Prediction of polyvinyl alcohol (PVOH) properties synthesized at various conditions by artificial neural networks technique

Flow behaviour of polyvinyl alcohol (PVOH) modified blends of polyvinyl acetate (PVAc)/natural rubber (NR) latexes

During compounding processes, polymer latexes are mixed with various colloidal systems (in particular, PVOH) or surface-active agents to modify the flow behaviour in order to suit the manufacturing process. In this study, the flow behaviour of aqueous dispersed PVAc, NR and different mixed dispersions were investigated both in the absence and presence of PVOH as flow modifier, using an Ostwald ...

The Prediction of Surface Tension of Ternary Mixtures at Different Temperatures Using Artificial Neural Networks

In this work, artificial neural network (ANN) has been employed to propose a practical model for predicting the surface tension of multi-component mixtures. In order to develop a reliable model based on the ANN, a comprehensive experimental data set including 15 ternary liquid mixtures at different temperatures was employed. These systems consist of 777 data points generally containing hydrocar...

Prediction of the changes in physicochemical properties of key lime juice during IR thermal processing by artificial neural networks

Thermal processing of the key lime juice leads to the inactivation of pectin methylesterase (PME) and the degradation of ascorbic acid (AA). These changes affect directly the cloud stability and color of the juice. In this study, an artificial neural network (ANN) model was applied for designing and developing an intelligent system for prediction of the thermal processing effects on the physico...

Rock Brittleness Prediction Using Geomechanical Properties of Hamekasi Limestone: Regression and Artificial Neural Networks Analysis

The cold climate is a favorable parameter for the development of tension cracks and decrease of rock brittleness. Therefore, this paper attempts to investigate the Hamekasi porous limestone in order to predict the brittleness indices during freeze-thaw cycles. The freeze–thaw test was executed for one cycle including 16 h of freezing, and 8 h of thawing. The geo mechanical properties and brittl...

PREDICTION OF COMPRESSIVE STRENGTH AND DURABILITY OF HIGH PERFORMANCE CONCRETE BY ARTIFICIAL NEURAL NETWORKS

Neural networks have recently been widely used to model some of the human activities in many areas of civil engineering applications. In the present paper, artificial neural networks (ANN) for predicting compressive strength of cubes and durability of concrete containing metakaolin with fly ash and silica fume with fly ash are developed at the age of 3, 7, 28, 56 and 90 days. For building these...

Prediction of Gas Lift Parameters Using Artificial Neural Networks