CALPHAD Based Predictions for More Accurate ICME Simulations

In February 2020, The Wall Street Journal highlighted the growth in the use of simulation software to create digital twins, allowing manufacturers to test new or re-engineered product lines before starting them. Citing a report from ABI Research, within the next five years an estimated 110,000 companies worldwide are expected to use some kind of simulation software at an annual cost of more than $2.5Bn. However, the accuracy of these simulations depends on the quality of the input data, which includes the materials data.

Metallurgists, process engineers and researchers all depend on good materials data throughout the materials lifecycle to make informed decisions each day. However, material properties and their behavior are strongly dependent on the chemical composition of the material and variations in processing conditions. Common sources of data, such as handbooks and data repositories, typically exist only for the most common materials and do not capture these variations.

Integrated computational materials engineering (ICME) provides a framework for combining simulations across length scales to create digital twins, optimize processes, and develop new materials. CALPHAD software packages like Thermo-Calc are a foundational part of these frameworks, capturing the composition and temperature dependence on material behavior, and providing material data to other tools in ICME frameworks.

You Will Learn:

• How the CALPHAD method can calculate thermophysical properties and predict material behavior across wide chemistry and process windows
• A case study linking a commercial FEA software to Thermo-Calc to predict thermal histories in additive builds of 718
• Multiple smaller case studies detailing uses for hypersonic materials, steelmaking, and solidification crack avoidance