Guidelines describe the general process of in-situ compressive strength assessment. This process is divided into three main steps, data collection (using nondestructive testing and destructive testing), model identification and strength assessment. Three estimation quality levels (EQL) are defined depending on the targeted accuracy of strength assessment, based on three parameters, mean value of strength and standard deviation of strength on a test region and local value of strength. All the necessary definitions (test location, test reading, test region, test result, ...) are given and the different stages of data collection, i.e. planning, NDT methods, cores (dimensions, conservation, location, testing, etc) are described. The identification of the conversion model is detailed and a specific attention is paid to the assessment of test result precision (TRP). For the identification of the model parameters, two options are considered either the development of a specific model or the calibration of a prior model. A specific option is also proposed, namely the bi-objective approach. Finally, the quantification of the errors of model fitting and strength prediction is described. The global methodology is synthetized in a flowchart.
In-Situ Strength Assessment of Concrete: Detailed Guidelines
A V;Vasanelli;
2021
Abstract
Guidelines describe the general process of in-situ compressive strength assessment. This process is divided into three main steps, data collection (using nondestructive testing and destructive testing), model identification and strength assessment. Three estimation quality levels (EQL) are defined depending on the targeted accuracy of strength assessment, based on three parameters, mean value of strength and standard deviation of strength on a test region and local value of strength. All the necessary definitions (test location, test reading, test region, test result, ...) are given and the different stages of data collection, i.e. planning, NDT methods, cores (dimensions, conservation, location, testing, etc) are described. The identification of the conversion model is detailed and a specific attention is paid to the assessment of test result precision (TRP). For the identification of the model parameters, two options are considered either the development of a specific model or the calibration of a prior model. A specific option is also proposed, namely the bi-objective approach. Finally, the quantification of the errors of model fitting and strength prediction is described. The global methodology is synthetized in a flowchart.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.