Review of Deterministic and AI-Based Methods for Fluid Motion Modelling and Sloshing Analysis

被引:0
|
作者
Filo, Grzegorz [1 ]
Lempa, Pawel [1 ]
Wisowski, Konrad [1 ]
机构
[1] Cracow Univ Technol, Fac Mech Engn, PL-31864 Krakow, Poland
关键词
liquid sloshing; modelling; artificial intelligence; neural networks; deep learning; NUMERICAL-SIMULATION; TANK; BAFFLES; PREDICTION; NETWORK;
D O I
10.3390/en18051263
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Contemporary fluid motion modelling techniques, including the phenomenon of liquid sloshing in tanks, are increasingly associated with the use of artificial intelligence methods. In addition to the still frequently used traditional analysis methods and techniques, such as FEM, CFD, VOF and FSI, there is an increasing number of publications that use elements of artificial intelligence. Among others, artificial neural networks and deep learning techniques are used here in the field of prediction and approximation, as well as genetic and other multi-agent algorithms for optimization. This article analyses of the current state of research using the above techniques and the possibilities and main directions of their further development.
引用
收藏
页数:21
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