Materials Lifetime & Performance Predictors
Goal: Deliver a new generation of physics-based mechanistically derived material lifetime and performance predictors for 347/347H, P91, and a family of alumina-forming alloys (X351).
- Develop a versatile approach to facilitate quick development of new material lifetime and performance predictors for other austenitic and ferritic steels.
- Produce a mechanistically based (i.e., physics and microstructure consistent) multi-axial lifetime model for 347/347H and P91 steels. Incorporate complex stress loading (i.e., multi-axial) with considerations for temperature and microstructure evolution.
Component Lifetime & Performance Predictors
Goal: Deliver a suite of engineering-level, finite element models that can predict the performance and lifetime of components subjected to multiple complex environments.
- Construct a reduced order model for 347/347H stainless steel that can be implemented into commercial finite element codes.
The model:
– Predicts degradation of microstructure during complex non-monotonic (cyclic) loading and
– Includes mechanical and oxide spallation failure mechanisms.
- Demonstrate the accuracy and flexibility of eXtremeMAT tools with industry partners on specific problems.
Data Science & Analysis Tools
Goals: (1) Deliver a database of experimental and simulation data, supported by quality metrics and data management and analysis tools that can be used in the development of new alloys. (2) Assess the performance of energy relevant alloys subject to extreme environmental conditions.
- A curated database of experimental and simulation data for Fossil Energy alloys of interest.
- A preliminary set of algorithms for automated detection of features in alloy microstructures that change with time and can be used to predict how long a component may survive under differential operating conditions.
