Fatigue Quick Start Guide > Residual Stress > Investigate Mean Stress
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Investigate Mean Stress
As with the S-N method, there are ways with the Crack Initiation method to account for mean stress also. The material properties (cyclic stress-strain and strain-life curves) are derived with zero mean stress (R = minus ­1). The signal used in this exercise has tensile mean stress and R=. Two methods are available for mean stress correction: Smith-Watson-Topper (SWT) and Morrow. SWT is the default and was used in these analyses.
It is not necessary to go back and redefine anything in the original jobs to investigate the effect of mean stress correction. Open the Results... form if it is not already open and set the Action to Optimize and click Apply. When FEFAT comes up in its Design Optimization mode, select Worst Case node, enter a Design Life of 500,000, and click OK. You should see the same fatigue life at the worst case node of about 255,000 fills or 67,000 fills for the first job. Click End to move to the main menu.
 
Hint:  
You can do this with either job (mold or residual). Type in the name of the analysis you want to investigate in the Jobname databox on the main MSC Fatigue job setup form. Any options you select will retrieve the jobname and use it.
Now select Sensitivity analysis | Mean stress correction (all). Then press or double-click the Recalculate switch. Note the life values calculated for each:
 
Table 6‑2
Mean Stress Correction
mold (no residual stress)
mold (with residual stress)
Smith-Watson-Topper
67,000 Fills
225,000 Fills
Morrow
132,000 Fills
323,000 Fills
Strain-Life (none)
546,000 Fills
546,000 Fills
The following observations are made:
1. Note that with no mean stress correction, the life prediction is identical. This is expected since all residual stress is an offset. The only difference between the two analyses is that they have different mean stresses. The actual strain range between the two is identical. If mean stress is not taken into account, the two will give identical answers.
 
2. SWT gives the most conservative answer for predominately tensile signals. SWT tends not to account too well for compressive mean stress. For this reason Morrow gives more conservative answers for compressive signals.
3. Had we not considered mean stress in this example we might have been mislead to think that we had met our design life of 500,000 Fills.
4. Changing the mean stress tends to only have effects in the high cycle fatigue (HCF) region. The effect of mean stress gets washed out with low cycle fatigue (LCF) problems due to the higher plasticity. This can be seen in the Morrow equation for mean stress where the mean stress is accounted for only on the elastic side of the equation. The plot above also illustrates this comparing a strain-life plot with and without Morrow mean stress correction (note only the HCF side is effected).
SWT mean stress correction has the effect of shifting the entire curve and plotting a new parameter on the right hand side of the equation by multiplying by the maximum stress.
To illustrate this last point using FEFAT, do a sensitivity plot from each analysis by increasing the loading. You will see that at higher load levels the answers tend to converge between the two analyses, negating the effect of the residual stress. Follow these instructions assuming you are at the Design Optimization main menu of FEFAT still:
1. Select Original parameters. This resets the analysis to all original settings.
2. Select Sensitivity analysis | Scale Factor. Enter (1,3,0.2) including the parentheses to calculate all factors between one and three by increments of 0.2.
3. Select Recalculate. This will calculate lives based on SWT.
4. Select Change Parameters. Change the Mean Stress Correction to Morrow. Leave all other settings as is.
5. Select Recalculate. This will calculates lives based on Morrow.
6. Select new Jobname and redo these steps with the other analysis job if you wish.
 
Table 6‑3
Scale Factor
mold (no residual stress)
mold (with residual stress)
 
SWT
Morrow
SWT
Morrow
1.0
67,000
132,000
225,000
323,000
1.2
23,700
37,700
51,500
65,500
1.4
10,100
15,300
18,172
21,500
1.6
5,400
7,600
8,400
9,600
1.8
3,200
4,400
4,700
5,200
2.0
2,100
2,800
2,900
3,200
2.2
1,500
1,900
1,950
2,100
2.4
1,100
1,400
1,400
1,500
2.6
820
1,050
1,040
1,100
2.8
640
814
801
860
3.0
515
650
635
680