Training on WATTS is enabled with a suite of simple examples:
- 1App_SAM_VHTR - Showcasing MOOSE plugin for SAM execution
- 1App_BISON_MetalFuel - Showcasing MOOSE plugin for BISON execution
- 1App_OpenMC_VHTR - Showcasing OpenMC execution
- 1App_MCNP_Jezebel - Showcasing MCNP execution
- 1App_PyARC_UnitCell - Showcasing PyARC execution
- 1App_SAS_SodiumLoop - Showcasing SAS plugin with a simple sodium loop problem
- 1App_MOOSE-MultiApp_Simple - Simple MOOSE MultiApp calculation
- MultiApp_SAM-OpenMC_VHTR - Workflow with MOOSE/SAM and OpenMC
- MultiStep_Griffin-BISON-Sockeye_MR - Advance MOOSE MultiApp calculation with steady-state and transient calculations
- PicardIterations_SAM-OpenMC_VHTR - Workflow with iterative MOOSE/SAM and OpenMC
- Optimization_SAM-OpenMC_VHTR-scipy - 1-criteria optimization of SAM/OpenMC workflow using scipy
- Optimization_SAM-OpenMC_VHTR-pymoo - Multi-criteria optimization of SAM/OpenMC workflow using pymoo
- Optimization_PyARC_DAKOTA - Multi-criteria optimization of PyARC workflow using Dakota
- Sensitivity_SAM-OpenMC_VHTR-scipy-LHS - Sampling with LHS of SAM/OpenMC workflow using scipy
- ParamStudy_SAM_VHTR - Showcasing SAM with parametric study