2022
DOI: 10.1016/j.enbuild.2021.111566
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Modelling platform for schools (MPS): The development of an automated One-By-One framework for the generation of dynamic thermal simulation models of schools

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Cited by 9 publications
(11 citation statements)
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“…More generally, however, the integration of detailed building simulation will enable a better understanding of the improvement potential of the stock. To this end, work is currently ongoing to apply the updated schools database into a fully disaggregate, one-by-one digital twin of the school stock (Schwartz et al 2022). This model, which includes detailed data on building form (footprints and heights) enables dynamic thermal simulation to be undertaken for each individual school block, allowing potential retrofit measures to be assessed with a consideration of issues such as temporal factors, changes to occupancy behaviour and climate change.…”
Section: Discussionmentioning
confidence: 99%
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“…More generally, however, the integration of detailed building simulation will enable a better understanding of the improvement potential of the stock. To this end, work is currently ongoing to apply the updated schools database into a fully disaggregate, one-by-one digital twin of the school stock (Schwartz et al 2022). This model, which includes detailed data on building form (footprints and heights) enables dynamic thermal simulation to be undertaken for each individual school block, allowing potential retrofit measures to be assessed with a consideration of issues such as temporal factors, changes to occupancy behaviour and climate change.…”
Section: Discussionmentioning
confidence: 99%
“…This paper builds on a significant body of work undertaken to date to explore energy performance in the school stock (Hong et al 2022;Schwartz et al 2021Schwartz et al , 2022Godoy-Shimizu et al 2021). It uses a highly detailed database to examine the potential for reducing emissions, with a focus on primary and secondary schools in England, which account for approximately 85% of schools in England by count (DfE 2017).…”
Section: (Dfe 2022a)mentioning
confidence: 99%
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“…However, additional uncertainties could be introduced into the models because the model inputs are often a combination of data sources with different types and formats, and data quality are diverse among the databases. Additionally, merging data from different sources will also lead to mismatch issue, A simple validation method is visual inspection of a sample of models to identify their quality, and the low-quality models are calibrated manually, 94 while as a more sophisticated approach to validating and calibrating models against actual buildings is recommended. 106…”
Section: Building Stock Modelling Approaches For Policy Decision-makingmentioning
confidence: 99%