• Computers and Concrete
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• v.27 no.4
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• pp.319-332
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• 2021

The performance of gene expression programming (GEP) in predicting the compressive strength of bacteria-incorporated geopolymer concrete (GPC) was examined in this study. Ground-granulated blast-furnace slag (GGBS), new bacterial strains, fly ash (FA), silica fume (SF), metakaolin (MK), and manufactured sand were used as ingredients in the concrete mixture. For the geopolymer preparation, an 8 M sodium hydroxide (NaOH) solution was used, and the ambient curing temperature (28℃) was maintained for all mixtures. The ratio of sodium silicate (Na2SiO3) to NaOH was 2.33, and the ratio of alkaline liquid to binder was 0.35. Based on experimental data collected from the literature, an evolutionary-based algorithm (GEP) was proposed to develop new predictive models for estimating the compressive strength of GPC containing bacteria. Data were classified into training and testing sets to obtain a closed-form solution using GEP. Independent variables for the model were the constituent materials of GPC, such as FA, MK, SF, and Bacillus bacteria. A total of six GEP formulations were developed for predicting the compressive strength of bacteria-incorporated GPC obtained at 1, 3, 7, 28, 56, and 90 days of curing. 80% and 20% of the data were used for training and testing the models, respectively. R2 values in the range of 0.9747 and 0.9950 (including train and test dataset) were obtained for the concrete samples, which showed that GEP can be used to predict the compressive strength of GPC containing bacteria with minimal error. Moreover, the GEP models were in good agreement with the experimental datasets and were robust and reliable. The models developed could serve as a tool for concrete constructors using geopolymers within the framework of this research.

• Journal of the Korean Recycled Construction Resources Institute
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• v.9 no.3
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• pp.383-388
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• 2021

In this study, constant head water permeability test was adopted to evaluate self-healing performance of mortars containing inorganic healing materials which consist of blast furnace slag, sodium sulfate and anhydrite. Clinker powder and sand replaced for a part of cement and fine aggregates. On constant head water permeability test for self-healing mortars, unit water flow rate of mortar specimens were measured according to crack width and healing period. As a result of evaluating the healing performance of self-healing mortar, it was confirmed that with the initial crack width of 0.3mm, the healing rate at healing period of 28 days increased by more than 30%p compared to plain mortar, greatly improving the healing performance. Furthermore, the coefficient(α) which was estimated from the relationship between crack width and unit water flow rate was used for calculating equivalent crack width. By analyzing the correlation of healing rate and equivalent crack width, the time and initial crack width attaining healing target crack width were predicted.