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In general, formed components are lightweight as well as highly economic and resource efficient. However, forming-induced ductile damage, which particularly affects the formation and growth of pores, has not been considered in the design of components so far. Therefore, an evaluation of forming-induced ductile damage would enable an improved design and take better advantage of the lightweight nature as it affects the static and dynamic mechanical material properties. To quantify the amount, morphology and distribution of the pores, advanced scanning electron microscopy (SEM) methods such as scanning transmission electron microscopy (STEM) and electron channeling contrast imaging (ECCI) were used. Image segmentation using a deep learning algorithm was applied to reproducibly separate the pores from inclusions such as manganese sulfide inclusions. This was achieved via layer-by-layer ablation of the case-hardened steel 16MnCrS5 (DIN 1.7139, AISI/SAE 5115) with a focused ion beam (FIB). The resulting images were reconstructed in a 3D model to gain a mechanism-based understanding beyond the previous 2D investigations.

Nickel-based filler metals are frequently used in high temperature vacuum diffusion brazing for austenitic stainless-steel joints when components are subjected to high static or dynamic loads, corrosive environments and elevated temperatures. Due to melting point depressing metalloids such as silicon and boron, hard and brittle intermetallic phases are formed during the brazing process depending on the diffusion mechanisms. These brittle phases significantly affect mechanical and corrosive properties of the compounds. To quantify the influences of their amount, morphology and distribution, deep learning image segmentation was applied to segment these phases of the athermal solidification zone and the diffusion zone. Subsequently, characteristic microstructure parameters were calculated from these. The parameters of six different brazed joint variations were compared with their experimental characterization of mechanical and corrosive properties so that several correlations could be identified. Finally, a layer-by-layer removal of a brazed joint was performed using a focused ion beam, and a 3D model was reconstructed from the generated images to gain a mechanism-based understanding beyond the previous 2D investigations.

As brazed stainless steel components in service often have to withstand cyclic loads in corrosive environments, the corrosion fatigue properties of brazed joints have to be characterised. Application-relevant corrosion fatigue tests in corrosive media are extremely rare for brazed joints and cyclic deformation curves are barely investigated. In this study, fatigue tests of brazed AISI 304L/BAu-4 joints were performed in air and synthetic exhaust gas condensate K2.2 according to VDA 230-214. The fatigue behaviour of the brazed joints was compared to properties of the austenitic base material. Strain, electrical, magnetic, temperature and electrochemical measurement techniques were applied within fatigue and corrosion fatigue tests to characterise the cyclic deformation and damage behaviour of the brazed joints. It was found that the fatigue strength of 397 MPa at 2 × 106 cycles was reduced down to 51% due to the superimposed corrosive loading. Divergent microstructure-related damage mechanisms were identified for corrosion fatigue loadings and fatigue loadings of specimens in the as-received and pre-corroded conditions. The investigations demonstrate the important role of corrosive environments for the mechanical performance of brazed stainless steel joints.