Stress-strain state analysis and fatigue prediction of D16T alloy in the stress concentration zone under combined tension-torsion load

Abstract

Engineering machines and components are prone
to structural failures during their service time due to certain
technical reasons and also due to some unforeseen
circumstances. The technical breakdowns sometime lead to
high economic imbalance and can also be fatal to life and
property. Predicting the failure and evaluating the breakage
characteristics of engineering components are crucial in
determining the life of the component and also increase
their maintenance and safety in daily life. This research study deals with the modelling and
numerical simulations of an aluminium alloy specimen in
3D stress-state and thereby predicting the fatigue failure of
the material subjected to external cyclic loadings. To
predict the failure of a component, a specimen with an
induced crack can be evaluated through cyclic loading
process. It is based on the fact that the presence of a cracks
tends to modify the stresses present locally on the
component that the elastic deformation and the stresses
attributed with them are totally insufficient for the design
against fracture. It is based on the assumption that the
specimen undergoes complete fracture when the crack
reaches its critical size even though the stress at the critical
crack tip is much lower than the yield stress of the
component. The critical size of the crack is based on the
application of the load and the number of load cycles it
undergoes.
The main aim of this research is to present and
validate the numerical method for the study of the
influence of cracks present in the engineering components.
Finite element method was applied for numerical
simulation. In this study the tension, torsion, combined

tension-torsion and fatigue loads was applied. The
experimental testing data of mechanical properties was
used in numerical simulation as input data. This research
study investigates the three-dimensional stress-strain state
and fatigue prediction of D16T aluminium alloy which is
predominantly used in the aerospace and automobile
industries for their high strength-to-weight ratio and much
better physical properties. The different specimen models
are then analysed and the most efficient one was selected
for the preliminary experimental tests.