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Lu, T. (author), Liang, X. (author), Liu, C. (author), Chen, Y. (author), Li, Z. (author)
This study experimentally investigated the effects of surfactants and water-repelling agents on the hydration process, relative humidity, and mechanical properties of Portland cement pastes. Based on the measurement results, the degree of hydration, degree of saturation, capillary tension of autogenous shrinkage, and magnitude of autogenous...
journal article 2023
document
Xu, Yaowen (author), Liang, X. (author), Wan, Chaojun (author), Yang, Hongyu (author), Feng, Xiaming (author)
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...
journal article 2023
document
Liang, M. (author), He, S. (author), Gan, Yidong (author), Zhang, Hongzhi (author), Chang, Z. (author), Schlangen, E. (author), Šavija, B. (author)
This paper employs computer vision techniques to predict the micromechanical properties (i.e., elastic modulus and hardness) of cement paste based on an input of Backscattered Electron (BSE) images. A dataset comprising 40,000 nanoindentation tests and 40,000 BSE micrographs was built by express nanoindentation test and Scanning Electron...
journal article 2023
document
Liang, M. (author), Gan, Y. (author), Chang, Z. (author), Wan, Z. (author), Schlangen, E. (author), Šavija, B. (author)
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...
journal article 2022
document
Gan, Y. (author), Zhang, Hongzhi (author), Liang, M. (author), Schlangen, E. (author), van Breugel, K. (author), Šavija, B. (author)
In this study, a numerical model using a 2D lattice network is developed to investigate the fatigue behaviour of cement paste at the microscale. Images of 2D microstructures of cement pastes obtained from XCT tests are used as inputs and mapped to the lattice model. Different local mechanical and fatigue properties are assigned to different...
journal article 2021
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