ArticlePolymers2025
Experimental and Theoretical Investigation into the Thermal Conductivity and Heating-Softening Bending of Glass-Fiber-Reinforced Polypropylene Rebars.
Article in Polymers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Thermoplastic fiber-reinforced polymer (FRP) reinforcement has a significant advantage over traditional thermosetting FRP reinforcements in that it can be bent on site by heating-softening processing. However, current experimental and theoretical research on the thermal conductivity and heating-softening processing characteristics of thermoplastic FRP reinforcements is quite insufficient. Through heating-softening processing tests, numerical simulation, and theoretical calculation, this study investigated the heating-softening processing time of a thermoplastic glass-fiber-reinforced polypropylene (GFRPP) reinforcement. In the heat transfer process, thermal conductivity is typically treated as a constant. However, the experimental results indicated that the thermal conductivity/diffusivity coefficient of the GFRPP reinforcement was temperature-dependent. On this basis, an equivalent modified thermal diffusivity coefficient of glass fiber was proposed to account for the time-temperature-dependent heat conductivity of the GFRPP reinforcement, utilizing a series model. Utilizing the modified thermal diffusivity coefficient, the simulation model presented a heating-softening processing time that coincided well with the experimental results, with a mean ratio of 1.005 and a coefficient of variation of 0.033. Moreover, based on an equivalent homogeneous circular cross-section assumption of the GFRPP reinforcement, an analytical solution to the heat conduction equation was derived. Combining the experimental and simulation results, a semi-analytical and semi-empirical calculation model was also proposed for predicting the heating-softening processing time of a GFRPP reinforcement with a silicone tube cover. The model's calculated results align with the simulation trends, with an average deviation of 1.0% and a coefficient of variation of 0.026, demonstrating strong potential for engineering applications.
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