Monte Carlo simulation of realistic transmission breast optical tomography data for optimization of finite element image reconstruction

Author(s):  
M. E. Martino ◽  
Q. Fang ◽  
D. A. Boas ◽  
S. A. Carp
2014 ◽  
Vol 12 (3) ◽  
pp. 031702-31706 ◽  
Author(s):  
Mengyu Jia Mengyu Jia ◽  
Shanshan Cui Shanshan Cui ◽  
Xueying Chen Xueying Chen ◽  
Ming Liu Ming Liu ◽  
Xiaoqing Zhou Xiaoqing Zhou ◽  
...  

2021 ◽  
Vol 50 ◽  
pp. 101301
Author(s):  
A.Z. Zheng ◽  
S.J. Bian ◽  
E. Chaudhry ◽  
J. Chang ◽  
H. Haron ◽  
...  

2022 ◽  
Vol 12 (2) ◽  
pp. 575
Author(s):  
Guangying Liu ◽  
Ran Guo ◽  
Kuiyu Zhao ◽  
Runjie Wang

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.


1997 ◽  
Vol 119 (3) ◽  
pp. 368-374 ◽  
Author(s):  
S. Charles Liu ◽  
S. Jack Hu

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.


1999 ◽  
Vol 35 (3) ◽  
pp. 1809-1812 ◽  
Author(s):  
D. Hadji ◽  
Y. Marechal ◽  
J. Zimmermann

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