Materials simulation is the computational prediction of material states and properties from composition, processing and microstructure. It answers questions such as: Which phases are stable at a given temperature? How does a steel transform on cooling? How do strength or thermal conductivity change with temperature? The results are used in materials development, in designing heat treatments and as input data for component simulation.
Methods of materials simulation
CALPHAD
The CALPHAD method (CALculation of PHAse Diagrams) goes back largely to Larry Kaufman (Kaufman and Bernstein, 1970). It collects experimental information on phase equilibria and thermodynamic data of a system and describes the Gibbs energy of each phase with a mathematical model. Its parameters are fitted so that they reproduce the measured data as well as possible. With these assessed databases, phase diagrams and thermodynamic properties can be calculated, including for multicomponent systems and metastable states for which no complete measurements exist.
Physically based models
Physically based models can build on the thermodynamic results, for example for phase transformations, precipitation or solidification. They describe processes through physical mechanisms and thus link composition and processing with microstructure and properties. JMatPro, for example, extends equilibrium calculations with calculation modules for phase transformations and precipitation.
Phenomenological models
Phenomenological models describe observed material behavior with mathematical formulations without modeling every mechanism in detail. Typical examples are flow curve models and other constitutive material models whose parameters are determined from test data and then used in FE simulation. In EDA MM, predefined material models such as flow curves or phase transformation models can be parameterized, modified and extended. Flow curves can, however, also be calculated on a physical basis, for example with JMatPro.
ICME as a framework
ICME (Integrated Computational Materials Engineering) links materials models across several length scales to describe the chain process – microstructure – properties – performance coherently. The goal is to develop materials, processes and products together. A prerequisite is the standardized exchange of simulation results between the tools involved.
Solidification: equilibrium and the Scheil model
There are two limiting cases for the solidification of an alloy. The equilibrium calculation assumes that concentrations in the liquid and the solid equalize completely at all times. The Scheil model, by contrast, assumes complete mixing in the liquid but no diffusion in the already solidified solid, with local equilibrium at the interface. It therefore describes the enrichment of alloying elements in the remaining liquid, i.e. segregation, and a solidification range that is wider than at equilibrium. Real solidification usually lies between the two limiting cases. Models with back diffusion therefore take into account that some elements also diffuse in the solid.
What materials simulation is used for
- Material properties: temperature-dependent physical and mechanical properties, for example thermal expansion, heat capacity, strength and flow curves, for alloys for which no complete measured data are available.
- Phase equilibria and solidification: stable phases, phase fractions and solidification behavior, for example according to the Scheil model.
- Heat treatment: transformation behavior on cooling and heating, shown as CCT and TTT diagrams or time-temperature-austenitization diagrams, and properties as a function of cooling and heating rate.
- CAE material cards: temperature-dependent data prepared as material cards for forming, heat treatment, welding, casting or structural simulation.
- Materials development: comparing composition variants before heats and tests are planned.
Typical results for component simulation
- Thermophysical data: From the calculated phase fractions and their composition, properties such as enthalpy, thermal expansion or heat capacity can be derived as a function of composition and temperature. They are a basis for material cards in FE calculations.
- Flow curves: Forming and heat treatment simulation require flow curves as a function of temperature and strain rate.
- Microstructure and strength after heat treatment: For certain material groups, such as nickel and nickel-iron-based superalloys, microstructure and strength after heat treatment can be calculated.
- Data for different CAE programs: Calculated data are provided as material cards for forming, heat treatment, welding and casting simulation programs or exported as ASCII files.
Designing alloys systematically
Materials simulation is also suited to investigating large composition ranges systematically. Instead of single calculations, series of calculations are planned and evaluated, similar to a statistical design of experiments. Optimization methods go one step further: they vary parameters such as composition, heat treatment or austenitizing temperature, cooling rate and holding time and search for combinations that meet several target properties as well as possible at the same time.
Limits of materials simulation
- Dependence on databases: CALPHAD calculations are only as good as the assessed thermodynamic databases. Uncertainty increases for systems or composition ranges with little experimental basis.
- Equilibrium and kinetics: equilibrium calculations describe the state after infinite time. Real processes often take place far from equilibrium, which requires additional kinetic models.
- Model assumptions: every model applies to certain conditions. Microstructural influences such as grain size or segregation are not always fully captured.
- Validation: for safety-relevant design, calculated values do not replace testing. They should be checked against test data and documented with their origin.
Materials simulation with Matplus
JMatPro® calculates temperature-dependent material properties for a wide range of engineering alloys, including steels and nickel, aluminum, titanium, magnesium, cobalt, zirconium and copper alloys. It is based on thermodynamics (CALPHAD) and physically based models. Among other things, JMatPro calculates phase equilibria, solidification (Scheil, back diffusion), isothermal and continuous transformation diagrams as well as physical and mechanical properties, and exports material cards to various CAE systems. Examples are shown on the page JMatPro application examples.
For targeted alloy design, the JMatPro Material Property Optimiser (MPO) combines JMatPro calculations with multi-objective optimization. EDA for JMatPro® enables systematic property calculations across large composition ranges and supports structured design of experiments.
EDA MM creates material models from test data with scientific Python libraries and exports them for CAE solvers. In materials data management with Matplus EDA®, calculated and measured data are managed together with their origin, so it remains clear which value was measured and which was calculated.
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