Additionally, operational windows can be established in terms of allowable chemistry ranges and temperatures on the process, times, etc. to provide flexibility in day to day operations while still benefiting from the insight that computations can provide.
Some examples include:
- Predicting phases formed as a function of temperature for an actual measured chemistry of an alloy can allow better decisions to be made prior to a heat treatment or hot rolling as to the potential formation of deleterious phases or other problems, rather than discovering these following post-treatment examinations. Calculations do not remove the need to perform such measurements as part of the quality control process, but they can aid in reducing the number of heats that may be scrapped for different reasons resulting in scrap of material, rework, lost opportunity costs etc.
- Alloys typically have a nominal or target chemistry and an allowable tolerance range for each element. Determining the sensitivity of a particular property, such as the solvus temperature of a given phase, for example, can be done for all combinations of chemistry within the allowed range, thus establishing a range for that given property rather than a single value based on nominal chemistry. Determining tail effects due to variation within chemistry can require many hundreds of experiments, but a computational approach can provide insight into these ranges in an efficient manner and allow customers to establish operational windows, both in terms of allowable chemistries and temperatures, during various stages of a process.
- Calculations can be performed to give better insight into slag-metal interactions and therefore the control of inclusions.
- Using Scheil calculations to predict the extent of micro segregation.
- Simulations can be made to investigate the kinetics of certain diffusion controlled transformations including precipitate growth and dissolution and also homogenisation to establish if processes are being run for long enough to yield satisfactory quality of the final product, or too long and thus allowing for efficiency savings.
- The size distribution of precipitate phases is dependent on the chemistry of the material, the temperature history and time. TC-PRISMA simulations can be made to give predicted insight into the nature of these precipitates in terms of their size distribution and number density.