Abstract
Evidence demonstrates that tackling indoor overheating is a key priority within the context of climate change adaptation, particularly for residential buildings, whose occupants are more likely to be highly exposed and vulnerable to it. The overarching aim of the research is to provide guidance for building designers on how to minimise the overheating risk of new residential buildings in the UK, to ensure these can be capable of maintaining thermal comfort in a changing climate. The first part of the research involved using two case studies to explore different aspects of the problem. A climate change adaptation study explored and assessed measures for future-proofing an extra-care scheme in the north of England, highlighting the importance of early-stage analysis and client’s engagement through effective communication. A post-occupancy study on a new social housing development helped to gain an understanding of the role of building occupants in perceiving and acting upon overheating, and emphasised discrepancies between design predictions and actual in-use performance. In the second part of the research, the development a Rapid Overheating ASSessment Tool is presented, seeking to encourage practitioners to appropriately consider thermal comfort in a changing climate, by providing rapid feedback on the overheating risk associated with the early-stage design decisions. The focus is on flats in multi-storey buildings located in London. An overheating risk database was populated with the results of a large number of parametric dynamic thermal simulations, which included iterative variations of design aspects corresponding to known over-heating risk factors. Statistical meta-models were developed by means of alternative regression techniques, allowing to quantify the relative importance of each risk factor and make ‘good-enough’ predictions with input available at the early-design stages. Finally, the work to develop two types of user interface is presented, with the goal of allowing relevant and meaningful information to be extracted from the engine of the tool by its prospective users.