A complex thermomechanical model for simulating the transient fields of the temperature, microstructure, stress, strain, and displacement during quenching of steel profiles is introduced. The thermoplastic material model is formulated on the basis of J2-plasticity theory with a temperature- and phase fraction-dependent yield limit. Coupling effects such as dissipation, phase transformation enthalpy, and transformation-induced plasticity are considered. The validity of the model is verified by comparing the simulation results with available experimental measurements. The introduced model serves as a basis for optimizing the cooling conditions for reducing residual stresses and distortions. The simulation results for T and L profiles of two different types of steel are described.
A complex thermomechanical model is introduced for the simulation of the transient fields of temperature and stresses during the quenching of steel products. The material behaviour is an extension of the classical J 2-plasticity theory with the extension of temperature and phase fraction dependent yield criteria. The coupling effects, i.e., dissipation of mechanical energy, transformation induced plasticity (TRIP), and phase transformation enthalpy, are considered. The model is used for the determination of the optimal cooling or quenching for reducing the distortion in the long steel profiles. The simulation results are presented in order to investigate the effects of material properties, boundary conditions, profile size and geometry. In the simulations, L-, T-and U-profiles made of steel C45 and steel CaD are considered. It is demonstrated that with a higher cooling rate in the mass lumped regions of the profiles, the distortion can be reduced. Basic Equationswhere k is the heat conduction coefficient, q is heat flux vector, and T is the temperature. The heat treatment process is a transient heat conduction problem where the tempera-sufficient to estimate the behaviour of the prismatic profile under such conditions with much fiever degrees of freedom. In addition, the dimensional reduction of the problem from three-dimension to two-dimension substantially simplifies not only the visualisation of the field variables but also the determination of optimal cooling strategy.Temperature field. The microstructure and mechanical properties are strongly temperature dependent. Hence the temperature field must be determined correctly for an accurate simulation. The latent heat of the phase transformation has to be taken into account. The heat conduction is governed by the Fourier law, after which the heat flux vector is parallel to the temperature gradient,The mathematical model of the heat treatment is described by a thermoelastoplastic theory which also covers the phase transformation effects. The temperature field has a great influence on the microstructure and mechanical properties. Hence the temperature field must be simulated accurately. The latent heat of phase transformation is considered as an additional heat source or heat sink. The microstructural evolution is obtained by using the isothermal time-temperature-transformation (TTT-) diagrams charts. The diffusion controlled phase transformations are computed according to the Johnson-Mehl-Avrami equation and the displacive phase transformation is calculated from the Koistinen-Marburger equation [2]. For the determination of stress/strain field, a constitutive relation is established, which depends on temperature and phase fraction. The total strain tensor is additively decomposed into several parts, as usual. The introduced model is applicable to 2D-and 3Dproblems. steel research int. 76 (2005) No.5
The blast furnace (BF) is a huge counter-flow reactor to produce pig iron. The molten pig iron and by-product slag are accumulated at the hearth of the furnace, from where they are regularly tapped. The campaign life of the BF is governed by the wear of the hearth refractory. Once the residual thickness of the hearth lining is critically low, it must be repaired during a long-term stoppage, which is quite costly. Therefore, it is essential to keep track of the residual lining thickness not only for the better planning of the relining but also for the operational safety (avoiding dangerous hearth breakthrough incidents). [1,2] Modern BFs are equipped with many thermocouples (TCs) in the hearth refractory because higher temperatures indicate a lower residual wall thickness. [3-7] However, the measured temperatures are also influenced by many other effects such as TC defects, brittle layers in the refractory hearth cooling conditions, production rate, temperature, and flow state of the hot metal within the hearth. The preparation of the measurement data is crucial and quite challenging. Existing models lack the comprehensive checks of the data plausibility or of possible effects unrelated to wear. [2] Therefore, the recorded TC data (usually denser than 15 min values) must be first filtered, e.g., by excluding the time intervals influenced by stoppages. Then, strange behaviors like sudden temperature drops or uncorrelation to other TCs must be identified, which can be used to assess TC plausibility. An inverse heat transfer model is developed and presented in this study to estimate the 3D hearth wear profile. The model uses the prepared and weighted online TC measurements. The numerical computations are performed using COMSOL Server. The LiveLink for MATLAB module is utilized for the 3D hearth wear geometry interpolation and optimization. Furthermore, a COMSOL application is programmed so that a standard web browser can be used to visualize the results interactively on any device connected to the internal network without local software installation. The new model provides a flexible platform to include other physical aspects that are important for operational hearth monitoring. For instance, the thermal stresses and the deformation of
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.