Strain accumulation during microstructurally small fatigue crack propagation in bcc Fe-Cr ferritic stainless steel

Strain accumulation was studied by digital image correlation technique (DIC) during microstructurally small fatigue crack propagation in polycrystalline 18%Cr ferritic stainless steel. Load-controlled fatigue testing was performed with R-ratio of 0.1 and frequency 10 Hz. The maximum applied stress was well below the yield stress of the studied material. The effect of the observed strain field on crack growth rate variation is discussed. Fracture surfaces were studied by scanning electron microscopy (SEM) evidencing the connection between the mechanism of the fatigue crack growth, accumulated strain and crack growth rate. Detailed study of fracture surface morphology was carried out by atomic force microscopy (AFM). Results indicate two processes of material damage accumulation and failure during cyclic loading: 1) local shear strain zones form successively ahead of the crack tip, and 2) fatigue crack growth occurs by both single- and multiple-slip mechanisms. The place and intensity of shear strain localization zones vary during the crack growth that is related closely to the local variation of crack growth rate.Peer reviewe

Hydrogen effects on mechanical properties of 18% Cr ferritic stainless steel

Role of microstructure in susceptibility of 18Cr ferritic stainless steel to hydrogen embrittlement was studied. Specimens of the studied steel were charged with hydrogen electrochemically from 0.1 N H2SO4 solution under controlled cathodic potential providing a homogeneous hydrogen distribution over the specimen cross-sections. Thermal desorption spectroscopy analyses were carried out investigating the uptake, trapping and diffusion of hydrogen in the ferritic stainless steel. Microstructural change caused by heat-treatment at 1050 °C and 1200 °C associated preferably with grain size growth from 18 µm to 65 µm and 349 µm, respectively, resulting in significant degradation of the mechanical properties of the studied steel. The effect of the grain size growth on hydrogen susceptibility was studied with constant extension rate test (CERT) performed under continuous hydrogen charging. It is found that hydrogen has a remarkable effect on the elongation to fracture of the Fe-Cr ferrite: in the presence of H elongation to fracture of the steel reduces up to 75% compared to the H-free counterpart. In general, the hydrogen sensitivity of the mechanical properties increases with increase of the mean grain size of the studied ferritic stainless steel. However, the detailed analysis reveals a complicated, non-linear behavior of the hydrogen sensitivity. Scanning electron microscopy (SEM) of the fracture surfaces of the tensile specimens tested during continuous hydrogen charging reveals a quasi-cleavage fracture surface morphology. Hydrogen-induced cracking in the studied 18Cr ferritic steel was studied using electron backscatter diffraction (EBSD) analysis from the side surfaces of the tensile tested specimens.Peer reviewe

Prediction of hydrogen concentration responsible for hydrogen-induced mechanical failure in martensitic high-strength steels

Abstract Hydrogen, at critical concentrations, responsible for hydrogen-induced mechanical property degradation cannot yet be estimated beforehand and can only be measured experimentally upon fracture with specific specimen sizes. In this work, we develop two deep learning artificial neural network (ANN) models with the ability to predict hydrogen concentration responsible for early mechanical failure in martensitic ultra-high-strength steels. This family of steels is represented by four different steels encompassing different chemical compositions and heat treatments. The mechanical properties of these steels with varying size and morphology of prior austenitic grains in as-supplied state and after hydrogen-induced failure together with their corresponding hydrogen charging conditions were used as inputs. The feed forward back propagation models with network topologies of 12-7-5-3-2-1 (I) and 14-7-5-3-2-1 (II) were validated and tested with unfamiliar data inputs. The models I and II show good hydrogen concentration prediction capabilities with mean absolute errors of 0.28, and 0.33 wt.ppm at test datasets, respectively. A linear correlation of 80% and 77%, between the experimentally measured and ANN predicted hydrogen concentrations, was obtained for Model I and II respectively. This shows that for this family of steels, the estimation of hydrogen concentration versus property degradation is a feasible approach for material safety analysis