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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