Publication

FRP-RCB ShearPred: An open-source platform for shear capacity prediction of stirrup-free FRP-reinforced concrete beams integrating design codes and ensemble machine learning

2026

Abstract

Reliable prediction of the shear capacity of stirrup-free FRP-reinforced concrete beams remains challenging because existing design provisions give inconsistent estimates, while most machine-learning studies are implemented as standalone scripts that are difficult to reproduce and retrain. This paper presents FRP-RCB ShearPred , an open-source Python application integrating five international design code formulations and eight regression algorithms within a single retrainable graphical workflow. Applied to a 728-specimen database, all eight ML models outperformed all five design codes under both held-out testing and leave-one-study-out (LOSO) validation across 49 independent experimental programmes, with Random Forest achieving the best LOSO R2 = 0.618 (RMSE = 44.3 kN) and recommended as the default deployment model.

Official source

https://infoscience.epfl.ch/entities/publication/1de63b8c-f05a-452f-8ff1-e0ffc125c7c5

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2026

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/1de63b8c-f05a-452f-8ff1-e0ffc125c7c5

About this result

Related concepts (32)

Machine learning

Machine learning (ML) is an umbrella term for solving problems for which development of algorithms by human programmers would be cost-prohibitive, and instead the problems are solved by helping machines 'discover' their 'own' algorithms, without needing to be explicitly told what to do by any human-developed algorithms. Recently, generative artificial neural networks have been able to surpass results of many previous approaches.

Linear regression

In statistics, linear regression is a linear approach for modelling the relationship between a scalar response and one or more explanatory variables (also known as dependent and independent variables). The case of one explanatory variable is called simple linear regression; for more than one, the process is called multiple linear regression. This term is distinct from multivariate linear regression, where multiple correlated dependent variables are predicted, rather than a single scalar variable.

Ensemble learning

In statistics and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from any of the constituent learning algorithms alone. Unlike a statistical ensemble in statistical mechanics, which is usually infinite, a machine learning ensemble consists of only a concrete finite set of alternative models, but typically allows for much more flexible structure to exist among those alternatives.

Related publications (32)

FRP-RCB ShearPred: An open-source platform for shear capacity prediction of stirrup-free FRP-reinforced concrete beams integrating design codes and ensemble machine learning

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