Papers by Keyword: JMAK

Abstract: Conducting experiments for material modeling is very costly and time-consuming when many parameters are involved, resulting in a large number of test conditions. Therefore, it is expedient to develop algorithms for the iterative identification of optimal test conditions. This method should allow the model to learn automatically so that only a small number of test conditions are selected at the beginning of the model calibration. In order to decide whether further experiments should be carried out and which test conditions need to be investigated, meta-models are generated, and the expected gain score is calculated. The next sample is selected based on the highest score, and this procedure continues until the material models meet a termination criteria. The result from the study shows that the implemented method uses 12 test conditions to generate a phase transformation model for 22MnB5 steel. The material models fitted with the proposed method provide acceptable predictions when compared with experimental data.

Abstract: Heavy-duty components used in the automotive industry, in wind turbines and in many other industrial applications are often produced using hot forging processes. Nowadays the design of hot forging processes aims for the optimization of process efficiency on the one hand and final mechanical product properties on the other hand. Excellent mechanical properties needed for hot-forged components e.g. high load capacity and high fatigue resistance depend on a fine homogeneous microstructure distribution across the final product’s cross-section. Efficiency in hot forging can be optimized by increasing the temperature during processing, which allows for lower forging loads and lower die stresses, thus improving die life in terms of mechanical fatigue. To guarantee for a fine homogenous microstructure across the cross section of the forged good, dynamic recrystallization (DRX) has to be initiated during deformation and Grain Growth (GG) has to be avoided during dwell times and cooling. Due to the high computational costs of finite element simulations an optimization aiming for lowest possible forging loads and finest possible grain sizes is very time-consuming. In this paper a Response Surface Model (RSM) of the forging process is introduced, which allows for much faster evaluation of the outcome of forging simulations, albeit by interpolation of simulation results, and thus allows for optimization. The information required to create the RSM is obtained by Design Of Experiments (DOE) techniques using an FE-model of the forging process which was calibrated earlier. The process variables considered include the initial temperature of the billet and the die kinematics. Subsequently, an optimization algorithm is combined with the RSM to find the design variables giving minimum possible loads during deformation and finest possible grain sizes in the forged product. The RSMs results are validated by the use of the existing FE-model.

Abstract: Ring rolling is an incremental bulk forming process. Hence, the process consists of a large number of alternating deformations and dwell steps. For accurate calculations of material flow and thus ring geometry and rolling forces in hot ring rolling processes, it seems necessary to consider material softening due to static and post dynamic recrystallization which could occur between two deformation steps. In addition, due to the large number of cycles, the modeling results, especially the prediction of grain size, can easily be affected by uncertainties in the input data. However, for small rings and ring material with slow recrystallization kinetics, the interpass times can be short compared to the softening kinetics and the effect of softening can be so small, that microstructure evolution and the description of the materials flow behavior can be de-coupled. In this paper, a semi-empirical JMAK-based model for a stainless steel (1.4301/ X5CrNi18-9/ AISI304) is presented and evaluated by the use of experiments and other investigations published in [1],[2]. Finite Element (FE) simulations of a ring rolling process with a high number of ring revolutions and thus multiple, incremental forming steps were conducted based on ring rolling experiments. The FE simulation results were validated with the experimentally derived rolling force and evolution of ring diameter. The microstructure evolution was calculated in a post processing step considering the investigated evolution of strain and temperature. In this calculation the interrelations between the fraction of dynamically recrystallized microstructure, the evolution of post-dynamically recrystallized microstructure and the final grain size have been considered. Both, the calculated final microstructure and the evolution of rolling force and ring geometry calculated stand in good agreement with the experimental investigations.

Abstract: The kinetics of static recrystallization in cold rolled ferritic stainless steel sheet tends to slow drastically over the last 10-20% of recrystallization. This has its origins in both the microstructure (deformed grain shape, precipitates) and in the local deformation texture. In this work we have sought to provide a physical explanation for the slow last stages of recrystallization through a texture dependent JMAK model which is informed by the microstructure of the partially recrystallized microstructure. The geometrical assumptions made in developing this JMAK model have been compared to phase field simulations using experimental observations as the source of their starting configuration.

Abstract: The texture and microstructure resulting from heavily drawn and annealed oxygen-free high conducting (OFHC) copper wires have been investigated using several microscopical techniques including orientation imaging microscopy and nano-indentation. In the as-drawn condition, the microstructure and texture were heterogeneous across the wires, and consisted of three distinct concentric regimes: the inner core, the mid section, and the outer region. Whilst the microtexture of the inner core was dominated by a strong <111>+weak<100> duplex fiber texture, the mid section and the outer region had a comparatively weak fiber texture. Analysis using a Taylor-type viscoplasticity model revealed that the weak texture observed in this material was a direct consequence of shear deformation during drawing. The recrystallization kinetics of the wires upon isothermal annealing at various temperature was influenced by the deformation heterogeneity, and can be accurately described by a modified JMAK-Microhardness model. In this approach, the JMAK model is expressed in terms of microhardness data, from which the parameters of the different restoration kinetics were determined.

Abstract: To predict strength evolution of precipitation hardening alloys, a wide range of modelling approaches have been proposed. The most accurate published models are physics-based approaches which use both nanoscale processes with their related constants and parameters, as well as parameters calibrated to one or more macroscale measurements of yield strength of one or more samples. Recent developments in submodels including analytical expressions for volume fraction and size evolution including impingement and coarsening are reviewed. It is also shown that Kampmann-Wagner and JMAK models are generally not consistent with data on the progress of precipitations in the main precipitation hardening Al alloys systems, and improved model formulations are described.