Random finite element analysis of backward erosion piping

2021 ◽  
Vol 138 ◽  
pp. 104322
Author(s):  
B.A. Robbins ◽  
D.V. Griffiths ◽  
Gordon A. Fenton
2016 ◽  
Vol 38 (1) ◽  
pp. 33-43 ◽  
Author(s):  
S. Drakos ◽  
G.N. Pande

Abstract This paper presents a procedure of conducting Stochastic Finite Element Analysis using Polynomial Chaos. It eliminates the need for a large number of Monte Carlo simulations thus reducing computational time and making stochastic analysis of practical problems feasible. This is achieved by polynomial chaos expansion of the displacement field. An example of a plane-strain strip load on a semi-infinite elastic foundation is presented and results of settlement are compared to those obtained from Random Finite Element Analysis. A close matching of the two is observed.


2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Jianye Ching ◽  
Yu-Gang Hu

In random finite element analysis (RFEA), continuous random fields must be discretized. The critical element size to achieve acceptable accuracy in effective Young’s modulus for an elementary soil mass is investigated. It is observed that the discrepancy between the continuous and discretized solutions is governed by the discretization strategy (element-level averaging versus midpoint), spatial variability pattern, and the adopted autocorrelation function. With the element-level averaging strategy, RFEA with element size less than (scale of fluctuation)/5 will not induce significant discrepancy from the continuous solution. Moreover, the element-level averaging strategy is more effective than the midpoint strategy.


2002 ◽  
Vol 11 (1) ◽  
pp. 30-40 ◽  
Author(s):  
Chatchai Kunavisarut ◽  
Lisa A. Lang ◽  
Brian R. Stoner ◽  
David A. Felton

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