This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
Integrating the Results from Process Simulation into Fatigue Life Prediction
Technical Paper
2007-26-071
ISSN: 0148-7191, e-ISSN: 2688-3627
Annotation ability available
Sector:
Event:
SIAT 2007
Language:
English
Abstract
In the last decades fatigue life prediction has reached a high level in respect to practical handling and accuracy. Deviations between numerical results and test results in terms of cycles till crack initiation are resulting mostly from insecure or lacking input data. On the one hand, the accuracy of Finite Element Analyses results gets better and better because of greatly increasing computer power and mesh density. Whereas on the other hand, the situation is much more critical regarding load data and especially regarding local material properties of the components (compared to specimen data).
But in the last few years also the possibilities of process simulation have improved in such, that at least a few local material properties or quality indicators can be predicted with sufficient reliability. While for instance the detailed simulation of the welding process is still difficult during the common development process, sheet-metal forming and casting simulations are already widely applied to optimize properties of components in an early stage of development.
Therefore, the idea to integrate process simulation into fatigue analysis is reasonable, because both simulation technologies represent a current state of the art. This integration has recently been realised both for forming simulation of steel sheet-metal as well as sand and die casting of aluminum and magnesium.
The distribution of the effective plastic strain is an output of forming simulation which can be used as an indicator for local material properties. The secondary dendrite arm spacing (SDAS), whose distribution is an output from casting simulation, correlates significantly with porosity and endurance limit. For die casting, a pore free surface layer can be accounted for.
All those parameters can be used as an input for fatigue analysis and practical examples demonstrate the influence on the predicted results.
Recommended Content
Authors
Citation
Dannbauer, H., Gaier, C., and Aichberger, W., "Integrating the Results from Process Simulation into Fatigue Life Prediction," SAE Technical Paper 2007-26-071, 2007, https://doi.org/10.4271/2007-26-071.Also In
References
- Brune, M. et al. DVM-Report 123 Cologne, Germany 119 134 Oct. 1997
- Steinwender, G. et al. “Fatigue Simulation of Multi-axially Loaded Suspension Components” 7th Aachen Colloquium Germany 1998
- Dannbauer, H. et al. “Virtual Fatigue Optimisation of Automotive Structures” Cambridge 2003
- Gaier, C. et al. “Theory and Application of FEMFAT - a FE-Postprocessing Tool for Fatigue Analysis” Proc. 7th International Fatigue Congress Beijing, China 821 826 June 1999
- Gaier, C. et al. 173 177 1999
- Haas, A. Johannes Kepler University Linz 1999
- Masendorf, R. TU Clausthal 2000
- Hatscher, A. TU Clausthal 2004
- Buxbaum, O. Stahleisen-Verlag Düsseldorf 1986
- Puff, M. FH Wiener Neustadt 2002
- Aichberger, W. FH Wiener Neustadt 2005
- Gaier, C. et al. “Coupling Forming Simulation and Fatigue Life Prediction of Vehicle Components” NAFEMS Word Congress Malta May 2005
- Eichlseder, W. “Influence of Dendrite-Arm-Spacing on Fatigue Life” 4th FEMFAT User Meeting Steyr/Austria May 2003
- Minichmayr, R. Eichlseder, W. 70 75 2003
- Wang, Q. G. et al. “Fatigue Behaviour of A356/A357 Aluminum Cast Alloys. Part II - Effect of Micro Structural Constituents” Journal of Light Metals I 2001
- Zhang, G. “Consideration of Porosity in Fatigue Life Analysis of Aluminum-Die-Castings” 4th FEMFAT User Meeting Steyr/Austria May 2003
- Nefischer, P. et al. Aachen 2003
- FEDIS User Manual 2005 Engineering Center Steyr