This paper aims to use a derivative of genetic programming to predict the bond strength of glass fiber-reinforced polymer (GFRP) bars in concrete under the effects of design guidelines. In developing bond strength prediction models, this paper prioritized simplicity and meaningfulness over extreme accuracy.
Assessing the bond strength of GFRP bars in concrete is a critical issue in designing and building reinforced concrete structures.
Ultimately, the equation of a linear form of a particular design guideline was suggested as the optimal prediction model. Improvements to the current design guidelines suggested by this model include setting a 1.31 magnification and considering the effects of the three significant parameters of bar diameter (db), minimum cover-to-bar diameter (C/db) and development length to bar diameter (l/db) under an acceptable root mean square error accuracy of around 2 MPa. Furthermore, the model suggests that the original influence parameter of concrete compressive strength (fc) may be removed from bond strength calculations.
The model suggests that the original influence parameter of concrete compressive strength (fc) may be removed from bond strength calculations.
The research presented in this paper was supported by the Ministry of Science and Technology, Taiwan under grant MOST 106–2221-E-011–019 held by H.-C. Tsai.
Compliance with ethical standards.
Conflict of interest: All authors declare that they have no conflict of interest.
Human and animal rights: This article does not contain any studies with human participants performed by any of the authors.
Chuang, Y.-J. and Tsai, H.-C. (2021), "Using genetic programming to model the bond strength of GFRP bars in concrete under the effects of design guidelines", Engineering Computations, Vol. 38 No. 5, pp. 2274-2292. https://doi.org/10.1108/EC-05-2020-0258
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