Concrete-to-concrete interface shear strength prediction based on explainable extreme gradient boosting approach

Effect of shear reinforcement corrosion on interface shear transfer between concretes cast at different times

(2021) Jie Liu et al.   ENGINEERING STRUCTURES

Implementing ensemble learning methods to predict the shear strength of RC deep beams with/without web reinforcements

(2021) De-Cheng Feng et al.   ENGINEERING STRUCTURES

Data-driven shear strength prediction of steel fiber reinforced concrete beams using machine learning approach

(2021) Jesika Rahman et al.   ENGINEERING STRUCTURES

Contribution of Shear Reinforcements and Concrete to the Shear Capacity of Interfaces between Concretes Cast at Different Times

(2021) Jie Liu et al.   KSCE Journal of Civil Engineering

Data-driven model for ternary-blend concrete compressive strength prediction using machine learning approach

(2021) Babatunde Abiodun Salami et al.   CONSTRUCTION AND BUILDING MATERIALS

Shear-friction behavior of concrete-to-concrete interface under direct shear load

(2021) Jin Xia et al.   ENGINEERING STRUCTURES

Explainable extreme gradient boosting tree-based prediction of load-carrying capacity of FRP-RC columns

(2021) Abdoulaye Sanni Bakouregui et al.   ENGINEERING STRUCTURES

Interpretable XGBoost-SHAP Machine-Learning Model for Shear Strength Prediction of Squat RC Walls

(2021) De-Cheng Feng et al.   JOURNAL OF STRUCTURAL ENGINEERING

Data-driven machine-learning-based seismic failure mode identification of reinforced concrete shear walls

(2020) Sujith Mangalathu et al.   ENGINEERING STRUCTURES

Failure mode classification and bearing capacity prediction for reinforced concrete columns based on ensemble machine learning algorithm

(2020) De-Cheng Feng et al.   ADVANCED ENGINEERING INFORMATICS

Failure mode and effects analysis of RC members based on machine-learning-based SHapley Additive exPlanations (SHAP) approach

(2020) Sujith Mangalathu et al.   ENGINEERING STRUCTURES

Compressive strength prediction of high-performance concrete using gradient tree boosting machine

(2020) Mosbeh R. Kaloop et al.   CONSTRUCTION AND BUILDING MATERIALS

Efficient machine learning models for prediction of concrete strengths

(2020) Hoang Nguyen et al.   CONSTRUCTION AND BUILDING MATERIALS

Machine learning framework for predicting failure mode and shear capacity of ultra high performance concrete beams

(2020) Roya Solhmirzaei et al.   ENGINEERING STRUCTURES

Regional Seismic Risk Assessment of Infrastructure Systems through Machine Learning: Active Learning Approach

(2020) Sujith Mangalathu et al.   JOURNAL OF STRUCTURAL ENGINEERING

Machine learning applications for building structural design and performance assessment: State-of-the-art review

(2020) Han Sun et al.   Journal of Building Engineering

Data-Driven Approach to Predict the Plastic Hinge Length of Reinforced Concrete Columns and Its Application

(2020) De-Cheng Feng et al.   JOURNAL OF STRUCTURAL ENGINEERING

Stripe‐based fragility analysis of multispan concrete bridge classes using machine learning techniques

(2019) Sujith Mangalathu et al.   EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS

Evaluation of Design Provisions for Interface Shear Transfer between Concretes Cast at Different Times

(2019) Jie Liu et al.   Journal of Bridge Engineering

Machine learning-based compressive strength prediction for concrete: An adaptive boosting approach

(2019) De-Cheng Feng et al.   CONSTRUCTION AND BUILDING MATERIALS

Shear friction performance between high strength concrete (HSC) and ultra high performance concrete (UHPC) for bridge connection applications

(2019) Ali A. Semendary et al.   ENGINEERING STRUCTURES

Classification of failure mode and prediction of shear strength for reinforced concrete beam-column joints using machine learning techniques

(2018) Sujith Mangalathu et al.   ENGINEERING STRUCTURES

Emerging artificial intelligence methods in structural engineering

(2018) Hadi Salehi et al.   ENGINEERING STRUCTURES

Effect of High-Strength Reinforcement Steel on Shear Friction Behavior

(2017) Andre R. Barbosa et al.   Journal of Bridge Engineering

Interface shear behavior between high-strength precast girders and lightweight cast-in-place slabs

(2016) Haibo Jiang et al.   CONSTRUCTION AND BUILDING MATERIALS

Effect of joint interface conditions on shear transfer behavior of recycled aggregate concrete

(2016) Jianzhuang Xiao et al.   CONSTRUCTION AND BUILDING MATERIALS

Shear-Friction Behavior of Groove Interface in Concrete Bridge Rehabilitation

(2016) Haibo Jiang et al.   Journal of Bridge Engineering

Push-Off Tests in the Study of Cyclic Behavior of Interfaces between Concretes Cast at Different Times

(2016) Diogo Figueira et al.   JOURNAL OF STRUCTURAL ENGINEERING

Push-Off Tests in the Study of Cyclic Behavior of Interfaces between Concretes Cast at Different Times

(2016) Diogo Figueira et al.   JOURNAL OF STRUCTURAL ENGINEERING

Prediction of shear strength of FRP-reinforced concrete flexural members without stirrups using artificial neural networks

(2014) S. Lee et al.   ENGINEERING STRUCTURES

Interface shear transfer of lightweight-aggregate concretes cast at different times

(2014) Dane M. Shaw et al.   PCI JOURNAL

A state-of-the-art review on shear-friction

(2012) Pedro M.D. Santos et al.   ENGINEERING STRUCTURES

Neural network based approach for determining the shear strength of circular reinforced concrete columns

(2009) Naci Caglar   CONSTRUCTION AND BUILDING MATERIALS