Dynamic Analysis of Incompressible Viscous Liquids

1979 ◽  
Vol 46 (2) ◽  
pp. 281-284
Author(s):  
G. R. Johnson

A Lagrangian finite-element analysis technique is presented for two-dimensional plane strain problems involving time-dependent incompressible flow of viscous liquids. The incompressibility feature is obtained with an iterative procedure which adjusts the nodal velocities until the anticipated volumetric strains are within specified limits. By eliminating the compressibility, it is possible to determine the integration time increment from the rate of distortion, rather than the sound speed transit time, as is required with various numerical methods involving wave propagation in compressible materials. This paper includes the formulation of the numerical method and illustrative examples.

1998 ◽  
Vol 5 (3) ◽  
pp. 145-151
Author(s):  
A. D. Kirwan, Jr. ◽  
B. L. Lipphardt, Jr.

Abstract. Application of the Brown-Samelson theorem, which shows that particle motion is integrable in a class of vorticity-conserving, two-dimensional incompressible flows, is extended here to a class of explicit time dependent dynamically balanced flows in multilayered systems. Particle motion for nonsteady two-dimensional flows with discontinuities in the vorticity or potential vorticity fields (modon solutions) is shown to be integrable. An example of a two-layer modon solution constrained by observations of a Gulf Stream ring system is discussed.


2021 ◽  
Vol 31 (4) ◽  
pp. 345-348
Author(s):  
Yasuhide Tsuji ◽  
Keita Morimoto ◽  
Akito Iguchi ◽  
Tatsuya Kashiwa ◽  
Shinji Nishiwaki

Author(s):  
Y Xu ◽  
B Liu ◽  
J Liu ◽  
S Riemenschneider

Empirical mode decomposition (EMD) is a powerful tool for analysis of non-stationary and nonlinear signals, and has drawn significant attention in various engineering application areas. This paper presents a finite element-based EMD method for two-dimensional data analysis. Specifically, we represent the local mean surface of the data, a key step in EMD, as a linear combination of a set of two-dimensional linear basis functions smoothed with bi-cubic spline interpolation. The coefficients of the basis functions in the linear combination are obtained from the local extrema of the data using a generalized low-pass filter. By taking advantage of the principle of finite-element analysis, we develop a fast algorithm for implementation of the EMD. The proposed method provides an effective approach to overcome several challenging difficulties in extending the original one-dimensional EMD to the two-dimensional EMD. Numerical experiments using both simulated and practical texture images show that the proposed method works well.


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