Investigating the fracture behavior and ductility of self-compacting concrete containing recycled nylon granules: An experimental and modeling study

Utilizing polymer waste materials like compacted nylon as partial aggregate substitutes in concrete mixtures represents a viable strategy to mitigate environmental concerns. This incorporation also affects the mechanical fracture response of self-compacting concrete (SCC), improving its ductility and energy absorption capacity. The present research evaluates how introducing nylon granules in place of fine aggregates at replacement levels of 0 %, 5 %, 10 %, and 15 % influences SCC's fracture and ductility properties through the application of the Boundary Effect Method (BEM). A total of 48 notched beams were tested in a servo-controlled testing system employing the three-point bending test. The results indicate that increasing the nylon granule replacement level in SCC up to 15 % led to reductions of approximately 24 %, 19 %, and 20 % in the size-independent fracture energy ($G_F$), the initial fracture energy ($G_f$), and the fracture toughness ($K_{\mathrm{IC}}$), respectively. Moreover, the results of the reference crack length parameter (${\alpha }_{\infty }^{\ast }$) indicated that by increasing the nylon granule content, the concrete became more ductile and its design criterion complied with the strength criterion. An increase in nylon granule content up to 15 % led to a rise in parameter ${\alpha }_{\infty }^{\ast }$of the SCC specimens. This rise was approximately 23 % compared with the reference specimen (concrete without nylon granules). On average, the $G_F/G_f$ratio obtained from BEM for SCC specimens containing nylon granules was found to be 3.17. Finally, the mechanical properties data and experimental variables were utilized to develop multivariate predictive models for fracture parameters in SCC incorporating nylon particles. A comparison of the current experimental results with findings reported in the literature confirmed that the models exhibit acceptable accuracy and reliability.