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Morhaf Aljber, Han Soo Lee, Jae-Soon Jeong and Jonathan Salar Cabrera
In tsunami studies, understanding the intricate dynamics in the swash area, characterised by the shoaling effect, remains a challenge. In this study, we employed the adaptive mesh refinement (AMR) method to model tsunami inundation and propagation in the...
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Haojie Lian, Xinhao Li, Leilei Chen, Xin Wen, Mengxi Zhang, Jieyuan Zhang and Yilin Qu
Neural radiance fields and neural reflectance fields are novel deep learning methods for generating novel views of 3D scenes from 2D images. To extend the neural scene representation techniques to complex underwater environments, beyond neural reflectanc...
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Kai Li, Quan Liu, Yuan Tian, Cong Du and Zhixiang Xu
Asphalt mixtures exhibit complex mechanical behaviors due to their multiphase internal structures. To provide better characterizations of asphalt pavements under various forms of potential distress, a two-dimensional (2D) finite element simulation based ...
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Bikram Kesharee Patra, Rocio L. Segura and Ashutosh Bagchi
This study addresses the vital issue of the variability associated with modeling decisions in dam seismic analysis. Traditionally, structural modeling and simulations employ a progressive approach, where more complex models are gradually incorporated. Fo...
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Martina Hauser, Stefan Reinstaller, Martin Oberascher, Dirk Muschalla and Manfred Kleidorfer
Owing to climate change, heavy rainfall events have increased in recent years, often resulting in urban flooding. Urban flood models usually consider buildings to be closed obstacles, which is not the case in reality. To address this research gap, an exi...
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Chia-Ho Wang, Hsiang-Lin Yu and Tsang-Jung Chang
Currently, for modeling two-dimensional (2D) solute transport during pluvial and fluvial floods, the finite volume (FV) models are widely used because of their strong ability to handle steep concentration and velocity gradients from the flow advection te...
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Giuseppe Pezzinga
Water hammer flow is examined, putting into evidence that unsteady friction cannot be fully responsible for observed oscillation damping. The measured piezometric head oscillations of water hammer flow experimental tests carried out for very long time (a...
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Qianjing Li, Jia Tian and Qingjiu Tian
The combination of multi-temporal images and deep learning is an efficient way to obtain accurate crop distributions and so has drawn increasing attention. However, few studies have compared deep learning models with different architectures, so it remain...
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Raffaele Martorana and Patrizia Capizzi
Electrical resistivity tomography (ERT) is a well-known geophysical method applied to geological, hydrogeological and geoenvironmental research. To date, 2D ERT is still used much more than 3D ERT, thanks to its greater immediacy, survey speed and lower ...
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Yu-Ming Zhang, Chia-Yuan Cheng, Chih-Lung Lin, Chun-Chieh Lee and Kuo-Chin Fan
Biometrics has become an important research issue in recent years, and the use of deep learning neural networks has made it possible to develop more reliable and efficient recognition systems. Palms have been identified as one of the most promising candi...
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