy demand calculations. The deviation in calculated energy use due to variability in the weather data were found to be different in different locations from a range of (-0.5% – 3%) in San Francisco to a range of (-4% to 6%) in Washington D.C. The ranges were calculated using TMY as the reference. These deviations on the demand were smaller than the ones due to operational parameters. For those, the ranges were (-29% – 79%) for San Francisco and (-28% – 57%) for Washington D.C. The operation parameters were those linked with occupants’ behaviour. The conclusion of this paper is that occupants will have a larger impact in energy calculations than the variability between synthetically generated weather data files. The spatial resolution of weather data files was the concern covered by Eames et al. Eames showed how a low spatial resolution of weather data files can be the cause of disparities of up to 40% in the heating demand.

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Performance gap

Start with the simplest possible case. Write down what Performance gap claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In physics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Performance gap before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Performance gap ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Performance gap

In research: Performance gap appears in physics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Performance gap in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Performance gap is common in secondary-school and first-year university syllabi. It links to neighbouring topics Building engineering, Energy consumption, so understanding it makes those chapters shorter.
In everyday life: Look for Performance gap outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Performance gap in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Performance gap means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Performance gap out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Performance gap in simple terms?

Why does Performance gap matter?

Because it connects several physics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Performance gap?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Performance gap.