Estimation of Grain Size and Composition in Steel Using Laser UltraSonics Simulations at Different Temperatures

Abstract

The applicability of laser ultrasonics for the determination of grain size and phase composition in steels under different temperatures was investigated. This was done by obtaining the velocity and attenuation of propagating ultrasonic waves in a simulated steel medium. Samples of ferrite and austenite with varying microstructures were modelled and simulated with the finite difference method, as were samples with varying ratios of austenite and martensite. The temperature of the medium was taken into account as an essential parameter, since both velocity and attenuation are temperature dependent. Results of the velocity and attenuation analysis showed that the use of the wave propagation velocity is not feasible for determination of grain size or phase composition due to a high sensitivity to temperature and sample thickness. The frequency-dependent ultrasonic wave attenuation was less sensitive to the variation of temperature and sample thickness. It can be concluded that accurate knowledge of the temperature is essential for obtaining a correct grain size or phase ratio estimation: a temperature accuracy of 100 °C yields a grain size accuracy in the order of a micrometer using the attenuation. Similarly, a temperature accuracy of 70 °C leads to a phase ratio estimation accuracy of 10%.

Practical Approach for Determining Material Parameters When Predicting Austenite Grain Growth under Isothermal Heat Treatment

“…Here, d G,experiment (i) and d G,prediction (i) are the measured and predicted AGS values, respectively, and N is the number of the temperature case study at which the grain size was measured. The parameters listed in Table 2 were then acquired using a GRG optimization technique [25,26] to predict AGS growth. With the proposed GRG optimization method, the material parameters can be quickly and accurately obtained without the need for complicated and time-consuming data processing, in contrast to the conventional methods used in earlier studies [15][16][17][18][19][20][21][22][23][24].…”

“…The AGS growth prediction based on Equation (1) was implemented using commercial FE software V23R02 [25]. Figure 5a illustrates an axisymmetric FE model of cylindrical specimens used in a heat treatment test, carried out under adiabatic conditions with 3000 quadrilateral elements.…”

“…Investigating AGG behavior during hot metal forming is crucial. In most cases, the traditional empirical equation, specifically the modified Arrhenius model, has been applied to mathematically describe the AGG in metallic materials [25]. Despite differences in formulation among the models, the effects of three factors, i.e., the initial grain size, holding time, and heating temperature, cannot be neglected when predicting AGS growth.…”