Modeling of strength of high-performance concrete using artificial neural networks

Several studies independently have shown that concrete strength development is determined not only by the water-to-cement ratio, but that it also is influenced by the content of other concrete ingredients. High-performance concrete is a highly complex material, which makes modeling its behavior a ve...

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Bibliographic Details
Published in:Cement and concrete research 1998-12, Vol.28 (12), p.1797-1808
Main Author: Yeh, I.-C.
Format: Article
Language:English
Subjects:
Applied sciences
Buildings. Public works
Computation methods. Tables. Charts
Concretes. Mortars. Grouts
Exact sciences and technology
Materials
Properties and performance tests of mortar and hardened concrete
Structural analysis. Stresses
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Summary:Several studies independently have shown that concrete strength development is determined not only by the water-to-cement ratio, but that it also is influenced by the content of other concrete ingredients. High-performance concrete is a highly complex material, which makes modeling its behavior a very difficult task. This paper is aimed at demonstrating the possibilities of adapting artificial neural networks (ANN) to predict the compressive strength of high-performance concrete. A set of trial batches of HPC was produced in the laboratory and demonstrated satisfactory experimental results. This study led to the following conclusions: 1) A strength model based on ANN is more accurate than a model based on regression analysis; and 2) It is convenient and easy to use ANN models for numerical experiments to review the effects of the proportions of each variable on the concrete mix.
ISSN:0008-8846
1873-3948
DOI:10.1016/S0008-8846(98)00165-3