Abstract
The article presents the hybrid metaheuristic-neural assessment of the pull-off adhesion in existing multi-layer cement composites using artificial neural networks (ANNs) and the imperialist competitive algorithm (ICA). The ICA is a metaheuristic algorithm inspired by the human political-social evolution. This method is based solely on the use of ANNs and two non-destructive testing (NDT) methods: the impact-echo method (I-E) and the impulse response method (IR). In this research, the ICA has been used to optimize the weights of the ANN. The combined ICA-ANN model has been compared to the genetic algorithm (GA) and particle swarm optimization (PSO) to evaluate its accuracy. The results showed that the ICA-ANN model outperforms other techniques when testing datasets in terms of both effectiveness and efficiency. As presented in the validation stage, it is possible to reliably map the adhesion level on a tested surface without local damage to the latter.
Highlights
Layered cement composites, recently an issue attracting numerous researchers [1,2,3,4], usually consist of an overlay placed on an existing concrete substrate
After applying the Chauvenet criterion of the elimination of questionable results and reducing the database to 239 sets of results, the resulting variables were randomly divided into artificial neural networks (ANNs) learning, testing, and experimental verification data
In order to include all the parameters in a numerical range and make the data dimensionless, the contributing input and output parameters should be normalized prior to the training phase according to Equation (1): xN = (x − MinX)/(MaxX − MinX) × 2 - 1 (1)
Summary
Recently an issue attracting numerous researchers [1,2,3,4], usually consist of an overlay placed on an existing concrete substrate. It is always necessary to ensure an appropriate bond between the overlay and existing concrete substrate. The measure of this bond is the value of the pull-off adhesion (f b ), obtained using the pull-off method [5]. It is not possible to individually use the above-mentioned NDT methods to make a full, reliable assessment of the value of f b [11,12,13]. In such a Coatings 2017, 7, 49; doi:10.3390/coatings7040049 www.mdpi.com/journal/coatings
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