Search

Digital twins are the most important parts of Cyber-Physical Systems (CPSs), and play a crucial role in the realization of the Metaverse. Therefore, two important factors: flexibility and adaptability, need to be focused on digital twinning systems. From a virtual perspective, constructing buildings, structures, and mechanisms in the Metaverse requires digital materials and components. Hence, accurate and reliable digital models can guarantee the success of implementation, particularly when it comes to completing physical twins in the real world. Accordingly, four Machine Learning (ML) methods to make digital twins of an advanced 42SiCr alloy considering all of its uncertainties and non-linearities have been employed in this paper. These ML methods accelerate the digitalization of the proposed alloy and allow users to employ them for a wide range of similar metals. Based on this technique, producers can borrow these virtual materials and build their structures in the Metaverse. This way, if the properties of the materials were satisfactory, they might buy them and start manufacturing their products. As a case study, we focus on digital twining of an 42SiCr steel with some influential factors in its mechanical properties, making the nature of the alloy complex. Processes, including heat treatment, may restore the material’s deformability; however, Quenching and Partitioning (Q&P) not only eliminates the impact of cold forming but also provides advanced high-strength steel (AHSS) properties. In this research, the combined impacts of different Q&P treatments were investigated on the mechanical properties of 42SiCr steel alloy. The results have shown the acceptability and accuracy of the proposed ML methods in realizing the digital twins of this complex alloy.

A series of experiments was conducted by quenching and partitioning (Q-P) heat-treated alloys to investigate the effect of cooling intensity on the mechanical properties of low alloy steel 42SiCr. By applying a conventional heat treatment, reasonable high strength can be achieved; however, the alloys become more brittle. To obtain an optimal balance, advanced heat treatment methods like the Q-P process can be used. It consists of quenching to temperatures between martensite start and martensite finish temperatures and holding, which leads to the stabilization of untransformed austenite by carbon partitioning. The martensitic microstructure is then formed with a small volume fraction of retained austenite embedded on a microscopic scale. The material’s deformability can be significantly improved by using such heat treatment processes. Moreover, to improve advanced high strength properties (AHSS), an additional Q-P process can be applied, which leads to erasing the influence of cold forming as well as enhancement of the mechanical properties. Several combinations of the Q-P process with/without partitioning were performed with various cooling rates for both heat treatment methods. Ultimate Tensile Strength (UTS), Ductility and Hardness (HV10), as well as the microstructure of the alloys, are compared to evaluate the cooling intensity effects. The cooling rate is found not to be a significant factor influencing mechanical properties, which is a crucial point for practical material heat treatment.

Existing oxide dispersion strengthened (ODS) alloys are, besides Ni-based superalloy single crystals, the most creep-resistant materials. The creep resistance of the ODS alloys may, moreover, be significantly improved thanks to increasing the volume fraction of the nano oxides by more than one order of magnitude so that the oxides play a decisive role in strengthening. The present experimental study deals with two systems of such a high-volume fraction of nano oxides, namely, the Fe-11Al-1O and Fe-17Cr-7Al-4Y2O3 systems prepared by mechanical alloying and hot rolling leading to a rather stable fine-grained microstructure. This microstructure undergoes static recrystallization at high temperatures. The kinetics of static recrystallization and coarsening of nano oxides in recrystallized grains is determined for both systems. The difference in kinetics of coarsening of Al-based and Y-based oxides in the Fe-11Al-1O and Fe-17Cr-7Al-4Y2O3 systems is expressive and predetermines the Fe-17Cr-7Al-4Y2O3 system or similar ones to become the new leading system among creep- and oxidation-resistant materials for applications up to 1200 °C.

This paper examines how the initial austenite grain size in quench and partitioning (Q-P) processes influences the final mechanical properties of Q-P steels. Differences in austenite grain size distribution may result, for example, from uneven heating rates of semi-finished products prior to a forging process. In order to quantify this influence, a carefully defined heat treatment of a cylindrical specimen made of the Q-P-capable 42SiCr steel was performed in a dilatometer. Different austenite grain sizes were adjusted by a pre-treatment before the actual Q-P process. The resulting mechanical properties were determined using the upsetting test and the corresponding microstructures were analyzed by scanning electron microscopy (SEM). These investigations show that a larger austenite grain size prior to Q-P processing leads to a slightly lower strength as well as to a coarser martensitic microstructure in the Q-P-treated material.