Statistical distribution for prediction of stress intensity factor using bootstrap s-version finite element model

Stress intensity factor (SIF) is one of the most fundamental and useful parameters in all of fracture mechanics. The SIF describes the stress state at a crack tip, is related to the rate of crack growth, and used to establish failure criteria due to fracture. The SIF is determined to define whether...

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Main Authors:	M. N., M. Husnain, M. R. M., Akramin, Chuan, Zun Liang, K., Rozieana
Format:	Conference or Workshop Item
Language:	English English
Published:	Universiti Malaysia Pahang 2019
Subjects:	TS Manufactures
Online Access:	http://umpir.ump.edu.my/id/eprint/26468/ http://umpir.ump.edu.my/id/eprint/26468/1/57.%20Statistical%20distribution%20for%20prediction%20of%20stress%20intensity.pdf http://umpir.ump.edu.my/id/eprint/26468/2/57.1%20Statistical%20distribution%20for%20prediction%20of%20stress%20intensity.pdf

id	ump-26468
recordtype	eprints
spelling	ump-264682019-12-06T04:16:29Z http://umpir.ump.edu.my/id/eprint/26468/ Statistical distribution for prediction of stress intensity factor using bootstrap s-version finite element model M. N., M. Husnain M. R. M., Akramin Chuan, Zun Liang K., Rozieana TS Manufactures Stress intensity factor (SIF) is one of the most fundamental and useful parameters in all of fracture mechanics. The SIF describes the stress state at a crack tip, is related to the rate of crack growth, and used to establish failure criteria due to fracture. The SIF is determined to define whether the crack will grow or not. The aims of this paper is to examine the best sampling statistical distributions in SIF analysis along the crack front of a structure. Box-Muller transformation is used to generate the statistical distributions which is in normal and lognormal distributions. This method transformed from the random number of the variables within range zero and one. The SIFs are computed using the virtual crack-closure method (VCCM) in bootstrap S-version finite element model (BootstrapS-FEM). The normal and lognormal distributions are represented in 95% of confidence bounds from the one hundred of random samples. The prediction of SIFs are verified with Newman-Raju solution and deterministic S-FEM in 95% of confidence bounds. The prediction of SIFs by BootstrapS-FEM in different statistical distribution are accepted because of the Newman-Raju solution is located in between the 95% confidence bounds. Thus, the lognormal distribution for SIFs prediction is more acceptable between normal distributions. Universiti Malaysia Pahang 2019 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/26468/1/57.%20Statistical%20distribution%20for%20prediction%20of%20stress%20intensity.pdf pdf en http://umpir.ump.edu.my/id/eprint/26468/2/57.1%20Statistical%20distribution%20for%20prediction%20of%20stress%20intensity.pdf M. N., M. Husnain and M. R. M., Akramin and Chuan, Zun Liang and K., Rozieana (2019) Statistical distribution for prediction of stress intensity factor using bootstrap s-version finite element model. In: International Conference on Mechanical Engineering Research, 30-31 July 2019 , Kuantan, Pahang. pp. 1-7.. (Unpublished)
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English English
topic	TS Manufactures
spellingShingle	TS Manufactures M. N., M. Husnain M. R. M., Akramin Chuan, Zun Liang K., Rozieana Statistical distribution for prediction of stress intensity factor using bootstrap s-version finite element model
description	Stress intensity factor (SIF) is one of the most fundamental and useful parameters in all of fracture mechanics. The SIF describes the stress state at a crack tip, is related to the rate of crack growth, and used to establish failure criteria due to fracture. The SIF is determined to define whether the crack will grow or not. The aims of this paper is to examine the best sampling statistical distributions in SIF analysis along the crack front of a structure. Box-Muller transformation is used to generate the statistical distributions which is in normal and lognormal distributions. This method transformed from the random number of the variables within range zero and one. The SIFs are computed using the virtual crack-closure method (VCCM) in bootstrap S-version finite element model (BootstrapS-FEM). The normal and lognormal distributions are represented in 95% of confidence bounds from the one hundred of random samples. The prediction of SIFs are verified with Newman-Raju solution and deterministic S-FEM in 95% of confidence bounds. The prediction of SIFs by BootstrapS-FEM in different statistical distribution are accepted because of the Newman-Raju solution is located in between the 95% confidence bounds. Thus, the lognormal distribution for SIFs prediction is more acceptable between normal distributions.
format	Conference or Workshop Item
author	M. N., M. Husnain M. R. M., Akramin Chuan, Zun Liang K., Rozieana
author_facet	M. N., M. Husnain M. R. M., Akramin Chuan, Zun Liang K., Rozieana
author_sort	M. N., M. Husnain
title	Statistical distribution for prediction of stress intensity factor using bootstrap s-version finite element model
title_short	Statistical distribution for prediction of stress intensity factor using bootstrap s-version finite element model
title_full	Statistical distribution for prediction of stress intensity factor using bootstrap s-version finite element model
title_fullStr	Statistical distribution for prediction of stress intensity factor using bootstrap s-version finite element model
title_full_unstemmed	Statistical distribution for prediction of stress intensity factor using bootstrap s-version finite element model
title_sort	statistical distribution for prediction of stress intensity factor using bootstrap s-version finite element model
publisher	Universiti Malaysia Pahang
publishDate	2019
url	http://umpir.ump.edu.my/id/eprint/26468/ http://umpir.ump.edu.my/id/eprint/26468/1/57.%20Statistical%20distribution%20for%20prediction%20of%20stress%20intensity.pdf http://umpir.ump.edu.my/id/eprint/26468/2/57.1%20Statistical%20distribution%20for%20prediction%20of%20stress%20intensity.pdf
first_indexed	2023-09-18T22:41:15Z
last_indexed	2023-09-18T22:41:15Z
_version_	1777416929518026752

Statistical distribution for prediction of stress intensity factor using bootstrap s-version finite element model

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