2013
DOI: 10.1016/j.enpol.2013.01.030
|View full text |Cite
|
Sign up to set email alerts
|

Methods for assessing domestic overheating for future building regulation compliance

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
12
0

Year Published

2015
2015
2022
2022

Publication Types

Select...
5
3
1

Relationship

0
9

Authors

Journals

citations
Cited by 28 publications
(14 citation statements)
references
References 7 publications
0
12
0
Order By: Relevance
“…In addition to a lack of clarity regarding the appropriate metrics used to define overheating there is evidence that the current methods of assessing overheating risk in dwellings may not be reliable (Jenkins, Ingram, Simpson & Patidar, 2013). It has been noted that much of the data used to analyse current overheating risk comes from the past (de Wilde & Coley, 2012) and therefore does not make allowance for the potential impacts of a changing climate.…”
Section: Overheating Assessment Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…In addition to a lack of clarity regarding the appropriate metrics used to define overheating there is evidence that the current methods of assessing overheating risk in dwellings may not be reliable (Jenkins, Ingram, Simpson & Patidar, 2013). It has been noted that much of the data used to analyse current overheating risk comes from the past (de Wilde & Coley, 2012) and therefore does not make allowance for the potential impacts of a changing climate.…”
Section: Overheating Assessment Methodsmentioning
confidence: 99%
“…Coley et al (2012) however, suggest that a more median approach (50 th percentile) with allowance only for 'hard' adaptations to resolve any overheating, as this would allow designers to avoid potentially unnecessary and costly adaptations. Jenkins et al (2013) suggest that both the DSYs, which is intended to test the building for overheating and TRYs, used to represent more normal conditions for energy estimates, be used so that both 'near extreme' and higher probability scenarios can be represented. This in turn allows for at least some of the probabilistic capabilities of UKCP09 to be realised, although as noted by Coley et al (2012) shown to be at high risk of overheating (Mavrogianni et al 2015) and several studies have explored these issues (Dengel & Swainson 2012), detailed exploration of the impact on houses are less prevalent and given the volume of dwellings involved (7.38m) consideration of the potential impacts on these units is merited.…”
Section: Building Performance Simulationmentioning
confidence: 99%
“…A large number of studies have explored the risk of overheating in UK homes using building simulation tools, to examine future climate scenarios and evaluate the potential impact of mitigation strategies, input data, occupant behaviour, building characteristics and adaption strategies (Jenkins et al, 2013;Mavrogianni et al, 2012;Mavrogianni et al, 2014;Peacock et al, 2010;Porritt et al, 2012;Taylor et al, 2014;Vardoulakis et al, 2015;Williams et al, 2013). Whilst building simulation can be very useful, there is a pressing need to identify the prevalence of overheating from live data, to ensure the protection of occupant health and wellbeing, to provide real world evidence and to support the call for concerted action from policy makers and the UK construction industry as a whole.…”
Section: Overheating In Energy Efficient Dwellings-existing Evidencementioning
confidence: 99%
“…If overheating is highlighted as the issue, quantifying this is non-trivial. As discussed elsewhere [11,12], although standardised definitions of overheating do exist (such as the threshold of 1% of occupied hours exceeding 28 °C [13], as used in this paper), the exact nature of overheating is more complicated than this, bringing together issues of adaptive comfort, location, and building services that are used to provide that comfort. Building modellers tend to use the more simplified definitions of overheating that can, at least, be quantified and compared between different cases, though adaptive comfort algorithms can be applied to building simulation [14] in an attempt to account for a more nuanced understanding of thermal comfort.…”
Section: Climate Change and Buildingsmentioning
confidence: 99%