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 (f_c) may be removed from bond strength calculations.

Originality/value

The model suggests that the original influence parameter of concrete compressive strength (f_c) may be removed from bond strength calculations.

中文翻译：

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在设计准则的影响下，使用遗传编程模拟混凝土中 GFRP 钢筋的粘结强度

目的

本文旨在使用遗传编程的导数来预测在设计准则的影响下混凝土中玻璃纤维增​​强聚合物 (GFRP) 钢筋的结合强度。在开发粘合强度预测模型时，本文将简单性和意义放在了极端准确性之上。

设计/方法/方法

评估 GFRP 钢筋在混凝土中的粘结强度是设计和建造钢筋混凝土结构的关键问题。

发现

最终，特定设计准则的线性形式的方程被建议为最佳预测模型。该模型建议的当前设计指南的改进包括设置 1.31 放大倍率并考虑三个重要参数的影响：钢筋直径 (db)、最小覆盖层到钢筋直径 (C/db) 和展开长度对钢筋直径 ( l/db) 在可接受的均方根误差精度约为 2 MPa 的情况下。此外，该模型表明，混凝土抗压强度 (f _c )的原始影响参数可以从粘结强度计算中删除。

原创性/价值

该模型表明，混凝土抗压强度 (f _c )的原始影响参数可以从粘结强度计算中去除。