[HTML][HTML] Structural health monitoring of exterior beam–column subassemblies through detailed numerical modelling and using various machine learning techniques
Structural health monitoring of beam–column joints is paramount, as they are critical load-
carrying components of reinforced concrete buildings. Evaluating the ultimate joint shear …
carrying components of reinforced concrete buildings. Evaluating the ultimate joint shear …
Strength models of near-surface mounted (NSM) fibre-reinforced polymer (FRP) shear-strengthened RC beams based on machine learning approaches
The shear strengthening of reinforced concrete (RC) beams using near-surface mounted
(NSM) fibre-reinforced polymer (FRP) bars/strips has gained substantial research attention …
(NSM) fibre-reinforced polymer (FRP) bars/strips has gained substantial research attention …
A robust approach to shear strength prediction of reinforced concrete deep beams using ensemble learning with SHAP interpretability
The behavior of reinforced concrete (RC) deep beams is complex and difficult to predict due
to factors such as compressive and shear stress and beam geometry. To address this …
to factors such as compressive and shear stress and beam geometry. To address this …
Using crack width for shear, stiffness, and stirrup strain history predictions for reinforced concrete beams
Shear failures in reinforced concrete structures occur with little or no warning. Reinforced
concrete members with shear cracks should be evaluated to ensure safety. Existing …
concrete members with shear cracks should be evaluated to ensure safety. Existing …
New semiempirical temporal model to predict chloride profiles considering convection and diffusion zones
TA Reichert, WA Pansera, CET Balestra… - … and Building Materials, 2023 - Elsevier
Chloride ions are primarily responsible for reinforcement corrosion in concrete structures in
the marine environment. Thereby, analyses regarding chloride penetration into concrete are …
the marine environment. Thereby, analyses regarding chloride penetration into concrete are …
A novel hybrid soft computing model using stacking with ensemble method for estimation of compressive strength of geopolymer composite
Machine learning technology is commonly used for the prediction of the compressive
strength of geopolymer composites. This research is focused on using algorithms …
strength of geopolymer composites. This research is focused on using algorithms …
The Efficiency of Using Machine Learning Techniques in Fiber-Reinforced-Polymer Applications in Structural Engineering
Sustainable solutions in the building construction industry have emerged as a new method
for retrofitting applications in the last two decades. Fiber-reinforced polymers (FRPs) have …
for retrofitting applications in the last two decades. Fiber-reinforced polymers (FRPs) have …
State-of-art: artificial intelligence models era in modeling beam shear strength
The computer aided models have received much attention in the recent years for solving
diverse civil engineering applications. In the current review, the applications of artificial …
diverse civil engineering applications. In the current review, the applications of artificial …
Machine learning-based predictive models for equivalent damping ratio of RC shear walls
Energy-based seismic design is being rapidly developed and suggests that the seismic
demands are met by the energy dissipation capacity of the structural members. Equivalent …
demands are met by the energy dissipation capacity of the structural members. Equivalent …
Metaheuristics‐optimized ensemble system for predicting mechanical strength of reinforced concrete materials
This paper develops a novel artificial intelligence (AI)‐based approach, called the
metaheuristics‐optimized ensemble system (MOES), to assist civil engineers significantly in …
metaheuristics‐optimized ensemble system (MOES), to assist civil engineers significantly in …