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Young's modulus for ferritic and austenitic steel at high temperatures is typically acquired through acoustic emission tests. In this study, we applied an inverse solution method to consider the effect of a temperature gradient on samples under experimental conditions. Wachman model, Varshni models, and power model were used to describe the influence of temperature on the sound velocity of steel. The constants for these equations were acquired using an optimization scheme that minimized the error between calculated and measured travel times of sound in the samples. Using equations developed for the change in velocity under various temperatures, we calculated Young's modulus at low and high temperatures with acceptable accuracy.This method is non-destructive, and can be applied to measure Young's modulus at different temperatures using a single sample. The acquired Young's modulus values were compared with the results of a modified uniaxial tensile test that accurately measures strain at elevated temperatures. The results showed good agreement between Young's modulus values obtained using the two methods, demonstrating that incorporating the non-linear dependency of the sound velocity on temperature in Young's modulus calculations leads to higher accuracy at low and high temperatures.

The static recrystallization (SRX) behavior of 42CrMo steel was investigated by a non-isothermal hot compression test. The conventional empirical equation for SRX was applied to a finite element (FE) simulator using a nonconventional manner of parameter characterization. Parameter characterization was conducted by applying the FE-coupled optimization method to cylinder compression, which is an axisymmetric upsetting process. An accurate and practical flow stress model was used to precisely determine the critical strain value and define the instant when SRX occurred. The results revealed that the microstructural evolution during SRX was substantially influenced by temperature, strain rate, degree of deformation, and initial austenite grain size. The predicted recrystallized SRX grain sizes exhibited good agreement with the measured values when the model's parameters for the calculation of grain size were obtained using a FE-coupled optimization scheme.

We present a direct method to calculate by which to calculate flow-related dynamic recrystallization (DRX) kinetic parameters, including the peak strain and the strain at 50% DRX which are essential when predicting microstructural evolution. The method is based on an accurate general description of flow curves using the general and improved C-m models in which C and m are defined, at various strains and temperatures, as functions of the strain rate. The method eschews mathematical modeling of these parameters when determining the volume fraction of dynamically recrystallized grains and greatly increases the practical utility of microstructural prediction. A finite element approach based on the direct method and the Avrami kinetic model is utilized to reveal the DRX behavior of the magnesium alloy AZ91D. A comparison among our present approach, other approaches, and experiments reveals that the new method predicts the DRX kinetics and the grain sizes during microstructural evolution with remarkable accuracy.

An investigation of austenite grain growth (AGG) during the isothermal heat treatment of low-alloy steel is conducted. The goal is to uncover the effect of time, temperature, and initial grain size on SA508-III steel grain growth. Understanding this relationship enables the optimization of the time and temperature of the heat treatment to achieve the desired grain size in the studied steel. A modified Arrhenius model is used to model austenite grain size (AGS) growth distributions. With this model, it is possible to predict how grain size will change depending on heat treatment conditions. Then, the generalized reduced gradient (GRG) optimization method is employed under adiabatic conditions to characterize the model’s parameters, providing a more precise solution than traditional methods. With optimal model parameters, predicted AGS agree well with measured values. The model shows that AGS increases faster as temperature and time increase. Similarly, grain size grows directly in proportion to the initial grain size. The optimized parameters are then applied to a practical case study with a similar specimen size and material properties, demonstrating that our approach can efficiently and accurately predict AGS growth via GRG optimization.

In this study, we present a new method for obtaining the parameters of the Johnson-Mehl-Avrami-Kolmogorov equation for dynamic recrystallization grain size. The method consists of finite-element analysis and optimization techniques. An optimization tool iteratively minimizes the error between experimental values and corresponding finite-element solutions. Isothermal backward extrusion of the AA6060 aluminum alloy was used to acquire the main parameters of the equation for predicting DRX grain size. We compared grain sizes predicted using optimized and reference parameters with experimental values from the literature and found better agreement when the optimized parameters were applied.

In this study, a promising model is presented to describe the flow stress curves with acceptable accuracy as well as generality. In this model, peak strain, peak stress, steady-state stress and hardening and softening constants are uncoupled and expressed as either bi-linearly interpolated or closed-form functions of temperature and strain rate. A practical method to obtain material constants is developed to render the model applicable in practice, which is based on optimization scheme. The flow stress curves of four materials are obtained using the new model and compared with experiments or the other models at some specific temperatures and strain rates. The comparison has revealed that the new model is feasible and general to describe the flow stress curves of various metals and alloys at different temperatures and strain rates with acceptable accuracy. Keywords: Flow stress model, Closed-form function, Bi-linear interpolation, Softening, Hardening

The temperature dependency of the dynamic recrystallization (DRX) activation energy and strain rate exponent, which are major material properties in the Johnson–Mehl–Avrami–Kolmogorov (JMAK) model affecting the DRX phenomenon, are quantitatively presented in experimental and numerical ways. A finite element analysis-based optimization method was used to acquire the material properties of the JMAK model. The first and second stages of a three-stage hot forging process for a bearing outer race were used to obtain and verify all of the material properties, including the DRX activation energy and the strain rate exponent of the JMAK model, which were assumed to be constants or functions of temperature. The predicted grain size after the third stage obtained with the optimized material properties was compared with the experimental values to validate the acquired material properties and reveal the dependence of the two major material properties on temperature. The comparison showed that the difference between the measured and predicted grain sizes was significantly smaller for temperature-dependent material properties, indicating that the DRX activation energy and strain rate exponent are highly temperature-dependent. Keywords: Activation energy, Dynamic recrystallization, Grain size, JMAK model, Strain rate exponent, Temperature effect

Multilayered fibre–metal laminates (FMLs) are composed of metal semifinished products and fibre-reinforced plastics, and benefit from the advantages of both material classes. Light metals in combination with fibre-reinforced thermoplastics are highly suitable for mass production of lightweight structures with good mechanical properties. As the formability of light metal sheets is sometimes limited at room temperature, increasing the process temperature is an appropriate approach to improve formability. However, the melting of thermoplastic materials and resulting loss of stiffness limit the processing temperature. Since single-ply layers have different through-thickness stiffnesses, the forming process changes the ply thickness of the multilayered laminate. In the present study, the deformation behaviour of multilayered FMLs was investigated using a two-dimensional finite-element model assuming plane strain. The thermoelastic-plastic finite-element analysis made investigation of the variation in thickness made possible by incorporating sufficient mesh layers in the thickness direction. The results indicate that a thermoelastic-plastic finite-element model can predict the delamination of plies during deformation, as well as in the final product. Additionally, the predicted changes in thickness of the plies are in good agreement with experimental results when a temperature-dependent friction coefficient is used.

A practical method for adjusting and optimizing isothermal transformation (IT) diagrams using the Jominy test is presented. The method is based on a finite-element optimization procedure, which iteratively minimizes the error between the target phase fractions and the corresponding finite-element solutions at the sample points using an optimization tool. A standard Jominy test of AISI 52100 bearing steel is used to investigate the feasibility and reliability of the method. Three optimization parameters for each IT diagram curve are mathematically applied to the modified Kirkaldy model. These parameters are the design variables in the optimization. The curves obtained from the modified Kirkaldy model are used as the initial guesses in the optimization and they approach the experimental IT diagram by minimizing the error. Good agreement is observed between the optimized diagram and the experimental diagram reported in the literature. The predicted phase fractions using the experimental IT diagram, the IT diagram obtained from the modified Kirkaldy model, and those obtained from the optimized model are compared and demonstrate that the adjustment or optimization procedure significantly improves the accuracy of the predicted phase fraction of the model. The applicability of the method is investigated in a practical case study.