Fatigue life prediction is a common task for engineers. How do we make sure that we are doing the right thing? There are many codes and FE tools available for fatigue analysis. Are those tools doing it right?
This article presents an overview of common mistakes made in fatigue analysis.
1. Misunderstanding fatigue
Crack initiation and crack growth are driven by cyclic loads, constant stresses will not cause fatigue crack initiation.
2. Confusing stress amplitude and stress range
In general, S-N curves are given with stress amplitudes vs. number of cycles to failure. The stress amplitude is defined as half the stress range. For welded joints, S-N curves are usually given with the stress range. An error by factor 2 in stresses is therefore easily made.
Sometimes, the maximum stress level instead of the stress amplitude is used in S-N curves.
3. Ignoring mean stress and residual stresses
Although fatigue life is determined by the cyclic character of stresses (i.e. stress amplitude), the mean stress has an effect as well. An increasing mean stress is unfavourable for the fatigue life, a decreasing mean stress is favourable.
Note that residual stresses at the critical location (pre-stresses, assembly stresses, etc.) have the same effect as mean stresses of the cycle.
4. Deriving fatigue data from static properties
The fatigue strength depends on much more factors than the static strength. Surface conditions, stress concentrations, component size, loading type, mean stress level, environment, etc., have a large impact on the fatigue properties.
5. Applying mean stress correction on stresses instead of fatigue limit
S-N curves are often given for a mean stress level of zero (R=-1). Mean stress corrections (Gerber, Goodman, Schütz, FKM) are available to estimate the fatigue data for mean stress levels other than zero. Note that these estimations are to be applied on the fatigue limit.
6. Assuming welds behave like base material
Welding ruins the carefully built micro-structure of the base material but only locally at the weld. In the base metal the material properties are determined by the processing of the material. In the weld zone the material processing is overruled by the welding process.
7. Incorrect cycle counting
Just counting the consecutive cycles like in the figure below may lead to a large overestimation of the fatigue life.
The best way to count cycles is “Rainflow Counting”. This method roughly implies that small cycles are taken from large cycles and counted separately, whereas the remaining large cycles are counted as well.
8. Underestimating small cycles
Small cycles (i.e. cycles with a small amplitude) lead to longer fatigue lives than large cycles (i.e. cycles with a large amplitude). This fact may lead to the incorrect conclusion that small cycles can be neglected.
9. Trusting the Miner rule
Damage accumulation according to the Miner rule is using this equation:
In reality, fracture occur at values of accumulated damage between 0.3 and 3 and even outside this range.
10. Using fixed S-N curve slope for local stresses
Always be aware that a local stress can be any combination of global stress and Kt. Different Kt‘s imply different gradients of the S-N curve. Furthermore, the gradient depends on the stress ratio as well.
11. Using S-N data for LCF
In the LCF (Low Cycle Fatigue) region, fatigue is driven by cyclic strains. The material behaviour in that region is dominated by plastic deformation, non-linear relation between strains and stresses. An S-N curve describes fatigue in the HCF (High Cycle Fatigue) region, i.e. elastic material behaviour and a linear relation between strains and stresses.
For HCF, sometimes the elastic part of the e-N curve is used. It is argued that because of the linear elastic material behaviour in that region, the e‑N curve is in fact a S-N curve. Since the strains are local strains, and the e‑N curve is based on unnotched specimens, this approach leads to the same problems as described in section 10.
12. Using equivalent stresses like Von Mises
Fatigue damage is propagating perpendicular to the largest principal stress range, therefore this stress range, and not some equivalent stress, determines fatigue behaviour.
13. Using scatter data from laboratory tests for actual service applications
Fatigue always shows a lot of scatter. This scatter is caused by (1) variability in material properties, (2) variability in surface conditions (process/manufacturing), (3) variability in loading, and (4) variability in environment. S-N data obtained from laboratory tests only cover the first two causes.
14. Ignoring surface conditions
Surface conditions have a large impact on fatigue behaviour but are easily neglected. S-N curves are often established using nicely manufactured specimens. Actual production of your components may be completely different. This difference should be taken into account.