Peanut shaped auxetic cementitious cellular composite (ACCC)

Auxetic cementitious cellular composites (ACCCs) exhibit desirable mechanical properties (e.g., high fracture resistance and energy dissipation), due to their unique deformation characteristics. In this study, a new type of cementitious auxetic material, referred to as peanut shaped ACCC, has been designed and subsequently architected using...

Automatic enhancement of vascular configuration for self-healing concrete through reinforcement learning approach

Vascular self-healing concrete (SHC) has great potential to mitigate the environmental impact of the construction industry by increasing the durability of structures. Designing concrete with high initial mechanical properties by searching a specific arrangement of vascular structure is of great importance. Herein, an automatic optimization...

Carbonation and related behaviors of hardened cement pastes under different hydration degrees

This paper develops a kind of molded disc samples to investigate the carbonation and related behaviors of hardened cement pastes under different previous hydration degrees. Weight and length changes of cement pastes over time are monitored during a multistep process including carbonation, drying, rewetting, and redrying. The combination of X...

Early-age creep of 3D printable mortar: Experiments and analytical modelling

In this study, an experimental setup to characterize the early-age creep of 3D printable mortar was proposed. The testing protocol comprises quasi-static compressive loading-unloading cycles, with 180-s holding periods in between. An analytical model based on a double power law was used to predict creep compliance with hardening time and...

Microstructure-informed deep convolutional neural network for predicting short-term creep modulus of cement paste

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 model for short-term creep is adopted to build a database that contains 18,920 samples. Then, 3 DCNNs with different consecutive convolutional layers are built to learn...

Interpretable Ensemble-Machine-Learning models for predicting creep behavior of concrete

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 are selected in this study: Random Forest (RF), Extreme Gradient Boosting Machine (XGBoost) and Light Gradient Boosting Machine (LGBM). Firstly, the creep data in...

The reinforcement effects of PVA, PE, and steel fibers on AAS material

This paper employs PVA, PE, steel fibers, as well as the hybrids of two of the three fibers to reinforce alkali-activated slag (AAS) material, aiming to prepare strain-hardening and clinker-free composites. The flexural strength, compressive strength, uniaxial tensile performance of the composites and bond behavior between fibers and the...