|
|
|
|
|
Jun Yeong Kim, Chang Geun Song, Jung Lee, Jong-Hyun Kim, Jong Wan Lee and Sun-Jeong Kim
In this paper, we propose a learning model for tracking the isolines of fluid based on the physical properties of particles in particle-based fluid simulations. Our method involves analyzing which weights, closely related to surface tracking among the va...
ver más
|
|
|
|
|
|
|
|
|
|
|
Zhiqiang Jiang, Yongyan Ma and Weijia Li
Accurate forecasting of ship motion is of great significance for ensuring maritime operational safety and working efficiency. A data-driven ship motion forecast method is proposed in this paper, aiming at the problems of low generalization of a single fo...
ver más
|
|
|
|
|
|
|
|
|
|
|
Michael van de Noort and Peter T. Ireland
Double-Wall Effusion Cooling schemes present an opportunity for aeroengine designers to achieve high overall cooling effectiveness and convective cooling efficiency in High-Pressure Turbine blades with reduced coolant usage compared to conventional cooli...
ver más
|
|
|
|
|
|
|
|
|
|
|
Kirttayoth Yeranee, Yu Rao, Chao Xu, Yueliang Zhang and Xiyuan Su
Additive manufacturing allows the fabrication of relatively complex cooling structures, such as triply periodic minimal surface (TPMS), which offers high heat transfer per unit volume. This study shows the turbulent flow heat transfer and thermal stress ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Song Xue, Jingyan Chen, Sheng Li and Huaai Huang
Early warning of safety risks downstream of small reservoirs is directly related to the safety of people?s lives and property and the economic and social development of the region. The lack of data and low collaboration in downstream safety management of...
ver más
|
|
|
|
|
|
|
|
|
|
|
Chunlin Zhong, Kangsheng Xue, Yakun Wang, Peng Luo and Xiaobo Liu
Understanding the fluid pattern is of special significance for estimating the hydraulic conductivity of fractured rock masses. The nonlinearity of fluid flow in discrete fracture networks (DFNs) originates from inertial effects and is enhanced by complex...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yuxuan Gao, Wei Xiong and Chenhao Wang
Dam operation is regarded as an effective way to increase water, food, and energy security for society. However, with the increasing water demand and frequent extreme droughts, numerous rivers worldwide go through periods of water scarcity and water ecos...
ver más
|
|
|
|
|
|
|
|
|
|
|
Pin Wu, Lulu Ji, Wenyan Yuan, Zhitao Liu and Tiantian Tang
The push-plate kiln is a kind of kiln equipment widely used in the oxygen-free sintering of high-temperature alloy materials. Its flow field monitoring has an important application value for the manufacturing industry. However, traditional simulation met...
ver más
|
|
|
|
|
|
|
|
|
|
|
Abouzar Choubineh, Jie Chen, David A. Wood, Frans Coenen and Fei Ma
Machine Learning (ML) and/or Deep Learning (DL) methods can be used to predict fluid flow in porous media, as a suitable replacement for classical numerical approaches. Such data-driven approaches attempt to learn mappings between finite-dimensional Eucl...
ver más
|
|
|
|
|
|
|
|
|
|
|
Xinyue Lan, Liyue Wang, Cong Wang, Gang Sun, Jinzhang Feng and Miao Zhang
In this research, we introduce a deep-learning-based framework designed for the prediction of transonic flow through a linear cascade utilizing large-scale point-cloud data. In our experimental cases, the predictions demonstrate a nearly four-fold speed ...
ver más
|
|
|
|
|
|