ArticlePolymers2026
Effect of the Hole Diameter Ratio (d/H) on the Web Crippling Capacity of Pultruded GFRP U-Channels Under Temperature and Loading Conditions.
Article in Polymers, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
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4 authors.
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Abstract
Glass fiber reinforced polymer (GFRP) composites produced by pultrusion are increasingly used in structural applications due to their advantages such as corrosion resistance, high strength-to-weight ratio, and lightness. However, the extensive use of fibers in the longitudinal direction causes imbalance in the cross-section, leading to web crippling behavior in profiles subjected to transverse vertical forces. In this study, the influence of temperature and hole diameter on the web crippling performance of pultruded GFRP U-section profiles was investigated experimentally and analytically. The specimens were perforated with circular holes with diameters of 32-50-70 mm (diameter/Height ratio d/H = 0.23-0.36-0.50) at the web center and exposed to high temperatures of 200-250-300 °C, respectively, along with room temperature. The experiments were conducted under ITF (interior-two-flange) and ETF (end-two-flange) loading conditions. According to the results obtained, ITF configurations exhibited approximately twice the load-carrying capacity compared to ETF configurations. Due to the effect of high temperature, the web-crushing capacity showed a significant decrease of up to 44% on average in all samples when the temperature was increased from 24 °C to 300 °C. Increasing the hole diameter (and consequently the d/H ratio) led to a gradual decrease in capacity ranging from 15.7% to 56.2%; in particular, it was demonstrated that the ETF loading configuration is more sensitive to the hole than the ITF. As a result of the study, an empirical equation considering the effects of temperature and hole size was proposed, and the model's predictions were compared with experimental results. Although the model successfully captured the general trend, the average absolute error rate in the predictions ranged between 12% and 14%, indicating improvement but not achieving ideal prediction accuracy.
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