2026-05-15T14:02:01Z https://api.figshare.com/v2/oai

oai:figshare.com:article/29314244 2025-08-05T10:38:46Z category_24952 portal_549 item_type_18 month_year_08_2025

10.5522/04/29314244.v1 https://figshare.com/articles/report/Estimating_the_effect_of_retrofitting_with_Deconstruct_/29314244 https://ndownloader.figshare.com/files/56735303 Medina Vazquez, Gustavo Gustavo Medina Vazquez Thevapalan, Anushiya Anushiya Thevapalan Patel, Nium Nium Patel Building science, technologies and systems retrofit buildings assessment in-use 2025-08-05 2025-08-05 Report 2025 University College London This study employs a machine learning model to estimate the heat transfer coefficient (HTC) of a sample of dwellings in two periods, before and after retrofitting measures took place as part of the Greens Home Grant (GHG). The aim is to determine whether these measures had a statistically significant effect on reducing the HTC of the dwellings, that is, increasing their thermal efficiency. University College London (UCL) has subcontracted EDF R&D UK to undertake this study using their solution, Deconstruct+, which can estimate HTC values remotely based on a dwelling’s energy consumption and weather data.

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