RETRACTED ARTICLE: Artificial neural networks to prediction total specific pore volume of geopolymers produced from waste ashes

Abstract

In the present work, total specific pore volume of inorganic polymers (geopolymers) made from seeded fly ash and rice husk bark ash has been predicted by artificial neural networks. Different specimens were subjected to porosimetry tests at 7 and 28 days of curing. One set of the specimens were cured at room temperature until reaching to 7 and 28 days, and the other sets were oven-cured for 36 h at the range of 40–90°C and then cured at room temperature until 7 and 28 days. To build the neural network models, training and testing using experimental results from 120 specimens were conducted. According to these input parameters, in the neural networks models, the pore volume of each specimen was predicted. The training and testing results in the neural networks model have shown a strong potential for predicting the total specific pore volume of the geopolymer specimens in the examined range.