Predicting long-term stress relaxation of geogrids using time–temperature superposition and the nonlinear three-component model

This study presents a method for predicting the long-term stress relaxation (SR) behavior of geogrids using shortterm testing combined with the time–temperature superposition (TTS) technique, known as SR-TTS. Two polymer geogrids—polypropylene (PP) and high-density polyethylene (HDPE)—were tested under constant tensile strain at multiple temperatures: 30 ◦C, 40 ◦C, and 50 ◦C for PP; and 30 ◦C, 37 ◦C, 44 ◦C, and 51 ◦C for HDPE. Master stress relaxation curves were constructed at a reference temperature of 30 ◦C by horizontally shifting short-term tensile load histories at elevated temperatures along the logarithmic time axis. Using this approach, 12-h tests for PP and 16-h tests for HDPE were extended to 115 and 4000 h, respectively, demonstrating the effectiveness of temperature-accelerated testing. A numerical simulation using the nonlinear threecomponent (NTC) model was also applied to replicate SR-TTS behavior. The master curves obtained from experimental SR-TTS tests showed excellent agreement with those from NTC-based simulations. Furthermore, both the experimental and simulated master curves closely matched long-term load decrement time histories from conventional stress relaxation (SR-CON) tests. These results confirm that SR-TTS, supported by numerical simulation, offers a reliable and efficient method for predicting long-term stress relaxation behavior of polymer geogrids under varying temperatures.