In recent years, experimental tests investigating properties of materials in gigacycle regime have suggested modifications to well-known statistical fatigue life models. Classical fatigue life models based on a single failure mode and on the presence of the fatigue limit, have been integrated by models that can take into account the occurrence of two failure modes (duplex S-N curve). Duplex S-N models involve a number of unknown parameters that must be statistically estimated from experimental data. The present paper proposes a simplified and automated procedure for statistical parameter estimation. Parameter estimation is carried out by applying the Maximum Likelihood Principle and by taking into account the possible presence of runout specimens with unequal number of cycles. The procedure is applied to experimental datasets taken from the literature. The application of the procedure permits to estimate different key material parameters (e.g., the characteristic parameters of transition stress and fatigue limit), as well as to statistically predict the failure mode of each tested specimen.

Statistical estimation of duplex S-N curves / Paolino, Davide Salvatore; Tridello, Andrea; Chiandussi, Giorgio; Rossetto, Massimo - In: Advances in Very High Cycle FatigueSTAMPA. - [s.l] : Trans Tech Publications, 2016. - ISBN 978-303835575-5. - pp. 285-294 [10.4028/www.scientific.net/KEM.664.285]

Statistical estimation of duplex S-N curves

PAOLINO, Davide Salvatore;TRIDELLO, ANDREA;CHIANDUSSI, Giorgio;ROSSETTO, Massimo
2016

Abstract

In recent years, experimental tests investigating properties of materials in gigacycle regime have suggested modifications to well-known statistical fatigue life models. Classical fatigue life models based on a single failure mode and on the presence of the fatigue limit, have been integrated by models that can take into account the occurrence of two failure modes (duplex S-N curve). Duplex S-N models involve a number of unknown parameters that must be statistically estimated from experimental data. The present paper proposes a simplified and automated procedure for statistical parameter estimation. Parameter estimation is carried out by applying the Maximum Likelihood Principle and by taking into account the possible presence of runout specimens with unequal number of cycles. The procedure is applied to experimental datasets taken from the literature. The application of the procedure permits to estimate different key material parameters (e.g., the characteristic parameters of transition stress and fatigue limit), as well as to statistically predict the failure mode of each tested specimen.
2016
978-303835575-5
Advances in Very High Cycle Fatigue
File in questo prodotto:
Non ci sono file associati a questo prodotto.
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2624711
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo