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Open AccessArticle

Machine Learning Techniques in Concrete Mix Design

Faculty of Civil and Environmental Engineering, Gdansk University of Technology, Gabriela Narutowicza 11/12, 80-233 Gdansk, Poland
Author to whom correspondence should be addressed.
Materials 2019, 12(8), 1256;
Received: 3 March 2019 / Revised: 4 April 2019 / Accepted: 12 April 2019 / Published: 17 April 2019
(This article belongs to the Special Issue Non-destructive Testing of Materials in Civil Engineering)
Concrete mix design is a complex and multistage process in which we try to find the best composition of ingredients to create good performing concrete. In contemporary literature, as well as in state-of-the-art corporate practice, there are some methods of concrete mix design, from which the most popular are methods derived from The Three Equation Method. One of the most important features of concrete is compressive strength, which determines the concrete class. Predictable compressive strength of concrete is essential for concrete structure utilisation and is the main feature of its safety and durability. Recently, machine learning is gaining significant attention and future predictions for this technology are even more promising. Data mining on large sets of data attracts attention since machine learning algorithms have achieved a level in which they can recognise patterns which are difficult to recognise by human cognitive skills. In our paper, we would like to utilise state-of-the-art achievements in machine learning techniques for concrete mix design. In our research, we prepared an extensive database of concrete recipes with the according destructive laboratory tests, which we used to feed the selected optimal architecture of an artificial neural network. We have translated the architecture of the artificial neural network into a mathematical equation that can be used in practical applications. View Full-Text
Keywords: concrete; concrete mix design; concrete strength prediction; data mining; machine learning concrete; concrete mix design; concrete strength prediction; data mining; machine learning
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Ziolkowski, P.; Niedostatkiewicz, M. Machine Learning Techniques in Concrete Mix Design. Materials 2019, 12, 1256.

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