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Jianlong Ye, Hongchuan Yu, Gaoyang Liu, Jiong Zhou and Jiangpeng Shu
Component identification and depth estimation are important for detecting the integrity of post-disaster structures. However, traditional manual methods might be time-consuming, labor-intensive, and influenced by subjective judgments of inspectors. Deep-...
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Sorin Zoican, Roxana Zoican, Dan Galatchi and Marius Vochin
This paper illustrates a general framework in which a neural network application can be easily integrated and proposes a traffic forecasting approach that uses neural networks based on graphs. Neural networks based on graphs have the advantage of capturi...
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Bomi Kim, Garim Lee, Yaewon Lee, Sohyun Kim and Seong Jin Noh
In this study, we analyzed the impact of model spatial resolution on streamflow predictions, focusing on high-resolution scenarios (<1 km) and flooding conditions at catchment scale. Simulation experiments were implemented for the Geumho River catchment ...
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Nicholas F. Giannelis, Tamas Bykerk and Gareth A. Vio
This paper introduces a generic model for the study of aerodynamic behaviour relevant to fifth-generation high-performance aircraft. The model design is presented, outlining simplifications made to retain the key features of modern high-performance vehic...
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Pengyue Zhao, Xifeng Gao, Bo Zhao, Huan Liu, Jianwei Wu and Zongquan Deng
The aerodynamic properties of rotor systems operating within low Reynolds number flow field conditions are profoundly influenced by their geometric and flight parameters. Precise estimation of optimal airfoil parameters at different angles of attack is i...
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