Using genetic programming to model the bond strength of GFRP bars in concrete under the effects of design guidelines. Issue 5 (25th January 2021)

• Record Type: Journal Article
• Authors: Chuang, Ying-Ji; Tsai, Hsing-Chih
• Is Part Of: Engineering computations. Volume 38:Issue 5(2021)
• Page Start: 2274
• Page End: 2292
• Publication Date: 2021-01-25
• Subjects: Genetic programming -- Design guidelines -- Bond strength of GFRP bars in concrete -- Functional mapping; Computer-aided engineering -- Periodicals; Computer graphics -- Periodicals; 620.00285
• DOI: 10.1108/EC-05-2020-0258
• Languages: English
• ISSNs: 0264-4401

Abstract

Abstract : Purpose: 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. Design/methodology/approach: Assessing the bond strength of GFRP bars in concrete is a critical issue in designing and building reinforced concrete structures. Findings: 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. Originality/value: The model suggests that the original influence parameter of concrete compressive strength (fc ) may be removed from bond strength calculations.