MINIMIZING CRUD DEPOSITION THROUGH OPTIMIZATION OF ASSOCIATED PARAMETERS

A strong correlation exists between subcooled boiling in assembly subchannels and CRUD deposition. In this work a genetic algorithm is used to optimize 17 x PWR fuel have minimized boiling, peak kinf, maximized end of cycle kinf. Optimization these parameters act as surrogate for the optimization deposition assemblies due their correlation. Subcooled measured by vapor void sub channel, values are calculated using VERA-CS. Due high computational cost VERA-CS, artificial neural networks models VERA-CS order be performed timely manner making design possible. Two were trained training library 1200 randomly generated designs validation 100 evaluated The combination algorithms formed an extremely fast capable evaluating designed set optimized pin lattices matter minutes. showed clear reduction solutions. This provides proof principle that complex phenomena requiring coupled, Multiphysics calculations, such deposition, may optimized.