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Non-destructive testing (NDT) techniques are crucial in making informed decisions about reconstructing or repairing building structures. The SonReb method, a combination of the rebound hammer (RH) and the ultrasonic pulse velocity (UPV) tests, is widely used for this purpose. To evaluate the compressive strength, C S , of the concrete under investigation, the ultrasonic pulse velocity V p and the rebound index R must be mapped to the compressive strength C S using a suitable conversion model, the identification of which requires supplementing the NDT measurements with destructive-type measurements (DT) on a relatively large number of concrete cores. An approach notably indicated in all cases where the minimization of the number of cores is essential is to employ a pre-existing conversion model, i.e., a model derived from previous studies conducted in the literature, which must be appropriately calibrated. In this paper, we investigate the performance of Gaussian process regression (GPR) in calibrating the pre-existing SonReb conversion models, exploiting their ability to handle nonlinearity and uncertainties. The numerical results obtained using experimental data collected from the literature show that GPR calibration is very effective, outperforming, in most cases, the standard multiplicative and additive techniques used to calibrate the SonReb models. [ABSTRACT FROM AUTHOR]

Abstract The evaluation of compressive strength in existing concrete buildings poses an engineering challenge, stemming from the development of structural sizing techniques. In this context, the evolution of non-destructive testing equipment and methodologies has allowed for a deeper analysis of the properties of the concrete under study and a reduction in the number of core extraction tests, which are more invasive techniques. Among the various approaches to strength estimation, the emergence of combined methods like SONREB (ultrasonic pulse velocity and rebound number) has stood out due to the comprehensive nature of the properties considered. However, the scarcity of real-world case study data and the challenges of in-situ evaluation hinder the consolidation and subsequent dissemination of this method, especially in Brazil. Thus, the present case study in a 95-year-old building allows the assessment of the effectiveness of different methods in estimating the compressive strength of the tested elements and the overall structure. The obtained results highlight the importance of calibrating the models to the reality of the analyzed structure and considering the effects of carbonation. Furthermore, the analysis of these results reveals the need to evolve the method in order to universalize it, given the low performance of the tested models. Despite this, it is noteworthy that the estimated overall average strength of the building is very close to the actual value, with an absolute error of approximately 2 MPa and a relative error of 8.5%.