Numerical and machine learning modeling of GFRP confined concrete-steel hollow elliptical columns
This article investigates the behavior of hybrid FRP Concrete-Steel columns with an elliptical
cross section. The investigation was carried out by gathering information through literature …
cross section. The investigation was carried out by gathering information through literature …
Prediction of mechanical properties of high‐performance concrete and ultrahigh‐performance concrete using soft computing techniques: A critical review
A cement‐based material that meets the general goals of mechanical properties, workability,
and durability as well as the ever‐increasing demands of environmental sustainability is …
and durability as well as the ever‐increasing demands of environmental sustainability is …
Development of hybrid gradient boosting models for predicting the compressive strength of high-volume fly ash self-compacting concrete with silica fume
In an effort to extend the service life of structures under harsh exposure conditions and
reduce the carbon dioxide emissions from cement production, researchers are examining …
reduce the carbon dioxide emissions from cement production, researchers are examining …
Development of a prediction tool for the compressive strength of ternary blended ultra-high performance concrete using machine learning techniques
This study addresses the challenge of quantifying the complex and non-linear correlations
between the technical properties of ultra-high-Performance concrete (UHPC) and its mixture …
between the technical properties of ultra-high-Performance concrete (UHPC) and its mixture …
Compressive behavior of elliptical concrete-filled steel tubular short columns using numerical investigation and machine learning techniques
This paper presents a non-linear finite element model (FEM) to predict the load-carrying
capacity of three different configurations of elliptical concrete-filled steel tubular (CFST) short …
capacity of three different configurations of elliptical concrete-filled steel tubular (CFST) short …
Modelling the mechanical properties of concrete produced with polycarbonate waste ash by machine learning
India's cement industry is the second largest in the world, generating 6.9% of the global
cement output. Polycarbonate waste ash is a major problem in India and around the globe …
cement output. Polycarbonate waste ash is a major problem in India and around the globe …
Prediction of compressive strength of high-volume fly ash self-compacting concrete with silica fume using machine learning techniques
The quality and composition of the components in Self-Compacting Concrete (SCC)
determine its compressive strength; however, determining these complex relationships …
determine its compressive strength; however, determining these complex relationships …
Utilization finite element and machine learning methods to investigation the axial compressive behavior of elliptical FRP-confined concrete columns
Nowadays, elliptical sections are among the geometric shapes that are becoming more and
more popular in the architecture world. Finite element analysis (FEA) software, such as …
more popular in the architecture world. Finite element analysis (FEA) software, such as …
Data-driven machine learning forecasting and design models for the tensile stress-strain response of UHPC
MS Barkhordari, HAG Jaaz, A Jawdhari - Structures, 2025 - Elsevier
The tensile behavior of ultra-high performance concrete (UHPC) is distinctive from
conventional concrete (CC) and is typically included in design. This study leverages …
conventional concrete (CC) and is typically included in design. This study leverages …
Efficient sensitivity analysis for structural seismic fragility assessment based on surrogate models
The variability in seismic fragility due to structural parameter uncertainty highlights the
necessity of sensitivity analysis (SA) to identify critical parameters. However, the …
necessity of sensitivity analysis (SA) to identify critical parameters. However, the …