This research investigates the performance of Steel Fiber Reinforced Rubberized Concrete (SFRRC) that incorporates high volumes of End-of-life tire materials, (i.e., both rubber particles and recycled tire steel fibers) in strengthening existing reinforced concrete (RC) beams. The mechanical and durability properties were determined for an environmentally friendly SFRRC mixture that incorporates a large volume (60% by volume aggregate replacement) of rubber particles and is solely reinforced by recycled tire steel fibers. The material was assessed experimentally under flexural, compressive and impact loading, and thus results led to the development of a numerical model using the Finite Element Method. Furthermore, a numerical study on full-scale structural members was conducted, focusing on conventional RC beams strengthened with SFRRC layers. This research presents the first study where SFRRC is examined for structural strengthening of existing RC beams, aiming to enable the use of such novel materials in structural applications. The results were compared to respective results of beams strengthened with conventional RC layers. The study reveals that incorporation of End-of-life tire materials in concrete not only serves the purpose of recycling End-of-life tire products, but can also contribute to unique properties such as energy dissipation not attained by conventional concrete and therefore leading to superior performance as flexural strengthening material. It was found that by incorporating 60% by volume rubber particles in combination with recycled steel fibers, it increased the damping ratio of concrete by 75.4%. Furthermore, SFRRC was proven effective in enhancing the energy dissipation of existing structural members.

This study presents the development and experimental assessment of novel, high strength, cementless binders that incorporate alkali-activated local waste. A silica-rich diabase mud (DM), currently considered as waste, was previously investigated for geopolymerization, signifying that the DM lacked the necessary reactivity to provide a stable geopolymer binder alone. Moreover, even after incorporation of small amounts of cement and metakaolin, the DM mixtures still did not yield adequate mechanical properties. In this study, the local DM was instead combined with another industrial byproduct known as Ground Granulated Blast-furnace Slag (GGBS) in varying mixtures. The mixture design trials enabled the development of three high strength cementless geopolymer mixtures with 28-day compressive strengths ranging between 60 and 100 MPa, comparable to conventional concrete compressive strengths. The results indicate that the innovative geopolymer material is very promising for the manufacturing of pavement tiles and other precast construction products. Most importantly, this study presents the first successful development of a construction material of adequate compressive strength that can absorb large quantities of the abundant quarry waste, following a course of 10 years of unsuccessful attempts to valorize the local DM. Although difficulties were encountered due to a high reactivity rate, especially for the mix that included the highest GGBS content, prototype pavement tiles were manufactured and assessed experimentally. The results reveal a promising potential of valorizing the local DM in the development of precast geopolymer products, despite the effects of shrinkage cracking on the experimental evaluation of the material mechanical properties.

This study investigates the application of clustering techniques to enhance the accuracy of hierarchical classification and regression (HCR) models for predicting concrete compressive strength (CCS). Following the hypothesis that integrating clustering at the initial levels of model hierarchy reduces classification errors and prevents their propagation to subsequent levels, HCR models were developed utilizing both the unweighted pair group method with arithmetic mean (UPGMA) and hard clustering (HC) methods. Findings demonstrate that models using UPGMA significantly outperform those based on HC. Furthermore, it was demonstrated that further hierarchical clustering allows for multilayered HCR models that improve predictive performance by further leveraging parent–child relationships within data clusters. Overall, this study demonstrates that the proposed methodology can be introduced in the model development pipeline to enhance the prediction accuracy of CCS models.

This study presents the environmental impact assessment of a newly developed geopolymer composite that combines fire-resistance and thermal insulation. The innovative product is developed through alkali-activation of ceramic titles retrieved from construction demolition waste. A comparative Life Cycle Assessment with conventional market products is performed, based on equivalent thermal and fire resisting performance. The analysis considers the amount of material required to cover a specific exterior wall area that would provide equal thermal insulation and fire-resistance, defining a functional unit that deliberates both properties. The results show that manufacturing the novel geopolymer composite over conventional market products, significantly reduces CO₂ emissions and other environmental impacts. This is primarily due to the reuse of waste ceramic tiles, which promotes sustainability in the construction industry. The promising findings of this study encourage the use of construction demolition waste in the development of geopolymer products for added value applications. Graphical Abstract