A comparative study of fatigue life prediction of 7020 Al-alloy under  load ratio effect

Mohanty, J R; Das, H C; Mohanty, A C

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Please use this identifier to cite or link to this item: http://nopr.niscpr.res.in/handle/123456789/28784

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DC Field	Value	Language
dc.contributor.author	Mohanty, J R	-
dc.contributor.author	Das, H C	-
dc.contributor.author	Mohanty, A C	-
dc.date.accessioned	2014-05-12T09:20:19Z	-
dc.date.available	2014-05-12T09:20:19Z	-
dc.date.issued	2014-04	-
dc.identifier.issn	0975-1017 (Online); 0971-4588 (Print)	-
dc.identifier.uri	http://hdl.handle.net/123456789/28784	-
dc.description	179-188	en_US
dc.description.abstract	Most of engineering structures and components come across complicated fatigue loading during their service lives. From economical point of view it is essential to predict residual life in order to avoid catastrophic failure by scheduling suitable inspection intervals. In the present investigation, fatigue life of 7020 T7 Al alloy under constant amplitude loading with load ratio effects has been predicted by adopting an ‘Exponential Model’. The performance of the proposed model has been compared with artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS). It is observed that the fatigue life predicted by exponential model is comparatively better with maximum percentage deviation of -0.65% in comparison to ANN and ANFIS which are -4.37% and -2.48% respectively.	en_US
dc.language.iso	en_US	en_US
dc.publisher	NISCAIR-CSIR, India	en_US
dc.rights	CC Attribution-Noncommercial-No Derivative Works 2.5 India	en_US
dc.source	IJEMS Vol.21(2) [April 2014]	en_US
dc.subject	Exponential model	en_US
dc.subject	Fatigue crack growth	en_US
dc.subject	Load ratio	en_US
dc.subject	ANN	en_US
dc.subject	ANFIS	en_US
dc.title	A comparative study of fatigue life prediction of 7020 Al-alloy under load ratio effect	en_US
dc.type	Article	en_US
Appears in Collections:	IJEMS Vol.21(2) [April 2014]

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