Effect of Overloads on Fatigue Performance

Strain-life fatigue data are most often developed under conditions of steady state constant amplitude. This provides a means of comparing the fatigue performance of various combinations of steel grade and processing. Many components, however, often experience random “spike” loads, or “overloads”, which are over and above those encountered during otherwise constant amplitude conditions. Automotive suspension and transmission components would be typical examples.

To simulate the effects of such overloads on fatigue performance, a fatigue testing protocol was implemented in which high amplitude cycles are inserted between groups of low amplitude cycles. The test protocol is shown schematically in Figure 1. As can be seen, the load history consists of repeated blocks, each with one fully reversed overload cycle and a series of small cycles with the same maximum strain as the overload cycle. An effective strain-life curve is determined for the small cycles, and then compared to results obtained under fully reversed constant amplitude conditions.

No. 26 Figure 1.jpgFigure 1

In the previous post, strain-life data were presented for a microalloyed steel, 1538MV. Data from both hot rolled bar stock and forgings were discussed. The hot rolled bar stock product form, chemical composition is shown in Table 1, and mechanical properties are shown in Table 2.



Comparative strain-life fatigue properties for both constant amplitude and overload testing are given in Figure 2.  The below graph presents the strain-life curve for the constant amplitude data and the effective strain-life curve developed from the load history (Figure 1).

No. 26 Figure 2.jpgFigure 2

It’s evident the insertion of overload cycles into the load history results in a significant reduction in fatigue life. Thus the performance of components subject to random overloads during fatigue loading is likely to reduce. There will be more discussion of this effect in future posts.

This entry was posted in News and tagged , , , . Bookmark the permalink.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s