A team of researchers from the Indian Institute of Science and the University of Wisconsin-Madison, USA, have developed machine learning models for designing next generation nuclear reactor materials.
- Ferritic-martensitic (FM) steels are being targeted for use in a range of advanced reactor concepts as cladding and structural components.
- A variety of FM steels can be made by changing the composition and processing conditions, and they behave differently under different levels of radiation exposures at different temperatures.
- Ferritic-Martensitic (FM) steel is more resistant to damage caused by nuclear radiation.
- A collaborative team from IISc and the University of Wisconsin-Madison has developed Ferritic-Martensitic models.
- These models forecast the impact of neutron irradiation on the strength of FM steels, employing input parameters such as composition, processing conditions, and testing variables such as radiation dose and temperature.
- The team used an algorithm called SHAP to pinpoint the most important input parameters/variables influencing the strength of FM steels upon irradiation.
- Using these variables, they deployed four ML algorithms to predict the strength of different FM steels subjected to varied radiation levels and temperatures.
