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Ryan Good, David Nguyen, Hossein Bonakdari, Andrew Binns and Bahram Gharabaghi
Predicting morphological adjustments in alluvial meandering streams remains a challenging task due to the complex nature of the governing inter-related dynamic flow and sediment transport processes. This difficulty is increased in streams with irregular ...
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Naseer Muhammad Khan, Liqiang Ma, Muhammad Zaka Emad, Tariq Feroze, Qiangqiang Gao, Saad S. Alarifi, Li Sun, Sajjad Hussain and Hui Wang
The brittleness index is one of the most integral parameters used in assessing rock bursts and catastrophic rock failures resulting from deep underground mining activities. Accurately predicting this parameter is crucial for effectively monitoring rock b...
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Jing Liu, Xuesong Hai and Keqin Li
Massive amounts of data drive the performance of deep learning models, but in practice, data resources are often highly dispersed and bound by data privacy and security concerns, making it difficult for multiple data sources to share their local data dir...
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Jian Yang, Ming Sun, Guohuang Yao, Haizhu Guo and Rumian Zhong
This study explores an advanced prefabricated composite structure, namely ECC/RC composite shear walls with enhanced seismic performance. This performance enhancement is attributed to the strategic use of engineered cementitious composites (ECC) known fo...
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Alejandro Pérez Caldentey, Yolanda G. Diego, Anastasio P. Santos, Lina López, María Chiquito and Ricardo Castedo
Within the research project ITSAFE, two full-scale structures were built, one consisting of a single-storey, two-span, 7.00 × 14.00 m2 RC frame with a solid slab and another consisting of a two-storey, 7.00 × 7.00 m2 RC frame with solid slabs. In the two...
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