EXPERİMENTAL EVALUATİON AND NUMERİCAL MODELİNG OF MECHANİCAL PROPERTİES OF POLYMERİC FİBER-REİNFORCED CEMENTİTİOUS COMPOSİTES

Abstract

This study investigates the mechanical behavior of polymeric fiber reinforced cementitious composites (PFRCCs), focusing on how factors such as fiber type, fiber dosage, and water to binder (W/B) ratio affect flexural strength (FS). A total of 82 mixes were examined, including 42 experimental mortar mixes and 40 from the literature, incorporating polypropylene (PP) and polyvinyl alcohol (PVA) fibers in varying volume fractions (0–1.4%) with two W/B ratios (0.30 and 0.45). Mechanical properties, particularly compressive strength (CS) and flexural strength (FS), were tested using standardized methods. To address gaps in previous research, additional parameters including fiber aspect ratio, fiber tensile strength, sand to aggregate ratio, and binder content were considered to provide a more comprehensive understanding of their influence. For predictive modeling, Multiple Linear Regression (MLR) and Gene Expression Programming (GEP) were applied based on input parameters such as fiber type, fiber content, W/B ratio, and specimen geometry. The results showed that a lower W/B ratio (0.30) consistently yielded superior mechanical performance, with flexural strength reaching up to 9.59 MPa, and the optimal fiber content for FS enhancement was between 0.6% and 1.0%. Among the two fiber types, PVA provided better results than PP due to its stronger bond with the cement matrix. In terms of modeling, GEP outperformed MLR by effectively capturing nonlinear relationships, achieving an R² of 0.90 for training and 0.74 for validation, compared with MLR’s lower R² of 0.68. Overall, the study offers valuable insights into the role of polymeric fibers in enhancing the mechanical properties of cementitious composites, while the predictive models particularly GEP serve as practical tools for engineers to optimize the design of fiber-reinforced concrete in diverse structural applications.