Predictive Modeling of Tensile Fracture in Synthetic Fiber Ropes Using Generalized Additive Models

ABSTRACT This study investigates the tensile failure behavior of synthetic fiber ropes composed of nylon (6‐PA), polypropylene (i‐PP), and polyester (PET) fibers. A comprehensive experimental program was conducted using 202 rope specimens, with nominal diameters ranging from 4 to 20 mm, subjected to monotonic and cyclic loading conditions. The resulting load–strain data were systematically compiled for advanced statistical analysis. Generalized additive models (GAMs) were developed using R programming to predict failure forces and strains, incorporating a Weibull distribution framework for failure responses. The GAM approach demonstrated superior predictive capability, revealing a linear correlation between rope diameter and failure strain across all materials, as well as a nonlinear relationship between diameter and failure force. Notably, GAM models utilizing natural‐spline representations exhibited enhanced performance over conventional Weibull models. These findings contribute to a deeper understanding of the tensile properties of synthetic ropes, offering a data‐driven approach to optimize testing efforts and improve the reliability of these materials for engineering applications.