Modelling the Influence of Waste Rubber on Compressive Strength of Concrete by Artificial Neural Networks

• Published in: Materials Vol. 12; no. 4; p. 561
• Main Authors: Hadzima-Nyarko, Marijana, Nyarko, Emmanuel Karlo, Ademović, Naida, Miličević, Ivana, Kalman Šipoš, Tanja
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 13-02-2019; MDPI
• Subjects: Accuracy; Aggregates; Artificial neural networks; Chipping; Compressive strength; Concrete; Genetic algorithms; Highway construction; Mechanical properties; Modulus of elasticity; Natural resources; Neural networks; Recycling; Repair; Rubber; Shrinkage; Studies; Tensile strength; Tires; Waste disposal; United States > US; compressive strength; artificial neural networks; tire rubber concrete; database of experimental results
• ISSN: 1996-1944; 1996-1944
• DOI: 10.3390/ma12040561

One of the major causes of ecological and environmental problems comes from the enormous number of discarded waste tires, which is directly connected to the exponential growth of the world's population. In this paper, previous works carried out on the effects of partial or full replacement of aggregate in concrete with waste rubber on some properties of concrete were investigated. A database containing 457 mixtures with partial or full replacement of natural aggregate with waste rubber in concrete provided by different researchers was formed. This database served as the basis for investigating the influence of partial or full replacement of natural aggregate with waste rubber in concrete on compressive strength. With the aid of the database, the possibility of achieving reliable prediction of the compressive strength of concrete with tire rubber is explored using neural network modelling.