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Chen, L, Yuan, B and Wang, X (2024) Simulation analysis of the constraints on the green retrofit of existing buildings and strategies for its promotion: a hybrid method based on ISM and SD. Building Research & Information, 52(05), 515–32.

Gallego Sánchez-Torija, J, García López, C and Fernández Nieto, M A (2024) Energy, water and economic savings by changing habits of users in twelve schools in Spain. Building Research & Information, 52(05), 596–609.

Kurvinen, A, Huovari, J, Lahtinen, M, Sen, T and Saari, A (2024) A dynamic model for estimating the long-term need for repairs and renovations in residential buildings. Building Research & Information, 52(05), 533–50.

Moradi, S, Hirvonen, J and Sormunen, P (2024) A qualitative and life cycle-based study of the energy performance gap in building construction: Perspectives of Finnish project professionals and property maintenance experts. Building Research & Information, 52(05), 564–76.

Sajjad, M, Jayasinghe, C and Perera, P (2024) Damage assessment automation for single storey detached masonry houses: a probabilistic approach. Building Research & Information, 52(05), 551–63.

  • Type: Journal Article
  • Keywords: Building performance; condition assessment; maintenance; building defects;
  • ISBN/ISSN: 0961-3218
  • URL: https://doi.org/10.1080/09613218.2023.2284983
  • Abstract:
    Assessing the existing condition of aging masonry houses are of high interest as the cost of retrofitting and repairing becomes significantly higher. Conventional condition assessment tools and methods for single storey detached masonry houses (SSDMH) are time-consuming, subjective, tedious, and sparse. This study aims to formulate a novel framework for assessing the condition of those houses by proposing a user-friendly, effective, and impartial model, for existing structures considering cracks in the masonry walls and the age of the house. This study adopted the bayesian belief network (BBN) method since the existing data on building assessment are subjective and consider multiple parameters. The application of the proposed model was formulated using wall cracks observed in a sample of thirty SSDMH. The Expectation Maximization (EM) algorithm was used to compute the conditional probabilities from the data set. The model was tested on ten houses for which the results were positive and validated with the Receiver Operating Characteristic (ROC) curve. However, the scope of the model is limited to SSDMH. Further development of this model may benefit the Surveyors, Engineers, and Architects to make informed decisions quickly by placing the structure at the correct severity level to decide on the renovation strategies.

Wingrove, K, Heffernan, E and Daly, D (2024) Increased home energy use: unintended outcomes of energy efficiency focused policy. Building Research & Information, 52(05), 577–95.

Winkler, C, Perez Vico, E and Widén, K (2024) Challenges to business ecosystem alignment when implementing solar photovoltaic systems in the Swedish built environment. Building Research & Information, 52(05), 497–514.