Preliminary communication

https://doi.org/10.14256/JCE.2438.2018

Prediction of concrete compressive strength through artificial neural networks

Pablo Neira
Leonardo Bennun
Mauricio Pradena
Jaime Gomez

Abstract

Concrete properties, including its compressive strength, are in general highly nonlinear functions of its components. Concrete mix design methods are basically simulations that require costly and time consuming adjustments in laboratory. A useful support tool based on artificial neural networks, using a multilayer perceptron network, is proposed in this paper as a means to predict compressive strength of concrete mixes. The developed models are useful for reducing the quantity of laboratory tests required for concrete mix design adjustments.

Keywords

concrete mix design; compressive strength; laboratory tests; artificial neural networks

Hrčak ID:

242386

URI

https://hrcak.srce.hr/242386

Publication date:

10.8.2020.

Article data in other languages: croatian

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