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Probabilistic climate projections with dynamic building simulation: Predicting overheating in dwellings
Highlights ► A method for using probabilistic climate projections with dynamic building simulation is presented through the use of a derived emulator. ► The application of this model to a domestic building, for an overheating analysis, is carried out. ► The effect of adaptations on this building, to reduce the overheating risk, is estimated by using the proposed regression tool. ► The use of this regression tool in industry for real building projects is discussed, with acceptable overheating risk outputs explored.
Abstract This study, as part of the Low Carbon Futures project, proposes a methodology to incorporate probabilistic climate projections into dynamic building simulation analyses of overheating in dwellings. Using a large climate projection database, suitable building software and statistical techniques (focussing on principal component analysis), output is presented that demonstrates the future overheating risk of a building in the form of a probability curve. Such output could be used by building engineers and architects to design a building to an acceptable future overheating risk level, i.e. providing evidence that the building, with specific adaptation measures to prevent overheating, should achieve thermal comfort for the majority of future climate projections. This methodology is overviewed and the use of the algorithm proposed in relation to existing building practices. While the methodology is being applied to a range of buildings and scenarios, this study concentrates on night-time overheating in UK dwellings with simple and achievable adaptation measures investigated.
Probabilistic climate projections with dynamic building simulation: Predicting overheating in dwellings
Highlights ► A method for using probabilistic climate projections with dynamic building simulation is presented through the use of a derived emulator. ► The application of this model to a domestic building, for an overheating analysis, is carried out. ► The effect of adaptations on this building, to reduce the overheating risk, is estimated by using the proposed regression tool. ► The use of this regression tool in industry for real building projects is discussed, with acceptable overheating risk outputs explored.
Abstract This study, as part of the Low Carbon Futures project, proposes a methodology to incorporate probabilistic climate projections into dynamic building simulation analyses of overheating in dwellings. Using a large climate projection database, suitable building software and statistical techniques (focussing on principal component analysis), output is presented that demonstrates the future overheating risk of a building in the form of a probability curve. Such output could be used by building engineers and architects to design a building to an acceptable future overheating risk level, i.e. providing evidence that the building, with specific adaptation measures to prevent overheating, should achieve thermal comfort for the majority of future climate projections. This methodology is overviewed and the use of the algorithm proposed in relation to existing building practices. While the methodology is being applied to a range of buildings and scenarios, this study concentrates on night-time overheating in UK dwellings with simple and achievable adaptation measures investigated.
Probabilistic climate projections with dynamic building simulation: Predicting overheating in dwellings
Jenkins, D.P. (author) / Patidar, S. (author) / Banfill, P.F.G. (author) / Gibson, G.J. (author)
Energy and Buildings ; 43 ; 1723-1731
2011-03-17
9 pages
Article (Journal)
Electronic Resource
English
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