The analysis of color expression of carbon amino silica black mortar using artificial neural network

Colored concrete is able to make various colors which a user and an architect require with various pigments in White Portland Cement (WPC). Pigments are used in permanent coloring of concrete with colors different from the natural color of the cement or the aggregates with mixing WPC. But in this study, color expression characteristics of WPC mortar using carbon amino silica black (CASB) and the basic data for the manufacture of special black color concrete was provided. An artificial neural networks study was carried out to analyze the color evaluation of black mortar using CASB. A data set of a laboratory work, in which a total of 8 mortars were produced, was utilized in the Artificial Neural Networks (ANNs) study. The mortar mixture parameters were 8 different CASB ratios. Each mortar was measured at ten locations on the surface and averaged. Color can be evaluated by measurements of tristimulus values L^*, a^* and b^*, represented in the chromatic space CIELAB. The L^* value is a measure of luminosity (0 darkness), from completely opaque (0) to completely transparent (100); a^* is a measure of redness (-a^* greenness) and b^* of yellowness (b^* blueness). ANN model is constructed, trained and tested using these data. The data used in the ANN model are arranged in a format of two input parameters that cover the carbon amino silica black and WPC and, an output parameter which is the color parameters of the black colored mortar. The results showed that ANN can be an alternative approach for the analyzing the color parameters using mortar ingredients as input parameters.