Prediction of microstructural evolution during hot forging

Manufacturing Rev. 2014, 1, 6 Ó F. Chen et al., Published by EDP Sciences, 2014 DOI: 10.1051/mfreview/2014006 Available online at: http://mfr.edp-open.org OPEN REVIEW ARTICLE ACCESS Prediction of microstructural evolution during hot forging Fei Chen*, Zhenshan Cui, and Jun Chen Institute of Forming Technology and Equipment, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, PR China Received 31 March 2014 / Accepted 10 June 2014 Abstract – Microstructural evolution, which is governed by temperature, strain and strain rate during hot forging, is a key factor influencing mechanical properties. Understanding the microstructural evolution of metals and alloys in hot forging has a great importance for the designers of metal forming processes. The principal objective of this paper is to provide an overview of the models for the prediction of microstructural evolution for metals and alloys during the hot forging process. In this review paper, the models are divided into four categories, including the phenomenological, physically-based, mesoscale and artificial-neural-network models, to introduce their developments, prediction capabilities and application scopes. Additionally, some limitations and objective suggestions for the further development of the modelling of microstructural evolution during hot forging are proposed. Key words: Forging, Microstructure, Recrystallization, Modelling 1 Introduction Hot forging can serve to tailor the service properties of metals through microstructure evolution, in addition to altering their shape [1, 2]. On the one hand, an optimal design scheme for hot forging must ensure the required shape and size; on the other hand, the most important issue in forging is that the forging scheme must meet the parts made in respect of their performance requirements such as strength and toughness as well as resistance to corrosion, etc., of high temperature parts, as well as the high-temperature tensile properties of performance, creep resistance and thermal fatigue properties. Metallography has indicated that grain size has a decisive effect on the above mechanical properties of the forgings after the chemical composition of the specific raw material has been determined, with regard to such as large power-station turbine rotors [3] and aeronautical blades [4]. In most metals and alloys, the grain size of forgings are mainly determined by forging and heat-treating processes, where a fine-grained microstructure produced by forging plays a key role in obtaining a fine-grained microstructure in the following heat-treatment process. Therefore, study of microstructural evolution during the forging process, and furthermore, prediction of the grain-size distribution of forgings, have important practical significance. This has become a very important consideration in the design and optimization of a forging scheme: it is also the cutting edge research in the field *e-mail: of thermal processing and significantly affects the future developments in this field. Generally, hot forging is often classified according to the forging equipment and how the forging operation is performed, i.e. by die forging or free forging. Microstructural evolution during die forging is mainly dominated by the following two steps: heating and single-hit deformation. In the heating process, the heating temperature, heating rate and holding time tremendously influence the grain evolution. For single-hit deformation, dynamic recrystallization (DRX), which affects the grain-size distribution of the final forging for metals with moderate-to-low stacking fault energy, plays a dominant role in the microstructural evolution at elevated temperature. Over the past half century, a number of research groups have attempted to secure better understanding and controlling of the grain evolution for various metal and alloys during heating and DRX, and a series of phenomenological models have also been developed to predict grain evolution during heating and DRX [5–29]. In recent years, with the rapid development of computer technology, mesosopic models have also been proposed to predict microstructural evolution during DRX. In distinct comparison to die forging, multi-hitting and multi-heating are the typical characteristics of free forging, such as in the production of heavy forgings, during which DRX, static recrystallization (SRX) and meta-dynamic recrystallization (MDRX) are important microstructural evolution mechanisms. The hotdeformed grains exhibit a quite different and more complex recrystallization behavior than that for single-blow deformed grains. In order to predict grain evolution during complex This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 2 F. Chen et al.: Manufacturing Rev. 2014, 1, 6 recrystallization processes, many empirical, semi-theoretical and mesocopic models for the grain evolution have been proposed by metallurgical and material researchers. Among these models, the phenomenological model that describes the relationship of austenite grain size with temperature, strain and strain-rate have been used practically [5, 6]. At the same time, with the use of the finite-element (FE) method, simulations coupled with the developed phenomenological models assumed a prominent role in investigation of the processing parameters such as temperature, strain and strain-rate. The following mainly presents a critical review of the methods for the prediction of microstructural evolution during the hot-forging process. Generally speaking, the methods are mainly divided into the following four categories: 1. Phenomenological model. This expresses mathematically the results of observed phenomena without paying detailed attention to their fundamental significance. In other words, the phenomenological model lacks a physical background that accounts for experimental observations. Additionally, the coefficients in the model are obtained by a regression method based on extensive experimental observations [5–42]. As a result, the model can only be used within a specified range, otherwise the use of the model beyond the range of the sample data is likely to result in serious error. Therefore, it is imperative to update the model parameters based on the details of the hot-forging scheme employed. 2. Physically-based on internal variable model. This accounts for physical aspects of the material behaviour, such as the constitutive behaviour and the dynamic microstructural development in the hot working of metals and alloys [43–45]. According to different scale lengths (SL), grain size, volume fraction of different types of grain, volume fraction of phases, sub-grain size, second-phase particles and dislocation density can be used as the mesoscale and microscale internal state (...truncated)