A Bayes study of inverse Gaussian based strength models with accelerating stress

The survival probability of a composite material subject to external stress is governed by the condition that the strength of the material must exceed the applied stress. There are several models proposed in the literature for studying such stress-strength relationships, especially with reference to...

Full description

Saved in:
Bibliographic Details
Published inCommunications in statistics. Simulation and computation Vol. 52; no. 8; pp. 3973 - 3990
Main Authors Sen, Rijji, Upadhyay, S. K.
Format Journal Article
LanguageEnglish
Published Philadelphia Taylor & Francis 03.08.2023
Taylor & Francis Ltd
Subjects
Bayes factor
Bayes model compatibility
Bayes predictive intervals
Carbon fibers
Comparative studies
Cumulative damage
Cumulative damage model
Damage assessment
Fiber composites
Fiber impregnated tows
Fibrous carbon composite
Inverse Gaussian Distribution
Metropolis algorithm
Stress functions
Online AccessGet full text
ISSN0361-0918
1532-4141
DOI10.1080/03610918.2021.1966462

Cover

More Information
Summary:The survival probability of a composite material subject to external stress is governed by the condition that the strength of the material must exceed the applied stress. There are several models proposed in the literature for studying such stress-strength relationships, especially with reference to modeling failures in carbon fiber composites. A strong contender in this group is the inverse Gaussian based cumulative damage model. The present paper outlines the Bayes analysis of the four models of this family, two for each of additive and multiplicative stress functions. Further a comparative study, based on a real data set, has been carried out to propose the best model among them.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0361-0918
1532-4141
DOI:10.1080/03610918.2021.1966462