QUANTUM ANNEALING OPTIMIZATION OF A HEURISTIC SURROGATE MODEL FOR PWR FUEL LOADING

Abstract

An efficient fuel arrangement must be generated by PWR operators every 6–18 months. This complex problem has been extensively researched with two broad approaches, heuristic and stochastic methods becoming accepted. This initial study qualitatively introduces the concept of encoding full-core PWR fuel loading patterns into a form suitable for quantum annealing. The concepts of adiabatic quantum computers and quantum annealing are introduced and a surrogate model encoding of a set of heuristics for loading pattern design produced in a form suitable for use in present-day quantum annealers. The simulated results show significant similarity to benchmark loading patterns.