Data mining techniques and ultrasonic pulse velocity tests for the assessment of damage levels in concrete exposed to high temperatures and subject to compression

摘要

A Data Mining (DM) process was applied, aiming to develop a numerical tool forthe assessment of the level of damage (measured from a strain parameter) ofconcrete columns subject to high temperature exposure (or fire). The database usedwas obtained from an experimental program carried out with measurements ofUltrasonic Pulse Velocity (UPV) through concrete specimens of various steelreinforcement arrangements after exposure to different levels of high temperature(reference, 250 ºC, 500 ºC and 750 ºC). The UPV tests were performed during theexecution of the compression tests. Different DM techniques were tested and asensitivity analysis was made. The obtained results show that DM models,particularly the k-nearest neighbours model, allow an acceptable prediction of theaxial strain of concrete elements exposed to high temperatures using UPV data.