Materials Modeling

Any metal or alloy, which is subjected to dynamic thermal cycles during welding, undergoes dramatic changes in microstructure. For example, in steels, heating above 800°C and subsequent cooling will destroy the original microstructure. An ability to understand these changes and its impact on the mechanical properties has remained as one of the crucial need for welding metallurgists. Over the period of last three decades, many numerical models have been developed to describe the same. In this location, access to some of the predictive power of these models are provided in a simple Internet interface. The tools are classified with respect to different alloy categories.

TTT/CCT Prediction 

Phase transformation is an integral part of the microstructure evolution in structural alloys. The rate at which the transformation occurs can be described by time-temperature-transformation (TTT) and continuous cooling transformation (CCT) curves. The TTT curve maps the time-taken for the product phase to form at different temperatures when kept at that temperature isothermally. Continuous cooling diagrams map the temperature and time at which the transformation will start as the parent phase is cooled from high temperature at a given rate. The TTT and CCT diagrams are governed by the chemical composition of the alloys.

• Prediction of TTT and CCT Curves for Steels: In steels, the parent phase is austenite and product phase is ferrite. The online tool calculates and plots the TTT and CCT curves for the initiation (1%) of the transformation as a function of steel composition

Ferrite Number Calculations

Function fit method
Prediction of ferrite number in stainless steels: Stainless steels solidify as delta-ferrite and transform to austenite on cooling. In some other cases, the may solidify as austenite. The ferrite number tool calculates the amount of residual delta-ferrite that remains untransformed at room temperature as a function of composition. Here the cooling rate effects are not considered. Use the Function Fit tool.

Neural net method
Prediction of ferrite number in stainless steels – Cooling Rate Effect: Stainless steel ferrite number as a function of composition and cooling rate. This model will qualitatively capture the effect of cooling rate on the transition from ferrite to austenite mode of solidification and also incomplete transformation of ferrite to austenite. Use the Cooling Rate Neural Net tool.

Weld Microstructure Prediction
Prediction of Microstructure and Hardness in Low-Alloy Steel Heat-Affected-Zones: The tool calculates the fractions of different ferrite morphology that forms from the austenite and relates the same to Vickers hardness. Use the Microstructure Prediction tool.

The on-line calculations are for educational purposes only and are based on published work in the literature. Some of the modules were developed at Oak Ridge National Laboratory (ORNL) and have been made available to EWI members as a part of the memorandum of understanding between ORNL and EWI. For additional information, please contact Edison Welding Institute