Yield strength and toughness in steels are directly associated with hot forging processes, especially by controlling austenitic grain size and cooling conditions. The phenomenological JMAK model in macroscale has been applied in different material classes to predict grain size after hot forming. However, on an industrial application, there is still a lack of understanding concerning the synergic effects of strain rate and temperature on recrystallization. This preliminary study aimed at investigating the applicability of coupled semi-empirical JMAK and visco-elastoplastic models in numerical simulation to predict austenitic grain size (PAGS). Hot forging of cylindrical samples of a ferritic-perlitic DIN 20MnCr5 steel was performed followed by water quenching. The main influences, such as temperature, strain and strain rate fields following the recrystallization model were investigated using the subroutine of FORGE NxT 2.1 software. The results were evaluated by comparing experimentally measured and simulated PAGS at process end. The forging process generates different strain and strain rate fields in the workpiece, which in turn lead to a variation in the PAGS and recrystallization fractions. The simulation was able to detect the PAGS variation showing a good agreement between the experimental forging results and the applied model.

It is well recognized the importance of the rheological characterization for the development of the steel in thermomechanical treatments, especially for the mechanical properties improvement of bainitic steels in subsequent hot forging optimization. Therefore, the plastic strain behaviour of a low carbon high silicon bainitic steel was studied through isothermal compression tests using a thermomechanical simulator at temperatures of 1123 K – 1423 K and strain rates of 0.1 – 5 s-1. Arrhenius equation was used to obtain the constitutive constants, which represents the material behaviour of flow stress in high temperature. Besides, work hardening, dynamic recovery, and the JMAK model in the dynamic recrystallization (DRX) of the steel parameters were determined. The second part of this research compared two proposed modified models from the literature, which showed the differences in modelled flow curves behaviour when they are applied for high strain levels. The flow curves were modelled in high strain levels for further implementation in numerical simulation, thus allowing an adjustment of parameters in hot forming processes for this bainitic steel. The proposed models presented an agreement with experimental values. However, only the Avrami equation to DRX showed the dynamic recovery mechanism in high strain levels, which has represented physical behaviour during the thermomechanical process.

Thermo-mechanical treatments using continuous cooling after forging are an established method for producing bainitic steels, mainly because of the elimination of energy intensive additional heat treatment processes. The cooling is usually employed in an uncontrolled manner in the industrial sector, which can be detrimental to the resulting microstructural morphology and, consequently, to the final product properties. In this study, a new controlled two-step cooling route based on the principles of bainitic displacive growth was designed and applied in a 0.18C (wt-%) steel. Inverse finite element method was used on the cooling data to obtain the evolution of temperatures for the samples during cooling, allowing to assess point to point cooling rates. Investigations via X-ray diffraction, optical microscopy analysis and hardness testing revealed a variation of bainitic morphology, namely, the transition from granular bainite to lath-like bainite with relatively high hardness and constituents/phase boundaries than the pre-treated microstructure.

Over the last decades, alloy 718 usage has expanded and requirements imposed by its industrial applications became more critical. The knowledge about grain boundary character distribution (GBCD) in alloy 718 and its effect on properties improvement is mostly built based on iterative processing through cold rolling steps interspersed with solution annealing. Alloy 718 is found in the industry in many different forms and geometries, and fabricated by multiple thermomechanical processes such as wire drawing, rolling, forging or extrusion. The present study focused on understanding how wires respond to deformation mode related to drawing in regard to GBCD evolution, crystallographic orientation, precipitation of δ-phase and grain size. Lastly, assessing the resulting mechanical properties. The findings show that microstructural evolution is a consequence of competing mechanisms such as strain induced boundary migration, recrystallization, grain growth and phase precipitation. The deformation gradient along wire cross section plays an important role in affecting microstructural features, such as δ precipitation, GBCD and microtexture.

The service life of hot forging dies is limited by severe thermomechanical loading that promotes localized plastic deformation, wear, and crack initiation. Conventional numerical assessments are commonly based on equivalent stress fields, which do not explicitly consider the temperature-dependent reduction of tool material strength, often leading to limited correlation between predicted critical regions and actual industrial failure locations. This work proposes a mechanically grounded post-processing methodology based on the Plasticity Ratio, defined as the ratio between effective stress and temperature-dependent yield strength, to evaluate local proximity to plastic yielding. The approach integrates thermomechanical finite element simulations, experimentally measured microhardness profiles, and industrial validation. Applied to gas-nitrided AISI H13 finishing dies, the method incorporates the hardness gradient of the diffusion zone through a resistance increment factor ( $$k_{\text {nit}} \approx 1.23$$ ), enabling correction of local mechanical severity without remeshing or constitutive remodeling. The analysis shows that less than 2% of the die surface governs failure initiation. A power-law relationship between loading severity and durability predicted tool life improvement consistent with the experimentally observed 83.6% increase under industrial conditions. The framework provides a computationally efficient strategy for predicting durability gains promoted by surface treatments in forming tools.