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Chao Wang, Jianhui Xu, Yuefeng Li, Tuanhui Wang and Qiwei Wang
Rockbursts are serious threats to the safe production of mining, resulting in great casualties and property losses. The accurate prediction of rockburst is an important premise that influences the safety and health of miners. As a classical machine learn...
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Gonghou Yao, Zhanqiang Liu and Haifeng Ma
The presence of residual stress seriously affects the mechanical performance and reliability of engineering components. Here, the authors propose a novel method to determine corresponding residual stress through micro-hardness measurements of machined su...
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Jaroslaw Chodór, Leon Kukielka, Grzegorz Chomka, Lukasz Bohdal, Radoslaw Patyk, Marek Kowalik, Tomasz Trzepiecinski and Andrii M. Radchenko
This article concerns the application of the FEM method for the prediction of stress and deformation states in the workpiece during diamond sliding burnishing (DSB). An updated Lagrange (UL) description was used to describe the phenomena at a typical inc...
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Celal Cakiroglu
The current study offers a data-driven methodology to predict the ultimate strain and compressive strength of concrete reinforced by aramid FRP wraps. An experimental database was collected from the literature, on which seven different machine learning (...
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Rui Zhou, Weicheng Gao, Wei Liu and Jianxun Xu
With advantages in efficiency and convenience, analytical models using experimental inputs to predict the mechanical properties of plain-woven fabric (PWF) composites are reliable in guaranteeing the composites? engineering applications. Considering the ...
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