Abstract

The work presents the results of an experimental campaign carried out on concrete elements in order to investigate the potential of using artificial neural networks (ANNs) to estimate the compressive strength based on relevant parameters, such as the water–cement ratio, aggregate–cement ratio, age of testing, and percentage cement/metakaolin ratios (5% and 10%). We prepared 162 cylindrical concrete specimens with dimensions of 10 cm in diameter and 20 cm in height and 27 prismatic specimens with cross sections measuring 25 and 50 cm in length, with 9 different concrete mixture proportions. A longitudinal transducer with a frequency of 54 kHz was used to measure the ultrasonic velocities. An ANN model was developed, different ANN configurations were tested and compared to identify the best ANN model. Using this model, it was possible to assess the contribution of each input variable to the compressive strength of the tested concretes. The results indicate an excellent performance of the ANN model developed to predict compressive strength from the input parameters studied, with an average error less than 5%. Together, the water–cement ratio and the percentage of metakaolin were shown to be the most influential factors for the compressive strength value predicted by the developed ANN model.

Highlights

  • In the last few years, several factors have contributed to the emergence of faster tests that enable the evaluation of concrete properties, namely, the compressive strength test

  • It should be mentioned that (1) the compressive strength test increases the use of high-strength concretes in civil engineering construction; (2) the test requires a relatively long period of time; (3) the insecurity related to the conservation conditions of the specimens in the laboratory do not satisfactorily represent the reality of the work, causing significant deviations in the concrete strength results; and (4) the destructive character of the extraction of specimens poses challenges to assessing the performance of the structure in service [1,2,3]

  • The tests were performed at different ages, and the concrete ones were made with some previously defined parameters: the maximum size of the coarse aggregate, the amount of cement replaced by metakaolin and the water/cement ratio

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Summary

Introduction

In the last few years, several factors have contributed to the emergence of faster tests that enable the evaluation of concrete properties, namely, the compressive strength test. It should be mentioned that (1) the compressive strength test increases the use of high-strength concretes in civil engineering construction; (2) the test requires a relatively long period of time; (3) the insecurity related to the conservation conditions of the specimens in the laboratory do not satisfactorily represent the reality of the work, causing significant deviations in the concrete strength results; and (4) the destructive character of the extraction of specimens poses challenges to assessing the performance of the structure in service [1,2,3]. Ultrasound is a truly nondestructive test, as its technique involves the propagation of ultrasonic waves that do not result in any damage to the element being tested. The pressure wave (p-wave) pulse velocity has been popularly applied to concrete structures for its easy generation and measurement

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