Abstract
Nuclear Thermal Propulsion (NTP) provides the leading potential due to its high thrust, improved specific impulse and long accumulated lifetime in the manned deep space exploration. Particle Bed Reactor (PBR) is the most efficient one among all proposed NTP concepts, which employs a radial flow pattern to reduce the pressure drop and fuel particles of high surface-to-volume ratio to increase the heat removal capability. The technical challenges, however, have arisen with the enhanced performance of PBR, such as the thermal hydraulic design. In this paper, a procedure based on the Non-dominated Sorting Genetic Algorithm with elitisms approach (NSGA-2) and uncertainty quantification is developed to prepare an optimal fuel element for PBR with regard to the thermal performance. The procedure has been verified through three cases, in which the thermal performance of all fuel elements has improved a lot after the optimization process.
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