Comparison between service life prediction methods for building rehabilitation: application on a case study

Service life prediction of a structure is imperative to model effective building rehabilitation strategies. Where the factor method presents an uncomplicated and straightforward approach to evaluate the service life, it has several shortcomings due to the subjectivity associated with it, making the results prone to high variability. Another deterministic method is the multiple regression analysis, which is deemed more accurate to predict the service life. Hence, in this study, an approach has attempted to compare the applicability and the variability associated with the two models by instituting them on a case scenario. It has been identified that using the factor model, the estimated service life is lower of the two values obtained, i.e., 25% lesser then the multiple regression models. However, the factor model comes out to be more straightforward, uncomplicated and less time consuming. Multiple Regression analysis, on the other hand, gives an accurate degradation path followed by the structure but does present a more precise estimation of service life, as it is based upon the actual values measured against each of the predictor variable. Nevertheless, it does require a regular assessment of the structure with respect to time, which might seem time consuming but is the correct approach towards maintenance and service life prediction. © 2022, The Author(s), under exclusive licence to Springer Nature Switzerland AG.