Modeling the Properties of Construction Materials. Modeling the Properties of Construction Materials Using Artificial Neural Network (ANN) and Nonlinear Relation Methods

      Аннотация: Advances in technology and environmental considerations require the construction industry to use more and more engineered high performance materials. In this study, mechanical properties of high volume fly ash (HVFA) concrete mixes were investigated for the Leadership in Energy and Environmental Design (LEED). Five HVFA concrete mixes containing class C fly ash up to 80% as replacement for cement were designed and tested. The performance of HVFA concrete mixes were compared with ordinary Portland cement concrete (PCC). In addition, the effects of initial temperature, catalyst and activator contents on the gelling time of two polymer grouts used in various civil infrastructural applications were investigated. Gelling times for the polymer grouts were measured and the curing temperatures for the mixtures were monitored during and after the gelling process. Using artificial neural network (ANN) and nonlinear relation (NLR) models, the compressive strength of concrete, gelling time and maximum curing temperature rise of polymer grouts were investigated.

Ключевые слова: artificial neural network, Concrete, LEED, Modeling, High Performance Construction Materials, Polymer Grouts, Fly ash