In this study, some NDTs (Ultrasonic Pulse Velocity UPV and Rebound Hammer) and uniaxial compressive test on microcores (UCSm) as a moderately destructive test, were investigated as tools for assessing the uniaxial compressive strength (UCS) of a soft limestone. Correlations between UCS and results of each above-mentioned tests were determined by a univariable regression analysis. Artificial Neural Network and the Multiple Regression Analyses were considered to search correlations between UCS and combined results of the non-invasive tests. An iterative cross-validation procedure was implemented to validate the predictive performances of the models. It was found that combining UPV and UCSm results gives the best reliability in the indirect estimation of UCS, with a notably reduced predictive error.
Combining non-invasive techniques for reliable prediction of soft stone strength in historic masonries
Vasanelli Emilia;Colangiuli Donato;Calia Angela;
2017
Abstract
In this study, some NDTs (Ultrasonic Pulse Velocity UPV and Rebound Hammer) and uniaxial compressive test on microcores (UCSm) as a moderately destructive test, were investigated as tools for assessing the uniaxial compressive strength (UCS) of a soft limestone. Correlations between UCS and results of each above-mentioned tests were determined by a univariable regression analysis. Artificial Neural Network and the Multiple Regression Analyses were considered to search correlations between UCS and combined results of the non-invasive tests. An iterative cross-validation procedure was implemented to validate the predictive performances of the models. It was found that combining UPV and UCSm results gives the best reliability in the indirect estimation of UCS, with a notably reduced predictive error.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.