Fatigue Crack Growth Prediction of Band Overloaded 7075-T651 Aluminium Alloy by Exponential Model and Gamma Model

Abhinay, Seelamanthula V (2015) Fatigue Crack Growth Prediction of Band Overloaded 7075-T651 Aluminium Alloy by Exponential Model and Gamma Model. MTech by Research thesis.

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Abstract

Fatigue is the most important cause of mechanical failure of engineering structures and components. In majority of the cases the stress amplitude does not remain constant and undergoes variation with time. Fatigue crack growth in structures/components subjected to variable amplitude loading is complex. Fatigue crack growth under multiple overloads is the building block to study the effect of variable amplitude loads. In the present investigation an attempt has been made to study the effect of single overload and band overloads on fatigue crack growth behaviour of 7075-T651 aluminium alloy at room temperature. The tests were conducted on compact tension specimens. Single overload and band overloads were introduced during constant amplitude fatigue loading in mode-I condition. The maximum retardation occurred on introduction of band overload consisting 7 overload cycles. It is known that the introduction of overload cycles alters the crack growth behaviour. In the present work an “Exponential model” and a “Gamma model” have been developed to predict crack growth rate and fatigue life of specimens subjected to overload cycles. The predicted results by both the models are found in good agreement with the experimental data.

Item Type:Thesis (MTech by Research)
Uncontrolled Keywords:Fatigue crack growth rate, Overload, Band-overload, 7075 T651 aluminium alloy, Exponential model, Gamma model
Subjects:Engineering and Technology > Metallurgical and Materials Science > Mechanical Alloying
Divisions: Engineering and Technology > Department of Metallurgical and Materials Engineering
ID Code:6953
Deposited By:Mr. Sanat Kumar Behera
Deposited On:25 Jan 2016 14:00
Last Modified:25 Jan 2016 14:30
Supervisor(s):Verma, B B and Ray, P K

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