Cyclic Plasticity and Low Cycle Fatigue of an AISI 316L Stainless Steel: Experimental Evaluation of Material Parameters for Durability Design

被引:16
|
作者
Pelegatti, Marco [1 ]
Lanzutti, Alex [2 ]
Salvati, Enrico [2 ]
Srnec Novak, Jelena [3 ,4 ]
De Bona, Francesco [2 ]
Benasciutti, Denis [1 ]
机构
[1] Univ Ferrara, Dept Engn, Via Saragat 1, I-44122 Ferrara, Italy
[2] Univ Udine, Dept Polytech Engn & Architecture, Via Sci 208, I-33100 Udine, Italy
[3] Univ Rijeka, Fac Engn, Vukovarska 58, Rijeka 51000, Croatia
[4] Univ Rijeka, Ctr Micro & Nanosci & Technol, Vukovarska 58, Rijeka 51000, Croatia
关键词
AISI; 316L; low-cycle fatigue; plasticity; hardening; softening; 600; DEGREES-C; BEHAVIOR; EVOLUTION; VACUUM; MODEL;
D O I
10.3390/ma14133588
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
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.
引用
收藏
页数:20
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