Reliability assessment of an open-pit slope using finite element strength reduction method and response surface method

2008 ◽  
pp. 479-482
Keyword(s):  
Finite Element ◽  
Response Surface ◽  
Response Surface Method ◽  
Reduction Method ◽  
Reliability Assessment ◽  
Strength Reduction ◽  
Open Pit ◽  
Strength Reduction Method ◽  
Surface Method

Failure Mechanism of a Slope Anti-Sliding Pile

2013 ◽  
Vol 639-640 ◽  
pp. 593-597
Author(s):  
Lin Chen ◽  
Yong Yao ◽  
Jiong Yang ◽  
Zhao Qiang Zhang
Keyword(s):  
Finite Element ◽  
Failure Mechanism ◽  
Reduction Method ◽  
Strength Reduction ◽  
Strength Reduction Method ◽  
Analysis Method ◽  
Feasible Method ◽  
Finite Element Software ◽  
Slope Excavation ◽  
Pile Design

According to finite element strength reduction method，the article has discussed the failure mechanism of anti-sliding pile by using finite element software MIDAS /GTS ，exploration report and anti-sliding pile design data.The comparative analysis shows that the failure of anti-siding pile is contributed by the slope excavation and rainwater.The analysis method and results can provide reference significance to other anti-sliding pile design.This paper also provide a feasible method for prediction of consequence in slope excavation.

Structural Optimization of a Machining Center Column Based on Response Surface Method

2012 ◽  
Vol 522 ◽  
pp. 663-667
Author(s):  
Ming Nan Sun ◽  
Guo Fu Yin ◽  
Teng Hu
Keyword(s):  
Finite Element ◽  
Structural Optimization ◽  
Response Surface ◽  
Response Surface Method ◽  
Surface Model ◽  
Element Analysis ◽  
Mean Frequency ◽  
Machining Center ◽  
Surface Method ◽  
Design Variables

In order to improve dynamic characteristics of a machining center column, this paper proposes a structural optimization method based on finite element method (FEM) and response surface method (RSM). In order to reduce number of design variables, the finite element analysis samples in design space are selected by using the central composite design (CCD) experiment method. On the basis of FEM results at these experiment samples, quadratic polynomials are employed to establish response surface model, which reflects the relationship between the response (mean frequency of the first four orders) and the design variables (the column structural sizes). The goal of getting maximum mean frequency is reached by using NLPQL algorithm in iSIGHT. Through the optimization, the mean frequency is increased by 8.12%.

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