|Title||Identification of Test Regions and Choice of Conversion Models|
|Publication Type||Articolo su Rivista peer-reviewed|
|Year of Publication||2021|
|Authors||Balayssac, J.-P., Vasanelli E., Luprano Vincenza A. M., Kenai S., Romão X., Chiauzzi L., Masi A., and Sbartai Z.M.|
|Journal||RILEM State-of-the-Art Reports|
The main objective of test region (TR) identification is to define an efficient conversion model. The first part of the chapter aims a difficult question, the identification of test regions (TR) because each structure is specific and so it is impossible to give a unique methodology. Here, three different possibilities are proposed. The first one is based on synthetic data obtained on a continuous structure for which TR are identified by means of k-means clustering method. The second approach concerns a real building for which TR are determined by means of two different statistical methods based on the analysis of confidence interval and ANOVA. On three real case studies, the second part of the chapter compares the performances of two scenarios, either the consideration of several TRs and so a conversion model on each one, or the consideration of a unique TR with only one model. The efficiency of each scenario is quantified by the error on the estimation of both mean strength and local strength. © 2021, RILEM.
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