Phase transformations in steels are based on diffusion of carbon, and the Leblond–Devaux phase transformation model is suitable to model this. You can choose between four formulations for the model — General coefficients, Time and equilibrium, TTT diagram data, and Parameterized TTT diagram. The first and second formulations require generally temperature-dependent functions that determine the characteristics of the phase transformation. The functions will be different for different phase transformations. The TTT diagram data formulation requires information that can be extracted from a TTT diagram, namely the time it takes at each temperature to reach a specified relative phase fraction. Typically, you would choose the transformation start line (for example, 1%). The Parameterized TTT diagram formulation is used to input three points from a TTT diagram, and let COMSOL Multiphysics construct a simplified TTT diagram using these points and additional curve shape parameters. The constructed TTT diagram is used internally to calculate the required parameters for the phase transformation model.

You can choose between five formulations for the model — Time, equilibrium, and exponent; TTT diagram data; TTT diagram data, fixed exponent; Parameterized TTT diagram; and Parameterized TTT diagram, fixed exponent. The first formulation can be viewed as a generalization of the Time and equilibrium form of the Leblond–Devaux model. In addition to the generally time-dependent functions describing the equilibrium phase fraction and the time constant, a time-dependent exponent is used. The exponent is called the Avrami exponent, and it alters the characteristic of the phase transformation. The TTT diagram data and TTT diagram data, fixed exponent formulations require information that can be extracted from the curves in a TTT diagram, namely the time it takes at each temperature to reach a specified relative phase fraction. The former requires two times to calculate the time constant and the Avrami exponent, at two respective relative phase fractions. These can represent, for example the transformation start (for example, 1%) and finish (for example, 90%) times, at each temperature. The TTT diagram data, fixed exponent formulation requires that you specify the Avrami exponent separately, and then use a single transformation time, such as the transformation start. The Parameterized TTT diagram and Parameterized TTT diagram, fixed exponent formulations are used to input points from a TTT diagram, and let COMSOL Multiphysics construct a simplified TTT diagram using these points and additional curve shape parameters. The constructed TTT diagram is used internally to calculate the required parameters of the phase transformation model. In the former, two TTT curves are used. These can represent, for example, the start and finish curves of the transformation. In the latter, a single TTT curve is used to internally calculate the time constant, and the Avrami exponent is specified separately.

This phase transformation model is suitable for diffusion-based phase transformations, such as occur in steels during quenching. You can choose between three formulations for the model — Rate coefficient, TTT diagram data, and Parameterized TTT diagram. The first formulation requires a rate coefficient that represents a lumped effect of temperature and chemical composition on the rate equation for the phase transformation. The TTT diagram data formulation requires information that can be extracted from a TTT diagram, namely the time it takes at each temperature to reach a given relative phase fraction. This information is then used internally to calculate the required parameters for the phase transformation model. The Parameterized TTT diagram formulation is used to input three points from a TTT diagram, and let COMSOL Multiphysics construct a simplified TTT diagram using these points and additional curve shape parameters. The constructed TTT diagram is used internally to calculate the required parameters for the phase transformation model.

This phase transformation model is used to model austenite decomposition according to the phase transformation modeling framework of Kirkaldy and Venugopalan, and that of Li, Niebuhr, Meekisho, and Atteridge. It is most naturally used in conjunction with the Steel Composition node, where information of, for example, chemical composition, is used to define phase transformation functions and transformation temperatures, that are used in the phase transformation model definition.

This phase transformation model is suitable to model the displacive martensitic transformation in steel, on rapid cooling. You can choose between two formulations for the model — Koistinen-Marburger coefficient and Martensite finish temperature. In the first formulation, you specify the Martensite start temperature Ms and, if applicable, select Stress-dependent start temperature. Then specify the Koistinen–Marburger coefficient β. The martensite start temperature defines the onset of the phase transformation, and the Koistinen–Marburger coefficient defines how rapidly the phase transformation progresses as the temperature decreases. The martensite start temperature Ms can be experimentally obtained from dilatometry experiments. If the integrated form of the phase transformation model is used (Equation 3-24), a value for the Koistinen-Marburger coefficient β can be correlated to the temperature at which the martensitic transformation is considered complete (see, for example, Ref. 9). In the second formulation, the phase transformation is defined by the Martensite start temperature Ms and, if applicable, select Stress-dependent start temperature. Then specify the Martensite finish temperature M90. The latter is the temperature corresponding to 90% martensite formation, using the integrated form of the phase transformation model.

If you have selected Stress-dependent start temperature, you can let stresses affect the onset of the phase transformation through a shift of Ms. The start temperature is shifted depending on the pressure and the effective (von Mises) stress. Two coefficients a1 and a2 define the dependence of these stress quantities on the martensite start temperature.

In some situations, you may want to limit the phase fraction of austenite available for martensitic transformation. If you select Incomplete transformation, you can specify a Minimum retained source phase fraction, , to represent the amount of austenite unavailable for martensitic transformation.

This phase transformation model can be used for example to model dissolution of α phase in titanium, on heating. The model assumes that the rate of formation of the destination phase is inversely proportional to the phase fraction of the destination phase.

This phase transformation model can be used to model for example austenitization of steels. It is a simple model that assumes that the rate of formation of the destination phase is proportional to the heating rate, between a lower temperature limit Tl, and an upper temperature limit Tu.