Parametric evaluation of an SMR design domain

Abstract

The complex and coupled behavior of the variables that affect the currently developing generation IV reactors and the increase of interest in Small Modular Reactors are major incentives to seek efficient design methods. Instead of the brute force design methodology, often applied to the analysis of nuclear reactors, other more economical and systematic methods should be applied. In a complex system with a high number of variables, it often is necessary to develop models to describe the behavior of each performance characteristic with respect to a set of variables and their interactions. If expensive experiments are needed to develop these models, the number of experiments should be minimized. This can be achieved by designing the experiments to be performed. Once the system’s models are developed, they can be used to decouple the variables’ effects on the performance characteristics and simplify the optimization process. In this article, three screening and sensitivity analysis methods are applied to decouple and understand the effects of fourteen variables on six performance characteristics of a Small Modular Reactor’s design, based on the Advanced Passive (AP-1000) reactor. The application of these methods facilitated the determination of the most important parameters of each performance characteristic, and resulted in several distinctive findings. These findings are applicable to any Light Water Small Modular Reactor that falls within the variables’ design domain.