Finite element and Monte Carlo simulation of submicrometer silicon n-MOSFET's

The existence of pores is a very common feature of nature and of human life, but the existence of pores will alter the mechanical properties of the material. Therefore, it is very important to study the impact of different influencing factors on the mechanical properties of porous materials and to use the law of change in mechanical properties of porous materials for our daily lives. The SBFEM (scaled boundary finite element method) method is used in this paper to calculate a large number of random models of porous materials derived from Matlab code. Multiple influencing factors can be present in these random models. Based on the Monte Carlo simulation, after a large number of model calculations were carried out, the results of the calculations were analyzed statistically in order to determine the variation law of the mechanical properties of porous materials. Moreover, this paper gives fitting formulas for the mechanical properties of different materials. This is very useful for researchers estimating the mechanical properties of porous materials in advance.

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Variation Simulation for Deformable Sheet Metal Assemblies Using Finite Element Methods

Journal of Manufacturing Science and Engineering ◽

10.1115/1.2831115 ◽

1997 ◽

Vol 119 (3) ◽

pp. 368-374 ◽

Cited By ~ 245

Author(s):

S. Charles Liu ◽

S. Jack Hu

Keyword(s):

Monte Carlo Simulation ◽

Finite Element ◽

Monte Carlo ◽

Sheet Metal ◽

Finite Element Methods ◽

Free Form ◽

Direct Monte Carlo Simulation ◽

Free Form Surfaces ◽

Variation Simulation ◽

Sheet Metal Assembly

Traditional variation analysis methods, such as Root Sum Square method and Monte Carlo simulation, are not applicable to sheet metal assemblies because of possible part deformation during the assembly process. This paper proposes the use of finite element methods (FEM) in developing mechanistic variation simulation models for deformable sheet metal parts with complex two or three dimensional free form surfaces. Mechanistic variation simulation provides improved analysis by combining engineering structure models and statistical analysis in predicting the assembly variation. Direct Monte Carlo simulation in FEM is very time consuming, because hundreds or thousands of FEM runs are required to obtain a realistic assembly distribution. An alternative method, based on the Method of Influence Coefficients, is developed to improve the computational efficiency, producing improvements by several orders of magnitude. Simulations from both methods yield almost identical results. An example illustrates the developed methods used for evaluating sheet metal assembly variation. The new approaches provide an improved understanding of sheet metal assembly processes.

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Estimation of forming limit diagrams by the use of the finite element method and Monte Carlo simulation

Computers & Structures ◽

10.1016/j.compstruc.2008.07.002 ◽

2009 ◽

Vol 87 (1-2) ◽

pp. 128-139 ◽

Cited By ~ 12

Author(s):

Ø. Fyllingen ◽

O.S. Hopperstad ◽

O.-G. Lademo ◽

M. Langseth

Keyword(s):

Finite Element Method ◽

Monte Carlo Simulation ◽

Finite Element ◽

Monte Carlo ◽

Forming Limit ◽

The Finite Element Method ◽

Forming Limit Diagrams ◽

Element Method

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Sensitivity Analysis on Solder Joint Fatigue Life of Solid State Drives by Finite Element Method and Monte Carlo Simulation

ASME 2017 Conference on Information Storage and Processing Systems ◽

10.1115/isps2017-5453 ◽

2017 ◽

Author(s):

Y. J. Cho ◽

J. W. Jang ◽

G. H. Jang

Keyword(s):

Finite Element Method ◽

Monte Carlo Simulation ◽

Finite Element ◽

Monte Carlo ◽

Fatigue Life ◽

Solid State ◽

Thermal Cycling ◽

Solder Ball ◽

Solid State Drives ◽

Element Method

We proposed a method to estimate a distribution of fatigue life of solid state drives (SSDs) due to thermal cycling excitation by using finite element method and Monte Carlo simulation. In the developed finite element model, we utilized the Anand model to represent the viscoplastic behavior of the solder balls, and we also utilized the Prony series to represent the viscoelastic behavior of the polymer material in underfill. We determined a fatigue life of the SSD by using the Morrow’s energy-based fatigue model. Finally, we determined a distribution of fatigue life considering the manufacturing tolerance of the design variables and the variation of material properties in the Monte Carlo simulation. Finite element analysis shows that the outermost solder ball at the corner of dynamic random access memory was the most vulnerable component under the thermal cycling excitation. We also show that temperature profile and diameter of solder ball affect dominantly the fatigue life of the SSD.

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