Proper orthogonal decomposition (POD)-based inverse optimization structural design and comprehensive thermal reliability assessment of RPV insulation structure

Minimizing heat loss from the reactor during normal operation necessitates a well-designed insulation structure for the reactor pressure vessel (RPV) to ensure operational reliability. Conventional trial-and-error methods are inefficient and often fail to identify the optimal parameter combination from a myriad of design variables. This paper presents a Proper Orthogonal Decomposition (POD)-based inverse design methodology to systematically optimize RPV insulation structural parameters, thereby significantly enhancing its thermal reliability. Three critical design variables were investigated, and three reliability indices associated with heat flux and temperature were employed for evaluation. The sensitivity of the design variables to the indices was analyzed using the extensive results from POD reconstruction. Additionally, a dimensionless score ( F P O D ) on a percentage scale was defined to assess the structure’s comprehensive thermal reliability. The results demonstrated that the POD method exhibited exceptional accuracy, with an average coefficient of determination ( R ²) exceeding 0.95 and a mean relative deviation ( MRD ) below 4.73%. Furthermore, it demonstrated remarkable efficiency, being approximately 900 times faster than conventional CFD. By traversing all the parameter combinations, the optimal design structures (60°-2 mm-150 mm) achieved a peak score of 94.7, representing a 202.6% improvement in the comprehensive thermal reliability of the RPV insulation structure over the original prototype design (35°-2 mm-75 mm).