Active learning-based KNN-Monte Carlo simulation on the probabilistic fracture assessment of cracked structures

Probabilistic analysis aims at providing an assessment of cracked structures and taking relevant uncertainties into account in a rational quantitative manner. The main focus of this research work is on uncertainties aspect which relates with the nature of crack in materials. By using cracked structures modelling, finite element calculation, generation of adaptive mesh, sampling of cracked structure including uncertainties factors and probabilistic analysis using Monte Carlo method, the rigidity of cracked structures is estimated. Assessment of the accuracy in probabilistic structures is essential when limited amount of data is available. The hybrid finite element and probabilistic analysis represents the failure probability of the structures. The probability of failure caused by uncertainties relates to loads and material properties of the structure are estimated using Monte Carlo simulation technique. Numerical examples are presented to show probabilistic analysis based on Monte Carlo simulation provides accurate estimates of failure probability. The comparison shows that the combination between finite element analysis and probabilistic analysis provides a simple and realistic of quantify the failure probability.

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Probabilistic Analysis of Cracked Structures With Uncertainty Parameters

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.33-37.223 ◽

2008 ◽

Vol 33-37 ◽

pp. 223-228 ◽

Cited By ~ 1

Author(s):

Ahmad Kamal Ariffin ◽

M.R.M. Akramin ◽

Syifaul Huzni ◽

Shahrum Abdullah ◽

Mariyam Jameelah Ghazali

Keyword(s):

Finite Element Analysis ◽

Monte Carlo Simulation ◽

Finite Element ◽

Monte Carlo ◽

Failure Probability ◽

Probabilistic Analysis ◽

Crack Size ◽

Probability Of Failure ◽

Element Analysis ◽

Cracked Structures

This paper presents a probabilistic approach for fracture mechanics analysis of cracked structures. The objective of this work is to calculate the rigidity of cracked structures based on failure probability. The methodology consists of cracked structures modelling, finite element analysis with adaptive mesh, sampling of cracked structure including uncertainties factors and probabilistic analysis using Monte Carlo method. Probabilistic analysis represents the priority of proceeding either suitable to repair the structures or it can be justified that the structures are still in safe condition. Therefore, the combination of finite element and probabilistic analysis represents the failure probability of the structures by operating the sampling of cracked structures process. The uncertainty of the crack size can produce a significant effect on the probability of failure, particularly for the crack size with large coefficient of variation. The probability of failure caused by uncertainties relates to loads and material properties of the structure are estimated using Monte Carlo simulation technique. Numerical example is presented to show that probabilistic analysis based on Monte Carlo simulation provides accurate estimates of failure probability. The comparisons of simulation result, analytical solution and relevant numerical results obtained from other previous works shows that the combination of finite element analysis and probabilistic analysis based on Monte Carlo simulation provides accurate estimation of failure probability.

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AK-MCS: An active learning reliability method combining Kriging and Monte Carlo Simulation

Structural Safety ◽

10.1016/j.strusafe.2011.01.002 ◽

2011 ◽

Vol 33 (2) ◽

pp. 145-154 ◽

Cited By ~ 523

Author(s):

B. Echard ◽

N. Gayton ◽

M. Lemaire

Keyword(s):

Monte Carlo Simulation ◽

Monte Carlo ◽

Active Learning ◽

Reliability Method

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Electron Scattering in Solids

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100133618 ◽

1990 ◽

Vol 48 (2) ◽

pp. 4-5

Author(s):

Ryuichi Shimizu ◽

Ze-Jun Ding

Keyword(s):

Monte Carlo Simulation ◽

Monte Carlo ◽

Angular Distribution ◽

Elastic Scattering ◽

Electron Scattering ◽

Cross Sections ◽

Expansion Method ◽

Electron Excitation ◽

Partial Wave Expansion ◽

Backscattered Electrons

Monte Carlo simulation has been becoming most powerful tool to describe the electron scattering in solids, leading to more comprehensive understanding of the complicated mechanism of generation of various types of signals for microbeam analysis.The present paper proposes a practical model for the Monte Carlo simulation of scattering processes of a penetrating electron and the generation of the slow secondaries in solids. The model is based on the combined use of Gryzinski’s inner-shell electron excitation function and the dielectric function for taking into account the valence electron contribution in inelastic scattering processes, while the cross-sections derived by partial wave expansion method are used for describing elastic scattering processes. An improvement of the use of this elastic scattering cross-section can be seen in the success to describe the anisotropy of angular distribution of elastically backscattered electrons from Au in low energy region, shown in Fig.l. Fig.l(a) shows the elastic cross-sections of 600 eV electron for single Au-atom, clearly indicating that the angular distribution is no more smooth as expected from Rutherford scattering formula, but has the socalled lobes appearing at the large scattering angle.

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Determination of Stoichiometry of GaAs Component in (Gaas)Ge Epitaxially Grown Thin Films by Electron Microprobe X-Ray Analysis

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100134922 ◽

1990 ◽

Vol 48 (2) ◽

pp. 264-265

Author(s):

D. R. Liu ◽

S. S. Shinozaki ◽

R. J. Baird

Keyword(s):

Thin Film ◽

Thin Films ◽

Monte Carlo Simulation ◽

Monte Carlo ◽

Compound Semiconductors ◽

Energy Dispersive Analysis ◽

X Ray ◽

Metastable Alloys ◽

Lower Voltage

The epitaxially grown (GaAs)Ge thin film has been arousing much interest because it is one of metastable alloys of III-V compound semiconductors with germanium and a possible candidate in optoelectronic applications. It is important to be able to accurately determine the composition of the film, particularly whether or not the GaAs component is in stoichiometry, but x-ray energy dispersive analysis (EDS) cannot meet this need. The thickness of the film is usually about 0.5-1.5 μm. If Kα peaks are used for quantification, the accelerating voltage must be more than 10 kV in order for these peaks to be excited. Under this voltage, the generation depth of x-ray photons approaches 1 μm, as evidenced by a Monte Carlo simulation and actual x-ray intensity measurement as discussed below. If a lower voltage is used to reduce the generation depth, their L peaks have to be used. But these L peaks actually are merged as one big hump simply because the atomic numbers of these three elements are relatively small and close together, and the EDS energy resolution is limited.

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