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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Faramarzi, Asaad
University of Birmingham
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (5/5 displayed)
- 2021Effect of transverse and longitudinal reinforcement ratios on the behaviour of RC T-beams shear-strengthened with embedded FRP barscitations
- 2019Effect of existing steel-to-embedded FRP shear reinforcement ratio on the behaviour of reinforced concrete T-beams
- 2015Predicting the probability of failure of cementitious sewer pipes using stochastic finite element methodcitations
- 2014Advanced numerical and analytical methods for assessing concrete sewers and their remaining service life
- 2014An evolutionary approach to modelling concrete degradation due to sulphuric acid attackcitations
Places of action
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article
An evolutionary approach to modelling concrete degradation due to sulphuric acid attack
Abstract
Concrete corrosion due to sulphuric acid attack is known to be one of the main contributory factors for degradation of concrete sewer pipes. This article proposes to use a novel data mining technique, namely, evolutionary polynomial regression (EPR), to predict degradation of concrete subject to sulphuric acid attack. A comprehensive dataset from literature is collected to train and develop an EPR model for this purpose. The results show that the EPR model can successfully predict mass loss of concrete specimens exposed to sulphuric acid. Parametric studies show that the proposed model is capable of representing the degree to which individual contributing parameters can affect the degradation of concrete. The developed EPR model is compared with a model based on artificial neural network (ANN) and the advantageous of the EPR approach over ANN is highlighted. In addition, based on the developed EPR model and using an optimisation technique, the optimum concrete mixture to provide maximum resistance against sulphuric acid attack has been identified.