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The use of boron compounds as composites of cementitious, except for the limited usage conditions like setting retarder has not become widespread because of the hardening and the related problems. In this study, the effects of the boron compounds into hydration process of the different cement types and controllability of these effects was investigated. Portland cement, boron modified active belite cement, and calcium aluminate cement were used in the mortar mixtures as binder material. Except for the control mixture, boric acid (BA) was used at the ratios of 0.25-1.00% of weight of cement in mortar mixtures with Portland cement. Setting times dependent on pH, EC and T changes of fresh mortars were measured. With increasing BA concentration, setting times of the mortars rather increased, pH, electrical conductivity, and T values of the mortars significantly reduced. To suppress the affect of BA on the hydration process, the two various stabilizers were used in the mortars, setting times, pH, electrical conductivity, and T values of these mortars were measured again. As a result, the optimum workability times and the parameters of the hydration reaction taking into account, the most suitable type and usage ratio of stabilizer were determined for mortars with BA.

Artificial neural network is generally information processing system and a computer program that imitates human brain neural network system. By entering the information from outside, artificial neural network can be trained on examples related to a problem, so that modeling of the problem is provided. In this study, compressive strength, Poisson ratio of the lightweight concrete specimens, which have different natural lightweight aggregates, were modeled with artificial neural network. The data which were provided by artificial neural network model were compared with the data obtained from experimental study and a good agreement was determined between the results.