2011
DOI: 10.1016/j.enbuild.2011.03.016
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Probabilistic climate projections with dynamic building simulation: Predicting overheating in dwellings

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Cited by 62 publications
(47 citation statements)
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“…In each case the software used enabled the window opening position to be triggered by internal temperatures of 23.9°C. This aligned to the work of Jenkins, Patidar, Banfill and Gibson (2011) who suggested that 23.9°C was the temperature at which occupants are likely to begin to adapt.…”
Section: Building Performance Simulationmentioning
confidence: 54%
“…In each case the software used enabled the window opening position to be triggered by internal temperatures of 23.9°C. This aligned to the work of Jenkins, Patidar, Banfill and Gibson (2011) who suggested that 23.9°C was the temperature at which occupants are likely to begin to adapt.…”
Section: Building Performance Simulationmentioning
confidence: 54%
“…8), the warmer homes were in the London, the South East, the East, the East Midlands, and the West Midlands, whereas the cooler homes were to be in the North East, North West and Yorkshire. 9 Chi-squared tests (Table 3), indicated that there were significantly fewer bedrooms in the North West with more than 1% of occupied hours over 26 C than bedrooms in other regions (4% cf. 21% for all the dwellings, p < 0.05) and there were significantly more living rooms in the East of England with more than 1% of occupied hours over 28 C than living rooms in other regions (13% cf.…”
Section: Assessment Using Static Criteriamentioning
confidence: 99%
“…Jenkins et al [15], on the same track, developed a surrogate model by means of a novel integration of dynamic energy investigations and probabilistic climate forecasts. The regression model is very reliable and is able to predict the hourly internal temperatures with an error of about 5%, compared to the outcomes of a transient commercial simulation software (ESP-r), for different investigated climates in the United Kingdom.…”
Section: Indoor Min Rmmentioning
confidence: 99%