Models for the Prediction of Service Life of Buildings – A Review
1*Omoare A. 2Arum C. and 3Olanitori L. M.
1,2,3Department of Civil and Environmental Engineering, Federal University of Technology, Akure, Ondo State, Nigeria
DOI: 10.36108/laujoces/2202.90.0160
Abstract
Service life models are a part of critical anchors to achieving sustainable development goals, offering sustainable solutions for infrastructural advancement. In spite of their indisputable usefulness and acceptability in the scientific circle, their real-world deployment is still grossly inadequate. The overall objective of this review is to assess the existing service life prediction models with highlights of their highs and lows. The models identified include deterministic, stochastic and engineering. Areas requiring more intensive research identified include the development of service life database, simplification of the complicated mathematical formats of service life models into simpler more practically-manageable formats, comparative study of expert opinions and computer integrated knowledge, as well as the place of structural elements in service life determination compared to non-structural elements. The study finally notes the areas that will give the required shape and speed of development to service life modeling of reinforced concrete buildings which include the provision of service life database, practical application of service life model for user-guidance, the superiority of service life data from non-destructive testing results to commercial data from manufacturers, placement of experts’ opinions at par with computer integrated knowledge system, and using complete building for service life determination rather than building elements. This review will serve as information base on various service life models which should assist early researchers in the subject area and speed up the application from the rudimentary to more advanced stages within the foreseeable future.
Keywords: Service Life Model, Database, Durability, Building Component, Sustainable Development