A practice for analyzing some raw data from fatigue crack growth tests, carried out on specimens obtained from a railway component (wheel), is presented. Despite the data sample is small, it allows to identify the material parameters of the “threshold” propagation model that make this latter amazingly realistic for the examined material. The proposed analysis method is based on the Evolutionary Algorithms theory and uses raw data obtained from C(T) specimens instrumented with crack gauges
Analysis Method of Crack Propagation Data by Genetic Algorithms / Grasso, Marzio; Penta, Francesco; Pinto, Paolo; Pucillo, Giovanni Pio. - STAMPA. - 452-453:(2011), pp. 869-872. ( 9th International Conference on Fracture and Damage Mechanics, FDM 2010 Nagasaki; Japan 20-22 Settembre 2009) [10.4028/www.scientific.net/KEM.452-453.869].
Analysis Method of Crack Propagation Data by Genetic Algorithms
GRASSO, MARZIO;PENTA, FRANCESCO;PINTO, PAOLO;PUCILLO, Giovanni Pio
2011
Abstract
A practice for analyzing some raw data from fatigue crack growth tests, carried out on specimens obtained from a railway component (wheel), is presented. Despite the data sample is small, it allows to identify the material parameters of the “threshold” propagation model that make this latter amazingly realistic for the examined material. The proposed analysis method is based on the Evolutionary Algorithms theory and uses raw data obtained from C(T) specimens instrumented with crack gaugesI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
