This study examines the interfacial bond characteristics of twenty mix proportions, comprising ten self-compacting concrete (SCC) and ten fiber-reinforced self-compacting concrete (FRSCC) formulations, the latter enhanced with 0.1 % polypropylene fibers for repair applications. Initially, experiments such as slump flow, 28-day compressive strength, and tensile strength tests were conducted to evaluate the mechanical properties of the repair layers intended for use in slant shear tests. The primary focus of the research then shifted to determining shear bond strength (SBS) and calculating interfacial cohesion and friction angles using slant shear tests across various inclination angles on these mix proportions applied over a normal vibrated concrete (NVC) substrate. Notably, FRSCC mixtures with 10 % microsilica exhibited notable enhancements, showing increased cohesion of 8.28 MPa and a tensile strength increase of 24.50 % compared to their SCC counterparts. Additionally, a general trend was observed where FRSCC mixtures demonstrated higher cohesion values compared to SCC, underscoring the effectiveness of fiber reinforcement. Furthermore, the research introduces a novel predictive model employing a fuzzy system with a generalized Mamdani's interference engine and Hamacher family of t-norms to accurately predict the SBS, achieving a predictive accuracy with an R² value up to 0.94. Employing the fuzzy model, characterized by its high predictive accuracy, can significantly reduce the frequency of experimental tests required in the field, thereby lowering construction testing costs and enhancing repair efficiency. These findings not only advance our understanding of SCC and FRSCC behaviors in repair scenarios but also contribute significantly to the development of more reliable and sustainable construction practices by improving the precision of SBS predictions in theoretical modeling and empirical testing.

This study investigates the shear bond strength between four widely used façade stones—travertine, granite, marble, and crystalline marble—and concrete substrates, with a particular focus on the role of polypropylene fibers in adhesive mortars. The research evaluates the effects of curing duration, fiber dosage, and mechanical anchorage on bond strength. Results demonstrate that Z-type anchorage provided the highest bond strength, followed by butterfly-type and wire tie systems. Extended curing had a significant impact on bond strength for specimens without anchorage, particularly for travertine. The incorporation of polypropylene fibers at 0.2% volume in adhesive mortar yielded the strongest bond, although lower and higher dosages also positively impacted the bonding. Furthermore, the study introduces a novel fuzzy logic model using the Dombi family of t-norms, which outperformed linear regression in predicting bond strength, achieving an R² of up to 0.9584. This research emphasizes the importance of optimizing fiber dosage in adhesive mortars. It proposes an advanced predictive model that could enhance the design and safety of stone-clad façades, offering valuable insights for future applications in construction materials.

This study offers a comprehensive analysis of Fiber-Reinforced Self-Compacting Concrete (FRSCC) with a focus on shear bond strength influenced by specific compositions of microsilica, zeolite, slag, and polypropylene fibers. Twenty distinct FRSCC mixes underwent extensive testing, including 28-day compressive strength, tensile strength assessments, and push-out and slant shear tests. A significant outcome is the strong correlation between the push-out and slant shear test results, exemplified by an R² value of 0.88, confirming the push-out test as a viable and practical alternative for bond strength assessment. Experimentally, fibers were found to enhance tensile strength, with the inclusion of 15% microsilica and slag further amplifying this effect, highlighting the critical role of precise pozzolan selection in achieving optimal mechanical performance and workability in FRSCC. Furthermore, the study introduces a fuzzy logic system for predicting shear bond strength, achieving high predictive accuracy with R² values reaching up to 0.96, depending on the t-norms utilized. This research not only validates the push-out test as a reliable method for evaluating shear bond strength in FRSCC but also demonstrates the efficacy of the fuzzy logic approach, representing a groundbreaking contribution in both computational analysis and practical methodology for concrete structural integrity.

This paper presents an investigation into the bond strength of three common façade stones, namely, travertine, granite, and marble, to a concrete substrate using a shear-splitting test. The effects of anchorage, the number of curing days, and the presence of an anti-freezing agent in cement–sand mortar on bond strength were studied. The results show that the number of curing days had a significant impact on the bond strength between the stones and the substrates. The presence of an anti-freezing agent and accelerator increased bonding during the initial days, but this effect gradually decreased. The use of anchorage had a positive effect on the bond strength, particularly with fewer curing days. Granite had the lowest bond strength when no anchorage was used due to its low permeability. Based on the findings, a novel fuzzy logic approach was proposed to predict the bond strength. This study provides valuable insights into improving the bonding of façade stones to substrates and can aid in the safe and efficient use of these materials in construction.

This study investigates experimentally and analytically the interfacial bond strength of coloured SCC repair layers. Ten SCC mixes with 5%, 10% and 15% of blue, green or red pigments were produced to examine their fresh properties. Subsequently, 60 coloured SCC specimens were tested to assess interfacial bond strength using pull-off and push-out tests. The results confirm that pigments reduce the mechanical properties of SCC and its bond strength to concrete substrates, with red pigment reducing (by up to 41%) interfacial bond strength. It is shown that the push-out test is effective to determine the interfacial shear bond strength between the SCC repair layers and substrates. A GNNC-Modified PSO algorithm is proposed to calculate accurately (R² = 0.95) the interfacial bond strength of coloured SCC repair layers. This study contributes towards developing more effective test methods and more accurate models to calculate interfacial bond strength of the SCC repair layers used in this study.