The Use of Artificial Neural Network for Predicting the Thermal Conductivity of Cement Based Mortar with Natural Zeolites

Abstract

Zeolites, in their natural state, have been used in construction materials since ancient times. The pozzolanic activity of zeolites and their use as supplementary cementitious materials has been investigated over the past three decades. The indoor comfort provided by a modern life style comes at a cost of consuming enormous amounts of energy. Materials with improved insulation properties are continuously researched and the use of zeolites showing encouraging results. The paper presents experimental results obtained on different cement-based mortar mixes incorporating natural zeolites. The main parameters of the research were: substitution of cement and sand by natural zeolites, three different replacement percentages for cement and sand (10%, 20% and 30%) and the curing age of mortar specimens (14 days, 21 days and 28 days). An artificial neural network (ANN) was developed to predict the values of the thermal conductivity by taking into account parameters such as density, humidity and surface temperature of the mortar samples. The ANN was able to accurately predict the experimental results for the thermal conductivity of cement-based mortars with natural zeolites.