AISI 316L stainless steels are widely employed in applications where durability is crucial. For this reason, an accurate prediction of its behaviour is of paramount importance. In this work, the spotlight is on the cyclic response and low-cycle fatigue performance of this material, at room temperature. Particularly, the first aim of this work is to experimentally test this material and use the results as input to calibrate the parameters involved in a kinematic and isotropic nonlinear plasticity model (Chaboche and Voce). This procedure is conducted through a newly developed calibration procedure to minimise the parameter estimates errors. Experimental data are eventually used also to estimate the strain–life curve, namely the Manson–Coffin curve representing the 50% failure probability and, afterwards, the design strain–life curves (at 5% failure probability) obtained by four statistical methods (i.e., deterministic, “Equivalent Prediction Interval”, univariate tolerance interval, Owen’s tolerance interval for regression). Besides the characterisation of the AISI 316L stainless steel, the statistical methodology presented in this work appears to be an efficient tool for engineers dealing with durability problems as it allows one to select fatigue strength curves at various failure probabilities depending on the sought safety level.

An elastica-type analytical solution to the problem of large deflections of slightly curved spring-strips, fixed at one end and loaded at the other with couples and with forces of various directions, is obtained in this work. The main methods of calculation of elliptic integrals are studied, and the limits of their applicability are established as functions of the required degrees of accuracy and of the loading conditions of the spring-strips. The results obtained with the proposed method are then compared to particular cases already developed in the literature with different approaches. It is shown that in all the cases considered the method permits accurate results to be obtained.