Machine learning prediction of 28-day compressive strength of CNT/cement composites with considering size effects

J Yang, Y Fan, F Zhu, Z Ni, X Wan, C Feng, J Yang - Composite Structures, 2023 - Elsevier
It is challenging for either traditional modelling or experiments to capture the complex
relationship between the strength of cement composites and the many influencing factors …

[HTML][HTML] Predicting the compressive strength of carbon-enhanced cementitious composites using two-dimensional convolutional neural networks

SB Jeon, S Kang, MH Jeong, H Lee - Case Studies in Construction …, 2024 - Elsevier
This study addresses the limitations of traditional statistical methods and artificial neural
networks (ANNs) in extracting relevant features from carbon-based cementitious composites …

Cyclic loading effects on the heat-generation performance of carbon nanotube-embedded cement composites

J Bang, D Jang, B Yang - Functional Composites and Structures, 2024 - iopscience.iop.org
This study investigates the heat-generation stability of carbon nanotube (CNT)/cement
composites after exposing to cyclic loading conditions. The specimens were fabricated with …

Data-Driven Prediction of Electrical Resistivity of Graphene Oxide/Cement Composites Considering the Effects of Specimen Size and Measurement Method

R Chen, F Chuang, J Yang, Z Hang, Y Fan… - Buildings, 2024 - search.proquest.com
The prediction of electrical resistivity of graphene oxide (GO) reinforced cement composites
(GORCCs) is essential to promote the application of the composites in civil engineering …