In the past few decades, due to the exponential increase of the world’s population, the number of discarded waste tires has become a serious ecological and environmental problem. Decomposition of waste tire rubber can take longer than 50 years, and every year the number of discarded tires is rapidly growing. With the inclusion of waste tire rubber into self-compacting concrete this global problem can be reduced. Waste tire rubber can be incorporated in self-compacting concrete by partially replacing the natural fine and coarse aggregate, reducing consumption of sand and gravel and preserving these natural materials. In addition, recycling and reusing waste tire rubber avoids the need for tire landfilling, as one of the major ecological problem of the near future. Replacement of natural aggregate with waste tire rubber can have an undesirable influence on the mechanical properties of self-compacting concrete, i.e., compressive strength, flexural strength, splitting tensile strength, and modulus of elasticity, however. On the other hand, replacing natural gravel or sand with waste tire rubber can improve impact resistance, ductility, and fatigue resistance. This paper presents an overview of the literature investigating recycled waste tire rubber used as a fine and/or coarse aggregate replacement in self-compacting concrete and its influence on several essential fresh and hardened self-compacting concrete properties.

Inclusion of rubber into concrete changes its behavior and the established shape of its stress-strain curve. Existing constitutive stress-strain models for concrete are not valid in case of rubberized concrete, and currently available modified models require additional validation on a larger database of experimental results, with a wider set of influential parameters. By executing uniaxial compressive tests on concrete with rubber substituting 10%, 20%, 30%, and 40% of aggregate, it was possible to study and evaluate the influence of rubber content on its mechanical behavior. The stress-strain curve was investigated in its entirety, including compressive strength, elastic modulus, strains at significant levels of stress, and failure patterns. Experimental results indicated that increase of rubber content linearly decreases compressive strength and elastic modulus, but increases ductility. By comparing experimental stress-strain curves with those plotted using available constitutive stress-strain models it was concluded that they are inadequate for rubberized concrete with high rubber content. Based on determined deviations an improvement of an existing model was proposed, which provides better agreement with experimental curves. Obtained research results enabled important insights into correlations between rubber content and changes of the stress-strain curve required when utilizing nonlinear material properties.

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.

Seismic risk is fundamental for the establishment of priorities in long-term prevention policy since urbanization and concentration of population in earthquake prone areas are increasing. To assess seismic risk, it is necessary to...

In order to test the reliability of neural networks for the prediction of the behaviour of multi-storey multi-bay infilled frames, neural network processing was done on an experimental database of one-storey one-bay reinforced-concrete (RC) frames with masonry infills. From the obtained results it is demonstrated that they are acceptable for the prediction of base shear (BS) and inter-storey drift ratios (IDR) in characteristic points of the primary curve of infilled frame behaviour under seismic loads. The results obtained on one-storey one-bay infilled frames was extended to multi-bay infilled frames by evaluating and comparing numerical finite element modelling(FEM) modelling and neural network results with suggested approximating equations for the definition of bilinear capacity by defined BS and IDRs. The main goal of this paper is to offer an interpretation of the behaviour of multi-storey multi-bay masonry infilled frames according to a bilinear capacity curve, and to present the infilled frame’s response according to the contributions of frame and infill. The presented methodology is validated by experimental results from multi-storey multi-bay masonry infilled frames.