• Calmunger, Mattias
• Moshfegh, Bahram
• Kuběna, Ivo
• Romanov, Pavel
• Jahedi, Arvid

Abstract

<jats:p> Soil‐working tools in agriculture are made of boron‐containing steels with high wear resistance and hardenability. Nevertheless, these tools are subject to high impacts, abrasive wear, and fatigue and are therefore prone to failure. To combine varying levels of properties within one component in as‐quenched condition can be beneficial for such products. To obtain this property variation, a component must undergo a complex and controllable cooling. Therefore, the aim of this work is to obtain a microstructure gradient along two 15 mm‐thick steel plates in a newly developed test rig by water jet impingement technique to confirm its controllability and flexibility. Furthermore, a quenching simulation model is created for hardness prediction using phase transformation data from a machine learning tool. Microstructure variation is observed using light optical microscopy and the electron backscatter diffraction technique. Mechanical properties are studied through tensile tests and hardness measurements and are also compared with simulation results. The 0.27 mass% C steel sample is obtained in almost fully martensitic state transitioning to a softer ferritic/bainitic condition, while the 0.38 mass% C steel sample results predominantly into a fully hardened martensitic state and slightly shows ferritic and bainitic features along the sample. The quenching simulation model shows promising hardness prediction for both steels.</jats:p>

Topics

• impedance spectroscopy
• microstructure
• phase
• simulation
• wear resistance
• steel
• fatigue
• hardness
• Boron
• electron backscatter diffraction
• optical microscopy
• quenching
• machine learning