Reference-Anchored Constrained Multi-Objective Optimization of High-Temperature Sodium Heat Pipes Under Rated Power-Test Conditions

High-temperature sodium heat pipes are promising passive heat-transfer components, yet numerical redesign is often disconnected from manufactured and power-tested hardware. This study develops a reference-anchored constrained bi-objective optimization framework based on the common nominal configuration shared by 139 manufactured and power-tested sodium heat pipes at 700 °C and a 4 kW total heat load. Five structural variables determine total mass and thermal resistance under a fixed rated cooling boundary, while eight nonlinear constraints represent wick geometry, five heat-transfer limits, hoop stress, and guide-contact/heat-leak feasibility. A staged workflow separates lexicographic sequential quadratic programming (SQP) endpoint construction, genetic algorithm (GA)-based global candidate generation, augmented-Tchebycheff scalarization, multistart SQP refinement, and independent ε-constraint verification. The scan retained 134 of 420 designs as feasible. The minimum-mass and minimum-resistance endpoints were 1.4837 kg at 0.1280 K/W and 0.0699 K/W at 2.4528 kg, respectively. The endpoint-seeded original GA produced 40 nondominated points, whereas the proposed hybrid method produced 119 nondominated points and recovered 23 of 27 unsupported points identified by the dense ε-constraint reference. The framework delivers numerical design candidates for prototype manufacture and rated power testing; its engineering value is to narrow prototype choices, identify constraint-controlled trade-offs, and connect batch-tested hardware with subsequent redesign and power-test validation.