This study aims to provide an efficient and accurate machine learning (ML) approach for
predicting the creep behavior of concrete. Three ensemble machine learning (EML) models …

A computational sequence to extract individual 3D aggregate from computed tomography
(CT) scans of bulk concrete is presented in this paper. The technique adopted a combination …

The time-dependent viscoelastic response of cement-based materials to applied
deformation is far from fully understood at the atomic level. Calcium silicate hydrate (CSH) …

Glass powder (GP) is a solid waste with increasing reserves. GP can be used as a
supplementary cementitious material (SCM) to produce concrete in order to effectively save …

This paper used machine learning to model the prediction of creep and the analysis of
characteristic factors for concrete containing supplementary cementitious materials (SCM) …

The mechanism behind the creep of concrete is primarily governed by calcium silicate
hydrate (CSH). The results presented in this study demonstrate the effect of varying relative …

This study aims to provide an efficient alternative for predicting creep modulus of cement
paste based on Deep Convolutional Neural Network (DCNN). First, a microscale lattice …

A multiscale creep model of concrete is proposed from C–S–H gel scale to mesoscale
considering the effects of ITZ and aggregates with irregular-shaped aggregates. A novel …

The influence of temperature on the expansive behavior and microstructural damage of
concrete due to the alkali–silica reaction (ASR) is studied experimentally by applying a new …

This paper presents a method to numerically investigate the microstructural effect on the
creep behavior of cement paste at the microscale. The lattice fracture model is extended to …