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Das ANSLC Programm zur Abschätzung zyklischer Werkstoffkennwerte

ANSLC artificial neural strain life curves
: Dsoki, C. el; Hanselka, H.; Kaufmann, H.; Röbig, A.


Materialwissenschaft und Werkstofftechnik 40 (2009), No.8, pp.612-617
ISSN: 0933-5137
Journal Article
Fraunhofer LBF ()
zyklischer Kennwert; Ramberg-Osgood; Manson-Coffin-Basquin; Abschätzungsmethode

A durable design for linear flow split sheet components requires suitable methods and transferability criteria which are not yet available for bifurcated structures. Knowledge of the cyclic material behaviour is essential for this. For this reason, the cyclic material parameters are determined as a function of the product's properties (level of deformation, microstructure, surface finish, residual stresses) and different loading parameters. However, since the determination of the cyclic parameters is associated with considerable experimental effort and costs, a cost-effective and easy method is sought to determine these parameters. A very promising approach for this is the application of artificial neural networks (ANN) [1, 2, 3, 4, 5] since they have the ability to generate the influences on the fatigue strength from the manufacturing and environmental parameters using sensibly selected input parameters. They offer the possibility to access acquired knowledge and to thus construct a multidimensional map based on a few tests.