AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
TL;DR
This study develops an interpretable ML framework using 624 externally bonded FRP-strengthened RC beam specimens and substantially outperforms ACI 440.2R-23, demonstrating 44–49% improvement in R2 and 45–64% reduction in MAE.
Design-code equations for the shear and flexural capacity of reinforced concrete (RC) beams are conservative and variable across structural conditions. This study develops a parallel modeling framework — two structurally independent machine-learning pipelines, one trained only on shear-failure specimens and one onl...
The bond behaviour between fiber-reinforced polymer (FRP) bars and seawater sea-sand concrete (SWSSC) governs load transfer, anchorage performance, crack development, and the structural reliability of marine concrete members. Although recent machine-learning (ML) models have demonstrated high predictive accuracy, they...
The structural integrity of precast concrete composite beams heavily relies on the new-to-old concrete interface. Existing numerical models and traditional analytical methods struggle to capture the complex, multi-variable interfacial degradation mechanisms. This study proposes an integrated framework combining high-fi...
Fibre-reinforced polymer (FRP) composites have emerged as an effective technique for enhancing the shear performance of reinforced concrete (RC) beams in existing structures. This study proposes a data-driven framework for predicting the total shear capacity (Vtotal) of FRP-retrofitted RC beams using exploratory data a...
Rutting deformation in flexible pavements of Southwest Nigeria constitutes a persistent infrastructure failure. Existing CBR-based design methods do not adequately capture the multi-variable interaction between subgrade stiffness, pavement thickness, and traffic loading, while three-dimensional finite element analysis...
This study addresses three recurring weaknesses of the machine learning literature in this area: model comparisons are seldom made under one shared data split and are rarely validated statistically; raw mix-design variables are usually passed to the learner without encoding established concrete science; and analysis co...
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